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HPE news. Tech insights. World-class innovations. We take you straight to the source — interviewing tech's foremost thought leaders and change-makers that are propelling businesses and industries forward.
Aubrey (00:10):
Hello and good day everyone. Welcome to another episode of the fabulous Technology Now, a weekly show from Hewlett Packard Enterprise where we take what's happening in the world around us and explore how it's changing the way organizations are using technology. We're your hosts, Aubrey Lovell.
Michael (00:27):
I'm Michael Bird. Aubrey, love this, so fabulous.
Aubrey (00:31):
Thank you.
Michael (00:31):
And in this episode we're exploring some of the emerging concerns around generative AI and why organizations are becoming wary of it. We'll be asking whether businesses are ready to fully step into the world of generative AI. We'll be looking at the reasons why despite their concerns, generative AI is still absolutely going to transform the way we do business. And of course, we'll be looking at the books that are changing the way you, our listeners see the world. So if you are the person who needs to know why, what's going on in the world matters to your organization, then this podcast is for you. And if you're enjoying it, do make sure you subscribe on your podcast app of choice so you don't miss out. All right, Aubrey, let's do it.
Aubrey (01:11):
Let's do it.
(01:14):
So AI has been a hot topic for businesses for a few years now, and for really good reason, it holds enormous potential for modeling and simulation, data management and business efficiency. But within that, there's a subset of AIs which have really hit the airwaves, and those are called generative AIs. They are a huge business right now. Chatbots, AI art tools and AI composers have taken off over the last four or five years as cloud storage and compute make accessibility and training large language models much more commercially viable. We do have some stats. Are you ready for some numbers, Michael?
Michael (01:55):
More than anything in the world, Aubrey.
Aubrey (01:57):
Okay. So to kick us off, the global generative AI market size was valued at 8.2 billion in 2021 and as projected to reach 126.5 billion by 2031. So that's roughly a compound rate of about 32%. So that's pretty mind blowing if you think about it.
Michael (02:19):
Yeah, it absolutely is. And it's not something that's limited to business or enterprise customers anymore. No, for little to no money, we as individuals can now subscribe to generative AI tools that can help make us more efficient in our work, improve our coding if that's our bag, or write that tricky email to a colleague or client. The thing is though, that efficiency and help comes a cost because whilst AI is helping us, it also sometimes is learning from us and about us. And if we're using AI to help us at work, well how secure is the potentially sensitive data we're feeding into it?
Aubrey (02:55):
It is a really good question. And many AIs don't simply forget an interaction. They use it to develop and tune their model. So that means any sensitive data is now stored on a cloud somewhere, and this can imply some risk. In fact, because of this challenge, the EU has just announced the creation of an AI task force to look at how various providers are treating our personal data. And as we know, security is key in how we manage AI responsibly. It's really top of mind for many organizations
Michael (03:25):
Yeah. And that's led some organizations to put stricter rules in place around the use of generative AI for working with anything that could be seen as sensitive information.
Aubrey (03:35):
And so that begs the question, what can we do to ensure we are using AI in a secure and strategic way?
Michael (03:41):
So tech market intelligence provider IDC recently wrote a blog post with some suggested questions that organizations should ask any potential generative AI partner. So including things like number one, making sure you can opt out of using your interactions to train the AI. Number two, making sure you retain the right to delete your data from the model. Number three, ensuring that you can opt out of having the prompts you input or stored on the model. Number four, making sure only a limited pool of employees at the provider can access the data. And finally, making sure the security and privacy policies they employ match up with your own.
Aubrey (04:20):
I mean, that's really good advice, but even then there's still other angles to be examined. For example, who owns what an AI produces? If you feed an AI data, does it then have rights to that data in the form of a solution it gives you? Does an AI owner own the code it generates? In fact, the school of law at the University of Portsmouth and the UK wrote a really interesting blog post on this topic which will link in the description. It turns out that there's already provision and law for AI generated content within the UK, and we do have a quote here under the Copyright Designs and Patents Act of 1988, they are, "Generated by computer and circumstances such that there is no human author of work." So the law suggests content generated by an artificial intelligence can be protected by copyright. So the blog goes on to add that AI in the UK can legally mine texts and data from the internet so long as it's not for commercial gain.
(05:20):
And that may explain why certain AI tools currently give their users all rights to the content. In some territories though, every country has its own rules obviously. However, the original sources of answers generated by AI chatbots can be difficult to trace and they might include copyrighted works. So even if you are free to use the content an AI generates it doesn't mean it's work doesn't infringe someone else's IP. So as the end user, you have to really be careful about how using what an AI gives you and of course terms and conditions can always be changed later to give the AI ownership of its content. And if at that point you're relying on it, that can be tough.
Michael (06:04):
Really interesting. And then of course there's our own overtrusting of technology. How strictly are we actually treating our due diligence when it comes to taking what the AI gives us before taking into the real world? I mean, you'd hope lots but us humans well, we are human and taking time to double check the work of our digital assistant is painstaking. In the release video for the new AI chatbot of one very large tech company, it was asked for a cool fact about NASA's James Webb Space Telescope. The AI responded it had taken the first pictures of a planet outside our solar system. That wasn't actually true, but the video was published and wiped tens of billions of dollars off that company's share value. So there's a few reasons why organizations should be skeptical about generative AI, but there's a lot of reasons to be really excited too. AI is good at numbers. It can use existing data sets to generate new unique ones and vastly increase your sample size for research and analytics without having to actually collect that much data.
Aubrey (07:12):
Yes, and pretty soon, and there's a few startups in this area, AI will be able to generate interactive experiences and shows tailored to specific user needs. So for example, and this is pretty cool, a virtual shopfront perfectly tailored to the style and taste of a potential customer right down to setting the mood with the right music. AI can also suggest new software and products based on buying habits and customer queries, preempting demand and finding niches and features that human analysts might miss. And we're seeing AI being used to generate more efficient search tools and consolidate search information into summary documents without human interaction, which is revolutionizing the way businesses do everything from training staff to financial reporting and projections.
Michael (08:02):
That is all so exciting and there's so much that generative AI can do for us already or we'll be able to over the next few years, especially in niche applications where it's been properly trained. That is why organizations should care and be careful about generative AI.
(08:18):
Okay. Next up it's down to you, our audience as we open the floor for you to give us your recommendations on books, which have changed the way that you look at the world, life and business in the last 12 months. Now they could be technology based, they could have changed the way that you work or they could have just made you look at the world in a slightly different way.
Aubrey (08:36):
And as always, if you want to share your recommendations, there's a link in the podcast description. Just record a voice note on your phone and send it over.
Daniel Johnston (08:53):
Hey. My name's Dan Johnson and I'm going to be reviewing an amazing book that I read last year called The Obstacle is the Way written by Ryan Holiday. Ryan has a unique ability to research stoicism, all of the classic writers and thinkers and bring together their ideas along with characters from history, real life instances where people used the principles of stoicism to either do something exceedingly great. You've got people like Ulysses S. Grant who won the Civil War for the United States, or people who failed to ego and do not follow the path of stoicism and ultimately end up destroying their own lives or destroying their companies. Howard Hughes would be an example of one of those, but Ryan Holiday just has the most amazing talent for bringing that together in a way that's engaging to read, but also in incredibly informative. I really couldn't recommend the book more highly.
Michael (09:53):
Awesome. Thank you so much for that. Now it is time for TIL, today I learned we need a theme chain for this, Aubrey.
Aubrey (10:00):
We do.
Michael (10:01):
We'll work on that another time. Anyway, it's the part of the show where we each share something amazing or at least important that we've learned about in the world of technology this week, and we're going to take it in turns to talk about an organization doing something that we think you need to know about. All right, Aubrey, I reckon you should go first this time.
Aubrey (10:17):
Okay. So I'm taking us to the Netherlands this week where for the first time a paralyzed man is walking again thanks to a unique brain spine interface. 12 years ago, Gert-Jan Oskam was paralyzed in a cycling accident, but in a medical first he's been given an implant in his brain that allows him to use his legs just by thinking about it. Pretty incredible.
Michael (10:45):
Yeah. Wow.
Aubrey (10:46):
Starting in 2017, a team based across Switzerland and France developed a system which uses sensors on Gert's head to detect his thought patterns, which are then wirelessly transmitted from the implant to a portable computer that is small enough to be worn in a backpack. The interface designed by researchers at France's Atomic Energy Commission uses AI algorithms to decode those brain signals in real time, and then the data is then transmitted to a spinal cord implant that instructs the leg muscles to move. This system is so successful that Gert can now walk over uneven ground and even climb stairs. All thanks to modern technology and a little AI magic.
Michael (11:28):
Wow, that's cool. Well, I'm going down right into the core of everything and anything this week with the news that an individual atom has been x-rayed for the first time. Now this is super nerdy, but also super important because we've been able to look at atoms for a while using scanning probe microscopes, which is cool, but X-rays do something awesome. They tell us what things are made of, that's why they're used in everything from medical imaging to rock analysis on Mars rovers.
(11:59):
Until now, we've only been able to x-ray collections of around 10,000 atoms. Any smaller, and the x-ray signal is too weak to detect. But using incredibly sensitive detectors, AI and an enormous amount of compute, a team of scientists from Ohio University, Argon National Laboratory and the University of Illinois Chicago have managed to scan just one iron atom. So why does it matter? Well, now we know exactly what atoms are made of, we know their chemical state, we can know their fine details, and with that, we can finally actually start to understand materials and how they work and change them for the better. Think better batteries, better electronics, better alloys, right down to the atomic scale. And it opens up a whole world of quantum tech two, including more effective quantum computing in the long run, which is pretty exciting. Nerdy, yes, but pretty exciting.
Aubrey (12:59):
We love nerdy both very fascinating stories and you can find links to them in the podcast description if you'd like to know more. Okay, Michael, I have to take a deep breath because this is the time. Got to get ready. Prep your body for this
Michael (13:18):
Vocal warmups.
Aubrey (13:19):
We're getting towards the end of this week's show, which means it's time for this week in history.
Michael (13:27):
This week in history. I think that worked.
Aubrey (13:27):
It's a different take.
Michael (13:35):
It was like a multi frequency experience, that was.
Aubrey (13:37):
Definitely, and we also have a one to two second delay, so that makes it even more interesting. But I'm into it, so it's great. Okay. So this is where we look at something in the world of business and technology, which has changed our lives.
Michael (13:51):
So last week's clue was it's 1969, let's make plans to connect. And it was of course the announcement to create the internet. Now on the 3rd of July, 1969, UCLA issued a press release stating that it will become the first station in a nationwide computer network, which for the first time will link together computers of different makes and using different machine languages into one time sharing system. The press release went on to say that creation of the network represents a major forward step in computer technology and may serve as the forerunner of large computer networks in the future. I mean, they had a point, although the first actual data wasn't sent over the network until October that year. Pretty cool though.
Aubrey (14:38):
Very cool.
Michael (14:39):
Now the clue for next week is this artificial star really beam down. Do you know what it is yet? If not, you will find out next week. All right. Well, that brings us to the end of Technology Now for this week. We'll be back next week. In the meantime, keep those suggestions coming for books that have changed your year.
Aubrey (15:00):
Until we meet again. Thank you so much for joining us. Technology now is hosted by myself, Aubrey Lovell, and the lovely Michael Bird.
Michael (15:08):
No cheers.
Aubrey (15:09):
This episode was produced by Sam Dadapollen and Zoe Anderson with production support from Harry Morton, Alicia Kempson, Allison Paisley, Camilla Patel, Alyssa Mitri, and Alex Podmore. Technology Now is a lower street production for Hewlett Packard Enterprise.
Michael (15:25):
And we'll see you next week. Thank you.
Aubrey (15:28):
Cheers.