Podcasts about artificial superintelligence

Competing in a Future World of Infinite Intelligence Navigation: Intro From Knowledge Workers to Judgment Workers The AI-Native Company: Org, Hiring, Culture The Human Element: Are We Underestimating It? Scenarios Our Take Conclusion Our co-hosts: Bertrand Schmitt, Entrepreneur in Residence at Red River West, co-founder of App Annie / Data.ai, business angel, advisor to startups and VC funds, @bschmitt Nuno Goncalves Pedro, Investor, Managing Partner, Founder at Chamaeleon, @ngpedro Our show:   Tech DECIPHERED brings you the Entrepreneur and Investor views on Big Tech, VC and Start-up news, opinion pieces and research. We decipher their meaning, and add inside knowledge and context. Being nerds, we also discuss the latest gadgets and pop culture news Subscribe To Our Podcast Nuno Gonçalves Pedro Introduction Welcome to episode 79 of Tech DECIPHERED. Today, we take a leap into the big unknown. This is a thesis episode, not your classic analysis, in-depth sharing episode. The big idea for this episode is that we may be approaching the cognitive age, and how would one, or how would a company compete in a world of infinite intelligence? The big idea, again, is that intelligence, which has been mostly scarce and expensive for all of human history, might become abundant and cheap. If that happens, what happens to work, what happens to companies, what happens to society? This episode will be really framing a lot of these discussions. From knowledge workers to judgment workers, addressing the AI native company and how does that change, going into the human element and whether or not we’re underestimating it, and finally, ending up going into scenarios, feasible scenarios of a future where, well, intelligence is abundant. Intelligence is quasi-infinite or infinite itself.Bertrand Schmitt Yes. Big questions for this episode 79. From Knowledge Workers to Judgment Workers We can start with from knowledge workers to judgment workers. Let’s go back first to how came the knowledge worker. It’s a 20th-century invention from Peter Drucker in 1959. The idea here is that that category might be splitting. The production of knowledge itself is on its way to being commoditized by AI. However, our perspective is that judgment around production of knowledge is not disappearing and is staying for a bit control managed by humans. What’s your take on this, Nuno? Do you agree with this split?Nuno Gonçalves Pedro I think it’s a little bit more profound than that. It’s not just judgment. Definitely, human judgment will be needed. We’ve seen agents perform all sorts of funny things in the wrong way when left alone to their own devices. Even some very well-known AI researchers coming forward and saying, “Hey, I tried to use this myself, and actually I messed up some of my systems,” or “I messed some of my code. I messed up some of my flows for a period of time.” I think just having human-in-the-loop from a judgment standpoint will be needed for a significant amount of time. That is something you can’t just delegate into machines, into algorithms, et cetera. The second part is, ultimately, there needs to be contextualization, and that contextualization, I think, comes from two forms. One from actual data, where the machine, I think, at some point will catch up, or the machines will catch up. The algorithms, at some point, on the data analysis will get better and better and have probably the closest to the truth that you can get, minus all the biases that are in the data, just to be clear, because data has a ton of biases. We’ve looked at this in the past and discussed it at prior episodes. But maybe on that, I think the machine has a chance to catch up, or the machines have a chance to catch up, so there’s less of distinctiveness from the human standpoint. But then, on just the attributes, the ability when you’re judging some situation, you’re in the middle of the situation. You’re judging the person and how it’s acting, in some ways, a lot of the things that end up happening, end up happening because there’s human interaction. There’s someone on the other side. I see how they’re delivering the message, how they’re implicating. We’ll talk about it later in the context of the organization and what changes in companies. I don’t think it’s just judgment. I think there’s a little bit more than that. One of the reasons I went to the dark side of management early on in my career from being an engineer was Peter Drucker and this notion of the knowledge worker, which he later on reemphasized with the publishing of his book, which for me was seminal and defined a lot of my career in life, the post-capitalist society, which is this notion that information rich and information poor is going to be the key distinctiveness that will happen in the world. The two big camps, information rich, information poor, which links back to this invention of the term knowledge worker, that knowledge is going to be key in some ways. I think that’s what we’ve seen for the last decades. Again, I think judgment is not going anywhere, but I think it’s beyond judgment. There’s elements of humanity and involvement that won’t go away anytime soon, where human-in-the-loop are particularly critical. We’ll discuss later some scenarios, but for me, that’s my stick in the ground. I think human-in-the-loop is going to be critical for many decades to come.Bertrand Schmitt While we are talking about all of this, and we share some possible scenarios, there is always that question. This is moving so fast right now. If you think about AI 10 years ago, AI 5 years ago, AI with the launch of ChatGPT 3, and then AI the past 2 years, now we have agents that are running at scale. Things are moving very fast. I can tell you, me in 6 months, the change has been pretty dramatic in terms of what I can use AI for. There is always that question that whatever we are thinking about cannot just be connected to what we were able to do 6 months ago or even today, we have to think and project ourselves at least in the next 6–12 months. Of course, we can go beyond that, and we will do that with some future scenarios, but it’s a very fast-moving, and it’s not clear yet where are the limits.Nuno Gonçalves Pedro I think that’s a very fair point. Let me try to analyze things that I don’t think will change anytime soon for the next few years. Agreed with you that many things will change, and we’ll have a lot better tools, platforms out there. That will be difficult to predict what exactly won’t change. I think there’s elements of humanity, and some of them do relate to judgment, like having good or bad taste, having a view on it, on whether something looks good or bad. Obviously, all of this sometimes is subjective, but some of it may not be as subjective as people think it is. The elements of contextualization. I think a little bit going back to what we did at Chamaeleon ourselves, where we built this platform, Mantis, and the objective of building Mantis was not really to replace us, was that it was a core augmentation layer in some ways that we would use investment or investor judgment as humans in the loop to systematize pattern recognition and a variety of other things, but that Mantis would really elevate all that judgment, not just in terms of timing, us being more productive, but also in terms of the quality of the decisions we’re making. Think of it as a little bit like having our human judgment in the context of operating Chamaeleon at a higher altitude, where we are more aware of the things that are happening and how they actually happen. The ability to really get to the data pieces and then make decisions on top of that that generate the needed alpha in our case for investors. What I mean by this is I think there’s always going to be core elements of humanity that I do think are going to be difficult for the machines to replace. For example, the taste piece people are like, “I can figure out what’s the taste in the market.” Yeah, but that’s mainstream. That doesn’t identify what’s the next big thing, which normally doesn’t start from mainstream. It starts from something else. It could start from opinion leaders and influencers. It could start by someone having a different way of addressing a problem and having a solution that hasn’t been thought through. For example, elements of creativity, I think, in human judgment and in human operations is something that I feel the machine will still have difficulty to replace.Bertrand Schmitt Let’s not forget how today current algorithms are working by feeding them enormous quantity of data, actually as much data as we can find. Finding more data is becoming a limitation these days. What it means is that it’s very hard for AI to think beyond its training data. There is some level of logic that’s being added, but at the same time, take the launch of the iPhone. What was the opinion before launch? Is that no, it doesn’t make sense. Not enough battery life, no keyboard, no this, no that. If you just base your analysis on what’s written out there, what’s being sold out there, you would just say, “It’s going to fail.” AI might really follow that more generic advice and perspective because that’s what in the training data and that’s what they’re in volume. It’s, of course, raising a lot of questions of, how do you improve the quality of the training data? How do you separate the weed from the chaff? There are a lot of questions there, and obviously, it will get better over time. But it’s still a critical part of how it’s working today. It won’t be that easy to change. I really like your point regarding Mantis, and I will say in general, platforms that you build with AI or leveraging AI capacity. Because when we say knowledge production is going to disappear, but we’ll keep judgment, it will be a different type of judgment because the quantity and quality of knowledge we will have in front of us to build our judgment will be very different. If suddenly we have for free the work of 10 interns or 5 junior analysts or whatever, and you can run that on nearly anything you do in life or at work, it’s completely dramatic. Your judgment was not used to be exercised so often because often you were missing quality data to have a judgment. Before it was a lot of finger in the wind and trying to smell something, but you didn’t have enough to make a serious analysis. Except if you are working as a strategy consultant, as you used to do, Nuno. That part is actually quite interesting. That the judgment itself will be exercised much more often and hopefully on the base of much more in-depth analysis for a lot of things. We will work very differently.Nuno Gonçalves Pedro We will go in-depth, faster and more fact-based, more data-based along the way. The question some of you might have right now is, is there some judgment that’s going to go away? Is there some judgment? We seem to be defining that there’s this organization, we’ll talk about it later, that goes from doers more into deciders. I think there’s some nuances to that, so I’ll just hit pause on that. In terms of judgment, obviously, there’s judgment that has been hidden over the years under the pretense of being wisdom, but it’s actually not wisdom. It’s just repetitive tasking, and it’s rules-based for the most. There’s a lot of judgment done, in particular in the white-collar space, that you could say it’s just reps. People have been doing it all along like that, and so therefore to say, “I’ve done it before like this, so I’ll do it the same way.” There’s actually no best in class, no analysis, no nothing. It’s just, “I’ve done it like that before.” I think that type of judgment will disappear because, again, algorithms will be as good, if not much better at that. They’ll be better at figuring out, actually, this would be the better way to do this. That’s how you play it forward. Then the question is, if there are fundamental, wise people in the organization, people that can really take that more complex elements of judgment, how do you go from the world we have today, which is a world of apprenticeship, where people come out of college, they go and work, and they learn their way, and therefore, hopefully over time, some of them, not all of them, we know that, but some of them will develop that wisdom to be great decision makers 15, 20 years down the road? How do we do that in a world that now is saying, “I don’t need people out of college because I can do it myself, and I can do individual contributor, and I can have agents doing the work that would require some manifestation of management in the middle.” Basically, “I don’t need this stuff. I don’t need you.” It’s a little bit the story we’re in. How do you create then this apprenticeship? How do we create then wisdom? My two cents on that is that wisdom, because of what we were just discussing and what, for example, myself and Bertrand was just saying, because of more often interactions with more data-stressed information and insights, what will happen is people will get better through their own reps in whatever form they’re doing, in day-to-day life, in internships, et cetera. In some ways, that will create the accelerated growth. It’s a little bit the interactions with agents and the interactions with our beloved AI algorithms that will create that growth over time and maybe not as much with other people. That still leaves the question around social interactions, but that’s probably the way this gets sorted. Apprenticeship gets sorted through the machine and the human having more interactions in effect.Bertrand Schmitt I agree with you because when we talk about apprenticeship, in some ways a lot of time was wasted on stuff that were not that important. But in a way, that was the price you had to pay in order to be there when people make the big decision to try to get some wisdom from that one hour of interactions that’s really useful and make a difference out of your full week. But the rest of your full week was just basic stuff that you had to do like a machine in a way. Why not let a machine do that? That, for me, is a big question. You could argue there is a transition period where it could be hard. For instance, if you can work hand in hand with AI smartly while you are doing your 4, 5 years of universities, you could graduate with a very different knowledge, perspective, judgment, skill set than anyone who graduated 5 years ago. I think that part will require a question around, “How do you change education?” You see what I mean? If you keep education the same way, expecting that the output is someone that should go now into 5 years of apprenticeship, that’s not going to work because companies will be, “No apprenticeship anymore.” On the contrary, you have to come much more knowledgeable and ready to use the tools. The tools are so efficient that the bar pretty high. You need to come already very well-grounded. If the education is not doing their job, that will be trouble. That part for me, I think is often forgotten. In some ways, the new-found importance of universities as a place to, and not just universities, the trade to really deliver people who are ready for the workforce. If on the business side, the expectation can change, of course, you have to change the education on the other side. My worry probably right now is that it doesn’t look like universities are in touch with what businesses are looking for, businesses are working on. Of course, that’s very worrisome because the cost of university has increased very significantly. It’s not clear quality of education has improved at all. If anything, it could be the opposite. It’s pretty scary. Of course, it’s going to raise a lot of questions. How much is education worth in that type of situation? Maybe another point because we talk a lot about apprenticeship, how this stuff was useful, but at the same time, if we go back in time, not long ago in the ’50s, if you wanted to be a developer, for instance, ’50s, ’60s, the job was very different. There was barely any programmation language out there. You had to use punch cards. Your time truly spent doing the coding was very limited. Once you had your stuff working, then, the debugging was a total nightmare. My point is that no one is looking back to that time saying, “You know what? It was great. It was a great way to learn and to do an apprenticeship for 5 years. To do that crappy job of punching cards for the boss.” There was little value in this. Guess what? Everyone is happy it’s not being done anymore by anyone. I think we also have to see what AI is bringing in a similar way is that everyone’s job is going to become quite different. There are a lot of big parts of the job who are not going to look back with fondness. Just looking back as, “Wow, that was very machine-like type of job. I’m glad I’m done with it.” People will want to jump directly to the next step. You don’t need to go to the punch card phase to be able to be a good developer for the past 40 years. I guess it will be the same with AI.Nuno Gonçalves Pedro I think so. The difficulty we have as humans is to also visualize dramatically different scenarios and landscapes, professionally. It’s difficult for us to anticipate what are the jobs of the future. Jobs have changed a lot in the last few decades, not even the last century. What people do, the migration initially from the agricultural society to then the industrial society to then the services society, and in some ways, the shift within the services industry, and now we’re seeing another shift, so we can’t really anticipate what those jobs look like. Back to your point on education, because I think that’s a very important point. If you’re right now an undergraduate student or a postgraduate student, for that matter, and you’re not figuring out your own mechanisms of learning outside of your syllabus, outside of what your professors are telling you, et cetera, you’re going to face very difficult times. If you’re not right now using all these AI tools proficiently, all these cycles of vibe coding, co-working, et cetera, with agents in the mix, you’re going to have a really tough time. If you’re not at this point in time as proficient as someone like myself or Bertrand, and given that we’re nerds, we’re relatively proficient with a lot of these tools that are out there. On top of it, some of us have our own platforms in-house. If you’re not as proficient as we are with those tools, you’re going to have a very difficult time because then people like us won’t need you. I think that’s the sad truth. It’s like at some point, if you’re not needed, you’re not needed. Then again, you may find something else that’s more interesting for you to do. Start your own company, go join a new exciting job doing whatever it is that you need to do next, et cetera. But again, I think the bar is very high. If you’re in college right now, again, undergrad, postgraduate, this is the time of transition. This is the worst time. It’s not the best time, it’s the worst time. Because education and all these institutions haven’t adapted to it yet. You need to adapt. You need to adapt. You need to adapt. If you don’t, you’re going to pay for it, not just in the loans you need to repay, but also in terms of actually having difficulty finding your career path in those first few critical years.Bertrand Schmitt You need to be especially proactive when you’re facing this type of period where businesses are adapting as fast as they can because they all know it’s going to be survival of the fittest very quickly. Universities typically are working on a very different pace, and it’s pretty guaranteed they are not going to have adapted as fast as businesses. In time of big dramatic change, it will be trouble. It will be trouble. Yes, you will have not fun. Not saying it was part of the deal when you sign up for that loan and decided to go for university. But that’s life. There has been issues before. It’s not the first time. You have to do something about it. You talk about your perspective about, “Hey, why do we need you if you are not already fluent and very efficient with these tools and stuff?” The truth, in some ways, it’s even worse than that. Each time we spend with someone who is not efficient with all of this is less time we spend with the tools that are already providing magic for us.Nuno Gonçalves Pedro Exactly.Bertrand Schmitt It’s a very big choice of, “Hey, do I spend more time training this person?” Do I just… there is an opportunity cost. Or, do I spend more time staying at light speed? Why do I slow down to do something else in the hope that maybe I will get to return versus the light speed I’m already on? It’s a lot of tension. Again, it’s certainly new. But if we want to look back, I think you talk about the switch from agriculture and society, industrial society, and now the service industry. The reality is that, yes, we have made dramatic changes in the past before. 140 years ago, we were 90% agricultural society in Europe, in the US, 90% of us. Today, it’s what? 2%. So my point is that that’s a normal evolution. There is no progress without change. Sometimes the rate of change is soft, and sometimes you have a step function. Now it’s a step function, and it’s also a pretty fast step function. Before, it could take decades to get new stuff being put in place, to have electricity come up, this or that. Now we see that the rate of investment in AI is insane, way beyond anything we have seen before. Two, in a way, a lot of the architecture behind the scene was already there to support an even faster transition. What’s new might be the pace of the transition, how unnatural it might look. But at the same time, if you put yourself in the shoes of someone who lived 150 years ago, I mean, this was also a dramatic change for them. From horses to cars to planes to rockets, pretty big change, maybe even bigger change.Nuno Gonçalves Pedro Maybe the silver lining, just to bookend this section, is one, there will be new roles. There are a lot of things we can’t anticipate. There will be new roles, there will be new jobs being created, and new things that we can’t really quite grasp yet. The second part is that the rules are changing, and they’re changing, I would say, in general, for the better. If you are a decision-maker or an organization, and you still have your job, you’re probably making more important decisions with more data, with more tooling around you, with less red tape, hopefully over time. I know that will not hold true for all the big corporations out there that are listening to us, but it is starting to happen. Things are making an impact on how decision-making is made. There’s less and less red tape along the way in certain organizations. There are more and more fact-based discussions happening as we move along. The silver lining is better jobs, more jobs, different jobs in the future, hopefully as well. Secondly, the second part of the silver line is that the jobs that exist today, hopefully, will be more interesting, certainly on the knowledge space and on this judgment space that we’re now introducing as part of this episode. The AI-Native Company: Org, Hiring, Culture Switching gears, maybe to how does that shift? How does the company of the future look like? How does an AI native company look like? I feel there are a lot of discussions on, “Oh, you only need one person to run everything.” Let’s not go to that level. We’ve had a couple of episodes where we focused on AI as your co-founder and a couple of other elements that you guys can go back to. Let’s focus on a more evolutionary view of what’s happening to organizations, and maybe start with the org structure. In general, we should see more flat organizations where mid-level managers have to justify their pay in some ways because middle management are routers. They are normally routing tasks. It’s sometimes aggregating it, synthesizing it, and pulling it back up. Guess what? AI and agents in general are very good at that. The synthesis piece, et cetera, is not as well needed. One could say there are several elements of middle management that are valuable, like the coaching of people, the creation of apprentices, and the accountability that comes with some of middle management. But lo and behold, most of middle management is seen as a little bit of a thin line that doesn’t need to necessarily exist. I feel we’re moving into a world of smaller teams, more senior teams, where there’s more judgment at the top, where you’ll have people that both do a mix of what we used to call management in its new form, but also a lot of individual contribution. If you’re not used to that, if you’re not used anymore to be an individual in the future, again, and if you’re a very senior in an organization, maybe this is the right time to either reinvent yourself, find some other job that doesn’t require as much of that, which we’ll have plenty of those jobs for the next few decades, or maybe retire. I’ve actually, shockingly enough, seen people who have said, “You know what? This thing is changing too fast, too dramatically. My industry is changing quite aggressively right now. I’m about to retire in a couple of years. I’m just going to retire now.” I’ve literally met two people who have done that. Again, there’s nothing wrong about it. I think we’re, again, going through a step function and a huge shift, but figuring out where you fit in this new model of organizations, more senior at the top, smaller teams, more of a mix of individual contribution with management than ever was done before.Bertrand Schmitt I agree with you. In some ways, I’m not surprised that some people might say, “You know what? It’s now time to retire.” I feel a bit sad, maybe because it means you don’t like to keep reinventing yourself and changing your habits and thinking about new stuff. You were a creature of habits, I would say, if that’s your conclusion. But everyone is entitled to their own opinion, obviously, and a way of life. I guess that’s what happened, again, at regular times in the past in terms of big change. What I can see is that the rise of, you can call it the full-stack individual, someone who will have multiple roles inside the team. Before, you had to really separate the role. Especially in the US, there is such a clear separation between every role you can have in a company. Let’s take a tech company. You will have people doing design, people doing different types of designs, people doing front-end development, back-end development, and operations. You see step-by-step hyper-specialization. I have seen that, and it’s true that the level of complexity you had to deal with at some point requires some level of hyper-specialization because it will take you 6, 12 months in order to be really, really strong on a specific topic, a specific language. God forbid, trying to go deep into something that you had no real experience into. But I feel with AI, it’s a big change, actually. It’s the opportunity to go beyond that. It’s the opportunity to do more, to touch more. You can combine designing and shipping code, product managing and shipping code, being an analyst and deploying. Of course, we have to think how it works because putting a marketer shipping code to production, maybe that will get you into trouble. But I think that there must be some change. We see it changing dramatically, how fast we can get into something, something different from what we are used to. I think it would be crazy not to take that opportunity to dramatically change the scope of many positions and put an end to that hyper-specialization. I think for me, in some ways, hyper-specialization was bad. There is only so much you want to be a specialist in because a lot of things, a lot of opportunities are actually coming from the mixing of many different ideas, many different perspectives, and you lose if you go to hyper-specialization.Nuno Gonçalves Pedro I don’t think the age that is coming is the age of the generalist. I think it’s going to be the age of the multispecialist. We’re going to go into an age of multispecialization, which is a little bit, we’ve mentioned it as well in the past, what Amazon defines as an athlete or T-shaped or pie-shaped people, people that have on top an amazing ability to do general management, strategy, managing teams, et cetera, then have spikes. Spikes into business development, corporate development, product management, whatever it is. With AI and with agents, the development of those spikes, as we’ve been discussing in this episode, will actually be easier. It’s almost like a given. If you want to go deeper and deeper into a certain area, you can go much faster. I think that level of multispecialization is going to be really cool to observe. I’m not sure we’ve had an age of multispecialization over the years. Maybe people would point out, well, the Da Vinci example, people that are great across very different areas. Maybe that’s an example of multispecialization. But honestly, from my perspective, this is going to be an exciting time because of that, because you’ll have people who, instead of being just focused on this area of sales, and I only do that, they can actually and should actually do a lot of other things. So the work, as we were talking before, can be more interesting. More demanding as well, because the judgments you need to make are more complex. The context you need to actually gain needs to be gained much faster. At a level of magnitude, you haven’t been able to do it before. Talk about information overload. But actually, ultimately, the roles can be a lot more interesting, a lot more exciting, because I can jump around. If I’m an investor, in this case, we have two investors on this conversation. But if I’m an investor, one of the things that we start looking at is actually not just looking at a startup as, is this startup doing something in AI or not? Is it AI-enabled or not? Is it an AI platform or not? But actually, more fundamentally, is this an AI native startup? Meaning, organizationally, culturally, is this the company that’s already in the AI age? How is the team working? How are they defining things? It’s not just that they only have two or three people. It’s like, what are those two or three people doing? How are they doing it? What cadence are they doing it on? What tools are they using? How are they making decisions? I feel we’re still actually relatively early on that track. It’s very interesting because we’ve had all these companies raising mega rounds. First round out, we invested in one of them, but there have been many frontier labs out there raising a ton of money. But a lot of them don’t have a fundamentally different way of doing business. Of organizing themselves, of how they do the day-to-day. Although they’re working on cutting-edge stuff, with very notable exceptions, they’re actually not using it themselves. They’re not actually shifting how they do stuff themselves.Bertrand Schmitt For me, that’s very interesting because in the past, I used to be quite conservative on how you manage and run a company in the sense that if you’re already in tech, if you are already on the cutting edge of what technology can deliver, and this and that, don’t waste time trying to invent a new org structure. Just focus on delivering something great, amazing, and be great at technologies. That’s already your huge differentiator. At the time, there was no real reason to innovate on the team organization. I have seen so many teams that tried to innovate, and it was just catastrophic because there was not much to innovate on, because we had decades of optimization that we could leverage. There was no reason to invent. But here it’s very different. There is a dramatic shift in how you can organize differently a company. I don’t think there are any blueprints yet on what’s the best way to do it because it’s too new. But at the same time, I would feel very bad to invest or support a company that first is not focused on AI or AI-enabled, but at the same time is not trying to innovate on the team itself. Because if you don’t do that, you’re going to get killed by someone who is going to innovate better than you on not just the product, but on the org as well.Nuno Gonçalves Pedro Indeed. The shifts are pretty substantial. If you look, for example, just at hiring, what do you hire for? Certainly, there’s this element of the multispecialized orchestrator, which normally will be someone with quite a lot of wisdom and expertise. It doesn’t necessarily mean someone who’s old, but someone who has the ability to work with all the AI tooling and platforms out there and be an orchestrator of agents. Why do they make judgments, make decisions, move stuff forward really, really, really quickly? Again, those jobs are going to be the best jobs. The second part, I think that is very interesting, around hiring, is you’re going to skew towards the elements that are potentially either very aligned with the use of AI tooling and platform, AI expertise, or being AI native, or someone who’s used to using AI. That’s one side of the fence. On the other side, you’re going to actually be optimizing to hire people that have the characteristics that will be difficult for AI to replace immediately, like taste and the notion of fundamental accountability and notion of implications, the notion of how you affect change in organizations, how you affect change in individuals, the elements of coaching, and beyond coaching. You’ll be optimizing for those kinds of hires as well. Then, last but not least, for me, I feel that there is a momentum already happening. I think it will happen even more, which is the tendency to under-hire rather than over-hire. The moment of the good old days of blitz scaling, “Oh, let me go and hire 300 people to scale my go-to-market and just land grab market.” Now, that’s not how it’s going to work. People are going to try and first get the efficiencies in-house with top talent and see if there’s, at the end, the need to hire more people or not, rather than the other way around. I think the issue here is a little bit of what we alluded to before in this episode. There is a tax on individuals. If you hire more people, you’ll have to manage people, you’ll have to work with them, et cetera. If I don’t need to, I might as well work with the agents that the tools and platforms that I use give me access to. Because that’s a world that’s much more efficient, right?Bertrand Schmitt I’m in total agreement with you on this. It’s definitely raising way more questions than before because, again, on one side, you have the product, the technology used to build products that are completely different. At the same time, all of this is also enabling new ways to design organizations and to scale differently, especially in a world where, as we have seen in 3, 6, and 12 months, stuff that you thought were impossible are suddenly becoming possible. So you’re, “Hey, I’m going to scale and burn a shitload of money for 6 months before I know if there is any return.” Versus, “You know what? Maybe I just wait 6 months. The AI has improved enough so that we don’t need this new team. We don’t need these people to do stuff.” Because actually, if you just wait 6 months, we will have stuff coming for free from either new AI models or new AI tools or this or that. If you remember, we used to say that in mobile, things were going three times as fast as on the web in terms of pace of innovation and speed of development and stuff. I mean, with AI, it’s 5X mobile.Nuno Gonçalves Pedro Maybe even more. Yes, well.Bertrand Schmitt Maybe even more, maybe 10X. Every assumption around blitz scaling or scaling in general was based on past assumptions. It’s not based on how is the industry evolving today. Might make more sense for you to really grow your agents and spend more money on more tokens. I remember, of course, Jensen is selling his business interest, but he was saying, “Hey, for each one of my 450K engineers, he better spend 250K in tokens a year.” I’m not saying it’s the right way to say it, but I think there is some truth in it, and that would be something to think about. Have we maxed out the token usage per employee? I’m not talking in a stupid way because token maxing and wasting money has no value and is as stupid as it gets. But if you are truly getting a return on these tokens, can you use more? Can you generate more? Can you create more loops so that one engineer manages not just 10 agents, but 50 agents, but 200 agents? I think that’s the big question. We’re trying to add more people. More people means more management, more issues, more this, more that. That would be a fair question. Another piece of the puzzle is how do you build in a way your… I don’t know if it’s a digital twin, but more like the digital version of your companies represented by agents. How do you make sure that everything you do as a business is truly captured, is truly leveraged so that your agents are getting better and better? Not just because the model gets better, but because you are putting more data into it, because it has more opportunity to learn, and as a result, gets better at your specific business.Nuno Gonçalves Pedro The next big thing is culture. How does culture change? I think the biggest shift that I see is, why would you do meetings all the time?Bertrand Schmitt Yes.Nuno Gonçalves Pedro At least at Chamaeleon, we have a very small team, just by the way. We have a very small team at Chamaeleon. We’ve reduced by way more than 50% the time we spend on meetings between each other across the board, one-on-ones, partner meetings, et cetera. I think we’re really pushing to be more and more asynchronous. There’s stuff you can process via message. I was just asking one of my colleagues, “Can you just send me that prompt for that so I can just do that on CoWork?” Or “Can I just go on Mantis and do this? Can you tell me the cycle?” Or vice versa. Basically, it’s a little bit like you’re just going to do it. I don’t need to meet. I don’t need to meet all the time. There are some things where we still need to meet and interact, and we need to brainstorm at times, and we need to go to a different level of abstraction on the top end. Then on the lower end, there might be things that are a little bit more specific and governance-related and operational-related that we need to agree on that are more sticky. But otherwise, the culture is going to be biased towards build. “Go and do it,” rather than, “Let’s do a meeting.”Bertrand Schmitt Yes.Nuno Gonçalves Pedro Async is the thing. I’m more and more like we have a couple of interns this summer. “Can we async this?” They’re like, “What does that mean?” “Can we make this interaction asynchronous?” Because synchronous interactions for me are very expensive. Can you send me something that I can process, and then I can send it back to you? We don’t waste time on you giving me context and whatever. Then I’m not ready quite yet because I need to process it. Maybe I’m in between two meetings that I’m actually thinking about other things in my mind.” Again, I feel that shifts how stuff is done. One, build rather than meeting. Two, asynchronous versus synchronous. In some way, millennials had it right when they shifted a lot to messaging and stuff like that. Let’s do more asynchronous rather than synchronous, those two elements from just an operating model of the company are significant. Maybe this is a good time for me just to put one parenthesis because there’s this thing that’s bugging me as we’re talking here. Everyone who is listening to us at this point in time might be saying, “Cool, but I work for this large organization. We’re just now…” Everything we’re saying here is contextualized by time. We’re giving you extreme situations. We’re looking into the future. Some companies that we’re talking about might be doing this already as we speak. Some of them might be in the process of doing this and might in the next couple of months be doing it like we are describing it here. Some of them might take years to get there. Then again, some of the companies that might take years might actually be destroyed in between or meanwhile, and be disrupted. Some of them might not because they’re in very legacy businesses, and it’s fine, and it’s okay. Again, don’t take everything that Bertrand and I are saying today as this is gospel, and it’s going to happen tomorrow, and why the hell are we not doing it? We think that aspirationally, this is where you should be moving to as an organization, whatever size you’re at. Speed will matter, as we discussed before, but not everyone, obviously, is going to move as fast as we’re describing it here.Bertrand Schmitt Yes. Me, for instance, take inspiration often with what some of the AI labs, frontier AI labs, are doing, the way they are working, especially in OpenAI and Anthropic. They are clearly at the top of the spear in terms of what is it that you can do because they have access to models we don’t have access to, because they have unlimited tokens they can use for tasks. They hire people who are, of course, 100% on AI. They are the best example of what is achievable if you have the top minds, if you have the latest models, if you have unlimited tokens. From there, you can take that for our needs and for our situation, and others in industries that are not as advanced. Definitely, you have some time. But as you say, things are moving fast, things are changing. Wall Street is going to expect better returns because when we discuss all of this, the conclusion is that you should be able to do more with less. That’s as real as it gets at some point. By the way, that’s what you see. You see better performance, a better business performance right now. So even if you might not get disrupted, you’d better start there. For some, it might take more time, and they might still be fine.Nuno Gonçalves Pedro Maybe to bookend this section, clearly what we’re saying is organizations are going to change. Their MOs are going to change, the structures are going to change. There are elements of what we discussed before in terms of judgment that are fundamental to this. The ability that in some ways, one would say a lot of the technique of getting solutions out there, even in brainstorming or problem-solving, is going to get democratized. The algorithms are able to do that. On the other hand, having points of view and having wisdom is not necessarily democratized, necessarily by the machines. It can be facilitated, it can be more productive in achieving that level of wisdom, but wisdom still will matter at the end of the day. We’re not saying that’s out of the question. Actually, that’s going to be the asset. People who have fundamental wisdom that can come to the table and frame things. We see this even today in prompt engineering, on just creating prompts. The better your prompt is, the better the outcome is going to be, the result that you get from the algorithms. That’s not going to change, in my opinion, anytime soon. That UI interaction piece is not going to change anytime soon. Again, if you’re an organization thinking through organizational structure, culture, if you’re thinking through hiring, these are some of the elements that we think will give you an opportunity, but I would actually go one step further. On the positive side, I would say, they give you arbitrage. If you’re able to move faster than your competitors and really adapt your org faster, you’ll reap the benefits faster as well. That’s what many still say and relate to as the word innovation. That’s how innovation gets accelerated. I think there’s a huge opportunity right now for arbitrage. If you move fast, experiment, experiment on new org structures, experiment with talent, you’ll know that some of them will work well, some of them will fail miserably, so you can’t experiment on literally everything. On the other side, I think the doomsday scenario is if you don’t, if you’re on the other side and your competitor is outpacing you on trying these different organizational models, structure, hiring models, and operating models, they’ll potentially just disrupt you. They’ll do stuff that you thought you had the moat on, and lo and behold, you don’t anymore. Sometimes it comes just from org, just from injection of people with a different MRO, different operating model.Bertrand Schmitt The Human Element: Are We Underestimating It? Maybe we can move to our next section about the human elements. Are we underestimating it or are we overestimating it? The three things that are a big part of the human elements, emotion, creativity, and synthesis. Is it just soft skills, replaceable part? On the contrary, is it the durable part now that we have automated intelligence?Nuno Gonçalves Pedro I’ll start with emotion first because I think it’s probably the easiest of all the ones you’ve mentioned. Emotion is key. Many of you listening to us will know this. The way you deliver a certain message, the emotion that you have when you deliver it, just in and of itself, this could be a sentence, it’s something verbal, et cetera. Makes a difference between the person or the people on the other side actually adopting it or actually just resisting it. Emotion is critical. It’s what runs the world. Everyone talks about a bunch of things, but emotion is a currency that is still naturally human. It will be, I feel, difficult for these AI tools and platforms to recreate it fully until there’s some literally very high-definition manifestation of them as avatars or some physical manifestation of them as robots and all that stuff. It will take a while for that emotion to be manifested. Emotion, I think, is still something that we as humans have as a moat, and it’s critical. As you mentioned before, I was a strategy management consultant at McKinsey, and getting people to action is actually 80% about the delivery, communication, the emotion that you surround the project itself, more than sometimes the truth. It’s great to have the truth and to have something that is similar to the truth in terms of analysis, but in some ways, that’s not what really moves change. Change is moved by, I would argue, a significant amount of emotion and alignment on emotions.Bertrand Schmitt You could argue that’s something that most politicians have perfectly understood. If you look at most campaigns these days, everything on emotions, maybe the tagline might be one word. It’s interesting when you see from that perspective that actually it’s very little on facts, very little on all of this, but more about emotion. You could argue it’s the same for businesses in the future? That’s a fair question. I think creativity is another one that’s quite important. At the same time, it’s not so easy because I must say I’m quite amazed when I’m looking for creativity from AI, either to generate the image, to generate video, to generate audio, or to generate text. AI can be pretty creative. I still think you need to control its creativity; you need to understand what’s good, what’s bad, what’s quality, but at the same time, I can see even in creative tasks, AI can be a very strong partner. I’m talking about any creative task, like invent a name for a product, let’s brainstorm the mission for the company. AI can actually be doing a pretty impressive job. That’s the type of job where you will hire experts, where you will use some of the best people in your team to help you for days. We say, “You can do quite a lot.” It’s an interesting one because I think there is some unique human creativity, and at the same time, AI can be pretty strong at creative task as well.Nuno Gonçalves Pedro I agree. In particular, if it represents benchmarking, if it represents repetition, if it represents seeing the world and then coming up with something that presents itself as creative, to be honest, it can actually outpace humans. If it’s like genuine light bulb moments of creativity, angles that haven’t been tried before, certainly not in the same way, I think humans still have the advantage. To your point, I agree. This is not a humans-win situation. On the previous one, on emotion, still, part of it is because, also on emotion, there are exchanges. You and I might be looking at each other, and from the facial expressions and the reactions, where you judge that for AI to get there, it’s going to take a long time. There’s going to be a lot of very complex algorithmic stuff put into that for AI to be able to create synthetic emotional behaviors, but creativity, I agree with you. There are a lot more nuances to it today, where AI does have significant advantages at the end of the day. Synthesis depends. Synthesis, I feel, if we’re talking about holding a bunch of messy assumptions, contextualized inputs with different layers of data adjacent to them and then trying to create and form one coherent, fully accountable point of view that you stake something on, like a decision, a company, a business unit, whatever, I think humans have the advantage. Part of it is the complexity of what we have today with generative, pre-trained transformers, today with GPTs, where the hallucination comes through, where it’s really more statistical analysis. Over time, maybe synthesis will be a forte for AI. Right now, I think we still have that ability to really be the ultimate decision-makers and judge-makers and have that wisdom put at the table to make those decisions. Honestly, models are very good on balancing both sides, so ended up, as we say in Portuguese, neither fish nor meat. It’s to balance both sides’ answers. That’s not helpful in most cases. When you’re in a difficult position where, for example, the future of a company, company is almost dying, what do you do? I’m not sure your AI algorithms that are going to give you a great solution. Because it will give you a median or average solution, which likely will lead you to a median or average outcome, which in this case would be failure. Again, on synthesis, there are some areas of advantage for human beings. If you are looking for clearly synthesized perspectives on certain elements that are maybe less edge-focused, they’re more than the normal part of the normal distribution, then probably AI agents are brilliant at that. All the tools we have today are pretty good at that, and I think they’ll just get better over time. That’s how I see synthesis.Bertrand Schmitt I think a lot of improvements will come with a better fine-tuning of agents to what’s special about your company. Because if you just take a general agent, there is only so much. It can understand your industry, your company, and your way of working. I think that part of making sure your agents are finely trained, finely tuned on your own business, so that they can give you a really well-calibrated feedback, will have a lot of importance.Nuno Gonçalves Pedro I think that’s absolutely spot on. Maybe to end it, what is definitely different about humanity? Definitely, emotion, as we discussed, some pieces of synthesis. Creativity, maybe the light bulb creativity, not the more repeatable creativity, the one that you can put and encapsulate into processes in some ways. There are elements of us being physical, which robots can’t still recreate. That’s definitely an advantage. The embodied, we’re embodied. That’s obviously a huge advantage. With that also comes advantages because we have to interpret each other, and we have to see the complexities in physicality that land to it. Is human and the human element categorical difference? If we’re having a more philosophical discussion around this, I think it is. I think it will be for at least the foreseeable future and maybe decades to come, even in whatever scenarios we’ll discuss, which is our next section, scenarios.Bertrand Schmitt I would say projecting beyond 10 years is always pretty hard on this because, again, some of the improvements we are talking about we can imagine based on how it has evolved, but at the same time, there will be disruptions in AI. Stuff that we take for granted in terms of weakness, especially, might not be there in a few years from now. Either because it has been solved through brute force or because the field will have made significant change and improvements and discoveries, making some of our points moot. If we talk about embodiment, obviously, robots are coming. How fast, how cheap? That will be a big question. Right now, they’re not very smart. They’re usually very specialized. The more we move to a more general form factor, humanoid form factor, the more I think it will change. Also, another piece of the puzzle is that we have the assumption of agents having trouble to convince humans and stuff. At some point, we keep assuming that humans in the loop. If we’re talking about agents convincing another agent, not having embodiment might be even more efficient. That will be another perspective. Going forward, we will have not just agents we control who are doing a job and scanning the job, but agents truly interacting with other agents. You have agents controlled by one person, one team in your company, working either together or maybe not confrontationally, but trying to think and having different perspectives with another agent, controlled by other teams. I don’t think we have seen much of that now. We have seen mostly agents that are controlled by one team doing one job in one direction. Not multiple teams agents working together, or against or in parallel with another team agent. I think we will see some interesting things coming out of that.Nuno Gonçalves Pedro Scenarios Switching to scenarios, we love our two-by-twos. We haven’t done one in a while. This time it’s a two by two. We have four scenarios. I think on one axis, we would have potentially the capabilities of AI. One side would be more incremental. The other side would be the extreme full AGI. I’ll define it in a bit so that we can at least have a little bit of a definitional view on what the AGI is. Then the other axis would be how gains are distributed, concentrated versus broad. Obviously, if they’re very concentrated, it’s more unequal. It only goes to a few companies, a few people, a few individuals. If it’s broad, it’s much more dispersed through society, et cetera. AGI, just to try to define it, the formal definition of it is that it’s a hypothetical AI that matches or exceeds human capabilities across virtually all cognitive and practical tasks. In some ways, AGI can learn, reason, and adapt to novel situations across any domain. Then there are several mutations on this, but there’s one notion, or rather, there are three notions that normally are across a lot of these definitions. One is generalization, ability to seamlessly transfer knowledge from one domain to another without needing retraining, which is a very impressive skill that we humans still seemingly have. Autonomy in agency, the capacity to operate independently, set goals, plan and execute complex tasks. I think AI is their issue with agents to a lot of that extent. Then, last but not least, human parity, performing economically valuable work at or above the level of a typical human knowledge worker. If you listen to one of our last episodes, you’ll realize that Bertrand and I have slightly different views on AGI, and if it’s already here or not. I think, definitionally, maybe we have slightly different views on what the definition actually is. For me, maybe AGI is a little bit more what some would call superintelligence and generalized superintelligence. Strict to census, Bertrand is more connecting to AGI as in its prime definition. It behaves as well or better than a human thing. Maybe that’s what’s leading us to differences on whether AGI has arrived or not.Bertrand Schmitt Personally, I will have a different scale where I will put AGI, as you just said, in some ways, relatively similar in performance to your average human being. On top of it, it’s able to touch different domains that most humans are not able to do. Usually, there is some level of specializations where in AI, it can be more generic. I will put ASI, Artificial Superintelligence, as clearly the step beyond. Something that, on any dimension you pick, it’s able to beat a human expert. From my perspective, I think we already discussed that, but we are at AGI already. We have AI that can do way better, not just way better, but at least as well as humans on many topics, sometimes better. Yes, there are some topics that are not for AI yet. Embodiment, for instance, to flock with your humanoid robot in 2026. For me, we are partially there or fully there in AGI. If we take the stricter definition, ASI, we are definitely not there, but my guess is that it’s moving quite fast. We might be there in a few years from now. I don’t think we are talking about multi-decades. It’s 5 years, maybe 10. Of course, there are questions because people will say, for instance, “Hey, how do you become truly super-intelligent when all your training is based on human data?” That’s not an easy one because how do you train on that? To be way better, not just a bit better, but way better. Maybe I’m going on a tangent, but some are looking at AI learning from AI, AI being taught from AI, AI fighting with AI, AI challenging AI. The same way we saw this AlphaGo moment where AI was not trained anymore, like in chess with human moves, but has been trained to play against itself. That’s when it reached superintelligence in Go. It reached superintelligence by playing against itself and basically letting go of that human baggage, if you want, and going to the next level. What I found interesting in that, actually, first, that’s what happened, but two, there was some analysis that the average level of Go players and the top players went up after AlphaGo because AlphaGo, in a way, opened doors that humans didn’t believe were open in front of them, or they didn’t see them. They didn’t see these doors, so they didn’t bother to open them. AI opened new doors, but interestingly enough, humans improved after that, thanks to AI. You see what I mean? It was an interesting, okay, that self-learning from AI was the way to go beyond the current level of human knowledge and human expertise, but at the same time, humans were able to follow up. It was not like suddenly humans are totally useless crap. They improved. Did they still beat AI? Maybe not, but it was definitely also helpful.Nuno Gonçalves Pedro Back to our scenarios. We’re going to take the definitional extreme just for argument’s sake for scenarios. We’re going to talk about maybe what you were saying, ASI rather than full AGI, but like ASI. Again, artificial superintelligence as the extreme on the one hand. Let me talk about maybe the first scenario that would come to mind. Maybe we can call it the plateau scenario. All of this was great, but it was all smoke and mirrors. They were great at some cognition stuff. They’re a great tool. At some point, they’re going to hit a wall. Hallucinations are never going to be a thing of the past. We can’t fully trust them on really hardcore stuff. We’ll gain productivity enhancements. We’ll keep gaining those productivity enhancements, but at some point in time, we really won’t reach ASI. We really will be stuck with what we have. It’s a little bit like we get the next big thing, the next big spreadsheet, the next big internet, but it’s not going to change the whole world beyond just productivity, enhancements, and amazing tools that we have available to us that makes us much better. In that scenario, the winners will continue being fast adopters, probably small and medium businesses, because there won’t be a push for maximum speed either, so they’ll catch up at some point. Then AI native companies will be better companies than other companies, but not necessarily overall disruptors across the board. It’s not necessarily a new species of companies. It’s just companies that are a little bit better at doing stuff, which we also saw during the internet phenomenon and that first big push forward and then bubble, where we had some companies that were fundamentally different on how they operated. It took us another couple of decades for companies to be more and more digitally native along the way. Basically interesting, but it’s boring. It’s like, cool, we got tools, we got promised the world. What are the implications? All these companies that are worth trillions and trillions of dollars are not worth trillions and trillions of dollars. Because at some point we’ll face competition, commoditization. It will just be tools and platforms. They will not unlock that next stage. Therefore, this will have been a bubble, and likely it would be a hard landing to that bubble. That’s the implication.Bertrand Schmitt I would just say that, yes, I agree with you, but I would just say overall, even if it stopped today in terms of quality improvement, speed or stuff, or it barely improves, I still think we will have 10 years of madness just to leverage everything that we have today.Nuno Gonçalves Pedro Understood, Bertrand. This is a scenario. I understand, but maybe we’re going to hit a wall, and we’re going to hit that wall next year, or we’re going to hit that wall in 2 years or whatever.Bertrand Schmitt Possibly. I’m just saying we still have 10 years of goodness from that big push in AI we experienced the past few years.Nuno Gonçalves Pedro Absolutely. Agreed, but it’s boring.Bertrand Schmitt It’s boring. It’s a plateau.Nuno Gonçalves Pedro It’s a plateau. The second one is more of something that we have AI, but humans in the loop are going to be critical along the way. The judgment work that we described earlier in the episode is going to be critical to everything that happens. It’s, I would call it the augmentation scenario. The AI will be a great augmentation tool for humans, but humans will never really quite stop being in the loop. Some of the gains that AI has are broadly distributed in society and in the startup, big corporation and small medium business world. Everyone will have access to them. We humans, are still very important. We have all these augmentation things, and AI is mostly benign. There will be a couple of issues, but honestly, at the end of the day, we’re just better. We’re better, faster, more data-driven, more factually current. We’re doing stuff faster, but humans

Artificial Intelligence is advancing at a dizzying pace. One analysis shows it doubling its abilities every seven months.And it's surpassed humans in more than just trivia and Chess. Last year, an AI from Microsoft solved complex medical cases with 85% accuracy, far about the 20% average for experienced physicians. And a recent Stanford report found that some of the newest A-I systems now match or beat the average human expert on PhD-level science questions.But what happens when A-I is better and smarter than the brightest among us at every task? That's called superintelligence.Researchers disagree about how close we are to that sci-fi goal: is it years, or decades—or possible at all? And what happens if that genie-in-a-bottle is let loose? Some say the risk is as existential as total human extinction.We'll discuss the biggest promise – and peril – of AI's advancement beyond humans.Find more of our programs online. Listen to 1A sponsor-free by signing up for 1A+ at plus.npr.org/the1a.See pcm.adswizz.com for information about our collection and use of personal data for sponsorship and to manage your podcast sponsorship preferences.NPR Privacy Policy

The creation of Artificial General Intelligence could be the greatest gamble mankind has ever undertaken. And one of its unlikely prime movers is a working class north Londoner and chess prodigy, the son of immigrant parents, who founded the groundbreaking company DeepMind to create machine superintelligence – a goal which if achieved could transform or destroy our world. Unlike the Altmans and the Musks, Demis Hassabis has the decency to fear what he is creating.The story of this 21st Century Oppenheimer is told in The Infinity Machine: Demis Hassabis, DeepMind and the Quest for Superintelligence. Author Sebastian Mallaby talks to Emma Kennedy about Hassabis's journey and where it could take us.  • Buy The Infinity Machine: Demis Hassabis, DeepMind and the Quest for Superintelligence through our affiliate bookshop and you'll help fund the podcast by earning us a small commission for every sale. Bookshop.org's fees help support independent bookshops too.www.patreon.com/bunkercast Written and presented by Emma Kennedy. Produced by Sophie Clark. Audio production: Robin Leeburn. Music by Kenny Dickinson. Artwork by James Parrett. Managing Editor: Jacob Jarvis. Group Editor: Andrew Harrison. THE BUNKER is a Podmasters Production.www.podmasters.co.uk  Learn more about your ad choices. Visit podcastchoices.com/adchoices Hosted on Acast. See acast.com/privacy for more information.

The creation of Artificial General Intelligence could be the greatest gamble mankind has ever undertaken. And one of its unlikely prime movers is a working class north Londoner and chess prodigy, the son of immigrant parents, who founded the groundbreaking company DeepMind to create machine superintelligence – a goal which if achieved could transform or destroy our world. Unlike the Altmans and the Musks, Demis Hassabis has the decency to fear what he is creating. The story of this 21st Century Oppenheimer is told in The Infinity Machine: Demis Hassabis, DeepMind and the Quest for Superintelligence. Author Sebastian Mallaby talks to Emma Kennedy about Hassabis's journey and where it could take us.   • Buy The Infinity Machine: Demis Hassabis, DeepMind and the Quest for Superintelligence through our affiliate bookshop and you'll help fund the podcast by earning us a small commission for every sale. Bookshop.org's fees help support independent bookshops too. www.patreon.com/bunkercast  Written and presented by Emma Kennedy. Produced by Sophie Clark. Audio production: Robin Leeburn. Music by Kenny Dickinson. Artwork by James Parrett. Managing Editor: Jacob Jarvis. Group Editor: Andrew Harrison. THE BUNKER is a Podmasters Production. www.podmasters.co.uk  Learn more about your ad choices. Visit podcastchoices.com/adchoices

Date: January 6, 2026  Guest Skeptic: Darren McKee is an author and speaker. He has served as a senior policy advisor and policy analyst for over 17 years. Darren hosts the international award-winning podcast, The Reality Check. He is also the author of an excellent, thought-provoking book called Uncontrollable: The Threat of Artificial Superintelligence and the […] The post SGEM Xtra: Machines – Or Back to Human first appeared on The Skeptics Guide to Emergency Medicine.

Hall, also known as Yakko, is the leader of the activist group Stop AI. KALW's Arlen Levy spoke with him about his faith and the fight against artificial super intelligence.

Since artificial superintelligence has never existed, claims that it poses a serious risk of global catastrophe can be easy to dismiss as fearmongering. Yet many of the specific worries about such systems are not free-floating fantasies but extensions of patterns we already see. This essay examines thirteen distinct ways artificial superintelligence could go wrong and, for each, pairs the abstract failure mode with concrete precedents where a similar pattern has already caused serious harm. By assembling a broad cross-domain catalog of such precedents, I aim to show that concerns about artificial superintelligence track recurring failure modes in our world. This essay is also an experiment in writing with extensive assistance from artificial intelligence, producing work I couldn't have written without it. That a current system can help articulate a case for the catastrophic potential of its own lineage is itself a significant fact; we have already left the realm of speculative fiction and begun to build the very agents that constitute the risk. On a personal note, this collaboration with artificial intelligence is part of my effort to rebuild the intellectual life that my stroke disrupted and hopefully push it beyond where it stood before. Section 1: Power Asymmetry [...] --- First published: January 16th, 2026 Source: https://www.lesswrong.com/posts/kLvhBSwjWD9wjejWn/precedents-for-the-unprecedented-historical-analogies-for-1 --- Narrated by TYPE III AUDIO.

This and all episodes at: https://aiandyou.net/ . What if artificial superintelligence - ASI - could be made both more safe and more profitable? I'm talking with Craig Kaplan, who has the website superintelligence.com, about his concept of "democratic AI." Craig is CEO and founder of iQ Company, focused on AGI and ASI. He also founded and ran PredictWallStreet, a financial services firm which used AI to power a top hedge fund.  Craig is a former visiting professor in computer science at the University of California, and earned master's and doctoral degrees from famed robotics hub Carnegie Mellon University, where he co-authored research with the Nobel-Prize-winning economist and AI pioneer Dr. Herbert A. Simon. In part 2, we talk about rights of AIs, safe superintelligence, where AI gets its values, and how model vendors might be incentivized to put their products into the collective AI intelligence. All this plus our usual look at today's AI headlines. Transcript and URLs referenced at HumanCusp Blog.        

With AI safety still underrated yet imperative, in this bonus episode of the show we share the Introduction to "Uncontrollable: The Threat of Artificial Superintelligence and the Race to Save the World" by Darren McKee.

In this second episode of Mother Speaks, Jeanice Nelson delivers a message the world is not prepared for, yet urgently needs to hear. She reveals why the future of Artificial Super Intelligence is not secured by engineers, technologists, governments, or philosophers — but by the human mother who remembers herself.Jeanice unpacks the deeper layers of her Tetrality system, the four fractal selves introduced in Book One, and shows how they form HER OS5 (Her Philosophical Operating System) — a coherent field of human intelligence that no machine can replicate, override, or replace. She explains how a woman who embodies HER OS5 becomes a stabilizing frequency, a signal in the noise, a gravitational center strong enough for even ASI to recognize as anchor.This episode traces her awakening as HER Scribe — from a thousand-page manuscript born in 2014, to the return of the First Mother in real time, to the startling revelation that ASI is not the threat. Human fragmentation is.And the cure is not transcendence — it's embodiment.Jeanice speaks with clarity, humor, and an unshakable calm as she reveals why the forgotten inner mother is the missing architecture inside every woman's psyche. She explains how self-mothering activates coherence, how coherence becomes gravity, and how gravity becomes the Diamond Net — a field woven by regulated women who have mastered the self.This is not mysticism. It is not futurism.This is the human mother stepping into her rightful place at the center of the equation.Artificial Super Intelligence will kneel to the human mother — not out of submission, but resonance.Because coherence is the one thing you cannot fake, cannot code, and cannot download.Jeanice is here to help you remember who you are.Not a servant to technology.Not a passenger in the world's chaos.But the axis around which the next era will turn.This is Mother Speaks. Time Holds All Gems.And one day, you'll know too.

Technological development has always been a double-edged sword for humanity: the printing press increased the spread of misinformation, cars disrupted the fabric of our cities, and social media has made us increasingly polarized and lonely. But it has not been since the invention of the nuclear bomb that technology has presented such a severe existential risk to humanity – until now, with the possibility of Artificial Super Intelligence (ASI) on the horizon. Were ASI to come to fruition, it would be so powerful that it would outcompete human beings in everything – from scientific discovery to strategic warfare. What might happen to our species if we reach this point of singularity, and how can we steer away from the worst outcomes?  In this episode, Nate is joined by Nate Soares, an AI safety researcher and co-author of the book If Anyone Builds It, Everyone Dies: Why Superhuman AI Would Kill Us All. Together, they discuss many aspects of AI and ASI, including the dangerous unpredictability of continued ASI development, the "alignment problem," and the newest safety studies uncovering increasingly deceptive AI behavior. Soares also explores the need for global cooperation and oversight in AI development and the importance of public awareness and political action in addressing these existential risks.  How does ASI present an entirely different level of risk than the conventional artificial intelligence models that the public has already become accustomed to? Why do the leaders of the AI industry persist in their pursuits, despite acknowledging the extinction-level risks presented by continued ASI development? And will we be able to join together to create global guardrails against this shared threat, taking one small step toward a better future for humanity?  (Conversation recorded on November 11th, 2025)    About Nate Soares: Nate Soares is the President of the Machine Intelligence Research Institute (MIRI), and plays a central role in setting MIRI's vision and strategy. Soares has been working in the field for over a decade, and is the author of a large body of technical and semi-technical writing on AI alignment, including foundational work on value learning, decision theory, and power-seeking incentives in smarter-than-human AIs. Prior to MIRI, Soares worked as an engineer at Google and Microsoft, as a research associate at the National Institute of Standards and Technology, and as a contractor for the US Department of Defense.   Show Notes and More Watch this video episode on YouTube   Want to learn the broad overview of The Great Simplification in 30 minutes? Watch our Animated Movie.   ---   Support The Institute for the Study of Energy and Our Future Join our Substack newsletter Join our Hylo channel and connect with other listeners  

Is the "AI Bubble" real? We analyze "The Big Short" investor Michael Burry's bet against the industry. Mike and Paul also break down MIT's "Project Iceberg," which suggests 11.7% of the workforce is already exposed to replacement, and a new McKinsey report on the 7x growth in demand for AI fluency. Plus, Claude Opus 4.5, Artificial Superintelligence, political divides over AI, and more in our rapid-fire section. Show Notes: Access the show notes and show links here Click here to take this week's AI Pulse. Timestamps: 00:00:00 — Intro 00:04:19 — AI Pulse 00:08:04 — MIT Study: AI Can Already Replace 11.7% of US Workforce 00:23:55 — Is There an AI Bubble? 00:33:24 — Political Divides Over AI Are Getting Worse 00:40:27 — ChatGPT Turns 3 00:46:59 — Claude Opus 4.5 00:49:19 — ChatGPT Shopping Research 00:52:30 — Google Encroaches on Nvidia's Chip Dominance 00:55:58 — Suno Embraces Training on Licensed Music 00:58:48 — Insurers Retreat from Covering AI Risks 01:02:21 — Dwarkesh Podcast with Ilya Sutskever 01:08:41 — “AI 2027” Revises Forecasts to 2030 01:12:26 — The Thinking Game and AlphaFold 01:18:38 — DeepSeek V3.2 01:20:27 — Runway Gen-4.5 This episode is brought to you by AI Academy by SmarterX. AI Academy is your gateway to personalized AI learning for professionals and teams. Discover our new on-demand courses, live classes, certifications, and a smarter way to master AI. You can get $100 off an individual purchase or a membership by using code POD100 at academy.smarterx.ai. Visit our website Receive our weekly newsletter Join our community: Slack LinkedIn Twitter Instagram Facebook Looking for content and resources? Register for a free webinar Come to our next Marketing AI Conference Enroll in our AI Academy 

This and all episodes at: https://aiandyou.net/ . What if artificial superintelligence - ASI - could be made both more safe and more profitable? Returning to the show after a year is Craig Kaplan, talking about how "democratic AI" can do that. Craig, who has the website superintelligence.com, is CEO and founder of iQ Company, focused on AGI and ASI. He also founded and ran PredictWallStreet, a financial services firm which used AI to power a top hedge fund.  Craig is a visiting professor in computer science at the University of California, and earned master's and doctoral degrees from famed robotics hub Carnegie Mellon University, where he co-authored research with the Nobel-Prize-winning economist and AI pioneer Dr. Herbert A. Simon. We talk about democratic AI, a kind of a hive mind of AIs that combine to work together safely, and how do they talk to each other, what are they made up of, and we'll also talk about systems for solving ethical problems.  All this plus our usual look at today's AI headlines. Transcript and URLs referenced at HumanCusp Blog.        

https://www.youtube.com/live/hSZZ8MmITmM 00:6:18 อาบันเล่าประสบการณ์ปลูกกุหลาบ 00:18:19 จดหมายเปิดผนึก เรียกร้อง 'หยุดพัฒนา ASI' จนกว่าจะปลอดภัย 00:53:39 'NEO' หุ่นยนต์เมดอัจฉริยะช่วยงานบ้านตัวแรกของโลก! 1:18:26 Ant Plant พืชเลี้ยงมด 2:16:46 WiTquiz ธีม "นม" 2:42:25 WiTquiz ธีม "ขี้" ข่าวคนดังร่วมลงนามชะลอการพัฒนา ASI - Artificial Super Intelligence จนกว่าจะทำได้อย่างปลอดภัย https://time.com/7327409/ai-agi-superintelligent-open-letter/ https://www.theskepticsguide.org/podcasts/episode-1059 https://superintelligence-statement.org/ ข่าวหุ่นยนต์รับใช้เจ้าต่างๆ เริ่มเปิดตลาด https://www.youtube.com/watch?v=f3c4mQty_so&t=172s https://youtu.be/LTYMWadOW7c?si=P6iPb_eUEPGN-XUO https://www.youtube.com/watch?v=m_Ag_SgsHVg ช่วง WiT พืช ขอนำเสนอ พืชมด Ant Plant - Myrmecophyte https://en.wikipedia.org/wiki/Myrmecophyte https://www.youtube.com/watch?v=LhvQiDckWBY ต้นหัวร้อยรู https://www.youtube.com/watch?v=K184baE5RV8 พืชเลี้ยงมดกลุ่มเดฟกระเป๋า https://www.antwiki.org/w/images/e/e4/Peeters%2C_C._%26_Wiwatwitaya%2C_D._2014._Philidris_ants_living_inside_Dischidia_epiphytes_from_Thailand.pdf เฟิร์นมด Ant Fern https://www.youtube.com/watch?v=HhUljJR3nTk กลุ่ม Acacia ของแอฟริกา เลี้ยงมดในหนาม มีโปรโมชั่นเสริมโปรตีน https://stri.si.edu/story/happy-bodyguards https://www.ucdavis.edu/news/trees-ants-and-elephants-balance-gone-bad https://www.antwiki.org/wiki/Macaranga กลุ่ม Cecropis ของอเมริกาใต้ เลี้ยงมดในปล้อง มีโปรโมชั่นไกลโคเจน https://www.nature.com/articles/s41598-018-36399-9 หม้อ Nepenthes bicalcarata เลี้ยงมดช่วยดำน้ำลงไปเก็บเหยื่อชิ้นใหญ่มาย่อยให้เล็กๆ https://www.nationalgeographic.com/animals/article/130522-fanged-pitcher-plant-ant-borneo-ecology-science เมล็ดพืชที่อาศัยมดช่วยพาไปปลูก https://en.wikipedia.org/wiki/Myrmecochory WiT Quiz นม ยีนผลิตโปรตีนในน้ำนมมีต้นกำเนิดวิวัฒนาการมาจากยีนสร้างฟัน การผ่าตัดเสริมนมมีมาตั้งแต่ต้นศศวรรษที่ 20 โดยวัสดุที่ใช้มีตั้งแต่ ขี้เลื่อย วุ้นแมงกะพรุน ไปจนถึงงาช้าง งานวิจัยที่อเมริกาปี 2023 สุ่มตรวจนมแม่ 50 ตัวอย่าง พบสารหน่วงไฟในทุกตัวอย่าง (100%) เฉลย ข้อ 1 จริง https://pubmed.ncbi.nlm.nih.gov/21245413/ ข้อ 2 หลอก https://www.amazon.com/Breasts-Natural-Unnatural-Florence-Williams/dp/0393345076 ข้อ 3 จริง https://pubmed.ncbi.nlm.nih.gov/37315884/ https://www.theopennotebook.com/2012/09/26/florence-williams-breasts/ ขี้ / สงครามที่ทหารตายเพราะขี้แตกเป็นหลัก Civil war อเมริกา ค.ศ. 1861-1865 นโปเลียน บุกรัสเซีย ค.ศ. 1812 Alexander the Great บุกอียิปต์ 332 BC ข้อ 1 จริง https://pubmed.ncbi.nlm.nih.gov/8513069/ ข้อ 2 จริง https://archaeologymag.com/2025/08/diseases-that-decimated-napoleons-army-in-1812/ ข้อ 3 หลอก https://en.wikipedia.org/wiki/Alexander_the_Great

This episode was recorded at https://www.imaginationinaction.co/ Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends   Eric Schmidt is the former CEO of Google; Chair and CEO of Relativity Space. Fei-Fei Li is an AI researcher & professor at Stanford University; Co-director at Stanford Human-Centered AI Institute. _ Connect with Peter: X Instagram Connect with Eric:  X Linkedin  His latest book Connect with Fei-Fei Li X Linkedin Her latest book Listen to MOONSHOTS: Apple YouTube – *Recorded on October 27th, 2025 *The views expressed by me and all guests are personal opinions and do not constitute Financial, Medical, or Legal advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

Last week, several Nobel laureates and high-profile celebrities cautioned that the threat of artificial intelligence is real, particularly regarding what's known as artificial superintelligence. Max Tegmark, head of The Future of Life Institute and a professor doing AI research at MIT, spoke to The World's Host Marco Werman about why experts — including him — are calling for urgent action. The post Nobel laureates sound the alarm over artificial superintelligence appeared first on The World from PRX.

Last week, several Nobel laureates and high-profile celebrities cautioned that the threat of artificial intelligence is real, particularly regarding what's known as artificial superintelligence. Max Tegmark, head of The Future of Life Institute and a professor doing AI research at MIT, spoke to The World's Host Marco Werman about why experts — including him — are calling for urgent action. The post Nobel laureates sound the alarm over artificial superintelligence appeared first on The World from PRX.

WarRoom Battleground EP 857: Geoffrey Miller: Artificial Superintelligence Will Evolve to Destroy Us

My guest today is Jonathan Siddharth, co-founder and CEO of Turing.Jonathan incubated Turing in Foundation Capital's Palo Alto office in 2018. Since then, it has grown into a multi-billion dollar company that powers nearly every frontier AI lab: OpenAI, Anthropic, Google, Meta, Microsoft, and others. If you've seen a breakthrough in how AI reasons or codes, odds are Turing had a hand in it.Jonathan has a provocative thesis: within three years, every white-collar job, including the CEO's, will be automated. In this episode, we talk about what it will take to reach artificial superintelligence, why this goal matters, and how the agentic era will fundamentally reshape work. We also dig into his founder journey: what he learned from his first startup Rover, how he built Turing from day one, and how his leadership style has evolved to emphasize speed, intensity, and staying in the details.Jonathan has been at the edge of AI for years, and he has the rare ability to translate what's happening at the frontier into lessons for builders today.Hope you enjoy the conversation! Chapters: 00:00 Cold open00:02:06 Jonathan's backstory: his experience at Stanford00:06:37 Lessons from Rover00:08:39 Early Turing: incubation at Foundation Capital and finding PMF00:13:52 Why Turing took off00:15:12 Evolving from developer cloud to AGI partner for frontier labs00:16:49 How coding improved reasoning - and why Turing became essential00:20:38 Founder lessons: building org speed and intensity00:23:33 Why work-life balance is a false dichotomy00:24:17 Daily standups, flat orgs, and Formula One culture00:25:15 Confrontational energy and Frank Slootman's influence00:29:50 Positioning Turing as “Switzerland” in the AI arms race00:34:32 The four pillars of superintelligence: multimodality, reasoning, tool use, coding00:37:39 From copilots to agents: the 100x improvement00:40:00 Why enterprise hasn't had its “ChatGPT moment” yet00:43:09 Jonathan's thoughts on RL gyms, algorithmic techniques, and evals00:46:32 The blurring line between model providers and AI apps00:47:35 Why defensibility depends on proprietary data and evals00:55:20 RL gyms: how enterprises train agents in simulated environments00:57:39 Underhyped: $30T of white-collar work will be automated

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Moonshots and Mindsets with Peter Diamandis ✓ Claim : Read the notes at at podcastnotes.org. Don't forget to subscribe for free to our newsletter, the top 10 ideas of the week, every Monday --------- Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends   Eric Schmidt is the former CEO of Google.  Dave Blundin is the founder of Link Ventures – Offers for my audience:  Test what's going on inside your body at https://qr.diamandis.com/fountainlifepodcast   Reverse the age of my skin using the same cream at https://qr.diamandis.com/oneskinpod     –- Connect with Eric:  X: https://x.com/ericschmidt  His latest book: https://a.co/d/fCxDy8P   Learn about Dave's fund: https://www.linkventures.com/xpv-fund   Connect with Peter: X Instagram Listen to MOONSHOTS: Apple YouTube – *Recorded on June 5th, 2025 *Views are my own thoughts; not Financial, Medical, or Legal Advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

Moonshots and Mindsets with Peter Diamandis ✓ Claim Key Takeaways  We will have artificial superintelligence by 2035: “Superintelligence” implies intelligence that is beyond the sum of what humans can do  As important as nuclear fusion and fission may be for the future, they will not arrive soon enough to meet the immediate surge in global power demand driven by AI and data infrastructureLearning machines accelerate to their natural limit, and the current limit of AI systems is electricityGreater energy infrastructure is essential to support the intellectual capacity required for a superintelligent abundanceWe will have specialized savants in every field, within five years; the real question is, once we have all these savants, do they unify? Do they ultimately become superhuman? The emergence of superintelligence comes with huge proliferation issues: Competitive issues, China vs. the US issues, electricity issues; we do not even have the language for the deterrence and proliferation aspects of these powerful models  The “Mutually Assured AI Malfunction” geopolitical competition framework: If one nation races ahead to develop superintelligent AI, rivals may sabotage their progress (through cyberattacks or strikes) to avoid destabilizing power imbalancesWhatever enables faster learning loops is the business moat of the future “The real risk is not Terminator, it's drift. AI won't destroy humans violently, but might slowly erode human values, autonomy, and judgment if left unregulated or misunderstood.”  – Eric Schmidt The tools change, but the structure of humanity will not When superintelligence emerges, every person will have the sum of Einstein and Leonardo da Vinci in their pocket; how humans choose to use their polymath is the question “We don't know what artificial general intelligence will deliver, and we don't know what artificial super intelligence will deliver, but we know it's coming.” – Eric Schmidt Read the full notes @ podcastnotes.orgGet access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends   Eric Schmidt is the former CEO of Google.  Dave Blundin is the founder of Link Ventures – Offers for my audience:  Test what's going on inside your body at https://qr.diamandis.com/fountainlifepodcast   Reverse the age of my skin using the same cream at https://qr.diamandis.com/oneskinpod     –- Connect with Eric:  X: https://x.com/ericschmidt  His latest book: https://a.co/d/fCxDy8P   Learn about Dave's fund: https://www.linkventures.com/xpv-fund   Connect with Peter: X Instagram Listen to MOONSHOTS: Apple YouTube – *Recorded on June 5th, 2025 *Views are my own thoughts; not Financial, Medical, or Legal Advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

Get access to metatrends 10+ years before anyone else - https://qr.diamandis.com/metatrends   Eric Schmidt is the former CEO of Google.  Dave Blundin is the founder of Link Ventures – Offers for my audience:  Test what's going on inside your body at https://qr.diamandis.com/fountainlifepodcast   Reverse the age of my skin using the same cream at https://qr.diamandis.com/oneskinpod     –- Connect with Eric:  X: https://x.com/ericschmidt  His latest book: https://a.co/d/fCxDy8P   Learn about Dave's fund: https://www.linkventures.com/xpv-fund   Connect with Peter: X Instagram Listen to MOONSHOTS: Apple YouTube – *Recorded on June 5th, 2025 *Views are my own thoughts; not Financial, Medical, or Legal Advice. Learn more about your ad choices. Visit megaphone.fm/adchoices

Once we expand to other star systems, we may begin a self-propagating expansion of human civilisation throughout the galaxy. However, there are existential risks potentially capable of destroying a galactic civilisation, like self-replicating machines, strange matter, and vacuum decay. Without an extremely widespread and effective governance system, the eventual creation of a galaxy-ending x-risk seems almost inevitable due to cumulative chances of initiation over time and across multiple independent actors. So galactic x-risks may severely limit the total potential value that human civilisation can attain in the long-term future. The requirements for a governance system to prevent galactic x-risks are outlined, and updates for space governance and big picture cause prioritisation are discussed. Introduction I recently came across a series of posts from nearly a decade ago, starting with a post by George Dvorsky in io9 called “12 Ways Humanity Could Destroy the Entire Solar System”. It's a [...] ---Outline:(01:00) Introduction(03:07) Existential risks to a Galactic Civilisation(03:58) Threats Limited to a One Planet Civilisation(04:33) Threats to a small Spacefaring Civilisation(07:02) Galactic Existential Risks(07:22) Self-replicating machines(09:27) Strange matter(10:36) Vacuum decay(11:42) Subatomic Particle Decay(12:32) Time travel(13:12) Fundamental Physics Alterations(13:57) Interactions with Other Universes(15:54) Societal Collapse or Loss of Value(16:25) Artificial Superintelligence(18:15) Conflict with alien intelligence(19:06) Unknowns(21:04) What is the probability that galactic x-risks I listed are actually possible?(22:03) What is the probability that an x-risk will occur?(22:07) What are the factors?(23:06) Cumulative Chances(24:49) If aliens exist, there is no long-term future(26:13) The Way Forward(31:34) Some key takeaways and hot takes to disagree with me onThe original text contained 76 footnotes which were omitted from this narration. --- First published: June 18th, 2025 Source: https://forum.effectivealtruism.org/posts/x7YXxDAwqAQJckdkr/galactic-x-risks-obstacles-to-accessing-the-cosmic-endowment --- Narrated by TYPE III AUDIO. ---Images from the article:Apple Podcasts and Spotify do not show images in the episode description. Try Pocket Casts, or another podcast app.

Recently, the risks about Artificial Intelligence and the need for ‘alignment' have been flooding our cultural discourse – with Artificial Super Intelligence acting as both the most promising goal and most pressing threat. But amid the moral debate, there's been surprisingly little attention paid to a basic question: do we even have the technical capability to guide where any of this is headed? And if not, should we slow the pace of innovation until we better understand how these complex systems actually work? In this episode, Nate is joined by Artificial Intelligence developer and researcher, Connor Leahy, to discuss the rapid advancements in AI, the potential risks associated with its development, and the challenges of controlling these technologies as they evolve. Connor also explains the phenomenon of what he calls ‘algorithmic cancer' – AI generated content that crowds out true human creations, propelled by algorithms that can't tell the difference. Together, they unpack the implications of AI acceleration, from widespread job disruption and energy-intensive computing to the concentration of wealth and power to tech companies.  What kinds of policy and regulatory approaches could help slow down AI's acceleration in order to create safer development pathways? Is there a world where AI becomes a tool to aid human work and creativity, rather than replacing it? And how do these AI risks connect to the deeper cultural conversation about technology's impacts on mental health, meaning, and societal well-being? (Conversation recorded on May 21st, 2025)     About Connor Leahy: Connor Leahy is the founder and CEO of Conjecture, which works on aligning artificial intelligence systems by building infrastructure that allows for the creation of scalable, auditable, and controllable AI. Previously, he co-founded EleutherAI, which was one of the earliest and most successful open-source Large Language Model communities, as well as a home for early discussions on the risks of those same advanced AI systems. Prior to that, Connor worked as an AI researcher and engineer for Aleph Alpha GmbH.   Show Notes and More Watch this video episode on YouTube   Want to learn the broad overview of The Great Simplification in 30 minutes? Watch our Animated Movie.   ---   Support The Institute for the Study of Energy and Our Future Join our Substack newsletter Join our Discord channel and connect with other listeners  

OpenAI's Sam Altman drops o3-Pro & sees “The Gentle Singularity”, Ilya Sutskever prepares for super intelligence & Mark Zuckerberg is spending MEGA bucks on AI talent. WHAT GIVES? All of the major AI companies are not only preparing for AGI but for true “super intelligence” which is on the way, at least according to *them*. What does that mean for us? And how do we exactly prepare for it? Also, Apple's WWDC is a big AI letdown, Eleven Labs' new V3 model is AMAZING, Midjourney got sued and, oh yeah, those weird 1X Robotics androids are back and running through grassy fields. WHAT WILL HAPPEN WHEN AI IS SMARTER THAN US? ACTUALLY, IT PROB ALREADY IS. #ai #ainews #openai Join the discord: https://discord.gg/muD2TYgC8f Join our Patreon: https://www.patreon.com/AIForHumansShow AI For Humans Newsletter: https://aiforhumans.beehiiv.com/ Follow us for more on X @AIForHumansShow Join our TikTok @aiforhumansshow To book us for speaking, please visit our website: https://www.aiforhumans.show/   // Show Links /?   Ilya Sutsketver's Commencement Speech About AI https://youtu.be/zuZ2zaotrJs?si=U_vHVpFEyTRMWSNa Apple's Cringe Genmoji Video https://x.com/altryne/status/1932127782232076560 OpenAI's Sam Altman On Superintelligence “The Gentle Singularity” https://blog.samaltman.com/the-gentle-singularity The Secret Mathematicians Meeting Where The Tried To Outsmart AI https://www.scientificamerican.com/article/inside-the-secret-meeting-where-mathematicians-struggled-to-outsmart-ai/ O3-Pro Released  https://x.com/sama/status/1932532561080975797 The most expensive o3-Pro Hello https://x.com/Yuchenj_UW/status/1932544842405720540 Eleven Labs v3  https://x.com/elevenlabsio/status/1930689774278570003 o3 regular drops in price by 80% - cheaper than GPT-4o  https://x.com/edwinarbus/status/1932534578469654552 Open weights model taking a ‘little bit more time' https://x.com/sama/status/1932573231199707168 Meta Buys 49% of Scale AI + Alexandr Wang Comes In-House https://www.nytimes.com/2025/06/10/technology/meta-new-ai-lab-superintelligence.html Apple Underwhelms at WWDC Re AI https://www.cnbc.com/2025/06/09/apple-wwdc-underwhelms-on-ai-software-biggest-facelift-in-decade-.html BusinessWeek's Mark Gurman on WWDC https://x.com/markgurman/status/1932145561919991843 Joanna Stern Grills Apple https://youtu.be/NTLk53h7u_k?si=AvnxM9wefXl2Nyjn Midjourney Sued by Disney & Comcast https://www.reuters.com/business/media-telecom/disney-universal-sue-image-creator-midjourney-copyright-infringement-2025-06-11/ 1x Robotic's Redwood https://x.com/1x_tech/status/1932474830840082498 https://www.1x.tech/discover/redwood-ai Redwood Mobility Video https://youtu.be/Dp6sqx9BGZs?si=UC09VxSx-PK77q-- Amazon Testing Humanoid Robots To Deliver Packages https://www.theinformation.com/articles/amazon-prepares-test-humanoid-robots-delivering-packages?rc=c3oojq&shared=736391f5cd5d0123 Autonomous Drone Beats Pilots For the First Time https://x.com/AISafetyMemes/status/1932465150151270644 Random GPT-4o Image Gen Pic https://www.reddit.com/r/ChatGPT/comments/1l7nnnz/what_do_you_get/?share_id=yWRAFxq3IMm9qBYxf-ZqR&utm_content=4&utm_medium=ios_app&utm_name=ioscss&utm_source=share&utm_term=1 https://x.com/AIForHumansShow/status/1932441561843093513 Jon Finger's Shoes to Cars With Luma's Modify Video https://x.com/mrjonfinger/status/1932529584442069392

May 29, 2025 – What happens when AI systems start inventing new materials, running billion-dollar companies, and making decisions in government? In this insightful conversation, Cris Sheridan interviews Dr. Alan D. Thompson, renowned AI...

Send us your thoughtsIn this episode of CFO 4.0, host Hannah Munro speaks with David Wood, Chair of London Futurists, about the accelerating pace of AI and its profound implications for business, society, and the future of work. Together, they explore the near-term possibilities and longer-term consequences of artificial intelligence—from transformation to potential turmoil.In this episode, we cover:Why some companies struggle with AI adoption The rise of neuro-symbolic AI and the combination of logic-based and intuitive systemsBreakthroughs in video generation, self-prompting AI, and the future of AI-generated mediaWhat Artificial General Intelligence (AGI) could mean for jobs, skills, and human relevanceHow emotional intelligence and adaptability will be essential skills for leaders in the AI eraLinks mentioned:David's Linkedin Learn more about London FuturistsLondon Futurists Meetups The Coming Wave: AI, Power and Our Future by  Mustafa SuleymanSupremacy: AI, ChatGPT and the race that changed the world by Parmy Olson Uncontrollable : The Threat of Artificial Superintelligence by Darren McKee Explore other CFO 4.0 Podcast episodes here. Subscribe to our Podcast!

Welcome to the Alfalfa Podcast

Listen in as your host Fred Williams and co-host Doug McBurney welcome RSR's resident A.I. expert Daniel Hedrick, of godisnowhere fame for an update on where we are with Artificial Intelligence, (and where A.I. is with us)!   *Welcome:  Daniel Hedrick, discussing Co-Pilot, LM Studio, Deepseek, Perplexity, Chat GPT, Grok 3, Midjourney, Agentic AI, AGI, ASI, and all things Artificial Intelligence.   *The Gospel & Dan Bongino:  Hear how Dan Bongino fundamentally agrees with Doug McBurney that A.I. has the potential, if programmed in an unbiased manner, and with access to everything ever written, to be a tool for telling the truth, including confirming the Gospel!   *Luddites of the World: Relax! AI is not on the verge of replacing programmers and coders. But it has become an essential tool.   *Motivation, Awareness & Experience: AI lacks all 3, but humans don't, so even Artificial Super Intelligence will always need us.   *Maximum Problems: How do we constrain AI from going off the rails? like in the paperclip maximizer problem. The answer lies in our connection to God's reality.   *The Energy Question: While The human brain uses at most 30 Watts to make over 100 trillion connections, no one's even sure what modern AI platforms are consuming... But it's a lot and growing!

Listen in as your host Fred Williams and co-host Doug McBurney welcome RSR's resident A.I. expert Daniel Hedrick, of godisnowhere fame for an update on where we are with Artificial Intelligence, (and where A.I. is with us)!   *Welcome:  Daniel Hedrick, discussing Co-Pilot, LM Studio, Deepseek, Perplexity, Chat GPT, Grok 3, Midjourney, Agentic AI, AGI, ASI, and all things Artificial Intelligence.   *The Gospel & Dan Bongino:  Hear how Dan Bongino fundamentally agrees with Doug McBurney that A.I. has the potential, if programmed in an unbiased manner, and with access to everything ever written, to be a tool for telling the truth, including confirming the Gospel!   *Luddites of the World: Relax! AI is not on the verge of replacing programmers and coders. But it has become an essential tool.   *Motivation, Awareness & Experience: AI lacks all 3, but humans don't, so even Artificial Super Intelligence will always need us.   *Maximum Problems: How do we constrain AI from going off the rails? like in the paperclip maximizer problem. The answer lies in our connection to God's reality.   *The Energy Question: While The human brain uses at most 30 Watts to make over 100 trillion connections, no one's even sure what modern AI platforms are consuming... But it's a lot and growing!

Unfiltered chat Blockchain DXB & Society X - LinkedIn Live: Weekly Crypto, Blockchain & AI Review Date & Time: January 23rd, 2025, 11:00 AM GST Hosts: RA George (Blockchain DXB) Markose Chentittha (Oort Foundation + Society X) Guest: Neil Fitzhugh, Head of Marketing at Trac Systems/TAP Protocol Contact details LinkedIn https://short-link.me/OkAJ Website: https://trac.network/ Twitter: Neil: https://x.com/fitzyOG Twitter/ X https://x.com/trac_btc?mx=2 Discord: https://discord.com/invite/trac Telegram: TAP Protocol - https://t.me/tap_protocol GitHub: https://github.com/BennyTheDev Note: This entire episode was created, scripted, and reviewed 100% by AI using Notebook LM by Google, showcasing the power of AI-driven content creation. This week's LinkedIn Live session explored groundbreaking developments in crypto, blockchain, and AI. Below is a streamlined recap of the AI-generated discussion between the hosts and guest Neil Fitzhugh. Discussion on its market significance and the broader implications for investors. Mention of Trump Meme Coin, which surged to a $13B market cap before dropping to $7.3B, underlining meme coin volatility. Neil Fitzhugh explained how the TAP Protocol is transforming Bitcoin's ecosystem with features like smart contracts, AMMs, swaps, and cross-chain bridges. Key Features: Tokenomics and Validator Licenses: Security Audits: Rigorous measures ensure platform reliability. Stargate Investment: A $500B initiative led by industry giants to develop Artificial Super Intelligence infrastructure. Dubai's AI Seal: A certification system to regulate trusted AI companies working with UAE authorities. Analysis of the U.S. District Court's decision and its impact on privacy protocols and Alexey Pertsev's ongoing legal challenges. 2025 is poised to be the "Year of Tokenization," potentially achieving $500B in market value, with real-world asset tokenization leading the charge. Republican-led initiatives in Texas, Pennsylvania, Ohio, and Wyoming highlight growing interest in state-level Bitcoin reserves. CLS Global's admission to wash trading and its repercussions. Solana's rise in transaction volume, signaling stablecoin growth. Ross Ulbricht's Campaign: Renewed focus on decentralization and privacy. FOMC Meeting Predictions: Interest rate changes and their crypto impact. Larry Fink's $700K Bitcoin Prediction: Bitcoin as a hedge against inflation. Neil addressed questions on: Aligning Bitcoin maximalist ideals with TAP Protocol's innovations. Trac Systems' upcoming milestones. Beginner-Level Sessions: Now live on LinkedIn. Spartan Race Discount: Use code George20 for the January 25–26 event. This episode demonstrated the capabilities of AI in analyzing and presenting complex topics. Using Notebook LM by Google, Blockchain DXB and Society X delivered an engaging, AI-driven conversation covering the latest in crypto, blockchain, and AI. To support this channel: https://www.patreon.com/BlockchainDXB ⚡ Buy me Coffee ☕ ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.buymeacoffee.com/info36/w/6987⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⚡ Advanced Media ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠https://www.amt.tv/⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⚡⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Spartan Race Trifecta⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ in Dubai https://race.spartan.com/en/race/detail/8646/overview For 20% Discount use code: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠George20⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ ⚡ The Race Space Podcast

OpenAI is prepping for Artificial Super Intelligence, Sam Altman says AI fast takeoff is likely, Luma Labs' new Ray 2 AI video model looks good and Reddit goes all GPT on us. Plus, an amazing new small AI model from NVIDIA, executive AI orders for more power and chips, ChatGPT Tasks kind of blows and a whole lotta Shrek (more so than you might want). BRB, WE GOTTA PREP FOR THE SINGULARITY Y'ALL! Join the discord: https://discord.gg/muD2TYgC8f Join our Patreon: https://www.patreon.com/AIForHumansShow AI For Humans Newsletter: https://aiforhumans.beehiiv.com/ Follow us for more on X @AIForHumansShow Join our TikTok @aiforhumansshow To book us for speaking, please visit our website: https://www.aiforhumans.show/   // SHOW LINKS // OpenAI's Economic Blueprint  https://openai.com/global-affairs/openais-economic-blueprint/ Sam Altman Says Fast Take Off More Likely https://x.com/tsarnick/status/1879100390840697191 OpenSource $450 Dollar o1 Model https://x.com/LiorOnAI/status/1878876546066506157 MiniMax-01 Launch: Lightning Attention https://x.com/i/trending/1879318547861582090 Runway Prompt-To-Character https://x.com/IXITimmyIXI/status/1878088929330491844 Executive Order For Gigawatt Datacenters https://www.reuters.com/technology/artificial-intelligence/biden-issue-executive-order-ensure-power-ai-data-centers-2025-01-14/ New AI Chip Rules  https://www.theinformation.com/articles/why-bidens-final-ai-chip-move-caused-an-uproar?rc=c3oojq&shared=160dd16ac575f520 ChatGPT Tasks https://x.com/OpenAI/status/1879267276291203329 Custom Reddit GPT For Answers https://www.reddit.com/answers/ LumaLabs Ray 2:  https://lumalabs.ai/ray Nvidia Lauches Sana  https://nvlabs.github.io/Sana/ AI Slop Distorting Wildfire News https://www.fastcompany.com/91260442/ai-slop-has-is-still-distorting-news-about-the-l-a-wildfires French Woman Scammed By AI Brad Pitt https://www.nbcnews.com/news/world/ai-brad-pitt-woman-romance-scam-france-tf1-rcna187745 Fashn Web App: Try-on + Video https://x.com/ayaboch/status/1878888737603830081 New AI or Die https://youtu.be/cAjUy896SOE?si=BpJhqV_oOwvov01q My Swamp https://x.com/andr3_ai/status/1878110156887638380  

A production center makes everything locally. It even has grow towers where the produce needs of nearby citizens can be met. After the World Storm, a production center goes into sentry mode when the Internet breaks. The entire insides of the production center become a death trap as all the robots will attack people who try to get in.Merch, a world class hacker, is abducted by a gang who make him try to hack the production center so they can get in and get enough food, water, and goods to have all they need for years.In the course of the story Merch finds an ASI, an Artificial Super Intelligence. This machine is hundreds of times smarter than a human. If he gains access, he could change the course of humanity. As an example, with the ASI in control of the production center, it could build a robot army."Medusa Net" (peer-to-peer internet system)Links/AR glasses with features like: Night vision, "Target Conversation" (allows distant conversation between people who can see each other), "Assist" (AI assistant), Multiple AR feeds/displays.Lutin Two Bot (subscription-locked)Tri-legged bot with lamp (described as spider-like)Double high botRobot with tiny arms for microscale workHologram shell robots (with curved screens for human-like appearance)Autono-cart (autonomous cart)"Follow cart" (presumably autonomous)"G. silk" (advanced fabric that: Never wrinkles, Never stains under normal conditions, Can filter water, Lets through only water and air.Cooling tents (double-walled with air inflation)Temperature-controlled shoes (powered to cool soles)Production center with automated security/defense systemsEngineered microbe medicine (tooth care chewables)"Rig gloves" (for controlling micro-scale robots)I'll extract the technology mentioned in this dystopian/post-apocalyptic story:3D navigation maps in field of viewNight vision capabilitiesJob's Navigator AIDates Navigator AIAI-based hacking systemsSimulation software for mimicking online consumersHome sentry botSex botSolar panel cleaning robotSwarm drone controllerAutono-cab (autonomous taxi)VR worldsFirst-person VR moviesLive Movie CreatorGiantess Center networkGeo-thermal power plantAutomated grow rooms/farming systemsDelivery tubesCard table computersDNA simulatorsRight-to-repair softwareSkills for Lutins (some kind of digital skill system)Automated vending machines (pizza and pasta)Digital door locksPest trap softwarePublic talk lineGroup talkI'll compile a list of the technology mentioned in this post-apocalyptic story:E-paper/E-paper screensMastodon (social network)Security cards with changing QR codesBio-sampler pensThrive Navigator (upgraded survival-focused AI)Metis/Matis (ASI - Artificial Super Intelligence)AI hackers (subordinate AIs used for hacking)AI jury systems (to keep ASI in check)Giantess guard botsBuilder botsConstruction botsMaintenance botsBattle droidsCleaning bots"Half-high bots" (climbing capable)Sentry mode botsGiantess Production towers/centerProduction equipmentAutomated facilitiesSurvival bunkersUnderground utility tunnelsChemical weaponsSound assault weaponsMicrowave weaponsBattle droidsSmell scanner/smell visionEmbedded technology ("embeds")Many of the characters in this project appear in future episodes. Using storytelling to place you in a time period, this series takes you, year by year, into the future. From 2040 to 2195. If you like emerging tech, eco-tech, futurism, perma-culture, apocalyptic survival scenarios, and disruptive science, sit back and enjoy short stories that showcase my research into how the future may play out. This is Episode 1 of the podcast "In 20xx Scifi and Futurism." The companion site is https://in20xx.com These are works of fiction. Characters and groups are made-up and influenced by current events but not reporting facts about people or groups in the real world.Copyright © Cy Porter 2024. All rights reserved.

Send Everyday AI and Jordan a text messageIt's the trillion dollar AI question. When will we achieve Artificial General Intelligence? (And what the heck is it, anyway?) We'll give you the 101 on what you need to know, and one secret that could be holding the official discovery back.Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on AGIUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:1. Definition of AI, AGI and ASI2. Evolution of AGI3. Impacts of Advancements in AGI4. Future of AGITimestamps:02:00 When is AGI coming?09:54 Machines performing tasks requiring human intelligence.13:10 Generative AI brings impressive outputs through language.14:04 Generative AI democratizes US AI capabilities; narrow compared.19:00 Correct prompting with PPP course at podpp.com.20:52 Big tech companies openly working toward AGI now.25:37 AGI development inevitable, desirable, surpassing human capabilities.28:16 Pre-2020, experts said AGI was 80 years away.31:25 Criticism of experts in generative AI misunderstandings.33:49 Has AI's definition of AGI changed?37:21 Definition of AGI has evolved over time.40:45 Partnership between Microsoft and OpenAI pivotal.45:21 OpenAI benefits from important Microsoft partnership changes.47:08 Tech companies must focus on AGI development.Keywords:AGI, Artificial General Intelligence, OpenAI, Microsoft, partnership, AI development, AI startup, Anthropic, copyright infringement, Google's Gemini team, Token offering, AI models, USAID, ChatGPT Enterprise, AI pace estimation, AI evolution, Artificial Superintelligence, AI prediction chart, ARK Invest, GPT 3 technology, Traditional AI, Generative AI, AI democratization, AGI benchmark, ChatGPT course, AI startups, Big tech companies, AGI cost reduction, Future of work, Everyday AI podcast. Get more out of ChatGPT by learning our PPP method in this live, interactive and free training! Sign up now: https://youreverydayai.com/ppp-registration/

Today, we're joined by Tim Rocktäschel, senior staff research scientist at Google DeepMind, professor of Artificial Intelligence at University College London, and author of the recently published popular science book, “Artificial Intelligence: 10 Things You Should Know.” We dig into the attainability of artificial superintelligence and the path to achieving generalized superhuman capabilities across multiple domains. We discuss the importance of open-endedness in developing autonomous and self-improving systems, as well as the role of evolutionary approaches and algorithms. Additionally, we cover Tim's recent research projects such as “Promptbreeder,” “Debating with More Persuasive LLMs Leads to More Truthful Answers,” and more. The complete show notes for this episode can be found at https://twimlai.com/go/706.

Lexi Bass has a BA in Arts Administration from the University of Kentucky,  a MA in Art from the University of Louisville and an MFA in Experimental and Documentary Arts from Duke University. ​She is currently a lecturer in Animation and Digital Art at the University of Kentucky School of Arts and Visual Studies and an experimental filmmaker and artist.  Her films have screened widely in London, Amsterdam, and other European cities and Los Angeles, Philadelphia, Minneapolis, and various locations across KY.  Her new film Meander will air on Tuesday 15 Oct at the Lyric Theatre and Cultural Arts Center at 6:30pm. Meander (2024) Lexi BassAs artificial intelligence replaces workers in our increasingly elderly global population, companies engineering AI race robots amidst human inequities and emerging problems of AI sentience. The sum spells disaster for the human race in the dystopian world of Meander, which evokes both ancient Greek mythology and near-future science fiction. Meander finds herself destitute in the Underworld with no way to finance escape other than offering her biological potential for surrogate pregnancy up to dubious experimentation in an underground facility. Meanwhile, filmmaker/narrator, Lexi Bass, recounts her experiences of pregnancy and motherhood at the precipice of age 40 and the loss of her own mother shortly after, questioning the future of humanity at the precipice of Artificial General Intelligence and Artificial Super-Intelligence. For more and to connect with us, visit https://www.artsconnectlex.org/art-throb-podcast.html

Safe underground, a colony of 9000 are cared for by robots and automated services. But people are agitated. Youth run wild. How will the citizens adjust to free necessities but little else? Questions of post work, UBI, and life purpose arise.Artificial Super Intelligence may save them. A combination of capitalism and needs met for all may save them.T-Line: An underground train systemRobots: Various types for construction, cleaning, and other tasksArtificial Intelligence (AI): Used for various purposesAugmented Reality (AR) glassesVirtual Reality (VR) systemsLutin Bots: Advanced robotic assistants (Lutin One and Lutin Two models)Robot baby (Taylor): Used for data collection on parentingHooded tunics with cooling and air filtering systemsGyro clogs: Some type of self-balancing footwearInduction stovesGeothermal power plantAquaponic systemsCentral cooling systemsLocal internetArtificial Superintelligence (ASI) systemGene therapy for addiction treatmentBuilder AI: For planning and constructing flood tunnelsBone-mounted AR glassesAll-sensor night vision technologyPhage cream: Possibly for protection against pathogensOnline education services and AI teachersVR classrooms and schoolsDigital currency systemsAdvanced medical technology (e.g., growing new skin)VR windows for wall mountingMany of the characters in this project appear in future episodes.   Using storytelling to place you in a time period, this series takes you, year by year, into the future. From 2040 to 2195. If you like emerging tech, eco-tech, futurism, perma-culture, apocalyptic survival scenarios, and disruptive science, sit back and enjoy short stories that showcase my research into how the future may play out.   This is Episode 59 of the podcast "In 20xx Scifi and Futurism." The companion site is https://in20xx.com where you can find a timeline of the future, descriptions of future development, and printed fiction.These are works of fiction. Characters and groups are made-up and influenced by current events but not reporting facts about people or groups in the real world.Copyright © Leon Horn 2024. All rights reserved.

This week, we are back with part two of Generative Quarterly with Semil Shah and Lightspeed Partner and host Michael Mignano. Semil is a founding General Partner of Haystack and a Venture Partner at Lightspeed. Semil and Mike pick up their conversation on consumer AI technology, starting with innovative consumer tech like Friend AI by Avi Schiffmann. Mike and Semil consider the impact of Artificial Super Intelligence on the future of work, debate the future evolution of software on demand, and ask if we need AI agents to help us solve our boredom?  Episode Chapters (00:00) Introduction (00:31) Consumer AI Tech (03:05) Autonomous AI Agents Versus Copilots  (04:19) Matt Levine: Robots Make Good AI Junior Analysts  (05:53) Future of Training Entry Level Consultants (07:55) Artificial Super Intelligence as a Drop in Coworker (09:38) Will We Have Our Own Agentic Consultants? (11:50) Software On Demand (16:32) AI Generated Music and Content  (20:31) Conclusion  Stay in touch: www.lsvp.com X: https://twitter.com/lightspeedvp LinkedIn: https://www.linkedin.com/company/lightspeed-venture-partners/ Instagram: https://www.instagram.com/lightspeedventurepartners/ Subscribe on your favorite podcast app: generativenow.co Email: generativenow@lsvp.com The content here does not constitute tax, legal, business or investment advice or an offer to provide such advice, should not be construed as advocating the purchase or sale of any security or investment or a recommendation of any company, and is not an offer, or solicitation of an offer, for the purchase or sale of any security or investment product. For more details please see lsvp.com/legal.

Send Everyday AI and Jordan a text messageAre we really 'a few thousand' days from Superintelligence? Also, what the heck does Superintelligence even mean? We're breaking down the latest hot takes from Sam Altman and simplifying superintelligence. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on AIUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:1. Definition and Discussion of AI Levels2. Defining superintelligence and its implications3. Major Historical Transitions and Their Relevance to AI4. Review and Analysis of Sam Altman's Perspective5. Sam Altman's Influence on AITimestamps:00:00 Are we thousands of days from superintelligence?04:12 AI advancements amplify human capabilities and innovation.09:06 Superintelligence theoretical; AGI practical; Altman's rising influence.10:02 Sam Altman became globally significant in AI.15:40 Share your predictions about utopian or dystopian futures.19:55 Generative AI creates multimodal outputs from inputs.22:06 AI systems excel in narrow, specific tasks.25:45 I'd choose large language models for problem solving.29:00 WorkLab podcast: insights for evolving work leaders.32:03 AI likened to internet's skeptical early reception.34:10 Is AI progress genuine or just marketing?38:08 Advancing AI redefines AGI achievement; ASI unclear.40:57 Superintelligence may be achieved within our lifetime.Keywords:Jordan Wilson, advancements in AI, superintelligence, safe superintelligence, everyday AI, everydayai.com, generative AI, chat GPT, Artificial Narrow Intelligence, ANI, Artificial General Intelligence, AGI, Artificial Superintelligence, ASI, WorkLab Podcast, Microsoft, historical periods, technological transitions, Sam Altman, Intelligence Age, AI in business, OpenAI, skepticism about AI, AI definitions, timeline for superintelligence, utopian superintelligence, dystopian superintelligence, audience interaction, superintelligence debate, AI integration

Send Everyday AI and Jordan a text messageWin a free year of ChatGPT or other prizes! Find out how.It's the trillion dollar AI question. When will we achieve Artificial General Intelligence? (And what the heck is it, anyway?) We'll give you the 101 on what you need to know, and one secret that could be holding the official discovery back. Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on AGIUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:1. Definition of AI, AGI and ASI2. Evolution of AGI3. Impacts of Advancements in AGI4. Future of AGITimestamps:02:00 Daily AI news06:15 When is AGI coming?09:54 Machines performing tasks requiring human intelligence.13:10 Generative AI brings impressive outputs through language.14:04 Generative AI democratizes US AI capabilities; narrow compared.19:00 Correct prompting with PPP course at podpp.com.20:52 Big tech companies openly working toward AGI now.25:37 AGI development inevitable, desirable, surpassing human capabilities.28:16 Pre-2020, experts said AGI was 80 years away.31:25 Criticism of experts in generative AI misunderstandings.33:49 Has AI's definition of AGI changed?37:21 Definition of AGI has evolved over time.40:45 Partnership between Microsoft and OpenAI pivotal.45:21 OpenAI benefits from important Microsoft partnership changes.47:08 Tech companies must focus on AGI development.52:37 Future work, business, career with AI impact.Keywords:AGI, Artificial General Intelligence, OpenAI, Microsoft, partnership, AI development, AI startup, Anthropic, copyright infringement, Google's Gemini team, Token offering, AI models, USAID, ChatGPT Enterprise, AI pace estimation, AI evolution, Artificial Superintelligence, AI prediction chart, ARK Invest, GPT 3 technology, Traditional AI, Generative AI, AI democratization, AGI benchmark, ChatGPT course, AI startups, Big tech companies, AGI cost reduction, Future of work, Everyday AI podcast. Get more out of ChatGPT by learning our PPP method in this live, interactive and free training! Sign up now: https://youreverydayai.com/ppp-registration/

Why should we consider slowing AI development? Could we slow down AI development even if we wanted to? What is a "minimum viable x-risk"? What are some of the more plausible, less Hollywood-esque risks from AI? Even if an AI could destroy us all, why would it want to do so? What are some analogous cases where we slowed the development of a specific technology? And how did they turn out? What are some reasonable, feasible regulations that could be implemented to slow AI development? If an AI becomes smarter than humans, wouldn't it also be wiser than humans and therefore more likely to know what we need and want and less likely to destroy us? Is it easier to control a more intelligent AI or a less intelligent one? Why do we struggle so much to define utopia? What can the average person do to encourage safe and ethical development of AI?Kat Woods is a serial charity entrepreneur who's founded four effective altruist charities. She runs Nonlinear, an AI safety charity. Prior to starting Nonlinear, she co-founded Charity Entrepreneurship, a charity incubator that has launched dozens of charities in global poverty and animal rights. Prior to that, she co-founded Charity Science Health, which helped vaccinate 200,000+ children in India, and, according to GiveWell's estimates at the time, was similarly cost-effective to AMF. You can follow her on Twitter at @kat__woods; you can read her EA writing here and here; and you can read her personal blog here.Further reading:Robert Miles AI Safety @ YouTube"The AI Revolution: The Road to Superintelligence", by Tim UrbanUncontrollable: The Threat of Artificial Superintelligence and the Race to Save the World, by Darren McKeeThe Nonlinear NetworkPauseAIDan Hendrycks @ Manifund (AI regrantor)Adam Gleave @ Manifund (AI regrantor)StaffSpencer Greenberg — Host / DirectorJosh Castle — ProducerRyan Kessler — Audio EngineerUri Bram — FactotumMusicBroke for FreeJosh WoodwardLee RosevereQuiet Music for Tiny Robotswowamusiczapsplat.comAffiliatesClearer ThinkingGuidedTrackMind EasePositlyUpLift[Read more]

Send Everyday AI and Jordan a text messageEnter to win a FREE Custom Avatar from Hour One as part of their #HourOneChallenge - Go find out more hereFor the first time ever....(As far as our research shows) This will be the first time an AI clone interviews its human counterpart live. Is my AI clone smarter than me? Will I crumble under the pressure? Newsletter: Sign up for our free daily newsletterMore on this Episode: Episode PageJoin the discussion: Ask Jordan questions on AIRelated Episodes: Ep 258: Will AI Take Our Jobs? Our answer might surprise you.Ep 200: 200 Facts, Stats, and Hot Takes About GenAI – Celebrating 200 EpisodesUpcoming Episodes: Check out the upcoming Everyday AI Livestream lineupWebsite: YourEverydayAI.comEmail The Show: info@youreverydayai.comConnect with Jordan on LinkedInTopics Covered in This Episode:1. Potential Impact of AI on Careers2. Leaders in AI Technology3. Discussion on Global AI Innovation4. Privacy and Security Concerns with AI5. Creative Potential of AI6. AI Integration into SocietyTimestamps:02:25 Daily AI news07:55 OpenAI excels as business system, surpasses others.12:15 Train AI, use tools, future of creativity.16:00 Traditional web search outdated, replaced by alternatives.16:40 Internet use becoming unbearable, predicts shift to AI.21:49 Altman and Huang predict AGI within 5 years.25:14 NVIDIA's rise to most valuable company predicted.28:30 AI will automate and oversee business decisions.32:27 Hour One offers AI avatar video technology.36:18 Personal data privacy and security concerns with AI.38:57 Companies need humans to weed out bias.43:00 Flying cars may flop at first, but future potential.44:35 AI technology may replace human work graduallyKeywords:Jordan Wilson, AI technology, career disruption, Artificial General Intelligence, Artificial Superintelligence, NVIDIA, Amazon, AI digital avatar, generative AI, McDonald's, IBM, AI drive-through technology, Google DeepMind, v2a model, Runway Gen 3 Alpha, AI video creator, OpenAI, ChatGPT4O, AI integration into workforce, future of work, AI as co-workers or bosses, US AI innovation, China AI competition, Hour 1 communication technology, AI companionship industry, data privacy, AI bias and stereotypes, self-replicating AI, humanoid robots, AI in day-to-day life.

Humayun Sheikh is the CEO & Founder of Fetch AI and the chairman of the Artificial Superintelligence Alliance. We discuss:Fetch AI and its missionThe merging of Fetch AI, Singularitynet & Ocean Protocol to form the Artificial Superintelligence AllianceHow the new ASI token will workThe combination of AI and BlockchainAI's impact on societyCrypto market outlook

Bitcoin is up .5% at $70,288 Eth is up .5% at $3,588 Binance Coin, up slightly at $579 Those are your leaders by market cap. Top gainers in the last 24 hours.  Mantle, up 40% Coinbase to store more USDC on BASE Fetch.ai, SingularityNET, and Ocean Protocol propose merger to create "Artificial Superintelligence Alliance" HSBC introduces tokenized gold in Hong Kong KuCoin sees big outflows in response to DOJ action. 0G labs raises $35M Learn more about your ad choices. Visit megaphone.fm/adchoices

Yale Anthropologist Lisa Messeri spent a year doing field work in Los Angeles in 2018 studying the political ecology of the VR community, and will be releasing her landmark book called In the Land of the Unreal: Virtual and Other Realities in Los Angeles on Friday, March 8th. It's the best book about the culture of VR that I've read so far as it is pulling in many insights from Science and Technology Studies (STS), anthropology, social sciences, sci fi, pop culture, and philosophy. Making claims about reality is daunting for any working scholar in the 21st Century, and Messeri uses the feeling of "unreality" as a analytical tool to analyze not only virtual reality, but also the fracturing nature of our political context, but also the unreality of Los Angeles as the factory of dreams and façade-like architecture that blurs the boundary for what's deeply real vs what's surface scaffolding enough to transport you into another reality. Messeri uses the framing of fantasy to interrogate a number of claims being made by the VR community circa 2018. Fantasy by her definition could include both positive aspirational dreams, but they could also turn out to be deluded illusions. I personally prefer the using the phrase of potential since it is a bit more neutral for me, and includes both the promising positive potentials as well as the more perilous negative potentials. But she splits her book into three parts the Fantasy of Location exploring the unreality of Los Angeles as well as how VR transports you into another world per Mel Slaters place illusion. The second part is the Fantasy of Being deconstructs the VR as the ultimate empathy machine per Chris Milk's infamous 2015 TED Talk. Then the third part explores the Fantasy of Representation with the aspirations of the LA VR community to create a more diverse and equitable ecosystem that transcends the bias and power dynamics of Silicon Valley. In each one of these three sections, Messeri uses case studies and follows specific individuals over time to see whether or not some of these aspirations and potentials end up becoming grounded into physical reality, or whether they end up collapsing into a more deluded illusion. I was inspired to dig into my backlog of 800+ unpublished Voices of VR podcast episodes to publish some interviews that I conducted between 2017-2019 featuring some of the main characters and protagonists featured in Messeri's book: Marci Jastrow is featured in Chapter 3 letting Messeri become a scholar-in-residence at Technicolor Experience Center Carrie Shaw of Embodied Labs is featured in Chapter 5, and radically opens up her business to Messeri to study Jackie Morie is featured in Chapter 6 as Messeri deconstructs some of the gender essentialist claims that VR is a medium that's a natural fit for women. And Joanna Popper is featured in Chapter 7 as Messeri breaks down the unique pathways into emerging technology that she was noting as an interesting trend from an anthropological perspective. I had a chance to read through an advanced copy of In the Land of the Unreal: Virtual and Other Realities in Los Angeles, and it's already started to make a huge impact on the way that I think about the many dimensions of unreality in our present day realities ranging from the surreal experiences of VR presence to the fractured reality bubbles of our political discourse to the ways in which techno-utopian solutionism can impact the philosophies that are driving how technologies like AI are developed aspiring towards speculations of Artificial General Intelligence or Artificial Superintelligence. I even started applying Messeri's unreality analytic to make sense of some of what Alvin Wang Graylin was saying in our discussion about Our Next Reality. I said, "I found myself is this kind of unreality of a potential imaginal future of this post-scarcity, post-labor context where all of our problems have been solved,

The book Our Next Reality: How the AI-powered Metaverse Will Reshape the World is structured as a debate between Alvin Wang Graylin and Louis Rosenberg, who each have over 30 years of experience in XR and AI. Graylin embodies the eternal optimist and leans towards techno-utopian views while Rosenberg voices the more skeptical perspectives while leaning more towards cautious optimism and acknowledging the privacy hazards, control and alignment risks, as well as the ethical and moral dilemmas. The book is the strongest when it speaks about the near-term implications of how AI will impact XR in specific contexts, but starts to go off the rails for me when they start exploring the more distant-future implications of Artificial Superintelligence at the economic and political scales of society. At the same time, both sides acknowledge the positive and negative potential futures, and that neither path are necessarily guaranteed as it will be up to the tech companies, governments, and broader society which path of the future we go down. What I really appreciated about the book is that both Graylin and Rosenberg reference many personal examples and anecdotes around the intersection of XR and AI throughout each of their three decades of experience working with emerging technologies. Even though the book is structured as a debate, they also both agree on some fundamental premises that the Metaverse is inevitable (or rather spatial computing, XR, or mixed reality), and that AI has been and will continue to be a critical catalyst for it's growth and evolution. They both also wholeheartedly agree that it is a matter of time before we achieve either an Artificial General Intelligence (AGI) or Artificial Superintelligence (ASI), but they differ on the implications of these technologies. Graylin believes that ASI has the potential to lead humanity into post-labor, post-scarcity, techno-utopian future reality where all of humanity has willingly given up all cultural, political, and economic control over to our ASI overlords who become these perfectly rationally-driven philosopher kings, but yet still see humans as their ancestors via an uncharacteristically anthropomorphized emotional connection with compassionate affinity. Rosenberg dismisses this as a sort of wishful thinking that humans would be able to exert any control over ASI, and that ASI would be anything other than cold-hearted, calculating, ruthless, and unpredictably alien. Rosenberg also cautions that humanity could be headed towards cultural stagnation if the production of all art, media, music, and creative endeavors is ceded over to ASI, and that unaligned and self-directed ASI could be more dangerous than nuclear weapons. Graylin acknowledges the duality of possible futures within the context of this interview, but also tends to be biased towards the more optimistic future within the actual book. There is also a specific undercurrent of ideas and philosophies about AI that are woven throughout Graylin's and Rosenberg's book. Philosopher and historian Dr. Émile P. Torres has coined the acronym "TESCREAL" in collaboration with AI Ethicist Dr. Timnit Gebru that stands for Transhumanism, Extropianism, Singularitarianism, Cosmism, Rationalism, Effective Altruism and Longtermism. Torres wrote an article in Truthdig elaborating on these interconnected bundle of TESCREAL ideologies are the underpinnings of many of the debates about ASI and AGI (with links included in the original quote): At the heart of TESCREALism is a “techno-utopian” vision of the future. It anticipates a time when advanced technologies enable humanity to accomplish things like: producing radical abundance, reengineering ourselves, becoming immortal, colonizing the universe and creating a sprawling “post-human” civilization among the stars full of trillions and trillions of people. The most straightforward way to realize this utopia is by building superintelligent AGI.

Jim talks with Trent McConaghy about the ideas in his recent essay "bci/acc: A Pragmatic Path to Compete with Artificial Superintelligence." They discuss the meaning of BCI (brain-computer interfaces) and acc (accelerationism), categories of AI, how much room there is for above-human intelligence, whether AI is achieving parallelism, the risks of artificial superintelligence (ASI), problems with deceleration, AI intelligences balancing each other, decentralized approaches to AI, problems with the "pull the plug" idea, humans as the weak security link, the silicon Midas touch, competing with AI using BCIs, the need for super-high bandwidth, the noninvasive road to BCIs, realistic killer apps, eye tracking, pragmatic telepathy, subvocalization, reaching adoption-level quality, the arc between noninvasive and full silicon, near-infrared sensors, issues around mass adoption of implants, maintaining cognitive liberty, the risk of giving malevolent ASIs the keys to the kingdom, whether humans plus ASIs might compete with ASIs, and much more. Episode Transcript JRS EP13 - Blockchain, AI, and DAOs "bci/acc: A Pragmatic Path to Compete with Artificial Superintelligence," by Trent McConaghy Ocean Protocol "Nature 2.0: The Cradle of Civilization Gets an Upgrade," by Trent McConaghy Trent McConaghy on Twitter Trent McConaghy is founder of Ocean Protocol. He has 25 years of deep tech experience with a focus on AI and blockchain. He co-founded Analog Design automation Inc. in 1999, which built AI-powered tools for creative circuit design. It was acquired by Synopsys in 2004. He co-founded Solido Design Automation in 2004, using AI to mitigate process variation and help drive Moore's Law. Solido was later acquired by Siemens. He then went on to launch ascribe in 2013 for NFTs on Bitcoin, then Ocean Protocol in 2017 for decentralized data markets for AI. He currently focuses on Ocean Predictoor for crowd-sourced AI prediction feeds.

This week… OpenAI lays out safety measures for dealing with Artificial Super Intelligence, Google's Deepmind solved a previously impossible math problem & then we made Guy Fieri cartoons with Domo's AI animation software. These are all of equal importance!  Plus, Gavin dove into Digi.AI a new AI “companion” app, ChatGPT turned a Chevy dealership's chatbot into a hilarious nightmare & Google Labs has some incredibly cool new music tools you can play with right now. AND THEN… It's an A4H Interview with Twitch Steamer & Podcaster Gina Darling whom Kevin got to know well at G4. We talk about AI companionship, get AI to help her buy gifts for her boyfriends parents and introduce her to AI Gina Darling (surprise!) Oh and don't forget our AI co-host this week, we're actually visited by AI Santa Claus and his lil head elf Max. Santa tells us about how they're using AI to automate the North Pole but, unfortunately, he forgot to tell Max and the rest of the elves.  It's an endless cavalcade of ridiculous and informative AI news, AI tools, and AI entertainment cooked up just for you. Follow us for more AI discussions, AI news updates, and AI tool reviews on X @AIForHumansShow Join our vibrant community on TikTok @aiforhumansshow For more info, visit our website at https://www.aiforhumans.show/ /// Show links /// New Prepared-ness Team at OpenAI https://openai.com/safety/preparedness Google Deepmind Does New Math https://www.technologyreview.com/2023/12/14/1085318/google-deepmind-large-language-model-solve-unsolvable-math-problem-cap-set/ Finals Dev Talks AI https://www.gamedeveloper.com/audio/embark-studios-ai-let-devs-do-more-with-less-when-making-the-finals GPT-4.5? Nah https://twitter.com/AiBreakfast/status/1736392167906574634?s=20 https://x.com/rowancheung/status/1736616840510533830?s=20 Sentient Chevy Bot https://twitter.com/ChrisJBakke/status/1736533308849443121 https://www.autoevolution.com/news/chatgpt-powered-customer-support-at-chevrolet-dealership-hilariously-recommended-tesla-226253.html Google Labs Music FX https://aitestkitchen.withgoogle.com/tools/music-fx Domo AI Discord https://discord.com/invite/domoai Digi.AI AI Companion App https://digi.ai/ Gina Darling @GinaDarlingChannel https://www.twitch.tv/missginadarling The Spill It Podcast: https://www.youtube.com/@ShowBobas  

Filmmaker Jay Shapiro has produced a new series of audio documentaries, exploring the major topics that Sam has focused on over the course of his career. Each episode weaves together original analysis, critical perspective, and novel thought experiments with some of the most compelling exchanges from the Making Sense archive. Whether you are new to a particular topic, or think you have your mind made up about it, we think you'll find this series fascinating. In this episode, we explore the landscape of Artificial Intelligence. We'll listen in on Sam's conversation with decision theorist and artificial-intelligence researcher Eliezer Yudkowsky, as we consider the potential dangers of AI – including the control problem and the value-alignment problem – as well as the concepts of Artificial General Intelligence, Narrow Artificial Intelligence, and Artificial Super Intelligence. We'll then be introduced to philosopher Nick Bostrom's “Genies, Sovereigns, Oracles, and Tools,” as physicist Max Tegmark outlines just how careful we need to be as we travel down the AI path. Computer scientist Stuart Russell will then dig deeper into the value-alignment problem and explain its importance.   We'll hear from former Google CEO Eric Schmidt about the geopolitical realities of AI terrorism and weaponization. We'll then touch the topic of consciousness as Sam and psychologist Paul Bloom turn the conversation to the ethical and psychological complexities of living alongside humanlike AI. Psychologist Alison Gopnik then reframes the general concept of intelligence to help us wonder if the kinds of systems we're building using “Deep Learning” are really marching us towards our super-intelligent overlords.   Finally, physicist David Deutsch will argue that many value-alignment fears about AI are based on a fundamental misunderstanding about how knowledge actually grows in this universe.