Technology Untangled

We’ve spoken before on this podcast about cyber security and protecting yourself from cyber crime - but what is being done to tackle the phenomenon internationally? That’s what we’re looking at in this episode. We’ve bought together some of the most senior global figures on cyber crime to find out how international collaboration and public/private partnership is taking the fight to the criminals.

It’s a big task. It is predicted that cybercrime will cost the global economy over 9.2 trillion dollars in 2024. The number of firms targeted by ransomware attacks has increased by almost 20% in the last five years, with 72% of organisations being hit in 2023.

Deepak Verma is Head of Product for HPE Data Protection. He says it’s not just the big financial players who are being targeted; in fact education and healthcare are the main victims of cyber attacks. Because cyber criminals don’t have to contend with geographical borders, attacks can be instigated from anywhere, to target anywhere.

Which is why, as Joanna Bouckaert, from the Centre for Cybersecurity of the World Economic Forum says, bringing governments and organisations together from across the world is imperative to protecting ourselves from the growing complexity of cyber attacks; as is increasing awareness within the private sector.

But there’s more to reducing the number of cyber attacks than prevention alone. Craig Jones is a law enforcement official working for Interpol as Director of Cybercrime. He says building a network of co-operation with different countries has been a key part of bringing down gangs of cyber criminals across the world.

Sources and statistics cited in this episode:
Cybercrime global cost - https://www.statista.com/forecasts/1280009/cost-cybercrime-worldwide
20th anniversary of the Budapest Convention - https://www.coe.int/en/web/cybercrime/20th-anniversary-budapest-convention
Bank thwarting billions of pounds worth of cyber attacks - https://www.ft.com/content/cd287352-cb3b-48d8-a85b-668713b80962
Schools hit by cyber attacks - https://www.gov.uk/government/statistics/cyber-security-breaches-survey-2022/educational-institutions-findings-annex-cyber-security-breaches-survey-2022
Stuxnet malware - https://www.cfr.org/cyber-operations/stuxnet
NIS2 Directive - https://www.nis-2-directive.com/#:~:text=What%20is%20the%20NIS%202,cybersecurity%20across%20the%20European%20Union.
Cyber security spending prediction - https://www.statista.com/outlook/tmo/cybersecurity/worldwide#:~:text=Revenue%20in%20the%20Cybersecurity%20market,US%2492.91bn%20in%202024.
HPE logs 2.6 billion events every day - https://www.hpe.com/us/en/newsroom/blog-post/2023/04/hpe-showcases-data-security-initiatives-via-the-2023-cybersecurity-report.html

In this episode we are looking at the challenges AI technology faces when it comes to becoming, and then remaining sustainable.
The benefits of AI are unquestionable: from improved medical assistance and increased efficiency in the workplace, to autonomous transportation and next-level gaming experiences. But the more expansive the abilities of AI become, the more data storage that’s required.

That data storage uses a lot of energy. In fact, it has been predicted that AI servers could be using more energy than a country the size of the Netherlands by 2030.

For HPE Chief Technologist, Matt Armstrong-Barnes, the rate at which AI has grown in recent years has had an environmental impact, and he believes that’s down to people rushing into training large language models without thinking about longevity, or the need for future change. And that, in turn, has led to data being stored that is no longer needed.

The sustainability issue is something that is also a main focus of Arti Garg, Lead Sustainability & Edge Architect in the office of the CTO at Hewlett Packard Enterprise. Like Matt, Arti has kept a keen eye on the exponential growth of AI data storage and the effect that is having on the environment, and agrees that the key to a more sustainable future is in how we train models.

However, whilst training models well is important, the tech itself is a key component in more efficient AI. Shar Narasimhan is the director of product marketing for NVIDIA's data center GPU portfolio. He believes that a combination of openly available model optimisations and chipsets, CPUs, GPUs and intelligent data centers optimised for AI is a key piece of the puzzle in avoiding energy wastage, and making AI more sustainable all round.

Sources and statistics cited in this episode:
Global AI market prediction - https://www.statista.com/statistics/1365145/artificial-intelligence-market-size/#:~:text=Global%20artificial%20intelligence%20market%20size%202021%2D2030&text=According%20to%20Next%20Move%20Strategy,nearly%20two%20trillion%20U.S.%20dollars.
AI could use as much energy as a small country report - https://www.cell.com/joule/fulltext/S2542-4351(23)00365-3?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS2542435123003653%3Fshowall%3Dtrue
Industry responsible for 14% of earth’s emissions - https://www.emerald.com/insight/content/doi/10.1108/JICES-11-2021-0106/full/html
Number of AI startups - https://tracxn.com/d/explore/artificial-intelligence-startups-in-united-states/__8hhT66RA16YeZhW3QByF6cGkAjrM6ertfKJuKbQIiJg/companies
AI model energy use increase - https://openai.com/research/ai-and-compute
European Parliament report into AI energy usage - https://www.europarl.europa.eu/RegData/etudes/STUD/2021/662906/IPOL_STU(2021)662906_EN.pdf

In this episode, we’re taking a look at how the explosion in our demand for data storage has led to needing more capacity than ever before, and whether long-vanished ideas from our computing past could influence technological innovation in the future. 

In 2022 the world generated 97 Zettabytes of data. It has been predicted that, by 2025, that number will almost have doubled to 181 Zettabytes. Although at the rate generative AI and machine learning is expanding, that figure could be even higher.

As the Head of the Hewlett Packard Enterprise storage division, Senior Vice President Patrick Osborne has storage at the forefront of everything he does. He sees just how much his customers' needs are growing every year and is always actively looking for new methods and fabrics to meet those needs.

Alongside those requirements for greater data storage also sits the need for faster data processing - and there are a number of technologies nearing maturity which could revolutionise the space. Aidong Xu is Head of Semiconductor Capability at Cambridge Consultants, and is keeping a close eye on these technologies, especially in the memory space. For him, the big challenge is combining performance with efficiency.

However, whilst we’re looking at the future of data storage, it’s hard not to draw parallels with the past. Colin Eby from the National Museum of Computing knows a thing or two about that, guiding us through the history of the storage technologies which marked our pathway to today - some of which, in the decades since they fell out of favour, may have come round once more.

But what if the future of data storage isn’t data at all, but something more organic. Mark Bathe is a professor of biological engineering at MIT, specialising in DNA storage, and what that can mean for the future of our digital archiving needs. 

Sources and statistics cited in this episode:
Zettabytes usage - https://www.statista.com/statistics/871513/worldwide-data-created/
Sales of storage units - https://www.statista.com/forecasts/1251240/worldwide-storage-unit-sales-volume
Hard drive shipment figures - https://www.statista.com/statistics/398951/global-shipment-figures-for-hard-disk-drives/
Random access DNA memory using Boolean search in an archival file storage system - https://www.nature.com/articles/s41563-021-01021-3

In this episode, we'll explore how technology is changing the way we communicate. But much more than that, we're going to be looking at how it's actually changing our relationship with language itself.

Ever since the first pictograms which date way back over 5000 years, we've been searching for technologies to communicate with each other in more widespread, more efficient ways. The printing press, the telegram, the telephone, and the internet have all evolved into what we're now using today: live streaming; chatbots; VR and AR technologies and, of course, social media. The thing is, the pace of change has grown remarkably in recent decades. We're more connected than ever.

And nothing is changing that faster than AI, in particular generative AI. It’s a core area of interest for HPE Chief Technologist, Matt Armstrong-Barnes. He can see the incredible potential for globe-spanning communication that AI brings, from instant translation to live captioning, but he’s also wary of taking the human out of the loop and losing the important context, nuance and difference that makes language so special and effective.

That’s also a challenge for Courtney Napoles. She’s Linguistic Engineering Director at Grammarly, an AI-enabled software platform which aids human writing. Despite being a tech firm with a strong machine learning underpinning, they rely on humans in the loop to ensure that communication remains effective for us, rather than trying to pull us towards homogenised, machine-learning inspired writing styles.

The rise in assistive technology is having unintended benefits, too – in particular, it’s opening up the door to greater representation in the workplace, and bridging communication barriers when it comes to accessibility needs. Rob Koch is a data engineer and principal at Slalom Build, and heads the group Deaf In The Cloud Dot Com. He’s seen a remarkable breaking down of barriers in the last few years as technology has enabled him to communicate more effectively with colleagues and customers. There’s a way to go, but he’s optimistic about the future.

And speaking of the future, where are we headed next? Leslie Shannon is Nokia’s head of trend scouting. She’s keeping a keen eye on the way we communicate and the language we use, and is seeing a stark generational shift away from text and towards video and augmented reality solutions, embracing the additional context that body language and gesture can add to traditional, ‘flat’ conversations – and changing the way we speak to our tech and the language we use in the process.

Statistics and sources cited in this episode:
Global communications market value: https://www.statista.com/outlook/tmo/communication-services/worldwide
US communcations market value: https://www.statista.com/outlook/tmo/communication-services/united-states
Size of the Digital Acessibility market: https://www.mordorintelligence.com/industry-reports/digital-accessibility-software-market

Sports and data are closely intertwined – and that’s especially true for spectators. So how can data, analytics, IoT and connectivity create better experiences fans? In this episode, we’re taking a look at how major sports venues and events are using technology to create the perfect experience for their customers.

It's something that’s been a recurring goal for clients of HPE Aruba Networking over the last few years. Simon Wilson is their Chief Technology Officer for the UK, and helps clients bring exceptional connected experiences. He explains that, in part, the demand has been driven by our own improved connectivity: In particular, smartphones are now used for everything from payments to ticketing. And thousands of devices means there’s a demand for rock-solid Wi-Fi and private 5G networks.

And that’s particularly important over large, outdoors sporting arenas where connectivity can be naturally spotty. Michael Cole is the Chief Technology Officer for the European Tour Group and Ryder Cup Europe. Not content with being responsible for laying tens of kilometers of cabling and fiber optic lines for golf’s marquee events, he’s been developing the concept of an Intelligent Course – a vast network of connected sensors and IoT devices which allow central control over every aspect of the event, from assessing queue length to measuring wind speed to account for wayward golf balls and moving spectators out of the way. 

Daniel Brusilovsky is on a similar mission. He’s the vice president of technology for the Golden State Warriors and Chase Center in San Fransisco. Their campus contains over 700 Wi-Fi access points, connecting upwards of 18,000 devices at key points. These devices not only provide seamless access, they allow the Chase Center to use intelligence and insight to perfect the flow of people through their site. Insight and analytics from the data they collect is being used for everything from stocking concession stands to streaming fans’ phones right onto the largest score screen in North America.

And that idea of fan experience is what really excites Leslie Shannon. She’s Nokia's head of trend and innovation scouting, and is impressed by some of the connected fan experiences that sports teams are trying out, from 3D cameras positioned on top of the goal posts, to apps using Augmented Reality to overlay a player’s stats and map their previous performance whilst they are playing.

Routes into STEM – Could apprenticeships solve the tech talent crunch?

There’s an acute shortage of candidates for tech jobs – in fact, research suggests tens of millions of potential roles are going unfilled. In a poll with global technology chiefs conducted by MIT’s ‘Technology Review’, a majority found that they weren’t getting enough candidates for roles, and those who did apply lacked necessary skills. 

Clearly, there’s a problem here. So what can tech companies do to bring more talent through the door? Could building a baseline of investment in new, or even unqualified, talent be a solution?

Maninder Randhawa believes so. He’s the Early Careers Leader for Hewlett Packard Enterprise in the UKIMEA region, and spends his time building programmes to upskill the organizations new talent. He believes that, whilst there’s absolutely a place for old hands, the fresh ideas and ability to adapt and mould that new talent brings makes them more than worth the investment.

A case in point is Stu Franks of Alces flight, an HPC services provider. He began at the firm at age 18 as a school leaver, and now heads a team building and marketing services and solutions. He believes apprenticeships, like his own, offer a route to great talent that’s not suited to academia but has all the practical talent and intelligence needed to excel in the field, and values demonstrable skills, personality and attitude above degrees and certificates.

In order to attract young people into the STEM fields, though, they need to know about it. That’s where outreach groups like Stemettes come in. They are a UK-based organization dedicated to reaching out to underrepresented groups in schools across the country, with programs to engage young people in STEM careers as an option, and provide mentoring and support for them to take their first steps. Floriane Fidegnon got into tech through the work of the group and now sits on the board, something her employer encourages as it creates a virtuous cycle of bringing in new talent, and encouraging existing talent like Floriane to become engaged ambassadors for the field.

But what about the kind of soft skills that come with a degree – just not one in STEM topics? Erin Young is a case in point. She’s a lead researcher for the Alan Turing Institute, which is dedicated to solving societal problems with technology. She came into the field from a background in classics, where her skills in research, reasoning and analytics, combined with a love of data analytics, made a move into tech a great – if seemingly disconnected – jump. 

Sources cited in this episode:

85 million unfilled tech roles by 2030: https://www.kornferry.com/insights/this-week-in-leadership/talent-crunch-future-of-work

MIT Technology Review poll with tech leaders on talent shortages: https://www.technologyreview.com/2023/09/21/1079695/new-approaches-to-the-tech-talent-shortage/

STEM apprenticeships in the UK increased by over a quarter in the last decade: https://explore-education-statistics.service.gov.uk/find-statistics/apprenticeships-and-traineeships

The National Science Foundation report on the STEM workforce between 2011 and 2021: https://ncses.nsf.gov/pubs/nsf23315/report/the-stem-workforce#:~:text=The%20size%20of%20the%20STEM,2011%20to%2024%25%20in%202021

UK government report into diversity and inclusion in STEM: https://committees.parliament.uk/publications/34531/documents/190060/default/

You've heard it from us before on this podcast, but we'll say it again. AI is transforming our world.

Depending on which market research you look at, AI in healthcare is already somewhere from a 14-21 billion dollar industry in 2023, which is almost double what it was worth just two years ago. By 2028, it's set to be a 100 billion dollar global industry, growing some 40% year-on-year. That's astonishing, even in the already skyrocketing AI sphere. In this episode, we'll be looking at a wide spectrum of expertise to get a sense of where the field is right now, what the future looks like, and some of the cool technologies which might fill it. We’ll be looking at the ways in which AI is making healthcare more efficient, and overcoming roadblocks, as well as examining the ethics of letting algorithms influence human outcomes.

We’re joined in this episode by Mike Woodacre, Chief Technologist at Hewlett Packard Enterprise. He starts by spelling out the origins of this explosive growth during the COVID Pandemic, which ushered in a new world of collaboration and inter-disciplinary use of AI and High Performance Computing to look at new vaccine options, as well as examine scientific research looking for patterns. He urges caution, though, in relying on AI solutions which haven’t been adequately trained in the locales they are being used in and so may not account for regional factors such as more or less common versions of a disease.

That’s something Andy Cachaldora, General Manager for Northern Europe at GE Healthcare, agrees with. They’ve seen an incredible expansion of AI tools not just in diagnostic machines, but also in making sure that every second of a healthcare professional’s time is being used wisely. For him, AI is about taking out the grunt work and uncertainty from running clinics, giving better outcomes all round. Again, however, he urges caution in the way AIs are trained and implemented, with poor data collection and poor planning a route to disaster.

The idea of good, global data sources to train AI is something that has inspired Joachim Schultze, professor of systems medicine from the German Centre for Neurodegenerative Medicine. In collaboration with HPE, he’s been working on a blockchain-based system of machine learning tools to analyse Leukaemia scans, which keeps the data in-hospital to ensure data protection, but sends the insights of the scans to dozens of other institutes worldwide to train their own machine learning algorithms. That’s ensuring that everyone’s AI is collaboratively being trained on the widest, global dataset possible, with no risk to patient privacy.
But where’s the human in all this? Well, right at the centre of it all. After all, any AI requires training, and the training in most cases is still provided by human medical experts, for use by their peers down the line.

And a fascinating new piece of research suggests that the reason AI imaging works so well is that the expertise of a dozen doctors looking at cases together – in clinic or when training Ais, are better than one. A kind of swarm intelligence or swarm learning experience. Rutwik Shah worked on the research at the Center for Intelligent Imaging, which found that by training with swarms of doctors, not only could inexperienced groups of junior doctors analyse scans more reliably than the best AI, they were as effective as groups of doctors with decades of experience. It’s fascinating work, which could revolutionise the way AIs are trained and behave, as well as changing the way scans are analysed.

It's a fascinating world. Come with us on the journey.

Citations:
00:57: https://www.apa.org/monitor/2022/01/special-burnout-stress

01:55: https://www.marketsandmarkets.com/Market-Reports/artificial-intelligence-healthcare-market-54679303.html?gclid=CjwKCAjw5_GmBhBIEiwA5QSMxOR1CRaYz_g_dcLRAd1aJwxb3tbPBUYcQ0l9mrrtZsRv93yUzWkJTRoCruUQAvD_BwE
https://www.statista.com/statistics/1334826/ai-in-healthcare-market-size-worldwide/

06:19: https://www.bma.org.uk/advice-and-support/nhs-delivery-and-workforce/pressures/nhs-diagnostics-data-analysis#:~:text=There%20is%20not%20enough%20diagnostic%20staff%20in%20the%20NHS&text=According%20to%20the%20Royal%20College,11%2C370%20additional%20staff%20by%202025.

30:28: https://www.nature.com/articles/s41598-021-90292-6

The dawn of the exascale computer has arrived. In May 2022, a computer named Frontier was switched on at the Oak Ridge National Laboratory in the USA. At well over twice the computing power of the previous world record holder, it has ushered in a new era of supercomputers, with at least two more to follow in the coming months and years.

In this episode, we’ll be looking at why this undeniably impressive milestone actually means, and more importantly, why it matters. We’ll also be looking at some of the challenges remaining as we enter the exascale era – namely, how do we actually use computers at this scale?

We’re joined in this episode by Mike Woodacre, Chief Technologist at HPE. He starts by spelling out some of the core statistics underpinning the Frontier exascale computer and its 60 million parts, as well as some of the challenges endemic to computing at the cutting edge of technology.

We also meet Doug Kothe, former Director of the Exascale Computing Project at Oak Ridge National Laboratory. He’s hugely excited about the possibilities of exascale as a source of incredible compute in-depth with the ability to return answers to complex questions and simulations in almost real-time. At the same time, he’s also keen to use Frontier as a gateway to open up HPC and supercomputing to more and more organizations, via an ‘app store’ which allows potentially thousands of users simultaneous access to Frontier for their own needs.

For different reasons, Professor Rick Stevens is also excited to be entering the exascale age. He’s Argonne National Laboratory’s Associate Laboratory Director for Computing, Environment and Life Sciences. He’s keen to put their upcoming Aurora exascale computer to work on projects to revolutionise cancer treatments, from diagnostics to drug discovery, through his CANDLE program. Rick’s also cautious, though. Whilst he appreciates the promise that exascale offers, he knows that it’s not an end-goal, but a stepping stone to the next generation and new technological advances.

That’s a sentiment shared by our final guest, Cristin Merritt. She’s the Chief Marketing Officer at Alces Flight, an HPC solutions provider. She’s keenly across worldwide demand for supercomputing power, and sees an evolving landscape of commercial demand and supply growing out of the innovations that exascale offers. She’s cautious, though – right now, exascale is too experimental and non-standard to be commercially mass-market. With time, though, she believes that might just change.

The world’s energy supply is in a state of flux. Australian coal is being bought up by China faster than it can be mined, Europe is coming to terms with Russian gas being shut off, and the US is grappling with how to produce more energy whilst meeting green targets and keeping people in mining areas employed. 
 
 It’s a tough balancing act. In the last episode we looked at how to produce more energy. But how do we make the most of the energy we already have? This time, we’ll be talking to experts and organizations using tech to reduce our consumption and get us all a little greener without resorting to drastic societal change - and save our organizations money at the same time. The focus, for this episode, is on how we transform the IT industry, and how we transform domestic usage.
 
 We start off by meeting HPE's John Frey, Chief Technologist for Sustainable Transformation. He explains that, in terms of the IT industry, there's sometimes a disconnect or lack of awareness from customers around the power-saving technologies that are put into the devices we use, from laptops to servers. There's a habit in large organizations of overriding or deleting manufacturer-built controls which could save tens of thousands of kilowatt-hours per year, and the first step in transforming our energy usage as an industry is simply to turn them back on. He also argues that the way we code could be a game changer - with more efficient languages and processes drastically reducing the amount of compute required to run them - by up to 90% in some cases. 
 
Joe Baguely agrees. He's the Vice President and Chief Technology Officer for Europe, the Middle Eastern Africa at VMware, a provider of (among other things) virtualisation solutions (in a siilar manner to HPE Greenlake) which allow for far more data and functionality to be run on less hardware, drastically increasing energy efficiency. VMWare is also leading the charge in local power generation and sourcing their electricity from renewable or green suppliers. 
 
Joe and John also argue that it's imperative that IT departments actually understand the cost of their energy usage, which has traditionally been the responsibility of buildings management or operations teams. Only with the advent of Cloud computing have IT departments become responsible for their own budgets, and that has drastically improved awareness of just how energy-intensive our organizations' IT infrastructure can be. 
 
Finally, on the domestic side, we meet Devrim Celal, CEO of KrakenFlex, part of the Octopus Energy Group. Devrim points out that in a world of renewables, it’s becoming increasingly difficult to make energy when we want it, so a new era of smart co-operation is needed to balance the grid and avoid wasting energy – or causing shortages at peak times. They are pioneering smart technology which pairs our energy-intensive devices, generators, and storage facilities (think electric vehicles and wind turbines) to ensure that the hungriest consumers aren’t using electricity at the most inefficient time, spreading the load through the day by telling the EV, for example, when to charge.

They are also pioneering ‘gamifying’ our energy use, to encourage consumers to care about how much they use, and their role in the wider, national picture. 

The world is in a state of flux when it comes to energy production. Australian coal is being bought up by China as fast as it can be mined, Europe is coming to terms with Russian gas supplies being a bargaining chip in international politics, and the US is grappling with how to produce more energy whilst meeting green targets and keeping people in mining areas employed. 

It’s a tough balancing act. So how can countries realistically become more energy independent in a sustainable way with the tech that’s viable today? This is the first of a two part special. Next time we’ll be looking at how to make the most of the energy we already have.

We start off by meeting Doug Kothe, a Nuclear Scientist who, until recently, headed up the Exascale computing team at the Oak Ridge National Laboratory in the US. He's hugely excited by recent developments in the field, but is also a realist who understands that Fusion energy is still a way off being commercially viable and scaleable. 

So what are the alternatives? Professor Patricia Thornley from Aston University is Director of the Energy & Bioproducts Research Institute. They look at the energy potential of waste biomass - sewage and agricultural by-products - to provide not only electricity, but also materials such as plastics, and fuels such as gasoline, diesel and even jet fuel and hydrogen. Their research shows enormous promise -  up to 45% of the UK's energy needs could be provided in a carbon-neutral or even net negative way simply by processing agri-waste. In many parts of the world, close to 100% is achievable. 

But what about countries where land is at a premium? There's alternatives here, too. Carnegie Clean Energy is an Australian-based engineering firm who are perfecting their CETO wave-generation technology. They use submerged bouys pulling on cords to generate energy in an environmentally non-destructive way. As Carnegie CEO Jonathan Fievez explains, the difference in their technology is that the generators can pull on their own cords to raise, lower or angle themselves. That lets them both generate more electricity, and protect themselves from the bad weather and turbulent seas which have traditionally made the tech difficult to implement commercially. 

They do this via an ingenious AI tool called reinforcement learning, whereby an AI learns to control the bouys by being rewarded for the amount of energy they generate. Testing is currently ongoing, but early results suggest a 20-40% performance improvement with less wear and tear, which could be a lifeline for remote and island communities currently relying on diesel generators. 

Driving this AI technology is Hewlett Packard Enterprise Labs, who have been working in partnership with Carnegie. Christian Temporale and Maria Ridruejo have been implementing the project for HPE, and are excited by the progress that's been made. They believe that machine learning techniques such as this could make significant improvements in other technologies, such as 'smart' wind turbines, and developing better forms of solar panels.