AI - June 2023

AI and ML: Generative AI fuelling data quality revolution

AI Applications: AI-powered biometrics fighting fraud

Technology: Powering the nextgeneration of driving aids

IOT DEVICES ENABLING SMART CITIES

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Data and IoT powering the world’s future smart cities

Data is the lifeblood of the world’s future smart cities. But as connected devices increase, so too will security threats

By 2050, two-thirds of people globally are expected to live in cities. As urbanisation continues to rise, cities are facing new challenges that require innovative solutions.

At the heart of one of these possible solutions, the smart city, is the smart sensor. Distributed in the tens of thousands across smart city test neighbourhoods, or even entire boroughs, IoT sensors monitor everything from traffic patterns and footfall to utility usage and emissions.

One such example of this is the city of Barcelona. The Spanish capital’s smart city pilot demonstrates how the smart application of data can transform everything from shopping to transportation, enabling services from autonomous driving to augmented reality.

But as the number of connected devices increase, so too will security threats.

The use of both AI and ML in smart city systems will improve the efficiency of systems and expand their advantages. However, this will also create new avenues for attack through the cloud, as well as make the detection of malfunction behaviours more difficult.

marcus.law@bizclikmedia.com

“The smart application of data can transform everything from shopping to transportation, enabling services from autonomous driving to augmented reality”

Innovators are paving the way for a more resilient, sustainable and efficient future. The rules have changed. It’s time for DISRUPTION.

Tech LIVE Virtual returns to highlight the innovators changing the industry through expert keynote speakers, interactive fireside and panel discussions. This exclusive 1-day virtual event will bring together the greatest voices in the industry for an essential deep dive into the future of Technology, AI and Cyber.

Brought to you by BizClik, Technology, AI and Cyber Magazines, the event will shine a light on essential topics such as the AI revolution, quantum computing, the virtual workplace, technology’s place in sustainability and much more.

It’s time for DISRUPTION.

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Position your business as a pioneer in Technology and showcase your values, products and services at Tech LIVE Virtual.

This is your chance to share your innovations with the technology community by making an impact in front of fellow decision-makers and influencers as well as accessing potential partners via an active and engaged audience.

See you on the 8th June 2023.

▶ Watch our showreel from TECH LIVE London 2022

CONTENTS

UP FRONT

14 BIG PICTURE Giving black hole researchers a clearer view

16 LIFETIME ACHIEVEMENT

Kevin Kennedy, SVP Products

20 FIVE MINS WITH Demis Hassabis, DeepMind Technologies

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6 - 7 September 2023

Business Design Centre, London

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BIG PICTURE

L. Medeiros (Institute for Advanced Study), D. Psaltis (Georgia Tech), T. Lauer (NSF’s NOIRLab), and F. Ozel (Georgia Tech)

Giving black hole researchers a clearer view

55 million light years from Earth

Researchers have developed a new machine-learning technique, known as PRIMO, to enhance the fidelity and sharpness of radio interferometry images. The purpose? Creating a new, high-fidelity version of the Event Horizon Telescope's iconic image of the supermassive black hole at the centre of Messier 87, a giant elliptical galaxy located 55 million lightyears from Earth.

Building on the image taken in 2017 by the Event Horizon Telescope, PRIMO relies on a branch of machine learning known as dictionary learning, which teaches computers certain rules by exposing them to thousands of examples.

“With our new machine-learning technique, PRIMO, we were able to achieve the maximum resolution of the current array,” said lead author Lia Medeiros. EHT with PRIMO

KEVIN KENNEDY

Kevin Kennedy, SVP Products, explains how Vectra AI provides enterprises with real-time attack signal

With more than 27 years in technology product management, and more than half of those spent in security, Vectra’s Senior Vice President of Products Kevin Kennedy has seen it all.

Today leading the Threat Detection and Response product vision and strategy for Vectra, Kennedy launched his career in threat intel at IronPort and has also held roles at Juniper, Cisco, and Agari Data.

“At Vectra, the thing that we do best in the world and why our customers invest, is we give real-time attack signal intelligence using AI,” Kennedy told AI Magazine. “Most organisations are in a digital transformation: they are moving to the cloud, and they will be hybrid forever. We give them a consistent view of detection and response across that, and really the clarity of signal that we give is why they choose Vectra.”

As Kennedy describes, Applied AI is central to Vectra’s approach. “The company's a little over 10 years old and our technical North Star, from day one, has been using AI, and we've had to do a lot of innovation to figure out how to apply it best to this problem set.

“While there's ChatGPT, most of the AI that is used today is applied AI, so you really have to understand your domain.”

‘The Windows XP days for cloud’

“If you look at the threat landscape today, there are a few things going on,” Kennedy says. “One is that there is more of it. So if you think about the typical enterprise going through a digital transformation, they've got their data centre, public cloud identity, workers outside, and it's very difficult.

“With things like the cloud, the understanding of how that will be attacked is really nascent. You can think all the

intelligence using the power of its ‘North Star’

2015

“You can think all the way back to Windows XP days. We're in those days for the cloud, because we're just discovering how people will use the cloud to attack itself”

Kevin

Kennedy Joined Vectra AI

way back to Windows XP days. We're in those days for the cloud, because we're just discovering how people will use the cloud to attack itself.”

Another issue, Kennedy explains, is the increasing accessibility of certain tools that used to be reserved for nation states.

“If you think about that threat landscape, tools that used to be reserved for nation-states are now available in tool kits that anyone can use. They're automated. On the AI front, I’ve seen some interesting things about ChatGPT, and people asking questions about how to hack. Anyone can have access to it. That's what defenders are up against.”

As Kennedy describes, solving problems with legacy tech signatures will still have a role to play, but utilising AI is key. “You're never going

to solve the problem though, because we're just burning out defenders. AI is the only way to get a good signal, both in individual attack surfaces and then pulling the narrative together.

“It’s one of our guiding principles that you've got to use AI. But it's just a tool, especially in applied AI, and it's all about how you use it. The methodology for using it is what defines success versus failure from the customer outcome standpoint. So that's been our focus: it's not just AI, but how you use AI in the right ways to solve the problem.”

Pushing the envelope of data science techniques

When it comes to detecting threats with AI there are a couple of philosophies, Kennedy explains.

“We've definitely placed our bet, and we believe it gives better outcomes,”

“Tools that used to be reserved for nation-states, are now available in tool kits that anyone can use”

Stop Cyber Attacks with Vectra AI's Attack Signal Intelligence™

he describes. “There's one school of thought that says, ‘You learn about an environment, and you do lots of counts and metrics, and then you flag what's unusual’; the bet is that in the unusual you'll find the threat.

“The challenges with that are that when you look at especially large enterprise environments, there's so much happening every day that lead to a lot of noise and alerts for the security teams to deal with.”

The other problem, Kennedy describes, is that attackers are good at blending in. “They're good at making themself look pretty close to normal,” he says. “So you actually miss a lot of the relevant signals.”

“So we said, ‘That doesn't really work well’. Rather than thinking about it as more of a pure data science problem, it's in reality a security problem.

“We are constantly pushing the envelope of data science techniques. Four or five years ago, there were lots of breakthroughs around Google Translate, and the use of recurrent neural networks, and long shortterm memory (LSTM) models. And we said, ‘Okay, that works really well for translation. It's actually the right technical approach for command and control tunnels’, and so we then applied that. We took the latest learnings from that domain and applied them to security, and we were the first to do that. And so we're always keeping up on data science.

“We're always keeping up with breakthroughs in security research,” Kennedy concludes. “We have to continue doing that work, and then bringing them together to deliver the best outcomes for our customers.”

Demis Hassabis: From chess prodigy to AI leader

As CEO and Co-Founder of Google DeepMind, Demis Hassabis is one of the most influential experts in the field of AI.

A child chess prodigy, at the age of 17 Hassabis joined the computer game company Bullfrog Productions, where he worked as a designer on science fiction game Syndicate. Here, Hassabis was the lead programmer for the highly influential Theme Park, released in 1994, which won the industry’s Golden Joystick Award.

In 2010, Hassabis founded the AI company DeepMind Technologies with Shane Legg and Mustafa Suleyman. The trio began working on AI technology by teaching it how to play old games from the 1970s and 80s, with a goal to create a general-purpose AI that can be useful for almost anything.

Hassabis attended Cambridge University where he studied for his computer science undergraduate degree, earning a double first-class honours.

At the start of 2014, Google announced the company had acquired DeepMind for $500m and agreed to take over DeepMind technologies. With Google, DeepMind established an artificial intelligence ethics board.

Later that same year, DeepMind received the ‘Company of the Year’ award from Cambridge Computer Laboratory. It also published research

on computer systems that are able to play the board game ‘Go’.

AlphaGo, a computer program developed by DeepMind, beat the European Go champion Fan Hui in 2015. This was the first time an AI defeated a professional Go player. Go is considered much more difficult for computers to win. Due to the high number of possibilities within the game, it is prohibitively difficult for traditional AI methods such as brute force.

With Amazon, Google, Facebook, IBM and Microsoft, in 2016 DeepMind became a founding member of Partnership on AI, an organisation dedicated to the society-AI interface.

AlphaFold makes headlines

Last year DeepMind made headlines with AlphaFold, which is capable of deciphering the structure of almost all proteins known to science.

The company partnered with the European Molecular Biology Laboratory (EMBL) to make the most complete and accurate database yet of predicted protein structure models for the human proteome.

In 2010, Demis Hassabis co-founded the artificial intelligence company DeepMind Technologies, which has been credited as bringing AI to the mainstream

“Our goal at DeepMind has always been to build AI and then use it as a tool to help accelerate the pace of scientific discovery itself”

“We are bringing together our world-class talent in AI with the computing power, infrastructure and resources to create the next generation of AI breakthroughs and products across Google and Alphabet”

DeepMind announced the data would be made freely available to the scientific community, allowing scientists to carry out work that would have previously taken years in just a few days.

“Our goal at DeepMind has always been to build AI and then use it as a tool to help accelerate the pace of scientific discovery itself, thereby advancing our understanding of the world around us,” said Hassabis at the time.

“For our team, AlphaFold’s success was especially rewarding, both because it was the most complex AI system we’d ever built, requiring multiple critical innovations, and because it has had the most meaningful downstream impact.”.

Google DeepMind

In April, Hassabis announced that DeepMind, which was acquired by Google in 2014, would henceforth be known as Google DeepMind, with the organisation joining forces with the Google Brain team to ‘accelerate progress towards a world in which AI helps solve the biggest challenges facing humanity’.

“When Shane Legg and I launched DeepMind back in 2010, many people thought general AI was a farfetched science fiction technology that was decades away from being a reality,” Hassabis said in an announcement to DeepMind employees.

“Now, we live in a time in which AI research and technology is advancing exponentially. In the coming years, AI – and ultimately AGI – has the potential to drive one of the greatest social, economic and scientific transformations in history.

“Through Google DeepMind, we are bringing together our worldclass talent in AI with the computing power, infrastructure and resources to create the next generation of AI breakthroughs and products across Google and Alphabet, and to do this in a bold and responsible way. The research advances from the phenomenal Brain and DeepMind teams laid much of the foundations of the current AI industry, from Deep Reinforcement Learning to Transformers, and the work we are going to be doing now as part of this new combined unit will create the next wave of world-changing breakthroughs.”

SAP’s Sam Castro on AI and risk resilience in manufacturing

SAP’s Sam Castro is a solution manager for Digital Manufacturing. He tells us about AI, risk resilience and supply chain sustainability

SAP is a global software provider and a leader for enterprise business process software, including solutions to manage supply chains. SAP provides technologies, supports the cloud and cloud platform environments, as well as artificial intelligence/machine learning (AI/ML) libraries, robotic process automation (RPA) and in-memory technology for high-end computers. SAP’s solutions for manufacturing execution and insights are part of a portfolio of products for supply chain management and leverages these technologies.

“We're an enterprise business software and a technologies company,” says Sam Castro Senior Director, Solution Management, LoB Digital Manufacturing.

Castro is a Senior Director at SAP and a part of the line of business manufacturing solution management team. The line of business covers the 27 manufacturing industries for which SAP provides software solutions.

“All of those industrial companies have needs around operations visibility, control and reporting,” Castro explains. “The different industries have different targets that they're after. Some are heavier on the asset side, some of them are heavier on product quality and yields, others are all about logistics and moving products around on-time through the supply chain.”

SAP is met with a diverse set of requirements and needs from its customers. Solution management takes these industry needs and applies them to market direction and invests them in the portfolio.

“We provide guidance on where to focus and the emphasis for development, and that strategy big picture where we want to take the products,” Castro explains.

In college, Castro completed a Bachelor's in computer engineering and a Master's in computer science at the Rochester Institute of Technology (RIT).

“I came from the hardware bridge to the software bridge very naturally after graduating,” says Castro. “I was dropped into the manufacturing floor because that is exactly where the hardware automation side bridges over into the software.”

He was faced with a great deal of information and digital signals from the automation layer and was tasked to turn it into information — how does SAP make that translation?

“I started at the very lowest level and moved my way through Lighthammer Software, which was acquired by SAP back in July 2005,” says Castro. “I worked my way through SAP into the role that I'm in today.”

“Being a sustainable enterprise means that you're an efficient enterprise”

SAM CASTRO SENIOR DIRECTOR, SOLUTION MANAGEMENT, LOB DIGITAL MANUFACTURING, SAP

Sam Castro is Senior Director of Solution

Management, LoB Digital Manufacturing at SAP

Don’t be surprised.

Today’s supply chain comes with constant uncertainty. So how are you preparing for whatever comes next?

Discover how Deloitte can help you enable a built-to-evolve digital supply chain that allows you to pivot quickly no matter what surprises the future brings.

Learn more about our Kinetic Supply Chain offerings for embedding flexible capabilities, intelligent insights, and sustainability from end to end.

Contact SAP@deloitte.com to get the conversation started.

Built for impact

Getting ahead of change with a disruption-ready digital supply chain

Digitally driven business is an imperative in today’s uncertain landscape, but to thrive organizations will need digital supply chains that can anticipate disruption and evolve in lockstep with change all while prioritizing sustainability and responsible practices.

At Deloitte, such capabilities are part of our vision for the Kinetic Supply Chain a built-to-evolve supply chain enabled by a clean-core ERP, intelligent technologies, responsive cloud solutions, and an inclusive ecosystem of capabilities. Kinetic Supply Chain capabilities can allow you to see issues and opportunities before they arise and to take action sooner.

Envisioning the future

Ultimately, it’s about flexibility which can be elusive for many organizations. While optimizing supply chains over the years, some companies may have gained efficiencies without gaining the flexibility that they need in today’s environment. For example, they may have gotten down to one or two key suppliers instead of 20,

but they may not have the ability to sense the need for new suppliers, in the event of a regional fuel or material shortage, for example. They also may lack the ability to seamlessly and quickly integrate any new suppliers into their digital ecosystem. And at the same time, they may lack visibility into what those suppliers will mean for their carbon footprint, their sustainability goals, and their impact on the planet.

With a Kinetic Supply Chain covering planning, procurement, distribution, and operations you can proactively address many of those challenges and become “disruption ready.” More than a vision, the Kinetic Supply Chain is real, and you can see it in action at The Smart Factory @ Wichita At this full-fledged manufacturing facility, housed in a net-zero-impact building, Deloitte, SAP, and others are collaborating to solve real business needs and understand what it takes to build and scale flexible digital supply chains. Contact SAP@deloitte.com to schedule a visit or to get more insights on enabling a built-to-evolve digital supply chain.

SAP’s Sam Castro on AI and risk resilience in manufacturing

Risk resilience and sustainability in the supply chain

When you talk about risk resilience at SAP, it’s about how to handle the real world, not setting up a plan and adhering to it day in and day out.

“You would like it to be like clockwork, for sure,” says Castro. “Where everything always aligns and meshes the way that it's supposed to all the time, every second. But we know that's not always the case.”

Weather events, pandemics, labour shortages or large sporting events can cause supply chain issues. For Castro, resiliency is the byproduct of having to have to handle these off-topic or out-of-sync scenarios and the ability to detect that you're out of sync

“Here are the enablers of AI and ML type algorithms that you can use and put together how you see fit”

SAM CASTRO SENIOR DIRECTOR, SOLUTION MANAGEMENT, LOB DIGITAL MANUFACTURING, SAP

with the original plan and react to it in a coordinated manner.

“The faster you can do that, the faster you can correct that problem,” says Castro. “Then you’re able to identify how often those deviations occur — that frequency of occurrence, that is your opportunity.”

Being able to quantify that opportunity and understand what those little deviations actually add up to, and how that impacts the business financially, is one of the key topics around what customers will hear about resiliency from SAP, says Castro.

“Sustainability is an overlay to that, sustainability is a byproduct of efficiency,” says Castro. “Being a sustainable enterprise means that you're an efficient enterprise.

EXECUTIVE BIO

SAM CASTRO

TITLE: GLOBAL VICE PRESIDENT, CENTRE OF EXCELLENCE

INDUSTRY: MANUFACTURING

LOCATION: PENNSYLVANIA, US

Sam Castro joined SAP in July of 2005 with the acquisition of a small company called Lighthammer. He was responsible for implementation consulting, field enablement, custom development, and training for the core products (Illuminator, Xacute, UDS, CMS). These products have since evolved into the core SAP Connected Manufacturing products (Mfg. Integration & Intelligence or MII and Plant connectivity or PCo) that you see today.

Sam is now part of SAP LoB Manufacturing Solution Management group, which is directly responsible for strategy, direction, and customer adoption of all of the manufacturing products at SAP. He is specifically responsible for Industrial Analytics, that is SAP MII, Digital Manufacturing for insights, and Digital Manufacturing for execution, and he is the solution owner for Process MES products. In this role, he is actively working on mid- and long-term features and deliverables and how they are positioned with the broader SAP portfolio; he also provides guidance for product development investment.

If things are running effectively, things are running safely, and in a very energy-friendly manner as well.”

Castro views the impact of the cloud on manufacturing as a positive one.

“There are benefits for the IT team from a maintenance perspective and a continuous update and management of that software package,” he explains.

Cloud users are not dealing out of sync or outdated documentation, they’re not dealing with security issues that creep into the environment over time. Updates and patches are handled in real-time by the cloud hosting and software provider, that SaaS provider in the cloud environment. Castro views offloading that burden from the manufacturing layer and the IT teams that support them centrally and locally as a big deal for organisations and businesses.

“It keeps that barrier to entry for managing efficient production and tracking off of those teams, and it puts it firmly on the shoulders of the software provider. What does that mean for the business? It means that the end users aren't working with stale software. You're not working with software that has a UI from 15 years ago. You're not working with an ad-hoc analytical environment that used to be cool but now uses plug-ins and stuff that your browser doesn't support and ultimately causes it to have problems,” Castro explains.

As businesses are not dealing with these issues from the end user perspective, they're able to take advantage of a very modern, easy to consume and use software experience and focus on their core business functions.

“Despite not directly interacting with it, the work around you is what's driving that environment for you,” says Castro. “You're not putting that burden of three or four extra clicks on somebody, this is just software that's being driven from digital signals; from

integration, automation, and the tasks that the operator is performing.”

This newer approach to software design is how SAP leverages the industry investment companies have made and it is what's ultimately reducing the impact that end users have on that environment themselves.

How manufacturers can focus on business value versus technology

There are different pillars within organisations, which have their own priorities. CEOs, CIOs, CTOs and CFOs are all working together and have overlapping needs that drive different business cases. But they need to have the right information at the top layer to make the right decision for the lowest layers within the organisation. This doesn't happen unless there is a framework in place for the distribution

and analysis of the data that is generated, from the very edges of the manufacturing and supply chain processes to the shop floor.

“If you don't have a way for that information to work its way up to the top, organisations

really struggle to understand where the priority needs to be,” says Castro.

For manufacturers to focus on business value versus technology, Castro believes that they need to intelligently manage profitability and investments. As a result of that additional profitability, they also need to protect that inflow of money and profitable behaviour for the company.

“Is that a CapEx investment? Is it an OPEX investment? Is it better granularity on product quality and an emphasis on quality for certain products or certain areas within a process that are very tricky and cumbersome?” asks Castro. “Maybe it's a new product that you're introducing and as a result, that process isn't fully stable yet. What is the emphasis in how

“Sustainability is an overlay to that, sustainability is a byproduct of efficiency”

SAM CASTRO SENIOR DIRECTOR, SOLUTION MANAGEMENT, LOB DIGITAL MANUFACTURING, SAP

much we put into that project to stabilise it? Those are the goals that are very coveted from the C-suite down, but they really are reliant from all edges of the supply chain and having that information roll all the way up.”

Enterprise-led manufacturing follows in tune with this exactly.

“The enterprise has to provide guidance to the manufacturing and supply chain teams as a whole,” says Castro. Where they want to see improvements and how much they're willing to invest in those improvements, what's it worth? How do you build that community up?”

To understand the role that manufacturing plays in an organisation’s reinvestment strategy, you must first understand where it matches up with other locales in the manufacturing environment.

112.6K+ employees worldwide (Sept. 30, 2022)

160 number of countries

22K+ partner companies

245mn+ Subscribers in SAP’s cloud-based user base

“Manufacturing isn't just a single-faceted environment. It's often made up of plants that have been around for a long time, some that were built up by your own organisation, some that came into the organisation through acquisition,” says Castro. “So you see different heritages and mentalities. They have this communal approach for how the plant manager wants to lead that group in the business forward.”

SAP’s AI standardisation journey

At SAP, being able to take advantage of AI standardisation in a universal way is important.

“You can take and apply these very technical algorithms in order to get information off them. Here's the technology, here are the enablers of data, here are the enablers of AI- and ML-type algorithms that you can use and put together how you see fit,” says Castro. “Then that carries over into

the application side, which says, we know we have these technologies, we know that this data is being generated from our transacting processes, so we have our own structured analytics pieces and now we can use these structures to drive our own models to influence our execution process.”

SAP has global partners, as well as local partners, who rely on its technology. When Castro talks about partnerships, he does not put one partner over another.

“We try to keep the community as open as possible,” he says. “We try not to promote one partner over another, because they're all very important to us.”

The openness of SAP and the openness of its software is for its customers to take advantage of, but also for their partners to put their own industry expertise behind.

“It is what gives SAP the power that we have to leverage in our own technologies to leverage partner-led innovation using those technologies to intelligently power our applications.”

“ You want it to be like clockwork, where everything always aligns. But we know that that's not always the case”

SAM CASTRO SENIOR DIRECTOR, SOLUTION MANAGEMENT, LOB DIGITAL MANUFACTURING, SAP

GENERATIVE AI AND ML FUELLING A REVOLUTION IN DATA QUALITY

By automating and simplifying data management tasks like never before, generative AI technologies will revolutionise how organisations handle their data

WRITTEN BY: MARCUS LAW

Anew data quality revolution is underway, powered by models that use generative AI and machine learning techniques such as ChatGPT. Although the use of AI in the data industry has, until now, mainly focused on predictive analytics, today we are entering an era of creative generative AI, where a powerful tool for NLP, data analysis, and automation will shape the future of data management and data quality.

Used in the data industry since the 1950s and 1960s – when they were developed to process and analyse data – early AI programs used rule-based systems, symbolic reasoning, and expert systems to make inferences and generate insights from data. Today, use of AI has accelerated dramatically:

according to the Data and Analytics

Leadership Annual Executive Survey 2023, 80.5% of data executives indicate that AI/ ML will be an area of increased data and analytics investment during 2023 and it will be the highest investment priority for 16,3% of them, followed by data quality for 10.6% of organisations.

“Data quality is a make-or-break aspect of data management,” explains Davide Pelosi, Manager, Solutions Engineering at data integration and data integrity leader Talend. “It ensures that businesses can make informed decisions based on accurate, complete, and consistent information. When data quality is poor, it can lead to errors in decision-making, loss of revenue, and damage to a brand's reputation.

“Fortunately, software solutions providers are leading the charge in innovative data quality tools and techniques that help businesses identify and fix data quality problems quickly and efficiently,” he says. “However, there's still much work to be done. In a recent survey, 97% of the people Talend surveyed indicated they face challenges in using data, and their top concern is ensuring data quality, coming in first with almost half of all respondents (49%). That means there's a massive opportunity for improvement - and the rewards can be huge for businesses that get it right.”

Data quality workflows of the future

According to a report by Gartner, by 2025, at least 50% of all data management tasks will be automated. Most will be completed using AI/ML-powered automation, such as generative language models, so it's time for old-fashioned data management techniques to move aside, as ChatGPT and other generative language applications promise to shake the market up.

From content creation to development task automation, these technologies are already making waves in the business world – and their impact on data management and data quality initiatives is, quite frankly, exciting.

“By automating and simplifying data management tasks like never before, these technologies promise to revolutionise how organisations handle their data,” Pelosi comments. “The prospect of nextlevel automation and efficiency means it's easier than ever for businesses to ensure their data's accuracy, completeness, and consistency. Let's take the example of a data quality workflow.

OVER AI/ML

50%: GARTNER PREDICTS OVER HALF OF ALL DATA MANAGEMENT TASKS WILL BE AUTOMATED BY 2025

“BUSINESSES CAN CREATE BUSINESS RULES SIMPLY BY ASKING IN NATURAL LANGUAGE, WITHOUT NEEDING DEVELOPMENT OR COMPLEX UIS”

DAVIDE PELOSI MANAGER, SOLUTIONS ENGINEERING, TALEND

LLMs and NLP

Large language models like GPT-4 or Google’s LaMDA use Natural Language Processing (NLP) to understand and respond to human-generated text inputs in a conversational manner. A subfield of AI that focuses on enabling computers to process and understand human language, these models utilise NLP techniques to analyse and interpret the text input it receives – including tasks such as partof-speech tagging, named entity recognition, sentiment analysis, and language modelling. These NLP techniques help related tools understand the meaning, context, and intent behind the text input, allowing them to generate relevant, coherent responses in a conversational style.

quantify the severity of the issues. Then, based on the assessment results, generative language models can be used to suggest data quality rules and transformations in natural language text that business stakeholders can easily understand.”

From there, these proposed rules can be reviewed and validated by data quality experts and business stakeholders, who may accept or reject them or suggest modifications to better align with their business requirements.

“Businesses can also create additional Business Rules simply by asking in natural language, without needing development or complex UIs,” Pelosi adds. “For example, a business user might ask, ‘Please raise the acceptable age to drink alcohol to 18 and mark all the people not following the rule as not being targeted for the spring marketing campaign’, like we do today with Alexa. Once the rules are accepted, they can be converted into executable code, such as Python or SQL, using a similar, template-based approach.

“Of course, before deploying the code to production, it will need to be tested and validated using a sample of data to ensure the rules are working as expected and the data quality metrics are being met. But, once done, the cleaned data can be used for various downstream tasks, from data analysis and visualisation to machine learning and business intelligence.

DAVIDE PELOSI MANAGER, SOLUTIONS ENGINEERING, TALEND

“Picture this: the world of data management and quality is about to undergo a significant transformation, and we've got a sneak peek at what's coming. Although the use of generative language models in this field is still in its infancy and is being researched by industry experts, there are already some jaw-dropping research projects and prototypes out there that show the mind-boggling potential of this technology.”

“GENERATIVE LANGUAGE MODELS CAN BE USED TO SUGGEST DATA QUALITY RULES AND TRANSFORMATIONS IN NATURAL LANGUAGE TEXT THAT BUSINESS STAKEHOLDERS CAN EASILY UNDERSTAND”

Hello World: Meet Generative AI | Amazon Web Services

Great care needed to deal with current limitations

With human-level performance on various professional and academic benchmarks, the latest version of OpenAI’s GPT technology, GPT-4, is highly impressive.

Despite its capabilities, however, GPT-4 has similar limitations as earlier GPT models. “Most importantly, it still is not fully reliable,” the OpenAI team says. “Great care should be taken when using language model outputs, particularly in high-stakes contexts, with the exact protocol (such as human review, grounding with additional context, or avoiding high-stakes uses altogether) matching the needs of a specific use-case.”

Aaron Kalb, Chief Strategy Officer and Co-Founder at Alation, reiterates this final point: tools like GPT should not yet be trusted to advise on important decisions.

“That’s because it’s designed to generate content that simply looks correct with great flexibility and fluency, which creates a false sense of credibility and can result in

so-called AI ‘hallucinations’.

As Kalb – who, when working at Apple, was part of the founding team behind its groundbreaking Siri voice assistant – explains, the authenticity and ease of use that makes GPT so alluring is also its most glaring limitation: “Only if and when a GPT model is fed knowledge with metadata context – so essentially contextual data about where it’s located, how trustworthy it is, and whether it is of high quality – can these hallucinations or inaccurate responses be fixed and GPT trusted as an AI advisor.”

“GPT is incredibly impressive in its ability to sound smart. The problem is that it still has no idea what it’s saying. It doesn’t have the knowledge it tries to put into words. It’s just really good at knowing which words ‘feel right’ to come after the words before, since it has effectively read and memorised the whole internet. It often gets the right answer since, for many questions, humanity has collectively posted the answer repeatedly online.”

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How data engineering is powering Pinterest’s global platform

WRITTEN BY: MARCUS LAW

PRODUCED BY: LEWIS VAUGHAN

With more than 460 million ‘Pinners’ using its platform each month, Pinterest is powered by its data architecture, ML and experimentation platforms

Pinterest is the visual inspiration platform people around the world use to shop for products personalised to their taste, find ideas and crafts to do offline, and discover the most inspiring creators.

Beginning as a tool to help people collect the things they were passionate about online, today more than 460 million people flock to Pinterest’s platform every month to explore and experience billions of ideas.

Central to powering this platform is data engineering on a vast scale – as Dr. Dave Burgess, VP of Data Engineering at Pinterest, explains.

“In Data Engineering we create and run reliable and efficient planet-scale data platforms and services to accelerate innovation at Pinterest and sustain our business,” he says. “We do everything from online data systems to logging data, big data and stream processing platforms, analytics and experimentation platforms, machine learning (ML) platforms, and the Pinterest Developer Platform for external developers to build applications using Pinterest APIs.”

As Burgess explains, one of the biggest challenges in data engineering is improving Pinterest’s developer productivity, which is measured through surveys and the time taken to complete tasks: “For example, the time it takes to train and deploy a new machine learning model or run an experiment.”

From the survey results, a developer productivity NPS (Net Promoter Score) is calculated, from +100 to -100. “When I first started at Pinterest four years ago, our developer productivity NPS was -5 and now it’s +65.”

Since joining the business four years ago, Burgess has overseen the replacement of many of Pinterest’s data engineering systems with the latest in open-source software. “We’ve also built machine learning and experimentation platforms on top of our data platform, increased ML Engineering velocity by 10x and run hundreds of new experiments every week,” he adds. “We’ve also democratised our data so that everyone in the company can use data to make decisions, build applications and experiment. All of this has significantly improved our agility, developer productivity, and the products for our customers.”

2010 Year founded

$2.8bn Revenue in 2022

4K+ Employees around the globe

460m+ Monthly users

Pinterest’s machine learning and experimentation platforms

‘Under the covers’, according to Burgess, Pinterest is a ‘massive ML machine’: “We use ML to generate recommendations for our home feed, search results, related products, advertising, and also have augmented reality for our Pinners (the affectionate name we call our users) to see makeup on their face.”

Central to Pinterest’s success is its ML platform. Used to power everything from product recommendations and image categorisation to online advertising and spam filtering, Burgess explains that it enables Pinterest’s engineers to be significantly more productive.

“Our ML engineers can iterate much more quickly, building and deploying new ML models in a day, performing offline training

“In data engineering, we create and run reliable and efficient planet-scale data platforms and services to accelerate innovation at Pinterest, sustaining our business”

DR. DAVE BURGESS VP DATA ENGINEERING, PINTEREST

How

data engineering is powering Pinterest’s global platform

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to iterate and improve their models offline before testing them with real production traffic, and have production ML systems be automatically monitored and self-healed,” he comments.

One such tool is Pinterest Lens, a visual search tool allowing users to search for ideas and products using images. The tech trick behind this feature is computer vision, which identifies objects in photos to suggest related content, allowing users to find similar items on Pinterest. These innovations, Burgess explains, are powered by open-source and internal advancements in ML technology.

“Our ML platform is built with a combination of open source ML technologies, like PyTorch, Tensorflow and MLFlow, and tech that integrates with our own big data and online systems,” he explains. “That enables us

to train ML models and automatically deploy them into serving systems for ML inference.”

Pinterest is an organisation defined by a culture of experimentation. As Burgess describes, its Experimentation Platform encourages experimentation and datadriven decision-making throughout the whole organisation, while also enabling the organisation to test thousands of new ideas.

“Our Experimentation Platform is designed to support rapid iteration and the continuous improvement of our products, and allow us to quickly test and refine new features, user interfaces, and other elements of the user experience. By using data to guide our product development decisions, Pinterest is able to better meet the needs and preferences of our users, as well as increase inspiration.”

Pinterest had long recognised the need to optimise its data storage system. Using HBase, the image sharing platform was carrying a large footprint, with more than 50 clusters and data totalling one petabyte. Enter PingCAP, an enterprise company launched in 2015 by seasoned infrastructure engineers frustrated with the way databases were managed, scaled and maintained.

Seeing no capable solutions on the market, they built TiDB, an advanced, open-source, distributed SQL database for powering modern applications with elastic scaling, realtime analytics and continuous access to data.

What was Pinterest trying to achieve?

“Pinterest’s storage and caching team wanted to find their next-generation, unifying storage system,” explains Liquan Pei, Principal Technologist at PingCAP. “As a NoSQL database, HBase offers a very simple key value interface, but the business logistics are complex. To add new features, Pinterest had to build additional layers on top of HBase, which incurs a very high maintenance workload.” With those motivations in mind, Pinterest

evaluated more than 15 solutions and settled on TiDB in 2020. Pei says the reason for Pinterest choosing PingCAP came down to TiDB’s robust technical capabilities and PingCAP’s high-quality enterprise support.

PingCAP brings lasting benefits to Pinterest data operations

TiDB is set to bring a host of benefits to Pinterest’s day-to-day operations. When carrying out the project, PingCAP evaluated Pinterest’s secondary index services system and, using TiDB, achieved better performance and 80% cost reduction.

“Because of TiDB’s capabilities, we were able to reduce the system from six components to one, greatly reducing the maintenance burden,” adds Pei. In the long run, TiDB’s expressiveness and scalability should also help Pinterest’s IT teams from a practical perspective. Pei continues: “People from Pinterest will enjoy peace of mind because a lot of work is handled by TiDB, so they can focus instead on more impactful work.”

As Pinterest went in search of a next-generation, unifying data storage system, the company found the perfect solution in PingCAP’s TiDB

A next-generation data warehouse

One of the number of changes made in Pinterest’s data systems involves the building of a next-generation data warehouse and the transition to a Data Mesh: an emerging approach to data architecture that aims to address the challenges of managing large and complex data environments, which was first introduced by Zhamak Dehghani – a software architect at ThoughtWorks – in 2019.

“At a high level, Data Mesh is a decentralised data architecture that emphasises data ownership and autonomy,” Burgess explains. “Rather than having a central data team manage all the data for an organisation, Data Mesh encourages each business unit or team to take ownership of their own data domains, managing their data in a way that is best suited to their needs.”

This approach involves breaking down data into smaller, more manageable domains that can be owned and managed by individual teams. Each team is responsible for the data within their domain, including defining the schema, ensuring data quality, and providing access to other teams that need to use the data.

To enable collaboration and sharing across domains, Pinterest has a catalogue of schemas and metadata stored in Apache DataHub, has standardised its data vocabularies and metrics, has tiered the quality of its data, and has integrated its open-sourced Querybook platform to collaborate and share SQL queries.

“Querybook is an open-source data collaboration platform developed by Pinterest,” Burgess explains. “It has a userfriendly interface for data analysts and engineers to collaborate on data analysis

tasks, allowing them to share queries, datasets, and insights with one another. It’s the most popular and highly-rated internal tooling platform at Pinterest.”

As Burgess describes, Querybook also benefits from advanced data analysis capabilities for ad-hoc data analysis, generating visualisations, and even building machine learning models: “We’ve also built a ChatGPT-like interface to automatically generate and execute queries from a text business statement. For example, you could ask it how many daily active users there are on Pinterest over the past month and it will generate a SQL query with the right tables and fields.”

“Overall,” Burgess asserts, “Data Mesh represents a new way of thinking about data architecture that helps us to manage our large and complex data environment more effectively, while also fostering greater collaboration and innovation.”

DR. DAVE BURGESS VP DATA ENGINEERING, PINTEREST

“By using data to guide our product development decisions, Pinterest is able to better meet the needs and preferences of our users, while increasing inspiration”

Building a successful partner ecosystem Pinterest’s Data Engineering department works with a number of third party partners, including AWS for cloud infrastructure and Percona for MySQL support, along with a number of other companies on open source software such as Netflix, Lyft, AirBnB, AWS, Starburst (for Presto/Trino), StarRocks Technologies, and Preset (for Superset), as well as close collaborations with the open source community.

Another of Pinterest’s partners, PingCAP, has assisted with the deployment of its TiDB system: a distributed SQL database engine that provided users with better data consistency, reducing tail latencies by 30-90% while reducing hardware instance costs by more than 50%.

“We had been using an older version of HBase for many years, which is a scalable open-source, distributed, column-oriented NoSQL database,” Burgess explains. “We’ve made many fixes to HBase over the years to make it faulttolerant at our scale on AWS, used it for different kinds of use cases, and added a lot of functionality on top.”

“The biggest pain points with this older version of HBase were: the total cost of ownership to maintain and run this; limited functionality, which led to lower engineering productivity and increased application complexity; the lack of data consistency across tables, affecting our users’ experience; and the scalability requirements our internal users wanted to run at.”

This partnership with PingCAP to use TiDB is already reaping benefits, providing better data consistency, a lower total cost of ownership, and more powerful features than the previous solution, HBase.

“As a NewSQL database, TiDB provides a scalable solution in a huge problem space for use cases that need stronger consistency or richer functionalities”, Burgess explains. “It fills in the gap between our existing SQL and NoSQL systems, allowing developers to build

storage applications faster without making painful tradeoffs.”

“All these factors combined enable us to more easily build and scale businesscritical applications including shopping catalogues, advertising index systems, trust and safety systems and many more.”

“Data Mesh represents a new way of thinking about data architecture that helps us to manage our large and complex data environment more effectively, while also fostering greater collaboration and innovation”

DR. DAVE BURGESS VP DATA ENGINEERING, PINTEREST

“We will make it easier for Pinners to shop for the things they love. Pinners will be able to go from being inspired to making this a reality in their lives”

DR. DAVE BURGESS VP DATA ENGINEERING, PINTEREST

What are Pinterest’s main aims for the next five years?

As Burgess describes, central to Pinterest’s plans for the future is innovating and creating new technologies and products that put Pinners first. “This means enhancing the user experience and driving growth internationally.”

The organisation will also look to improve its advertising products and expand its advertising partnerships with businesses of all sizes, while becoming a more sustainable and socially responsible company. Reducing its environmental impact is part of the latter, as is promoting diversity and inclusion, in addition to supporting causes related to social and environmental issues.

“We will make it easier for Pinners to shop for the things they love. They’ll be able to go from being inspired to making this a reality in their lives,” Burgess adds. “We will also be a more sustainable company, with almost 100% renewable energy for our operations. This includes renewable energy for our offices and data centres.”

With the space moving quickly, making the most of the opportunities presented by developments in ML and AI will also be central to Pinterest’s success going forward.

“This space is changing quickly with the recent advances in Large Language Models, Stable Diffusion, and Transformer models,” Burgess concludes. “We have the ability to generate images and text answers, augment ML models with more data, recognise objects in images, and create an augmented reality. We can also significantly improve our productivity with AI-assisted bots that generate code and answers.”

“There are many applications of this and it’s going to be a game changer.”

AI-powered biometrics helping fight the rising tide of fraud

AI-powered tools such as behavioural biometrics prevent fraud by detecting high-risk scenarios and helping institutions make better decisions

WRITTEN BY: MARCUS LAW

Already a familiar sight in technology from smartphones to laptops, biometric capabilities are increasingly embedded in everyday life.

With fraud on the rise, biometric technology has become increasingly popular in recent years, with the global biometric market's revenue projected to hit US$83bn by 2027.

Banks worldwide are expected to spend an additional US$31bn on AI embedded in existing systems by 2025 to reduce fraud, according to an IDC report, which also said fraud management featured strongly as a priority for banking executives.

AI-powered biometric verification helping combat identity fraud

Mitek brings the future to business with patented solutions and intuitive technologies that bridge the physical and digital worlds. The company’s leadership in identity verification, including facial biometrics, image capture technology and ID card verification enables customers to confidently onboard users, verify identities within seconds and strengthen security against cybercrimes.

As Chris Briggs, Global SVP of Identity at Mitek, explains, AI-powered behavioural biometrics prevent fraud by detecting highrisk scenarios and helping institutions make better decisions: “For example, if a customer who logs in twice each month suddenly starts logging in more frequently or if a client who always types their password in copies and pastes the password from a different location, those pattern anomalies signal that these logins carry additional risk.”

Research released by ID R&D, a provider of AI-based voice and face biometrics and liveness detection technologies,

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found that humans have greater difficulty identifying images of biometric spoofing attacks compared to computers performing the same task, with machines as much as 10x faster than humans at detecting fake faces.

“Furthermore, AI-powered liveness detection is better than humans at recognising what is real and what is not. It ensures the integrity of a biometric match by distinguishing both identity and liveness, through AI. For example, fraudsters are no longer able to bypass screening processes with photos of a printed image. Also, fraudsters cannot work around liveness, mitigating the threat of identity fraud.”

Biometric authentication and behavioural biometrics

With Verizon’s 2022 Data Breach Investigations Report finding that stolen password credentials were involved in 61% of all company data breaches last year, password technology is clearly no longer sufficient.

Enter biometric technology, where facial recognition or voice verification is used to verify a customer’s identity. “The software measures the capture to create a baseline data point template or the "lock" that will be the determining data point for future uses,” comments Briggs. “This means that only the matching biometrics, whether its

“AI-powered liveness detection is better than humans in recognising what is real and what is not”

BIOMETRIC BIAS

While biometric bias can be part of an identity lifecycle, biometric technology itself is not inherently biased – it is the design of biometric technology that can introduce discrimination, explains Mitek CTO Stephen Ritter.

“Biometric systems analyse the physiological or behavioural traits of an individual for the purposes of identity verification and authentication. This is often conducted through fingerprint and facial recognition technology built on machine learning and AI – all powered by algorithms. Bias occurs when the algorithm operates in a discriminatory fashion, which often stems from how the algorithm is built, designed or tested.”

First solution: Testing standards

“First,” Ritter says, “we need a way to evaluate biometric bias. There is currently no standardised, thirdparty measurement for evaluating demographic bias in biometric technologies.

“The industry needs a way to evaluate the equity and inclusion of biometric technologies. This would give service providers a way to ensure that their solution is equitable, regardless of whether it was built in-house or based on third-party technology from a vendor. This benchmark would provide the public with the information they need to select a service provider that’s more equitable.

Second solution: Global AI guidelines

“Determining ‘what is right’ goes beyond creating accuracy benchmarks – we also need to create ethical guidelines,” Ritter explains. “Until there are ethical guidelines for the use of this technology, there is no way to understand what is ‘right.’

“AI ethical guidelines would serve to solidify the rights and freedoms of individuals using or subject to datadriven biometric technologies. “Until we define what is and is not an ethical use of biometric technology, there is no metric or benchmark that will exist to gauge the quality of technology.”

physiological or behavioural characteristics, provided will confirm a person's identity and unlock the service or account.”

As Adam Desmond, Sales Director EMEA at OCR Labs, explains, biometric authentication is leading the charge in the growing fight against identity fraud: “Banks are already using AI-powered facial biometrics in conjunction with liveness detection to verify faces and documents.

“But voice technology offers the next level up in powerful and convenient biometrics, with a critical role to play in improving anti-fraud defences. In fact, when combined with face biometrics, voice is one hundred times more powerful than face alone. In our experience, the combination of both voice and face biometrics makes the verification process almost impenetrable by fraudsters.”

A step further, into behavioural biometrics, can detect unusual patterns of behaviour to improve security, using what Briggs describes as a ‘behavioural signature’.

“Behavioural biometrics uses customers’ digital breadcrumb trails, as well as how customers approach online logins, to effectively create a behavioural signature that fraudsters are hard-pressed to emulate. Implementing behavioural pattern analysis into continuous verification frameworks adds an additional layer of security that is difficult even for the most sophisticated fraudsters to crack.”

“When combined with face biometrics, voice is one hundred times more powerful than face alone”

ADAM DESMOND SALES DIRECTOR EMEA, OCR LABS

Behavioral biometrics + the future of identity

AI bias in identity verification

Biometric technology itself is not inherently biased – it is the design of biometric technology that can introduce discrimination.

But as Briggs explains, to tackle AI bias in identity verification, we first need a way to evaluate biometric bias: “There is currently no standardised, third-party measurement for evaluating demographic bias in biometric technologies.

“The industry needs a way to evaluate the equity and inclusion of biometric technologies. This would give service providers a way to ensure that their solution is equitable, regardless of whether it was built in-house or based on third-party technology from a vendor. This benchmark would provide the public with the information they need to select a service provider that’s more equitable.”

Determining ‘what is right’ goes beyond creating accuracy benchmarks – creating ethical guidelines is essential.

“AI ethical guidelines would solidify the rights and freedoms of individuals using or subject to data-driven biometric technologies,” Briggs explains. “Until we define what is and is not an ethical use of biometric technology, there is no way to understand what is ‘right’.”

The rise of transparency

As Ricardo Amper, CEO of digital identity company Incode, told Cyber Magazine, trust is critical to the success of AI-powered biometrics.

“But trust is crucial for its success; the impact that biometrics can have can be substantially limited if there is a lack of trust in how the technology is used,” he explained. “Users need to be sure that their data is being used for the purpose it was given and nothing else. This trust is hard to come by,

but if gained, then there will be no limit to the impact biometrics can have on our lives.”

As Briggs explains, the rise of transparency will be an important component of maintaining consumer trust in biometrics: “Consumers are becoming increasingly aware of exactly who and/or what technologies they are interacting with and how the data they are providing is being used. Over the next year, we can expect the leading technology innovators to lead by example – setting rules of engagement and standards for collecting and managing data.

“Separately,” Briggs concludes, “to reduce the risk of new cyberthreats, regulators should begin to define a clear private-public framework to address these problems within the private sector. Consumers should believe the regulators have their backs, but fully understand they themselves are responsible for all aspects of their data and identities.”

The leader in luxury electric vehicles

Barely a decade into the popularisation of electric vehicles, Faraday Future is launching the first ultra-tech luxury electric vehicle: meet the FF 91

WRITTEN BY: CHARLIE KING

PRODUCED BY: TOM LIVERMORE

Prashant Gulati is the esteemed Vice President of Strategy at Faraday Future. Now in his seventh year with the company, he handles the entirety of its strategic roadmap, which includes overseeing the business plan, mobility initiatives, manufacturing strategy, and directing fundraising efforts.

Fundraising is a key part of Gulati’s role: “My proudest professional achievement has been co-leading the public offering, which helped the company raise more than $1bn through a listing on NASDAQ,” he says.

With over 20 years of success in the technology and automotive industries, Gulati is an accomplished executive with a track record of scaling businesses. He has successfully led a public offering and held leadership roles to drive growth and expansion at several companies globally. In recognition of his industry contributions, Gulati was selected for the coveted Business Insider list of EV Industry Power Players.

Gulati holds a bachelor's degree in computer science and an MBA from the Indian School of Business.

Having grown up in India, Gulati has always had a deep affinity for the environment. This draw of environmental stewardship was heightened when Gulati and his wife were expecting their first child. “I had a sense of urgency to contribute to technology that could help slow climate change and create a better world for our children to grow up in,” he explained.

“I explored numerous fields, including renewable energy, smart grids and energy storage, before focusing on EVs and finding

Faraday Future. I immediately clicked with the company as it had such a bold vision and fit the environmentally-focused technological approach I was seeking. My journey into the auto industry has been quite unusual – almost accidental.”

Faraday Future: driving the EV industry

“Climate change is the defining challenge of our time, and transportation is one of the largest contributors to it,” says Gulati. “At the same time, the world cannot slow down. We need more growth, more productivity, more time to commit to our passions. So, at Faraday Future, we've been working on the intersection of these problems - of clean mobility and climate change on one

“We were founded with the mission to help people live, move, and breathe more freely – and that's one of the things that drives a lot of us”

PRASHANT GULATI VICE PRESIDENT OF STRATEGY, FARADAY FUTURE

hand, and helping people lead productive, connected lives on the other.”

Faraday Future has taken the first step towards achieving that mission by building the FF 91, which Gulati believes is the most connected, comfortable, and technologically advanced electric car in the world. The company achieved start of production of the FF 91 in California and plans to sell it through a direct sales model in its dual home bases of the US and China.

“The vision of the company is much more than building and selling electric cars, though,” Gulati tells us. “We want to engage our users, build a community, and offer internet and AI services throughout the vehicle lifecycle.”

PRASHANT GULATI

TITLE: VICE PRESIDENT OF STRATEGY

INDUSTRY: MOTOR VEHICLE MANUFACTURING

LOCATION: UNITED STATES

Prashant Gulati is the esteemed Vice President of Strategy at Faraday Future. Now in his seventh year with the company, he handles the entirety of its strategic roadmap, which includes overseeing the business plan, mobility initiatives, manufacturing strategy, and directing fundraising efforts.

With over 20 years of success in the technology and automotive industries, Gulati is an accomplished executive with a track record of scaling businesses. He has successfully led a public offering and held leadership roles to drive growth and expansion at several companies globally. In recognition of his industry contributions, Gulati was selected for the coveted Business Insider list of EV Industry Power Players.

Gulati holds a bachelor's degree in computer science and an MBA from the Indian School of Business.

BRINGING IDEAS TO LIFE FROM CONCEPT TO CONSUMER

WE DESIGN. WE ENGINEER. WE MANUFACTURE.

Achieve your product goals with JVIS

Our advanced electrical and lighting, battery storage, and thermal management solutions are the key to turning your ideas into reality. Trust us to provide smart solutions for your global technology needs and deliver results beyond your expectations.

Contact us today and let’s bring your product vision to life together.

JVIS USA: BRINGING IDEAS TO LIFE IN THE EV INDUSTRY

In an exclusive interview, Jason Murar, President and CEO of JVIS USA, discusses how JVIS is pioneering the EV industry while supporting Faraday Future

JVIS USA is a world-renowned manufacturing leader boasting unrivalled proficiency across both design and engineering. Blending state-of-the-art technologies with vertically-integrated processes, the company guides a concept from the initial sketch to the final product launch, and everything in between.

By prioritising innovation, JVIS has established itself as a leader in the continuous shift towards electric vehicles (EVs). It specialises in delivering technology and components uniquely optimised for EVs, continuously seeking out novel concepts, technologies, and procedures.

JVIS has also played a vital role in supporting Faraday Future (FF) to unveil their vehicles to the market. Jason Murar, President and CEO of JVIS USA, explains:

“We’ve assisted FF in almost every facet, from the initial product development – where we identified key product innovations for their consumers – all the way through to the actual testing and validation, in compliance with automotive standards for those components and the continuous supply of critical components used in their vehicles.

Advancements in the EV market

Armed with impressive electrical solutions, JVIS employs the latest technology, such as capacitive touch surfaces and smart panels.

Murar says: “In the EV market, you see a lot of change with smart panels, which are now highly integrated into both the exterior and interior of vehicles.”

JVIS is committed to leading the development of the EV industry, particularly as it plays a large part in the company’s growth. “Our customers see how we’re taking static panels and turning them into functional panels, giving expanded use of the vehicle,” Murar explains. “These components include sensors and software to increase the user’s experience, such as soft-close doors and ambient lighting.

“JVIS’s continued investment in innovation and growth will enable us to make significant contributions to this dynamic field. If you are looking to turn your product ideas into reality, contact us today to learn more about how JVIS technology can help.”

Throwing out the rule book in electric vehicle development

Faraday Future started from scratch, taking a “clean sheet approach” to building electric cars. Faraday Future’s technology innovations include its proprietary Variable Platform Architecture (VPA), propulsion system, and Internet, Autonomous Driving, and Intelligence (I.A.I.) systems. The company has approximately 660 patents across these areas.

“So far, the company has invested billions of dollars in creating industry-leading product and technology,” recounts Gulati. “Building cars is a capital-intensive business, and we've had our ups and downs.

“The way I would describe the ethos of the company is one of perseverance and tenacity; one of never, ever giving up in the service of our mission.”

FF 91: A new species reformatting the future of mobility

The FF 91 has been designed as an all-ability car, possessing the handling of a sedan, the space, reliability, and comfort of an SUV, and the top-level performance and driving dynamics of a sports car.

“A lot of people liken it to a Rolls-Royce, with increased comfort, connectivity, and performance ” Gulati tells us – and the statistics certainly speak for themselves.

“There's a lot that has gone into developing and thinking about the design, driving experience, and the overall user experience” says Gulati who is incredibly passionate about the vehicle.

“There is no electric car in our segment right now – competing with Rolls-Royce, Bentley, Maybach – so we're quite excited

about being the first EV of our kind, and we think it's going to redefine industry standards. The first ultra-tech luxury electric vehicle.”

Faraday Future: the leader in luxury electric vehicles WATCH NOW

“We are building what we believe is the most connected, most comfortable, most technologicallyadvanced electric car in the world: we call it the FF 91”

PRASHANT GULATI VICE PRESIDENT OF STRATEGY, FARADAY FUTURE

The technology under the bonnet Faraday Future describes the technology behind the FF 91 within three pillars:

1. Variable Platform Architecture

“Think of it like a Lego,” Gulati explains: “You can change the size of the platform and build different vehicles of different sizes for different purposes. You can put different motor and powertrain configurations. This skateboard-like platform approach enables us to build multiple vehicles on the same platform, reduce time to cost, time to market, and more.”

2. In-house Propulsion Technology

Faraday Future has developed a proprietary inverter design and propulsion system. The drive units are fully integrated with the inverter, and transmission and control unit to enable leading horsepower, efficiency, and acceleration.

3. Internet, Autonomous Driving, and Intelligence (I.A.I.)

“Our software, internet, and AI development is the most important of these pillars,” says Gulati. “That's where the company shines compared to all of our competition.” Faraday Future’s commitment to these technologies supports the user experience in the car, both practically and luxuriously, ensuring seamless user experience through different elements, one of which is advanced voice control to manage complex queries without driver or passenger distraction.

FF 91

The FF 91 has:

• 3 motors

• 1,050 horsepower

• 0 to 60 in 2.27 seconds

• Class leading EPA and CARB certified range of 381 miles

• Charge Time (20-80%): 25 min @ 200kW DC Fast Charge

• Overall length: 5,250mm/ 206.7in

• Up to three 5G modems and a newly developed operating system, allowing customers to use apps and stay fully connected

• Industry-leading 49 inches of rear seat legroom

• 60-degrees rear seat recline in NASA-inspired, zero-gravity seats

Supply chain management

Faraday Future invested a lot in creating its own technology. “Some companies basically source parts and build a car, essentially becoming assemblers,” explains Gulati. “At Faraday Future, we've invested a lot of time and capital on creating our own technology.”

Faraday Future has strong partnerships with, and relies on, key suppliers to ensure the FF 91 is completed in a timely manner and with the high quality its users will demand. The company was affected to a lesser degree by supply chain issues during the pandemic because of planned low volumes at launch, and because many of the parts are created by suppliers uniquely

for the FF 91, and so we don't compete with others for those. Notwithstanding, the company has taken lessons from that period and gotten even more diligent about planning and ordering across the supply chain.

In terms of scale, Faraday Future employs 590 people across the US and China, and with its production plant in California the company will ultimately be capable of producing approximately 10,000 vehicles per year. The current manufacturing setup is asset light, and the supply chain is built with expansion in mind: if needed, the company has a contract manufacturing partner for this anticipated expansion, allowing early-stage flexibility.

What does the future hold for Faraday Future?

“The company's DNA is completely global,” Gulati says: “We've designed and defined the product with an abundance of cutting-edge technology to cater to a global audience.”

The company is headquartered in Los Angeles, where much of the engineering and manufacturing takes place, but it also has roots in China – home to a Faraday Future engineering centre. The FF 91 will be initially launched in the US, followed by China, before being launched globally.

Distribution and beyond

“Looking to the next 18 months, we are very focused on the FF 91 production, sales, and

“Climate change is the defining challenge of our time, and transportation is one of the largest contributors to it”

PRASHANT GULATI VICE PRESIDENT OF STRATEGY, FARADAY FUTURE

deliveries,” Gulati explains. “We're going to be scaling our operation, ramping up supply chain – that's the key focus area making the FF 91 successful.

Gulati believes that the value chain disruption we’re seeing now is going to continue, not only accelerating on the product and technology front, but on the sales side, too, as industry sales volumes increase.

“In the distribution model, quite a few OEMs have expressed a desire to sell directly to customers” Gulati explains.

“For the industry, this transition away from ICE (Internal Combustion Engine) vehicles is going to impact sales economics. Today, auto dealers mostly earn margins from selling auto parts and services, and financial services, and that's going to change. Maintenance and parts and services replacement in EVs is far less than ICE vehicles. So, we expect to see changes on the business side as well as on the product and technology side.”

Despite this value chain disruption and anticipated global economic slowdown, Gulati himself doesn’t forecast a slowdown for Faraday Future, citing research from McKinsey that shows the luxury vehicle market (vehicles $150,000 and above) is projected to grow significantly over the next 10 years.

FF 91: The mould for the future

Looking to the longer-term future, Faraday Future has ensured built-in capability to add further models to its Variable Platform Architecture.

“We have plans for our next model –we call it the FF 81 – which will share 60% commonality of parts with the FF 91,” Gulati says. “Although, of course, such future developments are dependent on a number of things, including fundraising.”

What is the future for the electric vehicle industry?

To promote long-term growth and success within the electric vehicle industry, Gulati says the focus is – and should remain –on batteries, reducing cost of materials, recycling, and developing new chemistries.

“Since 2010, the price of batteries has dropped significantly – until about 2019,” Gulati recounts. “In the last few years, battery and raw material prices have risen again because of supply chain disruptions, due to the pandemic.”

The second focus that Gulati expects of the industry is in EV infrastructure.

“We are seeing significant regulatory support to promote the transition to electric vehicles,” he says. “Governments are allocating a lot of capital and policy support towards education, charging infrastructure, and local sourcing of electric cars, so we anticipate that will continue.”

The future is on its way – and it looks electric.

“We need more growth, more productivity, and more time to commit to our passions”

PRASHANT GULATI VICE PRESIDENT OF STRATEGY, FARADAY FUTURE

Data & the IoT key to smart cities of the future

Data is the lifeblood of smart cities like Barcelona, transforming everything from shopping and transportation to autonomous driving and augmented reality

WRITTEN BY: MARCUS LAW

By 2050, two-thirds of people globally are expected to live in cities. As urbanisation continues to rise, cities are facing new challenges that require innovative solutions.

Enter the Internet of Things (IoT), a network of interconnected devices that collect, analyse and share data. IoT is the backbone of smart cities, enabling the seamless integration of technology into urban infrastructure and services.

to enabling future

Get reliable network coverage and security protection, fast.

A modern network must be able to respond easily, quickly and flexibly to the growing needs of today’s digital business. Must provide visibility & control of applications, users and devices on and off the network and Intelligently direct traffic across the WAN. Be scalable and automate the process to provide new innovative services. Support IoT devices and utilize state-of-the-art technologies such as real-time analytics, ML and AI. And all these must be provided with maximum security and minimum cost.

This is the power that brings the integration of two cloud managed platforms, Cisco Meraki and Cisco Umbrella. This integration is binding together the best of breed in cloud-managed networking and Security. cisco.com

And just what are smart cities? Think about your phone and its capabilities, but on a city-wide connectivity scale. In essence, they are crucial for addressing urban challenges, with the IoT playing a pivotal role in their success – from water and electricity, traffic flow, and parking to refuse removal and sewerage – creating more effective, efficient management.

At the heart of the smart city is the smart sensor. Distributed in the tens of thousands across smart city test neighbourhoods, or even entire boroughs, IoT sensors monitor everything from traffic patterns and footfall to utility usage and emissions.

If local governments are curiously eyening smart city capabilities in their own backyard, they need to look at deploying

sensors while making use of those that already exist, harnessing the vital data required to catapult their cities into the future.

Data key to enabling smart cities

In smart city environments with IoT, everything from vehicles to hand-held devices is constantly interacting with one other, generating not only a large volume of data, but also different variants of datasets.

As Tikiri Wanduragala, Senior Consultant for Infrastructure Solutions at Lenovo, explains, this data is the lifeblood of smart cities. “It flows directly between the cameras, sensors and metres that connect our community services, from transport systems to water networks.

SMART CITY TECHNOLOGIES

Smart cities are powered by cutting-edge technologies that transform urban infrastructure and services. These include Internet of Things (IoT) devices that collect and analyse data to optimise resource allocation, improve transportation systems, and enhance public safety.

Advanced sensors and monitoring systems provide real-time data on air quality, traffic patterns, and waste management, allowing for data-driven decisionmaking. Artificial Intelligence (AI) and machine learning algorithms process data to enable predictive analytics and optimise energy consumption, water management, and urban planning. Additionally, smart grids, renewable energy sources, and intelligent transportation systems are some of the key technologies utilised in smart cities to create sustainable, efficient urban environments.

“Using data to enhance the lives of their citizens, smart cities represent the future of urban existence,” he explains. “Yet, for all the promise, cities across the globe are still failing to make the most of data and harness its potential within urban spaces. This will be fundamental to planning and designing smart cities around the world, with urban planners relying on data from both public bodies and private organisations to design and build truly forward-looking smart cities.”

Key to the concept of the smart city is the ability to manage assets and resources. As Eckart Zollner, Head of Group Business Development at Jasco Intelligent Technologies, told Technology Magazine recently, this

requires data from many thousands of data capture points – so-called ‘connected devices’ – to instantaneously transmit information to a central server. The IoT forms the platform and network for this data collection and transfer, as well as the resultant analysis and intervention. These devices include water and electricity meters, environmental sensors, flow meters, level sensors, parking sensors, a variety of tracking devices, RFID readers and more.

However, managing these datasets to ensure such data doesn’t go stale is a foreseeable challenge of the future. As a result, many technologists now look to the best of cloud and edge computing as a critical solution in managing data.

Data helping make Barcelona a flagship smart city As Wanduragala describes, Barcelona’s smart city pilot demonstrates how the smart application of data can transform everything from shopping to transportation, enabling services from autonomous driving to augmented reality.

“Its famous La Boqueria market, for example, was the site of an innovative 5G trial providing shoppers with a virtual shopping experience. This used augmented reality to create a unique link between real-world market shopping and ecommerce,” he says.

The pilot smart city programme is also using data to power experiments

“The growth in smart city applications, suppliers, and integrations also increases the potential for supply chain attacks and third-party vulnerabilities”

ILAN BARDA CEO, RADIFLOW

analysing how to monitor and control traffic, with an autonomous bus driving tourists to the Fira de Barcelona Gran Via venue while roadside cameras monitor traffic for accidents. “Data is also being used to investigate ideas such as ‘smart factories’ and ‘holographic’ teaching, where teachers appear remotely,” Wanduragala adds. “The smart city uses 5G to transform lives without the high costs of wired installations – and the city pulses with data.

“Data is delivered rapidly where it is needed with the help of edge computing enabled by server cabinets dotted around the city,” comments Wanduragala. “Edge computing is a distributed paradigm that brings computing power closer to the sources of data. It means that data doesn’t need to be sent to a far-away data centre for processing, enabling the sort of rapid decisions and responsive services that power a smart city.”

Securing connected devices to ensure the security of smart cities

The rapid proliferation of connected devices in smart cities has brought unprecedented opportunities for improved urban living. However, as the IoT becomes increasingly intertwined with critical urban infrastructure, securing these devices is critical.

Over the next five years, the smart city threat landscape is expected to grow in complexity and sophistication, with an everincreasing number of connected devices and integrated systems. As Ilan Barda, CEO of Radiflow, explains, this growth will inevitably create more opportunities for cybercriminals to find new back doors into systems and more data for them to target.

“The growth in smart city applications, suppliers, and integrations also increases the potential for supply chain attacks and thirdparty vulnerabilities. Critical infrastructure systems, such as ITS (Intelligent Transportation Systems), DER (Distributed

Lenovo Tech World 2022: The Smart City of Barcelona with Kirk Skaugen WATCH NOW

Energy Resources), and electric car charging will be widely deployed and will certainly become an attractive target for cyber attackers, and we will likely see attempts to breach these systems increase – especially by state-sponsored attackers.

“The use of both AI and ML in smart city systems will also increase, helping improve the efficiency of systems and expand their advantages. However, this will also create new avenues for attack through the cloud, as well as make the detection of malfunction behaviours more difficult.

“To address these continuously evolving threats, stakeholders must take a proactive and collaborative approach to cybersecurity, including regular security assessments, vulnerability management, incident response planning, staff training, and awareness programmes. Strong authentication, encryption, network segmentation, disaster recovery pnanning, and business continuity planning are also essential components of any effective smart city cybersecurity strategy.”

“The smart city uses 5G to transform lives without the high costs of wired installations – and the city pulses with data”

TIKIRI WANDURAGALA SENIOR CONSULTANT FOR INFRASTRUCTURE SOLUTIONS, LENOVO

Today, 54% of people worldwide live in cities, a proportion that’s expected to reach 66% by 2050.

WRITTEN BY: ILKHAN OZSEVIM

Leveraging procurement to shape the future

PRODUCED BY: MIKE SADR

Linda Siegert, SailPoint's SD of Global Procurement, on leveraging culture, sustainability & transparency in procurement to drive long-term strategic success

As technology accelerates at near-exponential rates, invariably bound up with the internet and big data, security considerations explode in accordance with this growth. A very large part of these security concerns is around ‘identity’.

PwC’s recent Global Economic Crime and Fraud Survey found that of 1,296 executives surveyed across 53 countries and regions, 51% of organisations said they had experienced fraud in the previous two years – the highest level in PWC’s 20 years of research.

We interviewed Linda Siegert, the Senior Director of Global Procurement for SailPoint Technologies, to find out how they leverage culture in procurement to influence the future.

SailPoint is the leading provider of identity security for the modern enterprise. They help organisations discover, manage and secure all identities across all environments.

As Senior Director of Global Procurement, Siegert began her career in accounting and quickly found that while she was good at the numbers, she more enjoyed the working relationships and the stories that the numbers could tell. Siegert transitioned into an HR role and then HR leadership, which further solidified how much she enjoyed “empowering people for success”.

SailPoint rope wall seating area at Austin HQ

EXECUTIVE BIO

LINDA SIEGERT

TITLE: SENIOR DIRECTOR OF GLOBAL PROCUREMENT

INDUSTRY: SOFTWARE DEVELOPMENT

LOCATION: UNITED STATES

SailPoint is a leading provider of identity security for the modern enterprise, empowering organisations worldwide to put identity security at the core of their business. With a foundation of artificial intelligence and machine learning, SailPoint identity security delivers the right access to the right identities and resources at the right time.

Linda Siegert, Senior Director of Global Procurement

Leveraging procurement to shape the future

“Procurement is really the brilliant marriage of the two: the numbers and the people. It enables me to do what I'm passionate about — giving me a unique perspective and approach to our strategic goals.”

“Today, I have the privilege of leading an incredibly talented procurement team with a focus on sustainable strategic procurement that stretches beyond simple spend management, but also includes risk in contractual management, supplier lifecycle management, compliance and audits and sustainability throughout the entire lifecycle. It allows us to be on a continual growth track. The exciting part is the continual maturity road on which I get to lead the team.”

Now at SailPoint, Siegert has set her sights on the intersection between culture, sustainability in procurement activity. These aspects mesh more naturally than one would expect.

“ We don't view the buying landscape as just a numbers game – because numbers are only a part of our overall success”

LINDA SIEGERT SENIOR DIRECTOR OF GLOBAL PROCUREMENT, SAILPOINT

WATCH NOW

SailPoint's unique procurement philosophy: the four ‘I’s Siegert says that SailPoint sets itself apart in that the company “lives and breathes culture” through the Four ‘I’s of Innovation, Impact, Individuals and Integrity.

Within procurement, these values are cornerstones to every interaction. They inform buying approach and allow the procurement team to look past dollars to drive ROI deeper into the business.

“Our dollars shouldn't just buy things, they should grow things,” Siegert says. “We don't view the buying landscape as just a numbers game - because numbers are only a part of our overall success.

“There really is no single way to solve a problem, and just because it’s worked ten other times already, that doesn't mean it's going to work for an eleventh”

LINDA SIEGERT SENIOR DIRECTOR OF GLOBAL PROCUREMENT, SAILPOINT

Use

SailPoint cafe at Austin HQ

“When two companies interact, it's relational, and if we're to achieve long-term strategic success, we can't only focus on the numbers. We need to look deeper, expect higher values from our suppliers, and ensure that our suppliers’ company goals align with SailPoint's goals for spend sustainability.”

SailPoint utilises its core values to maximise the value of its supplier interactions because, says Siegert, “within this structure, success can always be found.”

Core message as it relates to procurement Siegert says that what separates SailPoint is its ability to think outside of the box.

“We don't have to think like mainstream procurement,” she says. “Let's think from a human perspective; let's think from a creative perspective and use organisational values to provide a natural foundation for procurement strategic thinking.

“There really is no single way to solve a problem, and just because it's worked ten other times doesn't mean it's going to work for an eleventh. It’s important to always be thinking of a better way to do it. When it comes to our foundational core values for innovation within the procurement team, we're developing real solutions for challenges and solving problems.

“When we engage with suppliers, we are solving a need. Our suppliers and all those we have relationships with understand our challenges. They know there's a bottom-line impact – and they want to make us better. When we combine our knowledge with our suppliers to create a truly successful relationship, both parties win.”

Asked about overarching goals, Siegert says: “Our goal always is impact.” She points out that for SailPoint procurement, success

is based on measurable results, and this takes the form of KPIs, in-depth due diligence and clear standards for excellence and engagement.”

“We value individuals and both the work they do and the roles they serve. We treat people with integrity and deliver on the commitments that we make - and we expect others to deliver on the commitments that they themselves make.”

“We base our relationships on trust and offer honest solutions. We want our suppliers to do the same for us. If there are issues that need to be resolved, we do it with transparency. Achieving and maintaining strong, healthy relationships is foundational.”

Transparent supplier engagements Siegert says that SailPoint procurement approaches its supplier engagements

“When it comes to our foundational core values for innovation within the procurement team, we’re developing real solutions for challenges and solving problems”

LINDA SIEGERT SENIOR DIRECTOR OF GLOBAL PROCUREMENT, SAILPOINT

with transparency and deeply holds company strategy at the forefront of her team’s goals. “We partner closely with our business areas to understand their objectives and walk alongside them as partners so we can help them drive strategy and corporate vision in a sustainable way.

“Culture impacts the dollars we spend. It drives the talent and positioning of the team beyond just a job title. It empowers the procurement team to do what they love and creates healthy partnerships while making a long-term impact,” Siegert says.

“I encourage my team to be relationship driven with a focus on strategic partnerships and lifecycle sustainability. When coupled with spend management, that's impactful for everyone.”

Her team also offers its expertise and innovations to SailPoint’s suppliers. “We're all on an innovation journey and we regularly collaborate with our suppliers to innovate and find new and creative ways of solving SailPoint goals. For us, depth is key,” she says. “We don't want to wade in the pond when we can really swim in the ocean.”

SailPoint’s procurement partners

When asked about SailPoint’s procurement partner ecosystem Siegert says that they have a number of really amazing procurement partners and strategic supplier partnerships, and of course, that it's difficult for her to list them all, “but I'll mention a couple of examples from two opposite sides of business support,” she says.

“Since we are a global company and we're providing support in all areas, we hold events all over the world. We wouldn't be able to robustly serve the business without the partnership of companies like Prestige Global Meeting Source (Prestige), who support us globally through sourcing our

SailPoint breakroom at Austin HQ

SailPoint crew cafe at Austin HQ

company event locations with their intimate knowledge of the global meeting and event landscape.

“Prestige just outshines any other company I've worked with in this area. They are strategic, hands-on, and truly a genuine pleasure to work with. Prestige emulates our core values, placing our success as their top goal.

“On the operational side of the business, we partner with companies like ServiceNow who have a passion for innovation and value the individuals they work with inside of our company. This is highly important for us, as we provide for employee self-service and operational efficiencies at an enterprise level.”

The future of SailPoint’s procurement function

SailPoint’s procurement focus is on managing the current market and the fluctuations that we're all continuing to see – while better positioning the company over the next three to five years.

“We're doing that by continuing to drive depth within the company through our supplier and business stakeholder relationships. We work smart, which means we're always innovating and optimising how the procurement team works, interacts and how we accomplish our goals.

“We don't ever settle for, 'it's working today, so why fix it?' We are always looking for ways to work smarter and automate activities that don't bring long-term value.”

“My team is strategic in nature, so eliminating transactional churn really allows me to focus their talents on the procurement activities that matter and provides SailPoint with the most impact.”

Cloud, edge and the next generation of advanced driving aids

Advanced driver assistance systems, generating huge quantities of data, will rely on the building of robust systems, potentially aided by edge computing

WRITTEN BY: MARCUS LAW

There are multiple factors that determine safety and efficiency on the road. With more possibilities for danger and potential delays around every corner, drivers are less able than computers to see all the signs and determine the best course of action. In a heartbeat – or even less than – an advanced driver assistance system (ADAS) can save a life or direct a driver along a route that shaves minutes off their travel times.

Making use of an abundance of data, ADAS systems encompass various functions: a lane control mechanism, found in the most recent cars; emergency braking and pedestrian detection; and parking assistance. In fact, they’re becoming so smart that they can determine when the driver is drowsy or driving under the influence of illegal substances.

However, these systems, especially when combined with the data demands of the future’s autonomous vehicles, will require considerable improvements on current networking capabilities. Building networks and ecosystems that can handle the sheer volume of data these systems will generate – thought to be as much as 40TB of data an hour from cameras, radar, and other sensors from driverless cars – will determine the success, the safety, and the experience of autonomous driving, Jordan MacPherson, Director of Product Operations at Park Place Technologies, explained recently to AI Magazine.

“Investing in resilient, cyber secure and agile cloud computing strategies, that utilise powerful compute and ignite realtime analysis and decision making from edge devices is absolutely crucial,” he explains. “It’s critical now, not tomorrow. We are already driving partially automated, intelligent cars – but they are about to get smarter.”

ADAS no longer a luxury

ADAS was once a luxury provided by the premium segment OEMs but with edge computing and networking solutions becoming more affordable, ADAS has found a new position in the market, according to a report by STL Partners.

Companies like Mobileye, Netradyne & DrivebuddyAI aim to reduce the number of road traffic accidents through deploying AI to the edge to create a safer driving experience. By using radar/lidar/camera sensors on powerful edge compute systems, more frames per second of video can be analysed, with fewer redundancies.

As predicted in a report by Gartner, the benefits of 5G and edge computing could contribute to the greater use of edge applications within the automotive sector.

“Workloads that are not safetycritical – infotainment and smart traffic management, for example – could start to shift to the edge from onboard or in the cloud. Eventually, 5G connectivity could reduce latency to the point that certain safety-critical functions could begin to be augmented by the edge infrastructure, rather than relying solely on onboard systems.”

Data-driven AI

As of July 2022, EU regulation was put into place to ensure that ADAS is available across the entire automotive industry. ADAS is now mandatory for certain functions in all new cars, and includes advanced emergency braking systems (AEBS), lane departure warning systems (LDWS), speed assistance, rear-view cameras, and alcohol interlock installation –systems that prevent the driver from using the car with too much alcohol in their blood.

“These safety features have been designed to help drivers prevent collisions and improve the driving experience,” says Hayley Pells,

“Using AI, we can potentially provide realtime valuable insight into how roads are used, where traffic hotspots are, and how to better design infrastructure for automated driving safety”

ROBERT HOWARD ADAS PRODUCT SPECIALIST, TOMTOM

Policy Manager at the Institute of the Motor Industry. “Non-mandatory ADAS features that are common include blind-spot monitoring, parking sensors, and forward-collision warning systems. All ADAS technologies are today improving safety and helping drivers stay alert and aware while on the road.”

As Robert Howard, ADAS Product Specialist at TomTom, explains, vehicles equipped with ADAS tech have the capacity to anonymously gather large amounts of data. This data, if used appropriately, can help to build more efficient and safer infrastructure for an automated driving future.

A bridge to driver acceptance of autonomy

Driver assistance has been provided to many drivers through various means. But ADAS is becoming less of a luxury and more of a necessity, which can also be understood by looking at how Google manages traffic and provides real-time updates to drivers – allowing them to select the fastest, most economical routes based on traffic data and other factors.

“Connectivity also enables ADAS features like remote monitoring and control. With the help of mobile apps or web portals, drivers can remotely monitor their vehicle’s performance, receive alerts about maintenance issues, and even control certain functions such as locking and unlocking the doors or starting the engine,” Pells explains.

As Howard describes, connected cars create a dynamic environment for lowcost data sharing and aggregation, whereby massive amounts of anonymised data can be moved between the physical world and the cloud. “Using AI, we can potentially provide real-time valuable insight into how roads are used, where traffic hotspots are, and how to better design infrastructure for automated driving safety.”

There are many use cases for AI in vehicle engineering outside of self-driving cars, and one of the most potentially beneficial is monitoring driver awareness.

“Several manufacturers are now using in-car computer vision-equipped cameras to monitor driver faces for microscopic indications of fatigue, which could provide early warning of tiredness that may lead

“Investing in resilient, cybersecure, and agile cloud computing strategies that utilise powerful compute as well as igniting realtime analysis and decision making from edge devices is absolutely crucial”

JORDAN MACPHERSON DIRECTOR OF PRODUCT OPERATIONS, PARK PLACE TECHNOLOGIES

to injury,” comments technology expert and influencer Bernard Marr. “It's easy to see why this is considered an important use case in the industry, where fatigue is said to play a role in up to 25% of serious and fatal road traffic accidents. Bosch is one of the technology manufacturers that has created systems designed to detect fatigue and even ‘microsleeps’ – incidents where drivers nod off for just a second or two, often without noticing – but that are enough to frequently cause accidents.”

The role of infrastructure in a connected, assisted system

One of the biggest challenges that carmakers face in realising the full potential of automated driving is building safe and accurate systems in a scalable, costeffective way, Howard describes.

Aiding the safe operation of ADAS-enabled vehicles and autonomous cars, infrastructure has become a key component in making sure cars can leverage data to their fullest. The infrastructure conversation is driven by the demand on driver assistance technologies to rapidly share insights via the cloud and telecommunications networks, whereby the surrounding network must be capable of supporting reliable, real-time data transfer.

“ADAS systems require robust infrastructure to function safely and effectively,” Howard comments. “However, for this to happen, all the elements of the infrastructure need to operate in perfect harmony. For example, without high-speed connectivity between vehicles and the surrounding environment, then the transfer of masses of physical data to the cloud will not take place quickly enough to support the high-definition maps that provide accurate location and road information to ensure safe navigation.”

“Without highspeed connectivity between vehicles and the surrounding environment, then the transfer of masses of physical data to the cloud will not take place quickly enough”

ROBERT HOWARD ADAS PRODUCT SPECIALIST, TOMTOM

According to Morgan Stanley, vehicles will soon be generating as much as 40TB of data per hour

AI CONSULTING FIRMS

We take a look at the top 10 AI consulting firms that have established themselves as leaders in the field, providing exceptional expertise and innovative solutions to their clients

WRITTEN BY: CHARLIE KING

As the demand for AI solutions continues to grow across various industries and the expanding use cases are being illuminated across the world, the need for AI consulting firms has become more crucial than ever. With research showing barriers to AI adoption include limited expertise, data complexity and lack of tools for AI development, consulting companies can bridge this gap by providing insights and the correct tools, playing a significant role in business development. This month, AI Magazine looks at 10 of the top consultants that can help boost AI adoption for enterprises.

Deeper Insights 10

London based AI consultants Deeper Insights, whose partners include AWS and Google Cloud, utilise advanced data structuring, prediction, and insight algorithms to support its partners in making bolder decisions.

"It's about pushing the realms of possibility with technology for the good of humankind – whether that's by using data to drive more informed decisions or intelligent automation to transform organisational efficiency," says

Jack Hampson, Deeper Insights Founder and CEO.

The company’s plethora of awards include Forbes’ Top 10 Best AI Consulting Firms 2022, Good Firms’ Top AI Company.

PwC 09

Predicting $15.7tn global AI generated economic growth by 2030, PwC uses AI to transform its client’s today and create a new world for tomorrow.

The second-largest professional services network in the world’s leading report discusses the real value of AI in business, identifying healthcare and automotive as key sectors to be positively affected.

“There will be winners and losers,” says Euan Cameron, PwC’s UK AI leader. “The fourth industrial revolution will favour those with strong digital skills, alongside creativity, and teamwork – which machines find it harder to replicate.”

Deloitte

Deloitte is one of the largest professional services networks in the world. Founded in 1845, the company’s many spinning plates may have continuously changed and developed, but its core message remains firm: creating connections to make an impact that matters.

It empowers strategic choice by turning data into actionable insights, working with its clients and AI to enable more autonomous decision making. The company develops AI insights and engagement by utilising next-generation autonomous algorithms, augmenting human decision-making, and generating highly actionable predictions and insights from data.

Cambridge Consultants

Cambridge Consultants is the AI consulting arm of technology and information consulting company Capgemini Invent.

The company is known for its progressive attitudes, pushing for machine learning developments within AI – as machines create their own algorithms, they learn by experience.

“Deep learning is revolutionising almost every market we work in,” says Tim Ensor, Commercial Director and EVP at Cambridge Consultants. “We’re applying deep learning in diverse markets, driving forward the art of the possible.”

The connected supply chain turns volatility into opportunity.

The e2open connected supply chain platform provides the end-to-end visibility and collaboration you need to tackle unpredictability. Build trust and confidence with your channel, supply, logistics, and global trade partners. Take control of supply constraints through direct procurement and meet customer commitments in the face of disruptions and scarcity. The connected supply chain. Moving as

Infosys

International IT leader Infosys’ key AI and Automation offerings include:

• Automation acceleration - to save cost and build resilience whilst measuring ROI

• New revenue generation - to use proprietary loyalty data as both a tradeable currency and to better decisions

• Responsible AI - organisations can increase operating margins by as much as 5% by improving Responsible AI Index (RAII)

Pharmaceutical giant Pfizer has seen visible improvements across a spectrum of Pfizer’s operations since using Infosys, including 15% increase in joint team productivity.

EY offers intelligent automation consulting services, analytics consulting services and digital transformation services. Through incorporating robotic, intelligent, and autonomous capabilities to transform and innovate operations, its clients become true competitors in the Transformative Age.

The company operates in 150 companies across multiple sectors, ensuring that it’s in prime position for effective and up-todate AI utility.

Founded in 1989, the company saw its combined global revenues rise 7.3% yearon-year to US$40bn, offering a radically different approach to connecting strategy, transactions, transformation and technology.

Bain & Company 04

With a recent investment of over $1bn, Bain & Company helps extract maximum value from all data assets and looks for ways automation technology will fit in with its customers' digital transformation strategy.

Recently, the company has combined OpenAI's technology with their extensive knowledge of business strategy and social responsibility. Utilising AI, Bain & Company is able to quickly deploy a proof-of-concept, identify AI use cases that will generate the most value, and then implement the capabilities across businesses’ operating model, procedures, and data assets.

03

Pioneers of what the company refers to as ‘AI @ Scale’, Boston Consulting Group’s team of practitioners help clients quickly launch AI at scale with initiatives using a variety of techniques, including machine learning, large-scale optimisation, and simulations.

Looking beyond automation, BCG focuses on learning and organisational transformation. Organisations that have utilised ‘AI @ Scale’ have seen significant returns on their investments –most AI investments allocate 10% to algorithms, 20% to technologies, and 70% to integrating AI into business.

QuantumBlack

Beginning operations within Formula 1’s pitstop teams, the AI consultancy division of McKinsey, QuantumBack now offers a range of services to help businesses leverage data and technology to improve their operations, decision-making, and customer experience.

QuantumBlack Labs, the company’s centre of learning, serves as a hub for over 1,000 data technologists, designers, and product managers to develop state-of-theart tools and resources that mitigate risk and expedite progress across all stages of the AI transformation process. The company’s approach involves adapting technology stacks, debiasing models, and implementing risk mitigation strategies as they enhance the capabilities of AI applications.

Recently, QuantumBlack helped Emirates Team New Zealand successfully defend their America’s Cup title. With the use of their simulation technology, the consultancy offered valuable insights and predictions to aid the team in making informed decisions, ultimately allowing them to enhance their boat's performance.

IBM Consulting

As a trusted leader in AI consulting services, IBM offers end-to-end solutions for strategy, implementation, and management to help businesses integrate and expand AI capabilities across their enterprise. With extensive experience in developing AI technology and solutions, IBM Consulting possesses the necessary expertise, methods, and accelerators to deliver successful outcomes.

One such example is the deployment of a conversational AI for Netherlands-based bank, ABN AMRO Bank N.V. This improved the overall digital customer experience

by applying IBM Watson natural language processing and analytics to understand the customer’s needs at that moment. Then it automatically responds to routine queries, passing more complex requests to the right expert.

In the 2023 Gartner Magic Quadrant for Enterprise Conversational AI Platforms (CAIP) – which encompasses software platforms used to create, coordinate, and manage a variety of applications – IBM Watson Assistant was among the products assessed and was subsequently recognised as a leader within the field.