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.

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.

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. 

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.