Technology Untangled

We’re back, with a one-off episode looking at the challenges and opportunities tckled by leaders in their field throughout 2024, and looking ahead to 2025. 2024 has been quite a year. From elections and changes of Government around the world, to war, to lingering economic uncertainty - it has felt like the world is in a state of flux.But with uncertainty comes opportunity. Opportunities to find new competitive advantages. Opportunities to do things better this time around... And opportunities to make the most of the incredible pace of technological change bubbling under the surface.For HPE President and Chief Executive Officer Antonio Neri, 2024 was the year in which plans were consolidated to feed the ever-growing generative AI market. Whilst the last few years have been about providing the computing power to drive generative AI, it’s now time to look to other pieces of the puzzle - in particular networking and cooling, to ensure that training and inference are not only done quickly and without bottlenecks, but efficiently and sustainably too.AI has also been on the mind for Cathy Li, the head of AI, Data and the Metaverse at the World Economic Forum. Cathy’s focus for the last year - and into 2025 - has been on working towards global consensus on AI, including worldwide standards and regulations which mean that the entire world has access to AI’s potential, but also so that AI providers can tap into opportunities worldwide. That could mean seeking out more sustainable energy solutions or better infrastructure, without having to worry so much about local AI regulations. Meanwhile, over in the world of motorsport, the race to stay competitive is never ending, and with development on a new generation of cars starting in early 2025. That’s top of mind for George Russell, a driver with the Mercedes AMG-PETRONAS Formula 1 team. He joins us to talk through what it means to stay competitive when success or failure hangs on tenths of a second.Sources quotes in this episode: AI Market size predictions: https://www.statista.com/forecasts/1474143/global-ai-market-size#:~:text=The%20market%20for%20artificial%20intelligence,billion%20U.S.%20dollars%20in%202030.World Economic Forum statistics on data centre energy use: https://www.weforum.org/stories/2024/11/europe-data-centre-plus-other-technology-news-to-know/

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%3DtrueIndustry responsible for 14% of earth’s emissions - https://www.emerald.com/insight/content/doi/10.1108/JICES-11-2021-0106/full/htmlNumber of AI startups - https://tracxn.com/d/explore/artificial-intelligence-startups-in-united-states/__8hhT66RA16YeZhW3QByF6cGkAjrM6ertfKJuKbQIiJg/companiesAI model energy use increase - https://openai.com/research/ai-and-computeEuropean 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'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/worldwideUS communcations market value: https://www.statista.com/outlook/tmo/communication-services/united-statesSize of the Digital Acessibility market: https://www.mordorintelligence.com/industry-reports/digital-accessibility-software-market

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-workMIT 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-traineeshipsThe 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%202021UK government report into diversity and inclusion in STEM: https://committees.parliament.uk/publications/34531/documents/190060/default/

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 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.

Bad AI is becoming a major headache for organizations. Tech is a male-dominated sphere, which means that it produces, inherently, male-skewed AI driven by unconsciously biased datasets. The effects of this can be measurable. Run through the same AI, women can receive worse credit or loan agreements than their male counterparts, be pushed out from job openings, receive worse medical treatment, or even receive performance penalties for doing the same work as men to the same standard. So how has this situation emerged and, more importantly, what can be done about it?In this episode, we speak to Erin Young, research scientist from the Alan Turing Institute, who are dedicated to solving societal problems using technology. Their research has found deep structural inequalities in the field of AI, including higher attrition rates for women, who are generally filling lower paid, less prestigious jobs than their male counterparts. That's having a tangible, real-world effect. Anjana Susarla is a professor in Responsible AI from the University of Michigan. She's been tracking instances of biased AI finding its way into society, including documented cases of women in common-property states where spouses incomes and assets are joined being given lower credit limits on cards than their male counterparts. She also documents several cases of poor AI decision making in AI-assisted hiring and HR systems.So should these systems be using AI at all? Well, Ivana Bartoletti argues that sometimes, AI isn't the answer. She's the Global Chief Privacy Officer at WiPro, and an expert on bias in AI. She notes several cases where institutional bias has been backed up by AIs which reflected existing societal pre-conceptions, for example in AI giving lower exam scores to pupils from poorer backgrounds in the UK, and lower state benefits to migrants in the Netherlands.So what should be done? HPE's Chief Technology Officer Fidelma Russo argues that, as project leaders and managers, a lack of diversity in AI and the creeping problems it's causing should have been identified by the industry some time ago. She says drastic change is now needed to fix the problem. Fortunately, it's one the industry is rapidly becoming aware of and is now at pains to fix.

We hear a lot about Big Data. But what does it actually mean? Is it, quite simply, lots of data? Or is there more to it than that? Spoiler alert, there is. A lot more. In this episode, we're taking a look at the age of insight, and how Big Data has evolved from a technical concept to a way of extracting enormous value from the fumes of data meant for other purposes.

2022 has not been a straightforward year. A war in Ukraine has seen the world divided and global energy and food supplies disrupted. International tensions between China and Taiwan have reared their heads again. Recession is looming in many parts of the world, and whilst it makes less headlines, Covid is still very much a part of our lives. But organisations exist to solve problems and provide solutions. So, to mark the end of a rollercoaster year, we're pulling together leaders from three organisations to talk about the challenges they've faced this year, and how they are moving forward into 2023.

Since 1990, the global rates of extreme poverty have gone from around 40% to around 10%. However, progress is slowing, and 710 million people around the world still live in extreme poverty - currently earning below $1.90 per day. So how can technology help? In this episode, we’ll be meeting some of the people and organisations aiming to eradicate poverty through the use of technology.

Professional sport is a world where individuals can earn as much as a decent-sized business, and teams have evolved to become multi-national corporations. And where there's money, technology follows. In this episode, we'll be meeting with amazing people at the cutting edge of sports technology to look at how data has become a key part of the field - and looking at what organisations around the world can learn from the performance analysis revolution.

The Cloud has become a backbone of the world economy over the last decade, powering everything from streaming services to mobile banking. It’s a fantastic resource, but as time goes on the limits of the Cloud are becoming clearer, from over-reliance issues to incompatibility with legacy hardware. This week - part 1 of a 2 part special - we’re taking a look at the challenges of the Cloud, and how organisations can make sure they are making best use of the opportunities it presents.

2021 has been a year marked by new and continuing challenges worldwide. Coronavirus and travel restrictions have been joined by supply chain shortages in many industries - especially computer components - shipping issues, and financial uncertainty.