Two IPs In A Pod
Brilliant inventions, fresh product designs, iconic brand names and artistic creativity are not only the building blocks of successful business - they deliver a better world for us all. But these valuable forms of intellectual property must be protected in order to flourish. We are the Chartered Institute of Patent Attorneys - the UK's largest intellectual property organisation. Our hosts Lee Davies and Gwilym Roberts chat with entrepreneurs, creatives, patent attorneys and the occasional judge about how patents, trade marks, designs and copyright can improve our lives and solve problems for humanity.
Two IPs In A Pod
Redefining Creativity: AI, Patents, and the Future of Innovation
Join us as we explore this compelling question with Rachel Free, an esteemed patent attorney and the Vice Chair of the Computer Tech Committee at CIPA. Rachel takes us on a fascinating journey from her initial studies in chemistry to her foray into artificial intelligence, sharing intriguing insights into human-AI collaborations and the ethical dilemmas they pose. Along the way, we engage in some playful banter about verbal tics, adding a light-hearted touch to our deep dive into the crossroads of AI and intellectual property.
Lee Davis and Gwilym Roberts are the Two.
Speaker 2:IPs in a Pod and you are listening to a podcast on intellectual property brought to you by the Chartered Institute of Patent Attorneys. Good afternoon, Sir Amalot, Sir Amalot, Sir Amalot. Good afternoon Sir Um-a-lot, Sir Um-a-lot Sir.
Speaker 3:Um-a-lot. Are you picking up on something that I may have said in our little friendly chat before the podcast starts? It's embarrassed me in front of the listeners.
Speaker 2:I've never noticed how much you um. I like the name Um-a-lot and I think we should be counting. So, opinio, I know you're listening in. Can you count how many times Lee says um or er during this podcast, please, because it might be really distracting for the listener.
Speaker 3:I think I've got a lot better at it. By that I don't mean I do it more. I think I do it less, because when you become a podcaster, I think you listen to yourself more than you ever do normally and you become conscious of these little mannerisms in your speech. So what I'm doing at the moment, william, is a little tactic where I stop and, rather than filling that stop with uh or um, I'm no longer embarrassed by the fact that I stop. I'll just take a pause and then I'll speak again it sounds ridiculous.
Speaker 3:Please say I'm more um do you think, please, please, go back to umming and ah-ing.
Speaker 2:I was in Japan once. I love trying to pick up language and I always fail. But I noticed that they kept saying ano all the time and I thought, oh, that must be a really important word. In Japanese. That's, like you know, absolute key word that uh is. It drives conversation forward. So eventually I said what does ano mean? And they said it's Japanese for um, which made me laugh. Um. Second point what do I do? What's my irritating verbal tick?
Speaker 3:oh, you do tend to turn your head frequently. Uh, which is fine when you've got your little kind of in-ear mic thing in, because it turns with you, but, um, but sometimes you don't turn away and you keep talking and you've moved away from the microphone, you move back and your volume goes up and down. But it doesn't annoy me enough for me to have ever told you you did.
Speaker 2:Then I started this. I'm sorry.
Speaker 3:I'm sorry how's your afternoon gone? Second podcast recording of the day yeah, we've had some banter though so shall we crack on? Shall we get our guest on? Yes, yeah, yeah, yeah, so should we crack on? Should we get our guest on? Yes, so we have Rachel with us. Rachel Free. Welcome to the podcast, rachel.
Speaker 4:Oh, thank you very much, Lee. It's very kind of you to invite me.
Speaker 3:Oh no, it's a pleasure to have you on. Please don't feel nervous or anything like that. Gwilym and I have done so many of these now that it's second nature to us and we don't um and ah and things like that.
Speaker 4:So it's great to have you on, do I get 50p for every um?
Speaker 2:Yes, yes, you do From Lee, yes, you do from Lee.
Speaker 4:Let's try.
Speaker 3:Oh no, no, 50p, and I was doing so. Well, let let's crack on. So for the listeners, who? Who are you, rachel? What do you do?
Speaker 4:well, I'm a patent attorney. I'm a sepa member as well. I'm vice chair of the computer tech committee. My background is ai. I studied ai at university and I really enjoy patents. It's so wonderful. I'm so glad I became a patent attorney. So I'm a partner in a law firm called CMS, which is an international law firm, and it's quite unusual to have patent attorneys in a law firm. But I, there you are. I said an um, so do I owe you?
Speaker 3:let's not get fixated on it. Tell me a little bit about how your interest in ai came about. Was that, was that always what you were going to study, or did it come about sort of further down the track?
Speaker 4:I actually started off doing chemistry and then I switched subjects and for one of the finals papers I was able to choose my finals papers, and one of them was AI. I absolutely loved it and that led me to go on and study AI for a master's and a DPhil.
Speaker 3:One of my favourite things about AI at that time was representations how to represent knowledge and how you can do different things according to the representation that you use and at that time so ai is, variably across the years being something that's going to revolutionize the human race, something that's really scary and that we ought to be concerned about. Something needs regulating and control, uh, something that we just need to allow to be like freeform and organic. That's a lot that I've just chucked in already, isn't it? Where are you in? The great AI is something to be feared or celebrated continuum.
Speaker 4:I'm both, so I think it's very powerful technology and it's really going to improve our lives. There's lots of things we can do with machine learning technologies.
Speaker 2:Can I ask what your DPhil was about? What's the kind of specific research topic?
Speaker 4:Well, do you wear contact lenses? Because?
Speaker 2:it involves contact lenses. Go on go on that sounds amazing.
Speaker 4:So I was interested in representations. At the time there this uh researcher called david marr and he had a book um about the visual system and the idea was having different levels of representation, starting from the light that falls on the retina and then building up different levels of representation up to a 3d representation of the world as we perceive it and having different neurons in the brain for those different levels. So my research was involving vergence, eye movements and stereopsis. Vergence eye movements are where you move your eyes towards each other and away from each other.
Speaker 2:Yeah.
Speaker 4:That enables you to change the depth of the focal point and helps you to be able to see in three dimensions by fusing the images from your two eyes that are slightly displaced from each other because our eyes are next to each other in our head with a space between them.
Speaker 4:That ability is called stereopsis. So I had scleral contact lenses which are, it's, like a polo mint shape, and the contact lens goes on the white part of your eye and inside it was embedded a small coil of wire and you sit inside a magnetic field with your head on a bite bar so that your head is still as your eyes move. The movement generates a small voltage in the coil of wire, small current there, which can be then recorded and magnified in order to measure the eye movements. And then, whilst I was in this magnetic field with these contact lenses on, I was looking at random dot stereograms that I'd made, testing the relationship between those eye movements and the ability to see in three dimensions. And interestingly we found some differences according to how the random dot stereograms, the little small elements that those were made of, whether they were blobs or edges or lines, and that sort of tallied up with this David Marr idea of having different levels of representation actually hardwired into the brain somehow. It's interesting.
Speaker 3:It's really interesting and you don't know this, but before you came on, Gwilym and I were talking about colour and perceptions of colour and how you don't necessarily see colour in the way that it's presented in the real world. Your brain will do things to help you understand colour and it might look different to different people.
Speaker 4:Yeah, and there's many people who are colourblind or people who have more color rods in their retinas, so, like pigeons, can see more colors than humans, and there are some rare humans who have that ability as well. It's incredible.
Speaker 2:This is getting interesting, isn't it? Not what I was expecting at all? Funnily, I've heard of stereopsis, because I've heard of chromostere stereopsis, which is that weird effect where 2d different colors on the screen look 3d, like the netflix logo looks three-dimensional to me because it's black and red and your eyes do weird things with those colors and slightly different things. But um, apparently, um, and rachel, let's, I love you, love your default. So presumably this is all to do with machine vision and trying to work out. You know you had a training set which is the dots, and you had your activities and everything and you were using that presumably to kind of teach machines going forward or give them some data about how they might then do machine vision around.
Speaker 4:But it it had, it hadn't encountered the breakthroughs that came with image net and so, although machine learning techniques were available, I didn't use them.
Speaker 4:In my d phil.
Speaker 4:I was more looking at the representations and how the eye movements and how the human visual system was working.
Speaker 4:But it really does lead to an amazing thing today where we have these embedding spaces and the representation in the embedding space is just so cool because we can control that using the neural network. So it's an ability to create a representation that we have control over how it's created. So it's an ability to create a representation that we have control over how it's created, using language models or different types of neural network. And then, once you've got those representations, you can do things in the embedding space, doing work inside there, in an efficient way, because those embeddings are very compact representations, so it enables you to do computations efficiently and join together modalities. That's so exciting. Being able to join modalities was something that I was interested in when I was studying my DPhil. So being able to link together modalities of touch and the different senses that we have sight, smell how are those linked together? Embedding space, which is now enabling language models and image neural networks to join together and talk to each other in the language of the embedding space.
Speaker 2:You've got a bunch of inputs coming in. We should get to IP at some point. You've got a bunch of inputs coming in to this embedding space and the brain basically has tons of context and hardwired stuff that it does to link those together and kind of derive a much more coherent picture from it. Is that? Is that roughly what you, what you're talking about here? That?
Speaker 4:yes, you're filling in the gaps, being able to join those modalities and then apply attention. So being able to attend using the transformer architectures really has advanced the functionality.
Speaker 2:Back to IP Lee. Sorry.
Speaker 3:You carry on, Willem. You're in the driving seat at the moment.
Speaker 2:Okay. Well, let's move forward to where we're looking at AI in our space, and you mentioned that you were listening to the um ryan abbott um podcast that we did recently where of course, he's been very closely involved in one particular area really, which is the slightly boring legal question of whether ai can be an inventor. But there are also the underlying, rather more interesting idea can I, can ai be an inventive entity? I just wonder what your thoughts were on that whole dabos case and ai and where that went it's so wonderful.
Speaker 4:I love the right, ryan avid, and the podcast that you did so fantastic. And isn't it wonderful that we've had all the dabas case law? Because it's put society in a place where we've had the conversation. And we've had the conversation about can AI be an inventor? And it's leading on now to this question of AI assisted inventions, where a human creates an invention jointly with an AI tool or using an AI tool, and it seemed from the podcast that that's a new question that Ryan's bringing to the courts for them to debate. So I'm really, really keen to hear about that, because my personal opinion is that we should be able to have patents, no matter, because we want to facilitate knowledge sharing. That's really important in my view. Patents is one way to achieve that. Another way would be regulation, but that seems very heavy handed. Having more than one way to enable knowledge sharing would be good.
Speaker 2:Yeah, I think patents are a nice compromise, aren't they? They kind of they rely on the human innovative creative urge but just kind of hide away, they pull away the secret urge, keep everything a secret as well. I agree, I think it's a good. I think Ryan went on a bit about regulation actually, which is always interesting to step that far back into the kind of policy level. And do you think AI can invent? Because we hear different stories from different people on this.
Speaker 4:Yes, I think it can. I think we found that when um alpha go played against the, the world's best go player, and um made, was it move 36 or whatever. That was an invention, in my opinion I think it's excluded because it's a.
Speaker 2:It's a method or scheme for playing a game, but I'm sure I'm sure it's excluded, but yeah, yeah, but yeah, that's more regulatory of a problem.
Speaker 4:Yeah, yeah, yeah there's still an invention, even if it's excluded. Some inventions are excluded, fair point fair point, fair point.
Speaker 2:Yeah, yeah and and yeah, the the ai was the actual divisor true, true the other big case obviously it was knocking around in the uk at the moment is the emotional perception which, which I think has just had, leads to go to the Supreme Court, as I saw. Yeah and again. Rachel, you know we love an expert opinion. Do you want to kind of very quickly summarise that and what your thoughts are on it?
Speaker 4:So the emotional perception case is a neural network case and as far as I know it's a recommender system.
Speaker 4:In general, at the European Patent Office it's very difficult to get granted patents for recommender systems, and so the UK IPO in the first instance had refused the application, and then at the next instance the High Court made the opposite conclusion and decided that because there was an artificial neural network involved in the claim, that this made it the stuff of patents, and a patent should be allowed potentially as long as the other criteria for novelty and inventive step were met.
Speaker 4:This is now going to go to the court. It went to the Court of Appeal and they decided it was back to the same situation as the IPO, but with a slight difference, saying that even a hardware neural network would not be patentable, which is going differently from the status quo in the original situation. And then now this is going to be appealed to the Supreme Court, which is wonderful news because we will get legal certainty and it gives an opportunity for the Supreme Court to give their opinion not only about this particular situation of the artificial neural networks for the recommender system but also more broadly for computer implemented inventions and perhaps also for the way inventive step is assessed in the UK and the fact that that's different from the problem-solution approach.
Speaker 2:Gosh, that'd be interesting if it went that far Last time. The last one I'm aware of was the Davos itself. I think it was certainly on AI, and that was not quite as glamorous an outcome as I think people were hoping for.
Speaker 4:Yeah, but it's going to be very exciting, isn't it? Perhaps in 2026, we might have the decision.
Speaker 2:Gosh, if AI were running it it'd be a lot quicker, that's for sure. I was just going to ask Rachel where you see AI kind of impacting on your practice in terms of client, not AI as a tool in terms of kind of AI-related work. Are you seeing a lot coming in? Where are the hotspots for clients?
Speaker 4:So there's lots of work happening in machine learning and AI and agentic AI. Especially at the moment, agentic AI is really a hot topic. This is where you have lots of individual AI models that are able to work together and achieve something with synergy that's better than some of the individual parts. So that's a very powerful idea, and I was at a lecture recently given by an AI professor, michael Zhu, and he was saying that if we have an agentic ai systems, they can form an ai society and that this might lead to having, um, traits of that society which are something akin to consciousness. It seems a very interesting idea to me. He was saying that consciousness we could see as perhaps the ability to have memory of attention as well as attention. That was something I hadn't really thought of before. It's certainly having AI agents is going to be something that's going to improve all our lives, because we'll have agents that can do things for us. Like we might have one that does the grocery shopping and it would be able to find out, you know, do a meal plans, and it would be able to act with some autonomy, um, and you might have another AI agent that was maybe your fitness coach or one for coaching you at work or one to help you with financial management, but these are just some ideas that it's difficult to see into the future.
Speaker 4:My colleague said to me oh Rachel, what could we do?
Speaker 4:I want to try and make a benchmark for how I can compare the AI progress in different jurisdictions in terms of AI regulation and as well as the technology, and I was like like, well, I thought about that for quite a while and really I was thinking actually it's, it's what, it's what the AI can do for you, what it's permitted to do. So, for example, if, if you have an AI agent, if it's allowed to do the shopping for you on its own without your say-so, or if it's what things it's allowed to do the shopping for you on its own without your say-so, or what things it's allowed to do in that jurisdiction. Could it be a citizen? There's a sort of a scale of things, and perhaps that would be the way to do the benchmarking across jurisdictions. But it's definitely an interesting thing to think of consciousness as being a trait of an agentic AI system. Think of consciousness as being a trait of an agentic AI system. It made me think. Actually, do you think, gwilym, we could have a patent for a method of giving a machine consciousness.
Speaker 2:In terms of would that be something that the patent office would accept, given if you substantiated how to do it? I think so. I don't see why not. I always wonder where you you start wondering about what you use the patent system for. At that point, though, you think if you did get that one, you probably wouldn't open the public domain. Sadly, if you got there first, you keep it to yourself because it's not far off. A method of being god, which is a fun topic, lee what about article 53 um european?
Speaker 4:parents shall not be granted in respect of inventions, commercial exploitation of which would be contrary to morality. I think, it's a great question, I think, the morality.
Speaker 2:I think the most wonderful thing you could give, the most moral thing you could do, would be to give something inanimate, a conscience that's very moral, the opposite of immoral. It's lovely, but how would we tell? I've got to close and leave by the way I was going in the same way.
Speaker 4:Artificial general intelligence. We're on the way to it. When we reach there, how will we know, and what would be the difference between? What is it that makes us human and different from a machine that has got artificial general intelligence? Very different, very difficult question, well isn't?
Speaker 2:it funny how quickly you shift into philosophy in this whole area, and I think the turing test is now is now met, do you think so, wasn't it? Very simple test. If you can't tell the difference, I can't tell if something I I was marking some papers, I won't say where, recently, and the only way I could tell between the ones that were almost certainly human generated and the ones that had a bit of ai help, shall we say, was the ones the ai help were better, just so. It's kind of an exceeded, I think, because it was really difficult. The only reason I could tell it was probably ai generated was because it was just so good and so articulate and so accurate from a bunch of people who were just moving into the field that I thought, yeah, it's too good. So it's as if the Turing test has been flipped on its head. The only way to spot now is it's better than humans.
Speaker 3:Moving that forward, and this is more the philosophical side of things. We don't need to discuss this. This is one of the answers to the questions. Ai will know that it's doing damage to the world and will stop itself from doing damage to the world because it's beyond human intelligence. We're humans, though, that are doing damage to the world, and they just carry on.
Speaker 4:Yeah, that's very profound, you know it is.
Speaker 3:I had to get in somewhere. I was needing to get into this conversation.
Speaker 2:No, there's a distinction between, I suppose, consciousness and conscience there. But there's a distinction between, I suppose, consciousness and conscience there Big time isn't there, and conscience is an extra layer on top, isn't it?
Speaker 3:I think you have to build that in. Can I bring us back to more mundane patenty type things?
Speaker 2:Oh, go on then.
Speaker 3:So you may or may not remember this, rachel, but I'm unminded of it because it was almost 10 years ago, so 2015,. We had a public debate. Cp had a public debate on AI. So 2015 we had a public debate. So you've had a public debate on ai.
Speaker 3:And we had a bunch of patent attorneys. We had a bunch of scientists, we had members of the public about 500 people in the science museum, in the imax theater, there, and we asked the question, or posed the question, should I say. This house believes it is inevitable that within 25 years so now 15 years on a patent will be filed and granted without human intervention. And we had two futurists Chrissie Lightfoot, who's a lawyer but now perhaps more well-known for her work around AI, the naked lawyer. And Callum Chase, the author of one of the best books I've ever read, pandora's Brain.
Speaker 3:And then we had a patent examiner and a patent attorney probably shouldn't name them who spoke against the motion. We never, ever, reached a decision because from the floor, we had the bizarre question well, you know, the proposition that's been put to the floor doesn't say whether that patent would be any good or not. And we then got lost in the debate about whether we were actually talking about good patterns or bad patterns, but we did at one point during that talk about AI's role in examining in inventive step in those processes that are involved in proving the invention, and I know that you've done work on that, rachel, so I didn't know if you wanted to say something about where you are particularly around inventive step, but more generally, the use of AI in the patent office side of the equation.
Speaker 4:Yeah, I think it would be lovely if we could have some AI tools that would help with examining things like Inventive Step, although it should be a human that makes the final decision, which is based on the pre-search from the EPO, where the patent application would come in, go through the language model and be converted into an embedding, and then you would look in the embedding space to see if the volume in a certain radius is empty.
Speaker 4:Well, this embedding space is one that's been pre-populated with the prior art and if that volume is empty for far enough, you could somehow say that this patent application is groundbreaking and therefore there's an indication of inventive step. So it's not the problem solution approach, because it doesn't involve combinations of documents, but it's an indicator that could be done automatically and could help examiners in their assessment of inventive step. So I think that would be quite useful, although lots of people have said to me oh, it's no good because it doesn't consider combinations of documents. We could try to look at combinations of documents in that embedding space by adding and subtracting vectors in the space, but I'm not sure that that would work. So I think it comes back down to looking at the volume and seeing if the volume is empty, and also assuming that that space this is a space of inventions that it would be somehow continuous and that we could take account, or we would have a map showing the areas of excluded matter, the excluded matter holes in the space. We would know where they were, so we could take account to avoid those. And perhaps, after we'd done this indicator test, then also do a follow-up to apply the problem and solution or check that there was a technical effect there so that we'd avoided any excluded matter.
Speaker 4:Yeah, but in the end I think it should be a human that makes the decision, and that's because the case law influences. Law, is reflexive, so society creates law and law influences society. And because the case law, even in patents for words like technical, are not defined. And that's on purpose. Because we can't define technical, because technology is constantly advancing, so therefore it has to be defined through case law. And if case law is set by AI adjudicators, there's an immediate problem. So we have to have humans making the case law as far as we can.
Speaker 2:I was going to pick up on a couple of points there, actually, because again, there's been lots of conversation. Ai can invent. Ai becomes a skilled person that's cleverer than human skilled person, which changes that bit of the test which would be, I guess, part of the story trying to manage that story here. But there's another point for me on that the word knows intelligibility. We there's a lot of work, isn't there, on making sure that ai's decision making can be understood, that you know why it's doing what it's doing, and I guess a risk would be, if it was, if a lot of the stuff was the kind of the vector space kind of layer that, as you say, we wouldn't be able to work out how justice had been done, as it were, in terms of identifying whether there's an event of step or not, because it was hidden in a bunch of nodes and neural network steps that aren't human comprehensible. Is that something that you think could be a concern?
Speaker 4:Definitely yeah. I think what you're saying is that the, the language model that generates the embedding of that, represents the patent application, is not. We can't explain in a human understandable way how it made that embedding.
Speaker 2:Yeah quite, quite, quite yeah yeah yeah, yeah.
Speaker 4:Yes, that is definitely a concern, but I guess because we're able to test, we've got a huge body of supervised training examples, because we've got the whole of the granted patent literature, so there's plenty of scope for testing, to test if the, if it's working sensibly or not have I told you about the short story competition I won?
Speaker 3:if you did. I can't remember. Well, I'm sorry and I feel it is relevant.
Speaker 2:It is relevant because, um, I think, I think I was the only entry, which is always a good way of enhancing your chances, and it was for the I think it's american bar association ip you've never told me this.
Speaker 2:You've never told me okay, they wanted an ip short story and, rachel, I don't know if you read your science fiction, but I'm a big sci-fi fan and one of my favorite books is neuromancer, um, which of course was the ultimate cyberpunk defining novel back in the 80s.
Speaker 2:Um and I wrote a story about ai inventing stuff and then being examined by ai uh examiners, um, but it was all done in cyberspace and so they had this massive kind of um, funky video game sort of fight, but using novelty and inventive step as their weapons. And for some reason I think it must have been the only entry, because, unless you're reading your romance and you're a patent attorney and you you're me, I don't think it made any sense to anybody. But I did have this idea that we'll end up in a situation where ai is inventing stuff, ai is examining stuff, it's all getting done in real time and we're just sitting there seeing patterns being spewed out with no idea what to do with them, which, weirdly, then comes back to the question of conscience, because if ai does get to this point where you know, if we can automate all these things, how do you make ai continue to invent things that are actually useful for humans?
Speaker 4:well, that's easy to do. So you you have. So at the moment when you you do reinforcement learning, um, you create a neural network that buys a reward function. So you would have a um. You create a machine learning model that was trained. You could have one bespoke for guillem that knew about your preferences and get the results from the other model. And it would go will guillem like this yes or no mark out of 10 and then send it. Send that result back as a reinforcement learning I quite like that.
Speaker 2:Yeah, can we start? I'm very happy to be the training model.
Speaker 4:Not a problem, not a problem yeah, have you heard about this colossus?
Speaker 2:I don't know. No, no, no, it's amazing. No.
Speaker 4:I haven't. It's going to be like 100,000 GPUs and that is just mind-boggling to me. And apparently it's been built and it's going to even increase more in size. It's just phenomenal to even increase more in size. It's just phenomenal.
Speaker 4:So the models, that the size of the machine learning models that could be trained will be vast using this type of scale, because at the moment, the generalization ability of the machine learning is what really makes it powerful.
Speaker 4:So you train the model using some examples and then you can give a new example that the model's never seen and, because it's able to generalize its knowledge from what it learned, can give a good answer. And usually when you make the model bigger by giving, like having more GPUs and making the model bigger, you would think that it will just learn the training examples exactly, which is called overfitting. Yes, and very strangely, that hasn't happened yet, even though the sizes of the models are increasing and increasing and increasing and increasing. Sizes of the models are increasing and increasing and increasing and increasing. So, uh, they're getting bigger and emergent behaviors here ability to do, think to, to perform things that it was not trained to do, and and so colossus that's that lean yeah, it's just amazing, oh thanks so right, rachel, one of my jobs on the podcast is to keep half an hour of the time, and I'm conscious of it.
Speaker 4:Oh, it's half an hour.
Speaker 3:We're lurching towards an end and I know that we've not talked much about regulation and I know that's another area where you've been active. Do you want to give us your sort of like potty overview on where we are with regulation and where we're likely to go in the future potty?
Speaker 4:overview on where we are with regulation and where we're likely to go in the future. Yeah, I think regulation is important for us patents attorneys because it impacts ability to detect infringement, it impacts commercial ways that our clients can use their technology, and we have to advise our clients holistically. Not just can you protect this with patents holistically, not just can you protect this with patents. Think of more, everything in the round, and that includes regulation, especially because with powerful technologies come responsibilities and those responsibilities, increasingly, are going to be regulated. We have the EU AI Act, which began in August. We have the EU AI Act, which began in August, and already different countries are implementing that in their own laws, and Italy is one example where there's been a need felt in Italy to make even stronger regulation. Stronger regulation so there can be penalties of going to prison for not complying with AI regulation potentially in the future in Italy.
Speaker 4:And it does seem like AI regulation is going to happen in the UK soon. There's been some press releases about that and saying that the AI Safety Institute will become a regulation body as opposed to being something that's just looking at AI safety and is not doing regulation. So regulation is going to be part of our lives, for all of us working in AI fields, which is pretty much everyone, because it's going to be in all sectors. So it's interesting because regulation is like you must do this, you must do this. It's very different from oh, if you do this, I'll give you an incentive, I'll give you an incentive if you do this. Regulation is like you must do this. So, whereas I think patents are more of the incentive line of things and that therefore they can be useful, and often we think of patents as only being an incentive for creating innovation, whereas there's many more purposes, including helping us, helping share knowledge about technology.
Speaker 3:But, rachel, we've asked you lots of questions. Are you sat there thinking, oh, got away with it. They didn't ask me that one, or damn. I've had the opportunity to say this Is there anything else you want to add, as we kind of hurtle towards the close of the podcast?
Speaker 4:I could tell you about my funniest AI. Oh yeah, it's so funny. I think it was dave's garage. It's like this video on youtube and it's this guy he's. He's made an a chat bot of himself, his own voice, and so that when telemarketers phone him, it answers the phone and it has the goal of prolonging the conversation, but never coming to a final conclusion or giving any instructions or agreement. And the telemarketers phone up and you hear the conversation with the bot and it goes on and on. It's just very funny.
Speaker 3:I've always done that in real life. In fact, we had a telemarketer ring the office just earlier today and I had my EA, charlotte, tell the person that we weren't interested it's not that we're interested in and then Charlotte looked at me and she said he's asked to speak to my boss. So she put him on and he asked me whether I had a good day. So I started telling him about my good day and he said no, hang on, I'm trying. No, you've asked me if I've had a good day. I'm going to tell you about my day and he hung up. So it does work. It does work. Uh, rachel, thank you so much for coming on and sharing your um, your knowledge and your expertise, but also your um sort of ending with a uh, light, light-hearted, um example there. Guill, you said to me earlier that you might have a closing question. Do you have a closing question?
Speaker 2:I do. I do Actually just for opinion. If you're counting, I only got four ums, lee, so you owe Rachel two pounds and I'm going to. You also said continuum, but I'm not going to count that.
Speaker 3:Is that?
Speaker 2:where I can't stop umming.
Speaker 3:Is that the um, um, but I'm not going to count that. Is that where I can't stop umming, is that?
Speaker 2:the um Um.
Speaker 4:All the listeners now will be checking you, gwilym. You do realise this, don't you?
Speaker 2:And they'll be writing in complaining if it's not right, I know, go on then, let's just. I can only commend you on that. The continuum is a never-ending um. That's a beautiful concept. No, my closer was um a really simple one, which is that if you could give an inanimate object consciousness, what object and why? Rachel, you're up after lee, so wow what a what a stonking question.
Speaker 3:Bizarrely, it's not something I've ever given any thought to before.
Speaker 2:Walt Disney did it, didn't they in that Mickey Mouse early film dancing broomsticks and things?
Speaker 3:Yeah, so maybe I don't know. This is, I've no idea, gwilym, so I'm just going to pick something at random A cricket ball.
Speaker 3:Hit it A cricket ball, and maybe we could then finally come to understand the mystery of swing and reverse swing, because it doesn't always follow any kind of physical laws. Sometimes the ball will swing, sometimes it will reverse swing, sometimes it's about atmospheric conditions, sometimes it's about the pitch, sometimes it's about whether you've applied anything to it and rubbed it frantically. It's about whether you've applied anything to it and rubbed it frantically. So, yeah, I would animate a cricket ball so that you could tell me the the mysteries of swing bowling for reasons only if I couldn't think of anything else no, that's really good.
Speaker 2:I I would love. It's a bit cruel, but I'd love to hear the cricket balls in the monologue through the bowling batting cycle.
Speaker 4:Anyway, um make sure they give you, give you some thinking time there, perhaps the moon, I think the moon because it can see um the earth and it could probably tell us things, have some very useful insights we can find that it's actually populated by aching drum, which is what I've always told my children as well but, um so you obviously asked this question because you've got an answer.
Speaker 2:We know how this works well, I don't have more time to think about the answer. Actually, I want something. I want to hear its memories. Um. So, rachel, you want to know what the moon can see. I want to know what the river thames can remember I reckon how awesome would that have you ever?
Speaker 3:read the novel series rivers of london bits and pieces of it. Yeah, that's yeah, not, not the same, obviously, as its memories, but yeah, it would be fascinating, wouldn't it, to know what something that's been here since the dawn of time would be able to tell us.
Speaker 2:Yeah, there we go, gosh, that's been really good. It wasn't really much for AI, but it's very good fun.
Speaker 3:Rachel, thank you so much for coming on. Gwilym, thank you for working with me on two podcasts in one day. That's quite exhausting.
Speaker 2:On a range of topics.
Speaker 3:Thank you to the listeners, because without you, we don't have a podcast, and you could help us generate far more listeners if you just leave us a little review on the podcasting platform of your choice, so more people find us. Alternatively, gwilym and I are going to go away and try and find some kind of AI bot that will do that for us. That's our task. Unbelievable On it. On it. Thanks both. Thank you, we'll see you next time.