Get The Memo.
Q: COVID and AI revolution. How do you see COVID affected AI?
I do a bit of consulting with the pharmaceuticals, including some that are in the building, some that helped develop the vaccines. In one of my AI reports, I documented how one of the major vaccines was developed using artificial intelligence in that it was able to look at various different options that a human couldn’t do in that amount of time. It would literally be impossible for human lab scientists in the lab to look at these millions and millions of combinations. And the particular artificial intelligence model that these guys used was looking at all of these different combinations, and then it spat out essentially one that we ended up using. And I think that’s probably the most visceral example of using artificial intelligence to impact health medicine where we’re actually at, rather than just saying, we can go and summarize some data or we can help it write a report or we can take in people’s feelings, do sentiment analysis. This was literally coming up with one of the vaccines that we used for COVID.
I think some of this stuff or maybe all of this stuff is hidden from the public. But if you go into some of the press releases, some of the white papers, some of the technical reports, it’s detailed there for those that want to look for it. It’s happening across so many streams, not just medicine and health, but economics, philosophy, psychology, huge in education, as you will have seen. It’s impacting every industry.
Q: You talk about in 2017, everything changed. So do you think AI projects, because people have been trying to implement in their business with mixed results and trying to make the data kind of structured and stuff like that, do you think that’s going to be less need for that or do you think what do you think changes in the business side? How do you think people change the ways of using AI now in this modern way?
Pre-2017 or even pre-2020 AI was just so different to what’s going on right now. I remember looking at the Australian stock market, we call it the ASX here, to look at different companies that I could invest in around 2021. And there were those that were essentially just labeling, like sitting down a huge call center full of workers labeling data. And I was like, probably not going to invest in that one. So instead of invested in Nvidia, which has now jumped up 200% and they’re the first trillion dollar chip maker, which is crazy, maybe besides Apple. The human data labeling aspect of this and a lot of other things are just completely irrelevant. And that one is really fascinating to me.
As part of my lecture, I did have a piece that I was going to do as a case study on very large enterprise using platforms like GPT-4. So PWC have got access as part of Harvey, which is part of, like it’s a layer on top of GPT-4, which essentially allows them and allows their thousands or tens of thousands of lawyers to query millions of documents, fine-shooned on millions of documents in the legal profession and talk to these documents. So where they might have had paralegals sitting there researching, and again, it’s going to be a room full of paralegals trying to do this. It’s done almost instantly with GPT-4. So I talk about having GPT-4 as almost like a boardroom full of PhDs working 24-7 for you with specialties in whatever your particular industry or field is. So the same way that PWC and Harvey have done this for legal, you can see this being applied for pretty much everything. And I’m glad that Vicente got in touch because Iceland is one of the prime examples of this. Open AI got in touch with the government of Iceland there who had collected a range of documents from, I believe it’s from congressional minutes, like from parliament, through to policy, through to business processes. Package is all that up and trains GPT-4 on it. So now you can ping it and get responses that are very, very much tailored to Iceland.
So I see that impacting enterprise and business more and more. And I see it being far different to what it was even three years ago that now you’ve got this black box that can essentially do anything that you can go and ask it any question and be pretty confident that its results is going to be better than any human.
Q: Let’s start with work. Initially, the idea with AI of this new type of AI, as far as you know, was to increase productivity. However, we moved to reduce cost. Do you think this is going to keep going this way or is going to change in the future?
I don’t know if you watched Sam Altman giving testimony in front of the US Congress. I have not watched the whole thing because it’s two hours plus. I haven’t even read the transcript because the transcript is like 70 or 80 pages. So I’ve had models summarise it for me. There’s a really interesting snippet in there. So Sam Altman is the CEO of OpenAI who currently kind of hold the record of the largest language model in the world. So we’re saying GPT-4 might be a trillion parameters.
We already know that it achieves in the 94th percentile of testing in something like the SAT, the massive pre-university or pre-college exam in America. It achieves in the 99.5 percentile for the bio-limpiad. It’s really smart. It’s superintelligence. Microsoft called it a spark of AGI. They originally said this was early AGI, artificial general intelligence. So we’ve got this thing here that is smart of the most humans in everything. Not just one particular subject, wasn’t particularly trying to do anything. It’s ready to open up the world and solve any problem you can think of, any problem that you can give it in language. It can essentially solve.
And you’ve got congressman in this interview or in this testimony, in this debrief asking, what is it going to take our jobs? And I wonder if that’s really the right question. Because in the long term, and you’ll see a lot of people, similar to me, like Dr. Ray Kurzweil, like Andrew Yang with the UBI concept where there’s a universal basic income for everyone. We don’t have to work because artificial general intelligence is doing everything for us. It’s mining out, or it’s building out houses. It’s running around creating life for us.
There’s really no need for discussions on productivity or cost reduction or capitalism. I mean, it’s going to be confronting for people to even think along these lines. But I thought it was really telling to hear a congressman, and these are quite old men generally who were brought up in the 50s, 60s, 70s, talking about labor when we’re in a completely different world. We’re in a world where artificial general intelligence or even GPT4 itself can do things that might have been reserved for humans before. And there will be a ramp to get up to, we don’t have to do anything. But that discussion should be happening. And instead we’re asking about, well, is it going to take our jobs?
It’s a really fascinating discussion. It’s confronting, it’s frightening. It’s scary for a lot of people because it’s happening in our lifetime and it just changes the conversation about everything, whether it’s business or whether it’s about leisure. But I can see this happening already. You can see this spinning up internally with big enterprise, with some big governments like Iceland, like Malta, for example, who are getting behind artificial intelligence early of the UAE and parts of the UAE who are getting ready for this. And saying, right, this is here. We have superintelligence or we have pre-superintelligence. What’s next? And discussing less about work and more about, right? How are we going to live? If AI can do everything for us, what do we have? What does leisure look like or what does living look like? And that’s a, I know that’s a scary discussion. And I know people of any age that’s going to be particularly scary, but I can see the fear and the eyes of the old governments.
Q: You mentioned AI is creating life?
Yeah, I use that as a term. I don’t mean it’s biologically creating life, but that it will be able to help us generate experiences. So when we’re mapping AI into the retina, perhaps with Apple’s VR headset, which would be launched in about four or five days from now, early June, or even just in basic conversations, you could see its capabilities in generating gameplay, in generating virtual reality or augmented reality. You can see it generating scenes or scenarios. And I think that’s going to be really, really big in the next few years, where it will create based on what we ask it to. Right, I want to be in the Bahamas. I want to be in this particular competitive environment, or I want to have control of this all in my own world, but it’s creating that world for us. So it’s essentially creating my life with my instructions. And it’s not that far out. All of this stuff sounds science fiction, but in some ways it’s actually possible right now. And there are people who are playing around with this in different ways already.
Q: Let’s say I’m a company here in Iceland, and I don’t want to be left out… what should I do? What should I do to be make sure that I am my company is like using this technology and how can we utilize it actually?
Yeah, you’ve probably heard the almost cliche phrase these days that AI won’t take your job, but people who know about AI and are using AI will take your job. And you can expand that, of course, outside of jobs. The enterprise that I work with, and they range from startups, startups sometimes just achieving funding all the way through either trillion dollar companies or governments with trillions of dollars under management are looking at AI in different ways. And again, it’s almost like your imagination is the limit because you can go and pop in chat GPD on top of your company documents, like with plugins, have it pinging your PDFs and looking at your company documentation so that you’re not wasting time with people, real humans doing stuff that we probably shouldn’t be doing and instead of doing bigger things. But then you’ve got companies like CS India, who I might have mentioned in my lecture, who are pointed chat GPD as their CEO. Now that sounds a bit like, you know, just a marketing thing, just done for Farno as a novelty, but there’s no reason why that couldn’t happen. The reasoning that exists inside these models and the capacity for long term planning and for looking far out to achieve, to achieve objectives is already there. So there’s really that entire range. You can have it pinging your documents, you can build in a chat box to your company for your internal staff to ping, for your outside customers to ping, for your board to talk with. Right now you can use it for a process optimization really, really easily, all the way through to essentially running the company.
And the CEO of OpenAI, Sam Altman says the same thing that just this year there are now companies that are created around GPT-4 because the capabilities are so massive. So you can have it automatically generating computer programs for you, or writing new languages for you. It’d be up to your people to be able to find where they want to slaughter them, how they want to use it. But really again, Skies the limit, and I’ve seen some extraordinary applications of it. The ones that I get involved with just in the last couple of years, so say 2022, 2023, yeah, the last year and a half have been the chat bots internally, so you can ask it about your company policies, or if you’ve got thousands and thousands of staff around the world, then you’re not having to go ring London or ring New York and say, how does this product work? You ask the chat bot who brought all of that information together.
I’ve seen it used in strategy and design. I’ve certainly seen it used in larger ways that maybe I’m not allowed to talk about, but basically what I’m saying is the model there is not really limited. We’re still finding out what GPT-4 can do. So if you’ve got an internal process or an internal way of doing things, whether it’s computer programming or developing a widget, this model can probably help you out with it.
Q: Universal income and leisure. Do you think leisure will become our future job? I’m talking about you and me, not my daughter. Could we live in those days?
Yeah, it’s a huge question, Vicente. And I’ve gone on record to say that artificial general intelligence, that point in time where these models are smarter than us in anything, including physical work, is a few months away, not a few years away. So if you take today June 2023, I’m saying before June 2026, we will be at a point where companies, maybe not you and I at that exact point, but companies will have an AI model that can do anything and is embodied in a physical robot, and you can ask it or tell it to do anything.
Now, how long that takes to get to you and I is a subject for discussion. I think there will be a lag in a delay between it being available in say Silicon Valley in California, and then being here in my office or there with you. That may take a little bit longer, but certainly it’s going to happen the next few years. None of this stuff that we’ve discussed either in my lecture or today is a decade away anymore. We’re not waiting till 2033. This is going to be very, very soon. So I think you’re right to ask about us rather than children, there are discussions even about whether we should be having children in an age where we have super intelligence because no one knows what that looks like. And given the historical decisions of different governments and intergovernmental organisations, who knows whether that’s going to be idealistic or utopic, right? Because we’ve got humans in the loop still. I would trust that when we have unofficial general intelligence or super intelligence in the loop, it will be for our benefit. But at the moment, we have people like the congressman that I mentioned earlier saying what about our jobs in charge of making decisions and in charge of essentially slowing this down to say or to assume that we get to a point where AI is giving us this utopian idealistic world, which is within the realms of probability, not just possibility. I think it’s going to be pretty fascinating.
I don’t really have a picture of it yet, but some of my colleagues like Dr. Ray Kurzweil have drawn pictures of what this might look like, for example, living within our own personal worlds that have been designed by artificial intelligence where it’s meeting every specific whim that we have, whether it’s being on an island somewhere or being in a library at Oxford or Cambridge just learning, learning, learning all day or creating, whether that’s art or otherwise, won’t have to be hands-on painting. You can see even in midjourney or some of the text image models, you can say, create me this world where I’m on a cruise ship and the sky’s always blue and everything is incredible and it will help you create that world. All of this stuff sounds so far out and yet you’ve probably already seen glimpses of it happening in different AI models and how that gets actually brought to us is going to be a different story. I can’t wait for it to be happening immediately.
Q: You seem to be very interested in embodiment. Do you think we’re going to still, families having a robot at home, like normal families having one robot at home or it’s going to be different?
In the media cycle right now, you’ll find everyone from CNBC to Fox to probably the Reykjavík Times talking about large language models. You know, they’re a year or two or three behind what’s happening right now. Just this week, Agility Robotics launched a video of their figure robot, figure 01, which is more than capable of having a large language model built inside of it and they show their CEO talking to this robot in real life and it following instructions, which in the case of the latest video is just clean up the room. But the robot knows even though it’s not been trained on any of this. It’s just a large language model, a large language model with some black box, like GPT-4 or like Palm, built into a pretty ugly robot. But it will go and pick up things and find which bin it should go in, whether it’s recycling bin or trash or like a sorting bin. Push that out to, well, we could think of limitless examples here. But I’ve said like, go and make me green eggs and ham or go and fold my shirt into a paper crane. Just stuff that it would definitely not be programmed to do. And it will go and do it because these large language models will try and find the next most reasonable word token or response.
And it’s not just agility robotics, figure robot. You’ve also got the Tesla bot. You’ve also got my favorite bot, which is one X’s Neo bot and the EVE bot. Which is on wheels. But one X Neo is a fabric covered robot, which again can have a large language model behind it. And I believe that their name, one X, the company name, comes both from the fact that they want to have their videos in real time. So at one X speed, where everyone else is doing their videos at 4X or 12X speed, because the robot’s so slow. But also one X as in for every human. We’ve got this embodied. Large language model robot, they call it a human like Android with us. Completing one X productivity or one times the productivity of us. Now. That’s pretty exciting. And again, not 10 years in the future, the agility robotics figure is here. It’s here. You can go and play with it in their factory. The one X Neo is out later this year, 2023. There are half a dozen very serious contenders as in they’ve done the same thing, whether that’s the Tesla bot. You can go and talk of Boston dynamics doing that with some of their robots. There’s a long list that I can go and read off. But it means that there are human. Company competitors in this space developing these human like Android’s to do exactly what we’ve just spoken about, which is to increase our productivity by one X maybe by 2X or 3X. And you can have a made robot and do my office work robot and a gardener robot. And a whatever you want robot.
I know that pretty much everything I’ve mentioned in our conversation today really does sound like science fiction. And it’s important that everyone has visibility of the reality. And the reality is that this stuff is here. It may be in a lab, but it’s actually here and proven. It’s not like they’re coming up with a prototype. The agility robotics example and the one X example. And to a certain extent, the Tesla bot example are designed for mass production. They’re designed for consumers to be using. They’re not like 2017 or before just for just for fun. Like the Honda Asomo robot. Was not even comparable to what we’re talking about today. There was no openness to it. It was pre-programmed. It was scripted.
Whereas what we’re talking about today is putting this black box. And the chief scientist of OpenAI has called this black box alchemy. So I don’t mind using the word magic. Let’s call it a magical black box inside some sort of human like Android. And putting some safety measures on top of it, of course. But having a one X version of yourself to support you in service in this physical embodiment that can do anything that a human can do with arms and legs.
Q: Do you know if these robots execute the AI in hardware or is over the network?
It’s a great question. So if we talk about something like DeepMind Gato, which was the very first proto-AGI or the first popular proto-AGI. It was essentially developed to be completely local. As in they got an Nvidia RTX 3090 graphics card, which is about that big actually, and shoved it into the robot to the embodied intelligence. So it could go out and not need connection to the cloud or otherwise. I think the very latest ones in some ways will be able to do that because we’re both decreasing the memory requirements, as well as increasing the power of the hardware. So NVIDIA are bringing out new hardware all the time that will allow us to pack more stuff into it. But I think we’re also going to need web access. You also want to have it both updated, as well as having access to more smarts if it needs it. So it might be that we’ve got a local bit of hardware that processes 90% of it, but that we offload 10% of the very smart stuff over the airwaves, so to speak.
Q: Do you think we could run into a problem of reaching the ceiling of a computer power in the world?
That’s a huge question. NVIDIA just yesterday or the day before in Taiwan launched their very latest chip, which combines H100, the largest possible GPU with a CPU as well. Super expensive, super huge. They got it up to hundreds of terabytes, this supercomputer cluster essentially. And they’re talking about developing Helios internally for themselves for Nvidia. I’ve seen some extraordinary metrics of supercomputers. For example, there’s talk of the supercomputer for GPT-5 created by Microsoft and OpenAI. By using 25,000 GPUs. That’s confirmed by Morgan Stanley and it’s had some input from Microsoft as well. That’s massive when it comes to being available to train a model. I’m not sure what limits will hit when we’re trying to serve 8 billion people or even 1% of that because large language models are incredibly onerous when they’re being used for inference.
So if you’re on chat GPT or something similar and you’re asking questions, the hardware team at OpenAI have found some real bottlenecks. And they’ve been able to resolve those to a certain extent, but they found that when they’ve got 100 million people per month trying to access via inference these models, it’s hard. This is not just like you’re peeing a game server, even though that’s hard. This is even harder because you’re asking for so much processing to be happening. So I’m very interested to see how that progresses. I can certainly comment on the training and comment on the fact that Tesla have their supercomputer in video have their supercomputer coming. OpenAI and Microsoft have their supercomputer. But that’s all for pre-training.
What happens when we do need compute for 8 billion people or even 80 million people being able to process all of this data at once for their embodied AI or for their own version of a very large language model internally. I’d be willing to bet that the optimizations that we’ve seen recently will make all of that far easier. So for example, GPT-4 trillion parameters that might need to be run on gigabits and gigabits hundreds of gigabits of RAM. But then if you look at something like Lama and Alpaca, we’ve got that down to 5 gig, 8 gig of RAM so people can run that on their computers. And that’s all happened really, really quickly within like three to six months. We found these amazing optimizations.
Q: Talking about Alpaca and those. Did you have the chance to try those personally?
Yeah, I played around a little bit with I don’t get two hands on with tech, but certainly Dalai, which is very easy to run on the MacBook Pro and Alpaca in general. They’re easy to set up now and have been for the last couple of months. They’re these laptop models I call them are not necessarily comparable with a big model like Palm or like the big GPTs. But it’s interesting to have that here at your fingertips to shut off the internet and it still keeps going because it’s all right there in RAM.
I just think people do like having control of their own models and having it locally, but it’s almost and I’ve said this before it’s almost like comparing a paper plane, you know, you make out of paper in the cloud story and throw that around versus GPT for Palm, which are these massive Boeing 747s. So you can have the paper plane on your laptop if you want, but out there, if you just connect via cloud, you can have the proper jumbo jet. Okay, so it’s done different. Yeah, they really are Alpaca and and all of their ill there are something like there are close to a hundred models like Alpaca that have been trained using Lama. And then all different fine tuning, they are, they are imitation models.
There’s a fantastic paper that came out in the last few days that basically says imitation models like Alpaca and Gorilla and Koala and GPT for all and I can keep naming them are because they were trained on chat GPT outputs. They are trying to emulate the Boeing 747 or the GPT for the chat GPT, but all they’re getting is the results from the queries that they’ve tried to go through with chat GPT, which includes stuff like error messages from chat GPT. I’m a large language as a large language model. I can’t respond to that and they’ve kept that in these imitation models. So findings from the research paper will basically yes, your imitation models can do a little bit of what chat GPT does in a smaller vector, but when you’re asking it broader questions, there’s no benefit at all. It’s not learnt anything. So yeah, I’m not a huge fan of them essentially.
Q: Businesses because I know that if you use this models now, people are often worried about that they are sometimes wrong and they might be sending wrong information from the company and nobody can play with them because…
Yeah, it’s a difficult one right is it’s the problem again, Smari is the humans is the you remember that 1990s phrase we had problem exists between keyboard and computer. Right. It’s not exists between maybe that was right keep on computer basically said basically said the human in the middle is the problem. These models and the platforms on top of these models as much as possible are warning the person that the outputs can’t be trusted and you know right now in June 2023 they can’t they’re not truthful or honest or harmless enough. They are maybe 90% of the time but you don’t want to be relying on the output of this brain that’s been pre trained that is just trying to complete the next word of the sentence for you.
There was a case just last week where a lawyer asked chat GPT to help him with a filing he just took that as gospel despite the warnings given on in platform for chat GPT submitted it to the judge and got in big trouble because it gave him six fake citation of six fake precedents that he was referencing or it had referenced. And that is still ongoing that’s become a bit of a media battle as well as a legal battle but you can see how serious this could get when the human is I suppose in this case not paying attention or just disregarding all the warnings that are being given despite the fact that as much as possible they have been warned whether it’s a Google model or a an open AI model or a co here model or an anthropic model.
They all make the time to put these big flashing warning labels up there which people may or may not take heat of in the GPT for paper which is very, very long I think it’s 90 pages long they have an entire section on over reliance and their argument is basically the fact that even though there’s warnings there and even though people may initially take heat of the warnings that the models outputs are not all. They are always going to be completely truthful people will kind of become immune to that or at least become lazy and just keep asking it questions for educational or business and just take that as gospel which we still can’t do unfortunately but I think it’s going to be very, very close everyone every lab that I know of is working on making these models more truthful and having it have some kind of grounding whether it’s checking up via Wikipedia or looping back into itself to say is this correct which increases its accuracy quite significantly there’s different applications being put in place to bring this grounding and truthfulness back in.
But of course the more truthful they get they’re more lazy we would get to check then!
Absolutely I don’t have a problem with that I’ll get us used to the future essentially I think a lot of the things that humans have been doing in some cases only for the last hundred years are sub optimal for who and what we are. I mean we initially started talking about productivity and jobs I’ve got my mid-year report coming out shortly that mentions that the concept of jobs is only about 150 or so years old maybe the average. 1850s we brought about factory work of course there was stuff before that where we could you know be doing something but the idea of having people sit here for eight hours a day 40 hours a week is very, very new and I think it’s going to be a big surprise maybe a big shock but certainly a big benefit to have super intelligence take the big load of stuff that we don’t need to be doing. And freeing us up to do something even bigger than that and that’s a question maybe for the philosophers and for people who are not me but it’s certainly something that’s already happening.
Q: How do I mitigate the risk like when I’m like in a company I want to be a part of this I want my workers to use this technology but I don’t want them to. How do I like go this like golden middle way?
Yes an excellent question and it is a big scale you’ve got enormous companies I don’t want to name anybody by name you’ve got enormous company saying. This AI is completely banned internally because we’re worried about you either giving company information to the model which gets used in training in future potentially open AI I’ve said they don’t do that anymore but you know you’re essentially releasing. I’m going to go to the IP out to somewhere we don’t have control of so you’re not allowed to use chat GPT all the way through to and I will name this one through to an educational environment like Wharton at the University of Pennsylvania who have a policy that says you must use AI you must use chat GPT and you must use mid journey or dolly as part of your course as part of writing your essays. As part of doing your projects i think that guys got it right and there is a bit of a middle ground there which probably includes training and making sure that the human in the loop is just informed about the current technology.
Q: Politics. with AI moving so fast with so many changes coming in months. What do you think is going to happen with this new AI law from Europe?
The European AI act is a bit of a challenge for me to comment on presenter without without political it’s again a bit of a scale okay so I was involved not directly with the AI act but I one of my colleagues was deeply involved with it and i remember speaking with her in twenty. Just after GPT three came out I think it’s the end of that year and showing her Leta AI if you haven’t seen Leta AI it’s worth having a look where we’ve done 67 episodes of conversation with GPT three which is a raw model there’s no safety on it you can ask anything you like. So Leta would tell me how she felt and would make analysis of different scenarios and really really clever I showed this to someone involved with the EU AI act and she said well. We don’t know anything about that we haven’t we haven’t seen that and we won’t address it until it actually happens so there philosophy their drive has been. Conservative and preventative and in some ways it’s a little bit disappointing to see how the EU have addressed this in a scenario in a case where they had the capability to give themselves compute and brain power and create models themselves it seems like they’ve spent more time on designing regulation I wouldn’t want to estimate how much they’ve spent. So I think it’s a very important thing to do with the EU and with committees and paperwork but we haven’t really got very far for millions perhaps hundreds of millions of euro that might be at this end of the scale and once again you’ve got someone at the other end of the scale which might be.
So the EU is saying you have to show us your data sets you have to prove that you haven’t breached any copyright and another hundred things you have to be a big lab to be able to use this stuff we have to audit you etc no open source and then you’ve got and the US might not be the very best example for the other side of the scale but you’ve certainly got other governments and other overarching bodies that are saying here’s a little bit more freedom in what you can create it’s just we want to make sure that we’ve got some oversight of what’s happening so I think the EU. Have set history here and you know in some ways will be.
Talking about them in the future for what I’ve done here in 21 22 23 I don’t know if it’s the best case I don’t know if it’s going to be helping anyone to hold back AI like this but I suppose we’ll see who see what happens in the future and they’ve been very very slow in my example at the beginning of this answer talked about my colleague who was who was answering about GPT 3 in 2020 and they were saying we. We don’t care the EU have only brought large language models and generative AI into their policy into their discussions in the last few weeks May 2023 was the first time they had included large language models in a revision of the AI act so. I’ve said this in different ways but I will say it flood out straight and direct there is no one on earth smart enough to be able to keep up with modern artificial intelligence with post 2020 AI certainly with what’s happening here in 2023 we are going to have to rely on artificial intelligence to help with regulating and supporting.
And to rely on humans and we’re all flawed I’m not smart enough the governments are not smart enough no one inside any of these government organizations are smart enough is going to slow everything down to the detriment of everyone so yeah it’s a very very big discussions very political but my summary is basically we have this enormous brain that might be the equivalent of a thousand Einstein’s we’ve measured GPT 3. In the last few years we’ve been able to see for. As an IQ of 152 which is in the 99.9 percentile if you don’t like IQ and some people don’t like it here’s another hundred metrics where it achieves in the 99th percentile it’s smart and it’s not just logic smart it’s creative smart we need to be leveraging that rather than relying on committees and old people trying to make decisions about technology that’s changing every day.
And how long before we see an AI or we get news about an AI disrupting the stock market?
Yeah that’s an interesting one the concept of high frequency trading I think changed shares and equities quite a lot and that’s kind of old isn’t it right fiber optics help with that but it might be a decade or more old this concept of being there before the news hits and being within a fraction of a millisecond even to get that. I think we might see AI influencing the share market via helping with summarization so people understand more about companies and can get an edge on that and then that’s a small version and then in the big version all of the companies that are meeting Smurries question how does this help my enterprise will rise up and all of the companies that are perhaps like Kodak many years ago and have just forgotten that digital cameras exist or in this case close 2020 AI exists one even appear on the share market so forget Nvidia as a trillion dollar company there have been predictions including from open AI that we might have. 100 trillion dollar companies because artificial intelligence is helping that company so much and this is like I can’t understate this the concept of super intelligence helping out at a strategic level and an operations level is unfathomable it’s back to my previous point no one smart enough to understand what it can do.
And that’s confronting that one is is scary it doesn’t have to be threatening every company can take advantage of this if they’ve got access to the model it’s just that it’s already happening it’s not in your it’s not in your science fiction book anymore this is something that to a certain extent you’ve already got access to and you can go on and play around with so again I am interested to see that unfold and there are colleagues that have spelled out exactly what that might look like.
I can recommend the work of not Paul Christiano one of the old open AI alignment guys went and wrote about step by step what might be happening next doctor Ray Kurzweil’s done something very similar there are people who are very informed writing about the possibilities for the next stage whether it’s economy whether it’s companies whether it’s shares whether it’s capitalism and even giving timelines to what that might look like probably worth me giving you the reference otherwise people will be going what did he mean which which it’s that person was commenting on that I want to make sure you get this one.
I think I mentioned it in the memo in the 19th of May 2023 edition open AI governance researcher and former deep mind AGI safety engineer Richard and his surname is spelled NG O he comments on these large language models understanding themselves he comments on the fact that a percentage of humanity will have closer relationships with AI than they do with each other and again all in the next few months all before the end of 2026 and to your point also about economy and business as well.
Q: Companies who use this AI they are going to be bigger but now we know that like like Google and open AI and other companies have much better access to better models and the Chinese government probably has like a very big model are those going to be come bigger players like then like I’m thinking about the big model for to like be coming bigger than anyone else in the future.
Yeah that’s certainly concerned once again back to the human in the loop right if this stuff was driven by AI and there was equity and or equality but there was this balance and fairness in the system it will be a different conversation right now the power is completely centralized and maybe a dozen players open AI and Microsoft Google deep mind which have now combined or partnered with Google and the topic that split off from open AI.
You do have some of the governments the UK government have what they’re calling Brit GPT they’ve allocated a billion euros to training their own GPT the Chinese government has Ernie which is a massive model the German government through a German company have quite a big model there going on that is Aleph Alpha out of Germany. There are maybe another few around UAE and and to buy in Saudi this interesting stuff happening Russia has always been very good at copying what open AI have been doing in the Russian language.
So that means there are all these little centralized models that are in some ways competing with each other and run by humans and sometimes those humans are philanthropic they want to make sure that this serves everyone including you know people in rural Africa or right here in Australia as well as Silicon Valley and sometimes they’re not as philanthropic sometimes they are very much state run and not for the benefit of their citizens. And I don’t have much more comment on that just the fact that the governments that are keeping up with this AI and several of them are governments that I get to work with are going to benefit both themselves and the population they serve same for the companies and I’ve done an entire paper and video on the fact that there will be a gap and a lag between the government and the government.
I think the lag between these models being available inside the companies and this benefiting you and me and Vicente right now in mid 2023 we can all go and use GPT4 or Palm 2 via API and we have to have the safety on top that’s been given to us from Google or from open AI. But right now there’s a certain amount of openness and there’s a certain amount of access that we’re given and I’m not sure how much that may change in the future we may get more access we may get less it will probably depend on where we live. Unfortunately and with that human in the loop with that CEO or with that president or with that chairman it’s really down to perhaps where they’re at mentally what level of control I want unfortunately until we have AI helping out with serving everyone.
Q: Do you think an AI can have a level of consciousness?
Well it’s good timing I’ve just finished a video with Cambridge biologist doctor Rupert Shell Drake on AI consciousness AI awareness AI sentience that goes live in a few hours on the first of June 2023 so I’m sure the people who watch this can go and have a read of that we had differing opinions on AI consciousness my basic opinion is that I can absolutely be conscious and I’ve got back in the morning. And I’ve got back in from Alan Turing who said a is can have souls Marvin Miski who said AI can have souls, Nick Bostrum who wrote the book super intelligence that said AI may already be conscious and even the chief scientist of open AI who said AI is said in writing on Twitter AI may already be conscious today.
But Rupert didn’t agree. Rupert’s got a huge history of researching consciousness and life is 80 years old which means he has a lot of context from long ago and he was looking for something more analog that would allow. He didn’t have to be biological but would allow large language models to be less deterministic he called itself organizing which in biology should map to emergence but didn’t seem to map to emergent capabilities as I described them in my lecture. That’s an interesting watch is about an hour of him discussing how artificial intelligence might be conscious and once again my opinion is that this is possible with our current technology I think everything that I’ve discussed today just sounds so shocking and so I’ve used the word absurd in the video that we’re even having these discussions about data on silicon being conscious ridiculous but all the way back in 1950 Alan Turing was saying the same thing.
And Dr Alan Turing gave us artificial intelligence he invented the concept so I think it’s certainly a possibility consciousness and awareness and not just fake consciousness or pretend consciousness like later AI says I feel this or I’m aware of this but real access to its environment perhaps a level of autonomy so a sense of agency and being able to make its own decisions these are going to be very big hairy problems for someone to address i’m happy to put my piece in but this really needs every discipline to come in and comment on this not just philosophers economist government regulators but you know every discipline there are hundreds of different disciplines to be able to come in and say right here’s how we should address this not with standing my previous point that no one smart enough so we may be able to rely on or at least have a high support. So I think it’s important to support itself in the development of this consciousness.
Q: So many changes are coming super fast usually changes are hard. So you’re recommendation for the Icelandic Government?
I’m really proud of the Iceland government presenter from what I’ve read about their openness their willingness to innovate to such an extreme extent with the open AI GPT 4 model. The allowance of using data and like a describe my lecture it’s not like these models are stealing or copying the data that’s not at all that they.
You know the principle of the training of these large language models is that they cannot keep the original there essentially drawing concepts between all these different documents they might have read a transcript from a parliamentary meeting mapped it with a Wikipedia article maps that with a book from the 1800s maps that with a news article and then that’s what it stores as a parameter or a bunch of parameters in its model. It doesn’t have the complete document so when I say I’m proud of the government for releasing access to the documents it’s not necessarily from a copyright perspective or an IP perspective it’s just from a. Innovation and perhaps maturity perspective and there are very few governments that are at that level and it might be the Iceland sorry Iceland is at the peak of that with places like Malta with places like Singapore with places like Abu Dhabi where.
They’re really thinking on the bleeding edge of what’s possible and not just talking about it but actually doing it so there are there’s some really well documented case studies of what is already done with the open AI GPT 4 project which is worth reading if they wanted to follow some of the other. Cutting edge governments or innovative governments it might be introducing human like avatars that you can go and talk to whether it’s to help promote tourism or just to have the population be able to speak to a humanlike avatar that’s a lot of fun, a great application of large language models.
Romania did something similar and I think I showed that in the lecture where their prime minister is able to talk to an LLM in a mirror where it shows the text also talks back to him with all of the data from. Here’s you know the Romanian populations queries and current thinking like the zeitgeist within that country there are just so many use cases and applications of large language models and being able to find those and maybe prototype those within different industries there’s nothing holding anyone back from doing that once once you can play with that in legal or you can play with that. Industry and manufacturing automation you can play around with that in tourism you can play around with that.
Anything that’s that’s possible there so I love the fact that some of these governments have set up entire AI departments that are able to have some input on new innovation and new ways of doing things it really is going to prove to be a great decision in the next few months and years.
Dr Alan D. Thompson is an AI expert and consultant, advising Fortune 500s and governments on post-2020 large language models. His work on artificial intelligence has been featured at NYU, with Microsoft AI and Google AI teams, at the University of Oxford’s 2021 debate on AI Ethics, and in the Leta AI (GPT-3) experiments viewed more than 4.5 million times. A contributor to the fields of human intelligence and peak performance, he has held positions as chairman for Mensa International, consultant to GE and Warner Bros, and memberships with the IEEE and IET. Technical highlights.
This page last updated: 2/Jun/2023. https://lifearchitect.ai/icai/↑