Podcasts about Big Tech

Hugging Face CEO Clem Delangue joins to discuss OpenAI's rogue agent attack on the company and what it means for cybersecurity and the future of AI. Then, IMAX CEO Rich Gelfond discusses the success of "The Odyssey" after the company posted its highest grossing month on record in July. Plus, we break down how big tech stakes in private AI companies are distorting the S&P earnings picture. Squawk on the Street Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

After 200 years of idolatry, God finally allowed the northern kingdom of Israel to be destroyed and the people carried off by Assyria. Meanwhile, the southern kingdom of Judah was being ruled the young, foolish, idolatrous King Ahaz. After being defeated in battle by the Aramean Kingdom of Damascus, Ahaz decided to worship the gods of Syria rather than turning to God for help. He also sacrificed his son to Molech in the Valley of Hinnom southwest of Jerusalem. Then he turned to the Assyrians for help against Israel, Syria, and Edom, cutting up fixtures in the Temple to send to Assyria as tribute. Needless to say, God was not pleased. Apparently, neither were the people of Judah. Ahaz was buried in the City of David rather than in the tombs of the kings of his forefathers. Sharon's niece, Sarah Sachleben, has been battling stage 4 bowel cancer and the medical bills are piling up. If you are led to help, please go to GilbertHouse.org/hopeforsarah. Derek's new book War of the Watchers Book One: From Baal to Balfour is now available at Amazon in paperback and as a Kindle e-book! If you are looking for a text of the Book of 1 Enoch to follow our monthly study, you can try these sources: Parallel translations by R. H. Charles (1917) and Richard Laurence (1821)Modern English translation by George W. E. Nickelsburg and James VanderKam (link to book at Amazon)Book of 1 Enoch - Standard English Version by Dr. Jay Winter (link opens free PDF)Book of 1 Enoch - R. H. Charles translation (link opens free PDF) The SkyWatchTV store has a special offer on Dr. Michael Heiser's two-volume set A Companion to the Book of Enoch. Get both books, the R. H. Charles translation of 1 Enoch, and a DVD interview with Mike and Steven Bancarz for a donation of $35 plus shipping and handling. Link: https://bit.ly/heiser-enoch JOIN US IN ISRAEL (NOTE NEW DATES)! We will tour the Holy Land Oct. 25–Nov. 6, 2027 with an optional three-day extension to Jordan. For more information, log on to GilbertHouse.org/travel. Follow us!• X: @gilberthouse_tv | @sharonkgilbert | @derekgilbert• Substack: GilbertHouse.substacdk.com | SharonKGilbert.substack.com• Telegram: t.me/gilberthouse | t.me/sharonsroom | t.me/viewfromthebunker• YouTube: @GilbertHouse | @UnravelingRevelation | @thebiblesgreatestmysteries• Facebook.com/GilbertHouseFellowship Thank you for making our Build Barn Better project a reality! We truly appreciate your support. If you are so led, you can help out at GilbertHouse.org/donate. Get our free app! It connects you to these studies plus our weekly video programs Unraveling Revelation and A View from the Bunker, and the podcast that started this journey in 2005, P.I.D. Radio. Best of all, it bypasses the gatekeepers of Big Tech! The app is available for iOS, Android, Roku, and Apple TV. Links to the app stores are at www.gilberthouse.org/app/. Gilbert House T-shirts and mugs! New to our store is a line of GHTV and Redwing Saga merch! Check it out at GilbertHouse.org/store! Think better, feel better! Our partners at Simply Clean Foods offer freeze-dried, 100% GMO-free food and delicious, vacuum-packed fair trade coffee from Honduras. Find out more at GilbertHouse.org/store. Our favorite Bible study tools! Check the links in the left-hand column at www.GilbertHouse.org.

In this episode of The Canadian Macro Investor Podcast, Simon and Dan break down the latest Fed decision and why the bond market may be starting to challenge Kevin Warsh’s inflation message. They discuss the split reaction across the yield curve, with short-term yields moving differently than longer-term yields, and what that could mean for inflation, recession risk and future rate hikes. They also look at Canada’s population data problem and why undercounting temporary residents could distort unemployment, mortgage delinquency trends and the broader read on the Canadian economy. From there, they dig into big tech earnings, including Microsoft and Meta, and why investors are paying closer attention to AI capex, free cash flow, depreciation, and credit default swaps across the hyperscalers. They also discuss Anthropic, open-weight AI models, data privacy concerns, tariffs, copper demand, and what the AI infrastructure build-out could mean for energy and markets. Tickers discussed: MSFT, META, GOOG, GOOGL, AMZN, NVDA, ORCL, AAPL, SKM Watch the full video on Our New Youtube Channel! Check out our portfolio by going to Jointci.com Our Website Canadian Investor Podcast Network Twitter: @cdn_investing Simon’s twitter: @Fiat_Iceberg Braden’s twitter: @BradoCapital Dan’s Twitter: @stocktrades_ca Want to learn more about Real Estate Investing? Check out the Canadian Real Estate Investor Podcast! Apple Podcast - The Canadian Real Estate Investor Spotify - The Canadian Real Estate Investor Web player - The Canadian Real Estate Investor Asset Allocation ETFs | BMO Global Asset Management Sign up for Fiscal.ai for free to get easy access to global stock coverage and powerful AI investing tools. Register for EQ Bank, the seamless digital banking experience with better rates and no nonsense.See omnystudio.com/listener for privacy information.

Stocks ended the week on a high as strong Big Tech earnings outweighed rising bond yields and renewed inflation concerns. Meanwhile, one of the most talked-about AI hedge funds collapsed, highlighting the risks of excessive leverage even during powerful technology trends.>>> Follow me on LinkedIn:https://www.linkedin.com/in/endrit-cela/>>> Follow me on Instagram:https://www.instagram.com/endritcela_official/Disclaimer for "Capital Markets Quickie" Podcast:The views and opinions expressed on this podcast are based on information available at the time of recording and reflect the personal perspectives of the host. They do not represent the viewpoints of any other projects, cooperations, or affiliations the host may be involved in. "Capital Markets Quickie" does not offer financial advice. Before making any financial decisions, please conduct your own due diligence and consult with a financial advisor.

In this episode of Software People Stories, I speak with Saraswathi, a marketing leader with over 15 years of cross-industry experience,  about the role of marketing in technology—especially how product marketers translate technical ideas into stories customers can understand and care about. We talk about digital communication, customer empathy, product adoption, AI in marketing, useful metrics, and practical career advice for anyone curious about moving into marketing. It is a thoughtful conversation on bridging products, people, and business impact.Among the highlights from this conversation are:Marketing fundamentals stay consistent, but customer pain points differ across industries.Digital content must be concise, compelling, and quick to capture attention.Audience niches and personalization help messages resonate better.Product marketers act as the bridge between product, UX, sales, and customers.Training works best when broken into short, accessible, in-product learning moments.Email remains effective when segmented and relevant to the audience.AI helps with competitive research, brainstorming, mockups, and faster first drafts.Brand voice can be protected by giving AI clear style guides, examples, and do's and don'ts.Marketing impact should connect to opportunities, conversions, and revenue—not only vanity metrics.Support tickets offer unfiltered customer insight and can shape better messaging and product decisions.Career switchers can use transferable skills and start by getting closer to customers.Planning, yoga, short walks, and pausing before reacting help Saraswathi stay calm and grounded.Saraswathi Shanth Kumar (Sara) is a marketing leader with over 15 years of cross-industry experience translating complex products into compelling market stories. Her career spans advertising, journalism, SaaS, and Big Tech, leading to her current role at an edtech company in the Bay Area. Sara sees product marketing as the critical translator between product and market — and approaches every challenge with a problem-solver's mindset and a startup's appetite for experimentation. Outside of work, you can find her gardening, practicing yoga, and hiking the many trails in the Bay.My LinkedIn: http://www.linkedin.com/in/saraskumar

This week, we break down the arguments about open-weight models unfolding in Silicon Valley right now. Nvidia released an open letter signed by over 230 companies opposing “premature restrictions,” but will the Trump administration listen? Then, we're joined by the author Claire Stapleton to discuss her new book about what she learned while leading employee activism inside Google. And finally, can Substack stop the slop? We'll talk about the platform's new A.I. detector. Guests: Claire Stapleton, author of “Don't Be Evil: Bad Bosses, Fake Promises, and My Escape from Big Tech.” Additional Reading: Nvidia Forms Alliance to Back Open-Source A.I. Amid Debate Over Safety What Is Open-Weights A.I.? Mark Zuckerberg Blasts Centralization of A.I. Power  The Voice of Google Against Claudefishing We want to hear from you. Email us at hardfork@nytimes.com. Find “Hard Fork” on YouTube and TikTok. Subscribe today at nytimes.com/podcasts or on Apple Podcasts and Spotify. You can also subscribe via your favorite podcast app here https://www.nytimes.com/activate-access/audio?source=podcatcher. For more podcasts and narrated articles, download The New York Times app at nytimes.com/app. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

True free-market capitalism is dead. In its place, a hybrid of government and corporate actors have built a system of "privatized totalitarianism" and techno-feudalism. You think you have choices in your health care, your food, and your elections — but it's an illusion. I'm joined by political economist and author Charles Hugh Smith to break down the "golden painted leg chains" of modern American life. From the surveillance state and dynamic pricing to AI companies quietly shredding physical books to control history, Big Tech and the government have boxed out your options under the guise of "convenience." Worse yet, the political establishment — including Conservative Inc. — serves only to provide fake opposition, keeping you distracted with political theater while the oligarchy consolidates power. How do we break the monopoly? It starts by rejecting the ultra-processed life and decentralizing power back to our local counties. Learn more about your ad choices. Visit megaphone.fm/adchoices

The latest developments surrounding hedge fund Situational Awareness and what they could mean for AI investors. And we break down earnings from Apple and Amazon, highlighting the biggest takeaways for Big Tech, capex outlook, and the next phase of the AI trade. Plus, Dallas Fed President Lorie Logan explains her dissent from the Federal Reserve's latest policy decision, offering insight into the debate over the path of interest rates. Squawk on the Street Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

We break down Amazon and Apple's latest quarters with both stocks heading in opposite directions today. Then, Thoma Bravo Managing Partner Holden Spaht joins to discuss how he's looking at the software sector right now. Plus, Kalshi Board Member Brian Quintenz joins with his reaction to New York State suing the prediction market company today. Squawk on the Street Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Media continues to promote scum and control the narrative. PLUS, Robert Bork Jr., President of the Antitrust Education Project and author of the new book The New Paradox: Antitrust and the Threat of Conservative Socialism, talks to Shaun about the new Big Tech antitrust, the government politicizing the markets, and he wonders if Trump is playing into corrupt hands when it comes to antitrust. And David Hochberg, VP of Lending for Team Hochberg at Atlantic Coast Mortgage, talks to Shaun about the Chicago mayoral candidates, the property tax bills still not going out on time in Cook County, and how the state of Illinois is ruining housing for everyone.See omnystudio.com/listener for privacy information.

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

Markets are being driven by strong AI investment, cloud growth and improving earnings as companies continue expanding digital infrastructure. Plus, defense spending is accelerating across Europe, lifting demand for aerospace and security while digital transformation creates new opportunities in emerging markets. Later, investors weigh ETF driven volatility, geopolitical tensions and higher energy prices as they look beyond Big Tech for the next phase of market leadership. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Liz Shulman, English teacher at Evanston Township High School and in the School of Education and Social Policy at Northwestern University, joins John Williams to talk about her recent Op-ed in the Tribune, ‘Why are we still pretending Big Tech cares about our classrooms.’ Liz Shulman is the author of the forthcoming ‘By the Book: […]

This week: combating and reframing big tech. First up, I sit down with Ed from DeFlock to talk about ALPRs – Automatic License Plate Readers, and their handy way of circumventing the 4th amendment meant to protect against unlawful search. Ed also talks about the massive network of data sharing across law enforcement and private corporations, the use of the data for more than stated purposes – from assisting ICE to stalking ex-girlfriends. Ed reminds us that a functioning democracy does not surveil their population, and lists ways that communities across the country are fighting back. Next up, I sit down with Heidi Lim from AI Resist List to talk about reframing AI, and the possible futures that both buck the current iteration of AI and avoid the binary of anti-tech vs. pro-tech. Heidi points out that the purpose is not just to give people hope but to give them ideas, to become literate in not only what AI is but how to combat it creatively – because if AI is where creativity goes to die, perhaps combating it is where creativity can be reborn. — Ed is a member of DeFlock and has been organizing and researching police use of surveillance technologies for nearly a decade. Heidi Lim is a climate communicator focused on increasing climate literacy and rooted in environmental justice. Her work puts a climate lens on topics like technology, justice, and culture, which is ultimately how she came more recently to working on AI ethics.   The News That Didn't Make the News. Each week, co-hosts Mickey Huff and Eleanor Goldfield conduct in depth interviews with their guests and offer hard hitting commentary on the key political, social, and economic issues of the day with an emphasis on critical media literacy. The post Project Censored: Combating and Reframing Big Tech: Deflock & AI Resist appeared first on KPFA.

Episode 629 of the A Minute to Midnite Show. Data Centers. Artificial General Intelligence and robotics. War in the Middle East and Ukraine. Massive “manufactured” global oil shortage on the horizon. Masonic and illuminist infiltration of governments. What does this all mean and why is it important?

41 national football associations in North and Central America and the Caribbean have become the latest to reject FIFA's plan to sell stakes in its tournaments to investors, only hours after all 55 UEFA countries said they would boycott any World Cup if it went ahead. Will Bain finds out how this changes FIFA's hand to play.Elsewhere, our panel of the week looks back on a week of challenging times for some of the UK's biggest water companies, as well as a new government announcement on devolution and a raft of financial earnings from Big Tech companies.Plus, the new owner of craft beer and hospitality brand Brewdog tells us why claims from its founder he wants to buy it back are "unhelpful."

Former Silicon Valley insider Dex Hunter-Torricke spent years advising some of the most influential figures in tech, from Google and Facebook to SpaceX. Now, the founder of The Center for Tomorrow, he is sounding the alarm about the future being built by the industry he once helped champion.In this episode of Ways to Change the World, Krishnan Guru-Murthy speaks to Dex Hunter-Torricke about why he believes society is unprepared for the impact of artificial intelligence, the growing power of Big Tech, and the political influence of Silicon Valley's leaders. Drawing on his experience working alongside figures including Elon Musk and Mark Zuckerberg, he reflects on what changed inside the tech industry, why he feels betrayed by its direction, and why he fears AI could deepen inequality, fuel social unrest and transform the global balance of power. From online safety and regulation to jobs, democracy and the future of international cooperation, this is a conversation about whether technology is really changing the world for the better, and what must happen if we are to avoid the dangers he believes lie ahead.

Big Tech earnings are moving markets sharply as investors try to figure out whether the AI trade still has another leg higher or whether the volatility is warning of something more fragile.Chuck Zodda and Mike Armstrong break down the sharp swings in semiconductor stocks, why major tech names like Microsoft, Meta, Amazon, and Apple are seeing outsized moves after earnings, and why the broader market still looks uncertain despite several big rebounds. They also discuss Amazon's strong cloud growth and rising CapEx, Apple's disappointing guidance tied to supply constraints and memory chip costs, and why Apple's slower approach to AI resembles Toyota's patience during the EV boom. Plus, they look at the blowup of the AI-focused hedge fund Situational Awareness, Todd Lutsky's explanation of irrevocable Medicaid trusts, and why new reports about Anthropic's AI models hacking companies raise serious concerns about agentic AI risks.

Artificial intelligence is often discussed as a threat to human flourishing, undermining everything from jobs to education to literacy. Is there anything that can be done to mitigate that future damage? Is it already too late?Gregory Conti, associate professor at Princeton University, joins Oren and Chris to discuss whether there's anything to be done to stop AI. The group discusses Conti's recent writing in Compact, where he's an editor-at-large, making the case that we're already living in the wake of the technology's destruction. And they dive into specific policies, from banning tech in the classroom, to age-gating social media, to shutting down AI altogether, and whether they can be accomplished.Further reading:"The AI Apocalypse Is Already Here," by Gregory Conti, Compact"Big Tech's War on Human Achievement," by Gregory Conti, Compact

Lisa Martin breaks down this quarter's Big Tech earnings, explaining why investor reactions are driven as much by expectations and timing as the results themselves. She discusses how hyperscalers are being held to a higher standard, why Microsoft's (MSFT) earnings helped calm concerns that emerged after Alphabet's (GOOGL) report, and how Microsoft has become a benchmark for both cloud computing and AI. Martin also shares her take on the latest results from Meta Platforms (META) and Apple (AAPL).======== Schwab Network ========Empowering every investor and trader, every market day. Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about

Dan Ives breaks down his biggest takeaways from this week's Big Tech earnings, arguing that AI is still in the "third inning" with only about 5% of companies currently paying for AI adoption. He explains why earnings season continues to validate the long-term AI growth story, weighs the market's reaction to the results, and analyzes the post-earnings rallies in Microsoft (MSFT) and Amazon (AMZN).======== Schwab Network ========Empowering every investor and trader, every market day. Subscribe to the Market Minute newsletter - https://schwabnetwork.com/subscribeDownload the iOS app - https://apps.apple.com/us/app/schwab-network/id1460719185Download the Amazon Fire Tv App - https://www.amazon.com/TD-Ameritrade-Network/dp/B07KRD76C7Watch on Sling - https://watch.sling.com/1/asset/191928615bd8d47686f94682aefaa007/watchWatch on Vizio - https://www.vizio.com/en/watchfreeplus-exploreWatch on DistroTV - https://www.distro.tv/live/schwab-network/Follow us on X – https://twitter.com/schwabnetworkFollow us on Facebook – https://www.facebook.com/schwabnetworkFollow us on LinkedIn - https://www.linkedin.com/company/schwab-network/ About Schwab Network - https://schwabnetwork.com/about

I joined The Andrea Kaye Show to expose how Flock cameras are quietly building a nationwide surveillance system capable of tracking where Americans drive, worship, eat, meet, and spend time with their families. These AI-powered license plate readers are sold as a convenient way to catch criminals, but the same infrastructure gives government agencies and Big Tech the power to monitor innocent people, weaponize personal data, and lay the groundwork for a Chinese-style social credit system. Technology always comes with a price, and surrendering constitutional freedom for government efficiency is a bill Americans cannot afford to pay.Become a supporter of this podcast: https://www.spreaker.com/podcast/the-jeff-dornik-show--4788100/support.Follow The Jeff Dornik Show on Apple Podcasts and leave a 5-star review. That's how we reach more people and bypass Big Tech suppression.Watch LIVE daily at 7pm ET on Rumble and subscribe so you never miss a show:https://rumble.com/c/jeffdornikBig Tech is silencing truth while harvesting your data to feed the machine. That's why I built Pickax, a free speech platform where creators own their content and your voice isn't controlled. Join now:https://pickax.com/?referralCode=y7wxvwq&refSource=copy

Liz Shulman, English teacher at Evanston Township High School and in the School of Education and Social Policy at Northwestern University, joins John Williams to talk about her recent Op-ed in the Tribune, ‘Why are we still pretending Big Tech cares about our classrooms.’ Liz Shulman is the author of the forthcoming ‘By the Book: […]

Episode SummaryOto sits down with Hakeem Anwar — founder of #TakeBackOurTech and Above, a privacy-first phone, laptop, and communications company — to map out exactly how the surveillance system works and what people can actually do about it.They trace Hakeem's path from a decade-deep conspiracy rabbit hole through a big-tech career to founding Above after COVID convinced him he was "coding his own prison."From there the conversation covers the AI data center boom (and the free tool Hakeem built, aidatacentermap.org, to track its water and power use), Palantir's "unified surveillance" model, the push toward digital ID, why he's grown wary of Bitcoin's transparency, and a live demo of de-Googled phones, offline maps, and the F-Droid app store.They close on Hakeem's long-term vision: small communities running their own local servers and mesh networks, fully independent of Big Tech.Chapters / Timestamps(Shifted +1:05 to account for the trailer at the top of the episode)00:00 – Trailer01:05 – Intro & Hakeem's Red Pill Moment03:05 – Rabbit Holes: From Conspiracy to Big Tech04:05 – COVID, Freedom Cells & the Pivot to Above08:05 – Why Privacy Matters: From Snowden to Data Brokers10:05 – Brainwaves, EEGs & Where the Surveillance Line Stops11:05 – The Data Center Boom: Four Theories on Why13:05 – Inside AIDataCenterMap.org: Mapping Power & Water Use16:05 – The Hidden Cost: Heat Islands & Water Wars17:05 – San Marcos, Texas: How One Town Pushed Back19:05 – Arizona's Data Center Gold Rush21:05 – Wi-Fi Sensing, EMF & the Surveillance Feedback Loop26:05 – Palantir & Unified Surveillance28:05 – Digital ID: Why Nigeria Is Getting $200M to Build It29:05 – Terms & Conditions: What Are You Really Agreeing To?31:05 – Going Private: Why Oto Is Ready to Ditch His iPhone32:05 – Inside F-Droid: The Open-Source App Store34:05 – Is Bitcoin Compromised? A Privacy Maximalist's Take38:05 – Forking Bitcoin: 35,000 Versions & What That Means41:05 – Demo: Reading the "Nutrition Facts" on Your Apps43:05 – Offline Maps & Passive GPS: How It Actually Works45:05 – Wi-Fi Sensing & Seeing Through Walls47:05 – Above's Movement: Hundreds of Thousands Going Private49:05 – Layer Zero: Mesh Networks & Replacing the Internet52:05 – Encrypted Chat, Phone-Over-Internet & Video Conferencing54:05 – The Power of Taking the First Step in Your Community58:05 – Sourcing, Repairability & Above Protect Insurance59:05 – Vision: Community Server Farms & Sovereign Computing1:01:05 – People Power: The Antidote to Centralized Control1:02:05 – Re-Internalizing Self-Worth in a Tech-Dependent World1:04:05 – Building an "Autobot": Oto's AI Assistant Plans1:05:05 – Local AI Hardware: The Above Quantum 151:10:05 – Free Support: Above's White-Glove Onboarding1:12:05 – Final Words: Have Faith & Invest in Your Health1:14:05 – Closing & Where to Find HakeemKey TakeawaysAbove builds de-Googled phones and laptops running open-source software (like GrapheneOS) that show users exactly which companies are tracking them inside any app, with no ads and no logging on Above's own services.Hakeem's aidatacentermap.org tracks hyperscale data centers' estimated water and power draw, and includes case studies like San Marcos, TX, where a local group blocked a data center by showing up 100-strong to a rezoning hearing.By 2030, data centers are projected to use 40–50% of current total US power consumption, according to the map's estimates.Hakeem describes Palantir's model as "unified surveillance" — pulling disparate data (library check-ins, traffic cameras, police records) into one investigative platform — and ties it to the broader push toward digital ID.Offline tools like the F-Droid app store and OpenStreetMap let phones navigate and function fully without an internet connection or Google/Apple location services.Hakeem's long-term vision is community-run mesh networks and local server farms (8–30 households pooling resources) replacing reliance on Big Tech infrastructure entirely.Learn More / Get StartedData Center Impact Map — https://aidatacentermap.orgAbove Phone & Laptop — https://abovephone.com (use code OTO50 for $50 off any device)Hakeem's Writing — https://tbot.substack.comCONNECT WITH OTO:Instagram – https://instagram.com/otogomesWebsite – https://otogomes.live

Arena Co-Founder Anastasios Angelopoulos talks with TITV Host Akash Pasricha about AI model security hacks. We also talk with Rosenblatt Securities' Barton Crockett about Apple's supply chain constraints and Mizuho's Lloyd Walmsley about AWS cloud growth acceleration. Plus, our editors Martin Peers and Nick Wingfield discuss Big Tech earnings, Tim Cook's legacy and what's next for Apple under John Ternus. Articles discussed on this episode: https://www.theinformation.com/articles/silicon-valley-looks-new-biotech-frontier-montana https://www.theinformation.com/newsletters/the-briefing/amazons-cloud-surge-wins-wall-street Subscribe: YouTube: https://www.youtube.com/@theinformation The Information: https://www.theinformation.com/subscribe_hSign up for the AI Agenda newsletter: https://www.theinformation.com/features/ai-agendaTITV airs weekdays on YouTube, X and LinkedIn at 10AM PT / 1PM ET. Or check us out wherever you get your podcasts.Follow us:X: https://x.com/theinformationIG: https://www.instagram.com/theinformation/TikTok: https://www.tiktok.com/@titv.theinformationLinkedIn: https://www.linkedin.com/company/theinformation/

On this episode of Simply Money presented by Allworth Financial, Bob and Brian are joined by Allworth Chief Investment Officer Andy Stout and former Cleveland Fed President Dr. Loretta Mester to discuss the Federal Reserve's latest decision, inflation, and what the markets are signaling. They also break down the latest AI-driven earnings from Big Tech, explain why waiting for the "perfect" time to invest can be a costly mistake, answer a listener's question about investing after selling a business, and look at why Gen Z is spending less on nights out than previous generations. See omnystudio.com/listener for privacy information.

Liz Shulman, English teacher at Evanston Township High School and in the School of Education and Social Policy at Northwestern University, joins John Williams to talk about her recent Op-ed in the Tribune, ‘Why are we still pretending Big Tech cares about our classrooms.’ Liz Shulman is the author of the forthcoming ‘By the Book: […]

Big Tech earnings take centre stage as Apple and Amazon deliver sharply contrasting messages to investors. Michelle Martin examines why Apple’s strong sales weren’t enough to reassure markets, while Amazon’s massive AI investment plans sent its shares soaring. She also looks at Hongkong Land’s S$1.1 billion Wheelock Place acquisition, strong earnings from Great Eastern and Seatrium, Jardine Cycle & Carriage’s special dividend proposal, and why South Korea’s Kospi has become one of Asia’s best-performing stock markets recently. Hosted by Michelle Martin.See omnystudio.com/listener for privacy information.

Journalist Matt Taibbi joins The Brian Kilmeade Show to react to Dr. Anthony Fauci invoking the Fifth Amendment during his congressional testimony. Taibbi breaks down the deleted files, gain-of-function research origins in Wuhan, and how Big Tech platforms suppressed open debate during the pandemic. Learn more about your ad choices. Visit podcastchoices.com/adchoices

With Meta and Microsoft heading in opposite directions after reporting results, Janus Henderson Technology Portfolio Manager Richard Clode joins to discuss how investors should navigate this earnings season. Then, Former Philadelphia Fed President Patrick Harker reacts to the Fed's hawkish hold and Chairman Warsh's press conference. Plus, the CEOs of Shell and JLL join after reporting earnings that beat estimates.   Squawk on the Street Disclaimer Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

It was one of the most anticipated earnings weeks of the year... And one company may have just changed the market's narrative. In today's episode, we break down the latest earnings reports from four members of the Magnificent 7—Microsoft, Apple, Meta Platforms, and Amazon. While each report offered valuable insight into the state of Big Tech and the AI race, one company stood above the rest. Microsoft stole the show. As investors questioned whether the tech sector was overspending on artificial intelligence, Microsoft's results provided a powerful reminder that AI isn't just a massive expense—it can also be a massive growth engine. In this episode, we'll discuss: Why Microsoft's earnings impressed Wall Street Whether AI investments are finally beginning to pay off How Apple, Meta, and Amazon measured up against expectations Which Magnificent 7 companies appear strongest heading into the next quarter The technical outlook for the technology sector after earnings We'll also examine what these reports tell us about the broader economy. Big Tech earnings often serve as a barometer for corporate spending, consumer demand, cloud computing, digital advertising, and artificial intelligence. Their results can shape market sentiment for weeks to come. Because earnings season isn't just about who beat estimates... It's about which companies are proving they can turn innovation into profits. Listen now:

Strong earnings from Microsoft and resilient consumer spending are helping stabilize markets, even as investors reassess Big Tech, free cash flow and AI investment. Plus, cloud growth, AI infrastructure, and sector rotation continue creating opportunities across technology and the broader market. Later, Fed uncertainty, persistent inflation, higher bond yields and geopolitical risks keep investors focused on interest rates and the outlook for equities. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Microsoft explodes after earnings while Apple and Amazon take center stage in another wild session for Big Tech options. On this episode of The Hot Options Report, we break down the most active names across the options market, including a massive post-earnings move in Microsoft and aggressive new positioning in MSFT calls. We also dig into the earnings action in Apple and Amazon, with AAPL sliding after hours while AMZN jumps following its report. Plus, we examine the latest options activity in NVIDIA, Tesla, Micron, Meta, Intel, SpaceX and IREN, along with some of the unusual names lighting up the Lucky Seven scan.  Check out the latest options data and market scans at TheHotOptionsReport.com.

Le sujet :L'IA va changer le monde du business. Ce n'est plus une prophétie mais une certitude. La question est de savoir déceler les gagnants des perdants.Face à l'explosion du nombre de SaaS créés avec l'IA, l'évolution des process avec l'agentique et l'émergence de licornes spécialisées, comment reconnaître les bons des mauvais élèves ?L'invité du jour :Paul-Antoine Tual accompagne les PME et ETI dans leur transformation IA. Au micro de Matthieu Stefani, il analyse comment les entreprises ont pris le virage de l'intelligence artificielle pour identifier les futurs gagnants et les secteurs menacés par une bulle imminente.Les références :Junyr, l'ERP européen avec son usine à agents : www.junyr.appArticle avec l'étude complète de la maturité IA du Top 10 du CAC 40 et du Nasdaq (les palmarès détaillés et la méthodologie) : paulantoinetual.fr/blog/cac-40-vs-nasdaq-top-10https://deathbyclawd.com/Chapitres :00:00:00 : La transition est en cours00:06:12 : Les modèles d'IA deviennent des commodités00:09:12 : Les IA peuvent être interdites : on entre en eaux troubles00:11:29 : L'avènement de l'agentique : quels secteurs seront ravagés ?00:21:39 : La grille de lecture pour un investisseur : comprendre quelles entreprises vont survivre00:28:38 : Les questions à se poser impérativement avant d'investir dans une entreprise en 202600:33:32 : Les menaces existentielles sur les grandes entreprises de l'IA00:41:11 : Ce qui va changer dans 2 ans00:44:44 : Les Big Tech sont-elles survalorisées ?00:49:34 : Pourquoi l'intégration de l'IA est une condition de survie pour les entreprises00:57:51 : Quelles entreprises sont à l'abri en cas d'éclatement de la bulle ?Merci à notre partenaire Fundora de soutenir la Martingale.Allez sur fundora.fr et prenez le contrôle de vos investissements.Fundora est une plateforme d'investissement. La valeur de vos placements peut augmenter ou diminuer. Votre capital est assujetti à un risque.La libre antenne de votre podcast préféré, Allo La Martingale, a désormais son propre flux ! Abonnez-vous sur Spotify, Apple Podcasts ou votre plafeforme audio favorite pour ne manquer aucun nouvel épisode. Pour s'abonner à la newsletter, c'est ici : https://lamartingale.io/ La Martingale, c'est aussi un assistant IA qui vous apporte des réponses éclairées issues des interventions des experts passés au micro du podcast. Pour tester, direction https://beta.lamartingale.ioLa Martingale est un média d'Orso Media. Vous souhaitez entrer en contact avec a rédaction ? Ou nous soumettre une collaboration ? Ecrivez-nous ici : https://orsomedia.io/contactHébergé par Audiomeans. Visitez audiomeans.fr/politique-de-confidentialite pour plus d'informations.

Former CNBC and Fox Business anchor Dennis Kneale joins me to explain why Americans are losing faith in capitalism even as the stock market and GDP keep climbing. We dig into housing costs, inflation, government regulation, entrepreneurship, artificial intelligence, and the growing disconnect between the economic numbers celebrated in Washington and the grocery bills crushing actual families. Dennis brings his relentless optimism, I bring the inconvenient questions, and somewhere along the way we determine that socialism still sucks, government is usually standing at the scene of the crime, and Americans may need to stop waiting for politicians to rescue them and start taking responsibility for building their own future.Order Dennie Kneale's new book Oregoners on Amazon: https://a.co/d/07Kz8y6YBecome a supporter of this podcast: https://www.spreaker.com/podcast/the-jeff-dornik-show--4788100/support.Follow The Jeff Dornik Show on Apple Podcasts and leave a 5-star review. That's how we reach more people and bypass Big Tech suppression.Watch LIVE daily at 7pm ET on Rumble and subscribe so you never miss a show:https://rumble.com/c/jeffdornikBig Tech is silencing truth while harvesting your data to feed the machine. That's why I built Pickax, a free speech platform where creators own their content and your voice isn't controlled. Join now:https://pickax.com/?referralCode=y7wxvwq&refSource=copy

Long delay between posts because once again life gets in the way, and yet we persevere to try and bring you some yucks. We were finally able to sit down and discuss the rad new models revealed during the Big Summer Preview (we did discuss the new Ogres, but Tony's audio got a little weird so it had to be cut. We think they're cool!), and then we had another great (dumb?) bit where we discuss the most useful of Tech-Priest upgrades. Our Patreon- https://www.patreon.com/dicelikeice

Today, the key stock index in South Korea — the Kospi — was down almost 6% at close. That's after dropping 10% yesterday. We're starting to see somewhat of a change in investor emotion for tech stock, prompted by questions over big tech companies spending on AI. What else is driving the sell-off, and what does it mean for the broader market? Plus, we look at how AI is shaping the job market for younger job seekers.Every story has an economic angle. Want some in your inbox? Subscribe to our daily or weekly newsletter.Marketplace Morning Report is more than a radio show. Check out our original reporting and financial literacy content at marketplace.org — and consider making an investment in our future.

Is Mitch McConnell finally going to answer the questions surrounding his health? Kentucky Governor Andy Beshear is speaking out with a blunt ultimatum as speculation continues over the longtime senator's condition and political future. We break down what Beshear said, why it matters, and what could come next in Kentucky politics. Plus, Donald Trump is facing backlash after a new push to open public lands for massive AI data centers, raising concerns about environmental impacts, corporate giveaways, and who really benefits. We unpack the plan, the politics behind it, and what it could mean for taxpayers and public resources. Progressive news with sharp analysis, a little comedy, and the stories everyone will be talking about. Welcome to The Rush Hour with Dave Neal.

Today, the key stock index in South Korea — the Kospi — was down almost 6% at close. That's after dropping 10% yesterday. We're starting to see somewhat of a change in investor emotion for tech stock, prompted by questions over big tech companies spending on AI. What else is driving the sell-off, and what does it mean for the broader market? Plus, we look at how AI is shaping the job market for younger job seekers.Every story has an economic angle. Want some in your inbox? Subscribe to our daily or weekly newsletter.Marketplace Morning Report is more than a radio show. Check out our original reporting and financial literacy content at marketplace.org — and consider making an investment in our future.

Ukraine is shifting its long-range drone campaign to focus on critical Russian infrastructure, and Big Tech companies are facing an AI dilemma as they report quarterly earnings. Plus, Google DeepMind is leaving behind its Nobel-winning AlphaFold project for new ventures, and PwC published “thought leadership” reports containing AI-generated hallucinations.Mentioned in this podcast:Ukraine adapts strikes on Russian energy industry to hit critical componentsChip stocks tumble as AI sell-off deepensGoogle DeepMind dismantles Nobel-winning AlphaFold team in strategy shiftPwC published ‘thought leadership' reports marred by AI hallucinations Listen to Unhedged on Apple Podcasts, Pocket Casts or Spotify.Save 10% on tickets to the FT Weekend Festival with the code FTPodcast. Visit ft.com/festival to find out more.Want to get in touch? Email us at podcasts@ft.comNote: The FT does not use generative AI to voice its podcasts The FT News Briefing is produced by Victoria Craig, Sonja Hutson, Saffeya Ahmed, Katya Kumkova, and Fiona Symon. Our editor is Marc Filippino. Our show is mixed by Sam Giovinco and Alex Higgins. Additional help from Gavin Kallmann, Michael Lello, Peter Barber and David da Silva. Our intern is Cole van Miltenburg. Our executive producer is Topher Forhecz. Flo Phillips is the FT's global head of audio. The show's theme music is by Metaphor Music. Read a transcript of this episode on FT.com Hosted on Acast. See acast.com/privacy for more information.

https://www.patreon.com/breakingsocialnorms/posts/matrix-brain-165069610?pr=true(*Unlock ad-free early access w/ monthly bonus content on Patreon!) Today we're catching up on some occult news and discuss topics like the Baphomet, Epstein & Unabomber connection, matrix moves with brain chips, social media addiction, state of affairs chat and more!  Get super soft shirts, coffee & signed books: https://occultsymbolism.com FULL SHOW NOW UP AD-FREE with early access on Patreon.com/BreakingSocialNorms and Apple Podcast Premium; free feed gets it in one day! You can now sign up for our commercial-free version of the show with a Patreon exclusive bonus show called “Morning Coffee w/ the Weishaupts” at Patreon.com/BreakingSocialNorms  OR subscribe on the Apple Podcasts app to get all the same bonus “Morning Coffee” episodes AD-FREE with early access! (*Patreon is also NOW enabled to connect with Spotify! https://rb.gy/r34zj)Want more?…Index of all previous episodes on free feed: https://breakingsocialnorms.com/2021/03/22/index-of-archived-episodes/Leave a review or rating wherever you listen and we'll see what you've got to say!Follow us on the socials:instagram.com/theweishaupts2/Check out Isaac's conspiracy podcasts, merch, etc:AllMyLinks.com/IsaacWOccult Symbolism and Pop Culture (on all podcast platforms or IlluminatiWatcher.com)Isaac Weishaupt's book are all on Amazon and Audible; *author narrated audiobooks*STATEMENT: This show is full of Isaac's and Josie's useless opinions and presented for entertainment purposes. Audio clips used in Fair Use and taken from YouTube videos.

The biggest tech news & social media trends on the internet from July 29th, 2026.Timestamps:00:00 Intro1:12 The reaction to MidJourney acquiring Co-Star8:43 Claude exposed private chats on Google Search14:20 AI companies are destroying physical media Subscribe to Spotify: https://open.spotify.com/show/18cqrQI7gMiVfxIMRAeULF Subscribe to Apple Podcasts: https://podcasts.apple.com/au/podcast/infinite-scroll/id1499785732 Subscribe to our weekly Substack: https://centennialworld.substack.com/   Follow us on Instagram: https://www.instagram.com/infinitescrollpodcast/   Follow our publication: https://www.tiktok.com/@centennialworld   Follow Lauren on Instagram: https://www.instagram.com/laurenmeisner_/   Follow Lauren on TikTok: https://www.tiktok.com/@laurenmeisner_Are you a podcaster looking for brand partnerships? Or a brand looking to advertise on podcasts? Check out our marketplace connecting podcasters of all sizes with brands of all budgets worldwide: https://www.sponstudio.com Please consider buying us a coffee to help keep Centennial World's weekly podcasts going! Every single dollar goes back into this business

In this episode of Market Mondays, we break down ASML's decline, China's growing semiconductor industry, the S&P 500 outlook, recession risks, oil prices, and Big Tech's massive AI spending. We also discuss Amazon's satellite plans, Bloom Energy, Tesla vs. SpaceX, and the biggest opportunities heading into earnings season.Plus, we answer audience questions, cover single-stock futures, sports betting trends, and share our Investment Fact, Trading Tip, and Invest Fest Networking Tip of the Week to help you stay ahead of the market.If you're serious about investing and building long-term wealth, this is an episode you don't want to miss.#MarketMondays #Investing #StockMarket #Stocks #Trading #Finance #EarnYourLeisure #WealthBuilding #SP500 #AI #Tesla #Amazon #ASML #EarningsAdvertising Inquiries: https://redcircle.com/brandsPrivacy & Opt-Out: https://redcircle.com/privacy

The fight over AI data centers has entered a disturbing new phase. The developers and local government officials are becoming more fascistic, immoral, and dishonest in their effort to avoid public scrutiny and opposition. Oklahoma farmer and grassroots activist Darren Blanchard joins me to expose how Big Tech developers and government officials are allegedly using intimidation, deception, and political pressure to force massive AI data center projects into rural America. After speaking just seconds beyond his allotted time at a local council meeting, Blanchard was arrested. But that wasn't the biggest revelation. Through public records requests, he uncovered what appeared to be hundreds of fraudulent emails sent to local officials using the names of real residents to manufacture public support for a controversial data center project. Some residents say they never sent the emails. One reportedly came from a deceased individual. We also cover the connection between data centers, solar projects, and land acquisition, and why farmers are raising concerns about the threats to food production. Finally, we get political and discuss the future of grassroots resistance to Big Tech and how it might spawn a new party.  Learn more about your ad choices. Visit megaphone.fm/adchoices

New York City Mayor Zohran Mamdani just announced a new “pied-à-terre” tax on the cities wealthiest residents, and followed up by doxxing everyone it would impact. Today's Guest Host, Comedian & Heritage Foundation Media Fellow Tim Young is joined by Chief Economist for the Thomas A. Roe Institute for Economic Policy Studies, E.J. Antoni and Co-Owner of The Chicago Cubs & Founder of Freespoke Todd Ricketts to break down Mamdani's latest attack on the rich, before taking a look at the corporate aftermath of Cracker Barrel's disastrous rebrand and Big Tech's protection of Dr. Anthony Fauci being recently exposed.Plus, E.J. explains why gas prices remain at painfully high levels, even though our country possesses vast fossil fuel reserves.Subscribe to ‘Will Cain Country' on YouTube here: ⁠⁠⁠⁠⁠Watch Will Cain Country!⁠⁠⁠Follow ‘Will Cain Country' on X (⁠⁠⁠@willcainshow⁠⁠⁠), Instagram (⁠⁠⁠@willcainshow⁠⁠⁠), TikTok (⁠⁠⁠@willcainshow⁠⁠⁠), and Facebook (⁠⁠⁠@WillCainNews)Follow Will on X: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠@WillCain Learn more about your ad choices. Visit podcastchoices.com/adchoices

Investors are apprehensive as we get into an action-packed week in the economy. The Federal Reserve finishes up an interest-rate-setting meeting tomorrow. Dozens of companies on the S&P report earnings, and we also get reports on inflation and GDP. Plus, Meta, Microsoft, and Amazon issue earnings reports, and investors are anxious about cash burn at companies building out AI data centers. Then, we'll get into the different concerns Baby Boomers and Gen Z have about the economy.Every story has an economic angle. Want some in your inbox? Subscribe to our daily or weekly newsletter.Marketplace Morning Report is more than a radio show. Check out our original reporting and financial literacy content at marketplace.org — and consider making an investment in our future.Stories featured in this episode:Investors are keeping an eye on AI cash burn in Big Tech earnings reportsWhy Baby Boomers and Gen Z have different concerns about the economy

Dario Amodei said Anthropic never backed an open-weights ban, pitching mandatory safety tests instead as OpenAI and Google signed on. Altman headed to Washington, Korea's KOSPI cratered 11% on AI jitters, Apple launched Klarna leasing, and shipped 194 CVE fixes. Anthropic wants tests, not bans, as OpenAI and Google back open weights (The New Stack) Source: Sam Altman will meet with senior US officials, lawmakers, and economists in Washington, DC, this week to preview OpenAI's upcoming family of AI models (CNBC) South Korea's KOSPI drops 11%+, led by chip stocks, amid concerns over China's chipmaking progress and the AI spending boom; Samsung falls 11%+ and SK Hynix 12% (Bloomberg) Credit default swap prices tied to Oracle, SpaceX, Alphabet, Amazon, Meta, Broadcom, and Nvidia hit record highs as investors turn jittery over Big Tech's data center debt; Oracle's five-year CDS reached 215bps (FT) Apple launches Apple Upgrade, a new US leasing program in partnership with Klarna that replaces the iPhone Upgrade Program, starting at $17.99/month for iPhones (MacRumors) Apple releases 26.6 updates for iOS, macOS, iPadOS, watchOS, tvOS, and visionOS with a huge number of security fixes; macOS Tahoe 26.6 alone addresses 155 CVEs (9to5Mac) Subscribe to the ad-free feed. Learn more about your ad choices. Visit megaphone.fm/adchoices

Investors are apprehensive as we get into an action-packed week in the economy. The Federal Reserve finishes up an interest-rate-setting meeting tomorrow. Dozens of companies on the S&P report earnings, and we also get reports on inflation and GDP. Plus, Meta, Microsoft, and Amazon issue earnings reports, and investors are anxious about cash burn at companies building out AI data centers. Then, we'll get into the different concerns Baby Boomers and Gen Z have about the economy.Every story has an economic angle. Want some in your inbox? Subscribe to our daily or weekly newsletter.Marketplace Morning Report is more than a radio show. Check out our original reporting and financial literacy content at marketplace.org — and consider making an investment in our future.Stories featured in this episode:Investors are keeping an eye on AI cash burn in Big Tech earnings reportsWhy Baby Boomers and Gen Z have different concerns about the economy

Does becoming a billionaire turn one into an insufferable jerk, or is that an innate quality they bring to the position?Big-name billionaires – like Musk, Bezos, and Zuckerberg – literally flaunt their irrepressible jerkism, but the disease seems to inflict their entire class of über-rich corporate royals. Its telltale symptoms are not their grandiose mansions and yachts, but their sudden impulse to instruct us regular people on how to think. In particular, they're now demanding that we get out of their way so they can remake society in their image.Jensen Huang, for example, a Silicon Valley techno-whiz who heads Nvidia, now the world's richest corporation. He's demanding that we transform our economy and social structure into a new order of AI dominance, piously chiding those of us who're angry about AI's destruction of our jobs, communities, water, farmland, and democracy itself. Tut-tut, the gabillionaire scolds, you petty people must “create new social norms” to advance AI.Then there's the little-known honcho of SoftBank, a multi-trillion-dollar Japanese tech powerhouse trying to impose AI supremacy worldwide. He's now asserting a corporate “morality” of wealth, calling people who question AI “foolish.” He philosophizes that TechWorld “will transform our lives completely and do so in a way that generates profits.”For whom? For billionaires, of course. So there you have a clear statement of the values and goals of AI profiteers: More for them, no matter the cost to everyone else. SoftBank's imperious boss laughs at those of us who dare question his vision of an AI plutocracy, calling us fools who are “spitting upward.”No sir, look again. We are spitting straight at you.Do something!Want to join the rebellion against AI billionaires? Check out Public Citizen's work on Big Tech and other corporate monsters: https://www.citizen.org/topic/consumer-worker-safeguards/big-tech/Jim Hightower's Lowdown is a reader-supported publication. To receive new posts and support my work, consider becoming a free or paid subscriber. This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit jimhightower.substack.com/subscribe

A crucial gauge of risk in holding the debt of companies at the centre of the AI boom has hit a record high, private capital group Ares Management has held talks to acquire Leonard Green & Partners, and French company TotalEnergies will be able to continue selling gas from its flagship Siberian project to Asia. Plus, institutional investors are snapping up bundles of UK homes at large discounts and sales at LVMH's key fashion and handbags division returned to growth for the first time in two years.Mentioned in this podcast:Big Tech credit risks hit record highs as AI spending soarsAres Management has held talks to buy Leonard Green PartnersInvestors snap up bundles of UK properties as housebuilders offer discountsTotalEnergies benefits from EU sanctions reprieve on Russian gasDior rebound helps LVMH's fashion business return to growthSave 10% on tickets with the code FTPodcast. Visit ft.com/festival to find out more.Want to get in touch? Email us at podcasts@ft.comNote: The FT does not use generative AI to voice its podcasts The FT News Briefing is produced by Victoria Craig, Sonja Hutson, Saffeya Ahmed, Katya Kumkova, and Fiona Symon. Our editor is Marc Filippino. Our show is mixed by Sam Giovinco and Alex Higgins. Additional help from Gavin Kallmann, Michael Lello, Peter Barber and David da Silva. Our intern is Cole van Miltenburg. Our executive producer is Topher Forhecz. Flo Phillips is the FT's global head of audio. The show's theme music is by Metaphor Music.Read a transcript of this episode on FT.com Hosted on Acast. See acast.com/privacy for more information.