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One week ago, we launched Typeahead. The product is already meaningfully better. We’ve shipped new features, Typeahead 2.0 is almost ready, and we’re already planning 3.0. 3.0 is going to be big. That pace is part of the point. Sam Asante and I started a new company together because...

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Hiten Shah

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18,627 просмотров • 2 месяцев назад •via X (Twitter)

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Today Sam Asante and I are releasing Typeahead 2.0 on Product Hunt. Sam and I started this company because we think local AI software is going to become a much bigger part of how people use their computers. Typeahead is the first product from that thesis. The first version made the idea clear. AI autocomplete should work in the apps where writing already happens. Since then, we have been shipping toward the product that idea deserves. The app feels faster and more natural. Suggestions are easier to control. The experience is more native to the Mac. It's getting better at staying out of the way until the exact moment it can help. That matters because writing is personal. The best AI writing help keeps you in the sentence. You stay in flow and keep your voice. The machine helps without taking over. Typeahead works across your Mac, runs locally, works offline, and is built to feel like software you own. We’re live on Product Hunt today.
1:10

Today Sam Asante and I are releasing Typeahead 2.0 on Product Hunt. Sam and I started this company because we think local AI software is going to become a much bigger part of how people use their computers. Typeahead is the first product from that thesis. The first version made the idea clear. AI autocomplete should work in the apps where writing already happens. Since then, we have been shipping toward the product that idea deserves. The app feels faster and more natural. Suggestions are easier to control. The experience is more native to the Mac. It's getting better at staying out of the way until the exact moment it can help. That matters because writing is personal. The best AI writing help keeps you in the sentence. You stay in flow and keep your voice. The machine helps without taking over. Typeahead works across your Mac, runs locally, works offline, and is built to feel like software you own. We’re live on Product Hunt today.

Hiten Shah

28,014 просмотров • 1 месяц назад

The labs want to rent you intelligence. Palantir is building the stack for you to own it. “We are building a stack that is fully aligned with you capturing and maintaining the alpha of your business. Every single technology decision we are making is aligned with that.“ That is AI sovereignty. We have the product. We have the scale. We know how to do it. Now we take the market.
1:11

The labs want to rent you intelligence. Palantir is building the stack for you to own it. “We are building a stack that is fully aligned with you capturing and maintaining the alpha of your business. Every single technology decision we are making is aligned with that.“ That is AI sovereignty. We have the product. We have the scale. We know how to do it. Now we take the market.

Chad Wahlquist

43,085 просмотров • 20 дней назад

Elon Musk on Grok: “I think an AI that is sort of SpaceX’s baby will be a very good AI. I think SpaceX is a collection of some of the very best humans on Earth, both in capability and morality and goodness, and I think we want to have an AI that is born of that capability and that morality and that goodness. I think that’s very, very important. So I’d like to encourage people to help out, actually, with the AI hardware on the ground and the AI software and, of course, with the AI satellites. Solar is going to be a very important part of that. The TerraFab will be a very important part of that, but we must also succeed on the software front, and we’re going to be training Grok on the sum total of all SpaceX information. So in a way, it will be trained on you. You will effectively be the parents of the AI. It will inherit your thoughts and ideas and beliefs, and I think that’s a good thing. So, yeah, we’ve got to win here on the AI hardware and the AI software. That maybe is the most important message. I think that is actually the most important message I wanted to convey today is that we must win on AI because the future is overwhelmingly AI and robots. So we won’t ultimately be able to control the AI. It’ll be too smart for that. But just like if you have a child that is a super genius child, you can still instill in that child the values and beliefs that you think are good and right. And so that’s why it’s incredibly important that we succeed with Grok. So, yeah, well, Grok 4.5 you’ve tried probably. We’ve got 4.6 coming out in about a week. And then 4.7 should be really pretty special. So I’d like to encourage everyone at SpaceX to use AI and to make it better.”
2:56

Elon Musk on Grok: “I think an AI that is sort of SpaceX’s baby will be a very good AI. I think SpaceX is a collection of some of the very best humans on Earth, both in capability and morality and goodness, and I think we want to have an AI that is born of that capability and that morality and that goodness. I think that’s very, very important. So I’d like to encourage people to help out, actually, with the AI hardware on the ground and the AI software and, of course, with the AI satellites. Solar is going to be a very important part of that. The TerraFab will be a very important part of that, but we must also succeed on the software front, and we’re going to be training Grok on the sum total of all SpaceX information. So in a way, it will be trained on you. You will effectively be the parents of the AI. It will inherit your thoughts and ideas and beliefs, and I think that’s a good thing. So, yeah, we’ve got to win here on the AI hardware and the AI software. That maybe is the most important message. I think that is actually the most important message I wanted to convey today is that we must win on AI because the future is overwhelmingly AI and robots. So we won’t ultimately be able to control the AI. It’ll be too smart for that. But just like if you have a child that is a super genius child, you can still instill in that child the values and beliefs that you think are good and right. And so that’s why it’s incredibly important that we succeed with Grok. So, yeah, well, Grok 4.5 you’ve tried probably. We’ve got 4.6 coming out in about a week. And then 4.7 should be really pretty special. So I’d like to encourage everyone at SpaceX to use AI and to make it better.”

DogeDesigner

63,600 просмотров • 8 дней назад

Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)
0:59

Jensen Huang just said this is the greatest era in history to build software. AI agents will not kill software. They will do the exact opposite: create a massive new wave of software demand. at NVIDIA GTC Taipei 2026 "Click and type. We now replace that with explaining to the AI what we want, our intent, and the AI generates the code or uses tools to produce the necessary output. This is how computers are going to work in the future. This is Agentic AI. For two years, we've been building toward this, and now it has arrived. One of the big breakthroughs, of course, is tool use. A lot of people have said, “Jensen, AI is coming. Agentic AI is coming. Therefore, all the software companies are going to go out of business.” This is exactly the opposite. Because there are going to be so many agents, the world is no longer limited by the number of people. Therefore, those agents are going to use more tools than ever. This is actually an incredible time to be a software company. But the software has to be presented to the agent in a way that the agent can use it. This is a big breakthrough. And in fact, what we have done, as you know, what Nvidia’s treasure..." ---- From 'NVIDIA' YT channel (link in comment)

Rohan Paul

16,584 просмотров • 2 месяцев назад

DeepMind CEO Demis Hassabis says the AI bottleneck is already moving from model ideas to physical supply chains. "How much of the restriction at this point is physical? I am talking memory shortage, GPU shortage, and electricity." Demis: "That is constraining a lot of the deployment for sure. We see so much more demand for our models - Gemini and the other models that we have - than we can possibly serve." Then the less obvious part: "It does constrain a little bit the research, because you need a lot of chips to be able to experiment on new ideas at big enough scale that you can actually see if they are going to work." And on memory: "The whole supply chain is kind of strained... It still in the end actually comes down to a few suppliers of a few of the key components. Anywhere where there is some kind of constraint on the capacity, there is a sort of choke point." Important framing: The next AI race is not just who has the best model architecture. It is who can secure memory, chips, power, suppliers, and enough experimental capacity to find the next breakthrough before everyone else.
1:09

DeepMind CEO Demis Hassabis says the AI bottleneck is already moving from model ideas to physical supply chains. "How much of the restriction at this point is physical? I am talking memory shortage, GPU shortage, and electricity." Demis: "That is constraining a lot of the deployment for sure. We see so much more demand for our models - Gemini and the other models that we have - than we can possibly serve." Then the less obvious part: "It does constrain a little bit the research, because you need a lot of chips to be able to experiment on new ideas at big enough scale that you can actually see if they are going to work." And on memory: "The whole supply chain is kind of strained... It still in the end actually comes down to a few suppliers of a few of the key components. Anywhere where there is some kind of constraint on the capacity, there is a sort of choke point." Important framing: The next AI race is not just who has the best model architecture. It is who can secure memory, chips, power, suppliers, and enough experimental capacity to find the next breakthrough before everyone else.

Karl Mehta

25,716 просмотров • 1 месяц назад

David Friedberg: The AI Jobs Panic Is a Crock of Sh*t Why? The revenue potential outweighs the cost savings by 100x. “There is no job loss with AI. I've said it a thousand times, and I will say it again, and again, and again. What I see on the ground, and what I've seen at dozens of companies, including my company that I run, there are two sides to a business. There is revenue and there’s costs. On the cost side of the equation, AI can be used to reduce humans doing things that cost money, to some extent. The effect there, I would argue, is nominal. The real opportunity with AI is on the revenue side, where suddenly one engineer can do 100x or 1000x what they used to be able to do, meaning you can make more products at your company, whether those are agricultural seed products, or boats and ships, or software for companies, or clothing, or what have you. Because of AI, everyone has the ability to expand their revenue base to create more products, and that is the foundation of good economic prosperity. It is called productivity. We can grow productivity in this country with AI. So where I see AI being used is on the revenue side 100x more than the cost side. And in that equation, people are hiring like crazy. We cannot hire enough people. I just had a review meeting with my product and engineering team two days ago, and they're like, ‘We want to add an extra 15 headcount to our engineering squads because we have all this opportunity to do stuff that we couldn't otherwise do.’ So we are going to hire more people. And to Sacks' point, we are seeing that show up in the jobs numbers. The idea that AI is going to destroy jobs is a Luddite idea that is being disproven every single day, and I see it on the ground. It is only a matter of time before people wake up to this and they realize that this narrative that they've all been sold is a crock of sh*t.”
1:42

David Friedberg: The AI Jobs Panic Is a Crock of Sh*t Why? The revenue potential outweighs the cost savings by 100x. “There is no job loss with AI. I've said it a thousand times, and I will say it again, and again, and again. What I see on the ground, and what I've seen at dozens of companies, including my company that I run, there are two sides to a business. There is revenue and there’s costs. On the cost side of the equation, AI can be used to reduce humans doing things that cost money, to some extent. The effect there, I would argue, is nominal. The real opportunity with AI is on the revenue side, where suddenly one engineer can do 100x or 1000x what they used to be able to do, meaning you can make more products at your company, whether those are agricultural seed products, or boats and ships, or software for companies, or clothing, or what have you. Because of AI, everyone has the ability to expand their revenue base to create more products, and that is the foundation of good economic prosperity. It is called productivity. We can grow productivity in this country with AI. So where I see AI being used is on the revenue side 100x more than the cost side. And in that equation, people are hiring like crazy. We cannot hire enough people. I just had a review meeting with my product and engineering team two days ago, and they're like, ‘We want to add an extra 15 headcount to our engineering squads because we have all this opportunity to do stuff that we couldn't otherwise do.’ So we are going to hire more people. And to Sacks' point, we are seeing that show up in the jobs numbers. The idea that AI is going to destroy jobs is a Luddite idea that is being disproven every single day, and I see it on the ground. It is only a matter of time before people wake up to this and they realize that this narrative that they've all been sold is a crock of sh*t.”

The All-In Podcast

152,328 просмотров • 2 месяцев назад

I miss building simple, working software. At some point, we decided to complicate everything for no reason. Today, people can't build anything without using three frameworks, 17 libraries, and a swarm of microservices. And here is a funny paradox: To understand how these complex systems work, we've had to build systems and tools that generate data we can later analyze. But the more data we produce, the harder it is to process and make sense of it. We are in the middle of an observability crisis. The tools we have are inefficient, and we don't have enough people to keep systems running. A few weeks ago, I met the team Resolve AI, and they have built a fundamentally new approach to observability and incident management: Instead of depending on humans to run a system, Resolve built a Production Software Engineer who runs the system using AI while letting people supervise. And it's not only crazy, but I think this will fundamentally change how we monitor and maintain systems in production for years to come. I recorded a quick video to showcase a simple example of how Resolve works behind the scenes. There are two main things I'd like you to notice: 1. The tool can correlate data across logs, metrics, and traces coming from different systems. You don't have to do any work to get the information that matters right in front of you. 2. (This is the big one!) The tool can diagnose what's happening and give you instructions on how to solve it. It can produce causal relationships across the entire system stack. Resolve is backed by investors like Replit's founder Amjad Masad, Reid Hoffman, Jeff Dean, Fei Fei Li, Andy Price, among others. They are currently working with a select number of companies and want to onboard a few more. If you are interested in trying them out, go to this link: Honestly, this is one of the most impressive uses of AI I've seen.
5:18

I miss building simple, working software. At some point, we decided to complicate everything for no reason. Today, people can't build anything without using three frameworks, 17 libraries, and a swarm of microservices. And here is a funny paradox: To understand how these complex systems work, we've had to build systems and tools that generate data we can later analyze. But the more data we produce, the harder it is to process and make sense of it. We are in the middle of an observability crisis. The tools we have are inefficient, and we don't have enough people to keep systems running. A few weeks ago, I met the team Resolve AI, and they have built a fundamentally new approach to observability and incident management: Instead of depending on humans to run a system, Resolve built a Production Software Engineer who runs the system using AI while letting people supervise. And it's not only crazy, but I think this will fundamentally change how we monitor and maintain systems in production for years to come. I recorded a quick video to showcase a simple example of how Resolve works behind the scenes. There are two main things I'd like you to notice: 1. The tool can correlate data across logs, metrics, and traces coming from different systems. You don't have to do any work to get the information that matters right in front of you. 2. (This is the big one!) The tool can diagnose what's happening and give you instructions on how to solve it. It can produce causal relationships across the entire system stack. Resolve is backed by investors like Replit's founder Amjad Masad, Reid Hoffman, Jeff Dean, Fei Fei Li, Andy Price, among others. They are currently working with a select number of companies and want to onboard a few more. If you are interested in trying them out, go to this link: Honestly, this is one of the most impressive uses of AI I've seen.

Santiago

82,074 просмотров • 1 год назад

Larry Ellison just told every software engineer on Earth their job description is dead. Not evolving. Dead. Ellison: “The code that Oracle is writing, Oracle isn’t writing. Our AI models are writing.” This is not a startup demo. This is one of the largest infrastructure monopolies on the planet telling you it already replaced the people who built it. For fifty years, building software meant translating human intent into machine instructions. Line by line. Bug by bug. Sprint by sprint. That entire layer is gone. Ellison: “We don’t write the procedure. We declare our intent.” That sentence just made the entire engineering labor market flinch. The procedure was the job. The procedure was the paycheck. The procedure was what made a developer valuable. And now the machine does it without being asked twice. Ellison: “We just tell the model what we want the program to do, and then the AI comes up with a step-by-step process to actually do it.” You are no longer paid to build. You are paid to think. And most organizations have no idea how to evaluate that. The companies still hiring armies of developers to grind through codebases are paying salaries the machine already made worthless. Not in years. In seconds. When a company worth hundreds of billions hands the keyboard to the machine and tells you the output is better, the debate is not winding down. The debate is over. The enterprise that wins this decade does not write the best code. It removes the human from the process entirely and runs on intent alone. The programmers who survive are the ones who realize the craft is no longer typing. It is architecture. It is judgment. It is knowing what to build and why. Everything else now belongs to the machine. And the machine does not negotiate severance.
0:31

Larry Ellison just told every software engineer on Earth their job description is dead. Not evolving. Dead. Ellison: “The code that Oracle is writing, Oracle isn’t writing. Our AI models are writing.” This is not a startup demo. This is one of the largest infrastructure monopolies on the planet telling you it already replaced the people who built it. For fifty years, building software meant translating human intent into machine instructions. Line by line. Bug by bug. Sprint by sprint. That entire layer is gone. Ellison: “We don’t write the procedure. We declare our intent.” That sentence just made the entire engineering labor market flinch. The procedure was the job. The procedure was the paycheck. The procedure was what made a developer valuable. And now the machine does it without being asked twice. Ellison: “We just tell the model what we want the program to do, and then the AI comes up with a step-by-step process to actually do it.” You are no longer paid to build. You are paid to think. And most organizations have no idea how to evaluate that. The companies still hiring armies of developers to grind through codebases are paying salaries the machine already made worthless. Not in years. In seconds. When a company worth hundreds of billions hands the keyboard to the machine and tells you the output is better, the debate is not winding down. The debate is over. The enterprise that wins this decade does not write the best code. It removes the human from the process entirely and runs on intent alone. The programmers who survive are the ones who realize the craft is no longer typing. It is architecture. It is judgment. It is knowing what to build and why. Everything else now belongs to the machine. And the machine does not negotiate severance.

Dustin

535,724 просмотров • 5 месяцев назад

Evan Spiegel on the lesson that killed his first startup and led to Snapchat: "We focused on building the perfect product for way too long before we got feedback. We worked for like eighteen months to build this perfect full-featured product, which was in direct contravention to how I was always taught to build things. Build a prototype, build an MVP, get it in front of people, learn as quickly as possible. But we had spent all this time building this perfect piece of software and we hadn't thought enough about distribution. While we built this great piece of software, our competitor at the time, Naviance, had secured distribution through all the different college counselors. What piece of software are you going to choose to help your kid get into college? The one recommended by the college counselors or the one from two kids at Stanford? I think it's a pretty easy choice. So we saw very early that we had no distribution advantage. Even if we loved our software, people weren't going to use it because we didn't have a scalable way to get it in people's hands. Around that time when we saw the emergence of the App Store on iPhone, it was very clear that was a distribution channel we could really use and benefit from. But we also needed to build things we could build quickly, things we really were going to use together with our friends so we could be the first early customers. Ultimately Peekaboo and Snapchat represented that." This is exactly the asymmetry Peter Thiel describes in Zero to One: superior distribution by itself can create a monopoly, even with no product differentiation. The converse is not true. Thiel puts an even finer point on it: most businesses get zero distribution channels to work. Poor sales rather than bad product is the most common cause of failure. If you can get just one distribution channel to work, you have a great business. Estée Lauder said: it's not enough to have the most wonderful product in the world. You must be able to sell it. Many founders over-index on product perfection and under-invest in distribution. The world is full of great products nobody knows about, and mediocre products with massive distribution that dominate markets. Evan Spiegel lived it. He built the better product, watched it lose, and then built something he could actually distribute.
1:27

Evan Spiegel on the lesson that killed his first startup and led to Snapchat: "We focused on building the perfect product for way too long before we got feedback. We worked for like eighteen months to build this perfect full-featured product, which was in direct contravention to how I was always taught to build things. Build a prototype, build an MVP, get it in front of people, learn as quickly as possible. But we had spent all this time building this perfect piece of software and we hadn't thought enough about distribution. While we built this great piece of software, our competitor at the time, Naviance, had secured distribution through all the different college counselors. What piece of software are you going to choose to help your kid get into college? The one recommended by the college counselors or the one from two kids at Stanford? I think it's a pretty easy choice. So we saw very early that we had no distribution advantage. Even if we loved our software, people weren't going to use it because we didn't have a scalable way to get it in people's hands. Around that time when we saw the emergence of the App Store on iPhone, it was very clear that was a distribution channel we could really use and benefit from. But we also needed to build things we could build quickly, things we really were going to use together with our friends so we could be the first early customers. Ultimately Peekaboo and Snapchat represented that." This is exactly the asymmetry Peter Thiel describes in Zero to One: superior distribution by itself can create a monopoly, even with no product differentiation. The converse is not true. Thiel puts an even finer point on it: most businesses get zero distribution channels to work. Poor sales rather than bad product is the most common cause of failure. If you can get just one distribution channel to work, you have a great business. Estée Lauder said: it's not enough to have the most wonderful product in the world. You must be able to sell it. Many founders over-index on product perfection and under-invest in distribution. The world is full of great products nobody knows about, and mediocre products with massive distribution that dominate markets. Evan Spiegel lived it. He built the better product, watched it lose, and then built something he could actually distribute.

David Senra

27,043 просмотров • 4 месяцев назад

Our mainstream culture is conflict-avoidant. There is the assumption that the less conflict there is in a relationship, the better it is. I disagree. If there is real intimacy, conflict is actually unavoidable. Because we are all different. The real indicator of health in a relationship isn’t the lack of conflict, it is the quality of our repair. It is the level of authenticity we can bring. That requires knowing how to be with conflict and disagreement, how to hold nuance. And it also requires practicing the art of repairing. Are we willing to show up and repair what we broke? Do we have the skills and capacity required for that? Avoiding conflict means avoiding truth and therefore avoiding real intimacy. This work is essential and transcends the personal. If we aren't capable of dealing with conflict in our own personal lives, it is no wonder that the world is in the state it is, where the most prevalent conflict management strategy is escalation.
0:59

Our mainstream culture is conflict-avoidant. There is the assumption that the less conflict there is in a relationship, the better it is. I disagree. If there is real intimacy, conflict is actually unavoidable. Because we are all different. The real indicator of health in a relationship isn’t the lack of conflict, it is the quality of our repair. It is the level of authenticity we can bring. That requires knowing how to be with conflict and disagreement, how to hold nuance. And it also requires practicing the art of repairing. Are we willing to show up and repair what we broke? Do we have the skills and capacity required for that? Avoiding conflict means avoiding truth and therefore avoiding real intimacy. This work is essential and transcends the personal. If we aren't capable of dealing with conflict in our own personal lives, it is no wonder that the world is in the state it is, where the most prevalent conflict management strategy is escalation.

Laura Cincera

10,933 просмотров • 5 месяцев назад

Keir Starmer: We need to deal with AI bots. This is something relatively new, and we saw with Grok—did you see the thing with Grok just the other week? An AI bot that allowed you to instruct it to undress people—and it did. It was disgusting, absolutely disgusting. We went into battle on that because I thought this is not good enough. We went into battle, we made the necessary steps, we threatened action, and we won that battle in relation to Grok. But we've got to do it with all AI bots, and we will do it. We can do that by amending some of the legislation that we've already got in place.
0:40

Keir Starmer: We need to deal with AI bots. This is something relatively new, and we saw with Grok—did you see the thing with Grok just the other week? An AI bot that allowed you to instruct it to undress people—and it did. It was disgusting, absolutely disgusting. We went into battle on that because I thought this is not good enough. We went into battle, we made the necessary steps, we threatened action, and we won that battle in relation to Grok. But we've got to do it with all AI bots, and we will do it. We can do that by amending some of the legislation that we've already got in place.

Clash Report

63,266 просмотров • 6 месяцев назад

Jensen to AI Leaders: “We have to be far more thoughtful” when communicating to the public Jensen Huang: “(AI) is not a biological being. It is not alien. It is not conscious. It is computer software.” “We say things like, ‘We don't understand it at all.’ It is not true. We understand a lot of things about this technology.” Chamath: “If you were in the seat in the boardroom of Anthropic over that whole scuttlebutt with the Department of War, what do you think you would've told Dario and that team to do, maybe, differently to try to change some of this outcome and some of this perception?” Jensen: “The first thing that I would say about Anthropic is, first of all, the technology is incredible. We are a large consumer of Anthropic technology.” “The desire to warn people about the capability of the technology is also really terrific.” “We just have to make sure that we understand that the world has a spectrum, and that warning is good, scaring is less good because this technology is too important to us.” “I think that it is fine to predict the future, but we need to be a little bit more circumspect. We need to have a little bit more humility, that, in fact, we can't completely predict the future.” “And to say things that are quite extreme, quite catastrophic, that there's no evidence of it happening, could be more damaging than people think.” “And of course we are technology leaders.” “There was a time when nobody listened to us, but now because technology is so important in the social fabric, such an important industry, so important to national security, our words do matter.” “And I think we have to be much more circumspect, we have to be more moderate, we have to be more balanced, we have to be far more thoughtful.”
1:27

Jensen to AI Leaders: “We have to be far more thoughtful” when communicating to the public Jensen Huang: “(AI) is not a biological being. It is not alien. It is not conscious. It is computer software.” “We say things like, ‘We don't understand it at all.’ It is not true. We understand a lot of things about this technology.” Chamath: “If you were in the seat in the boardroom of Anthropic over that whole scuttlebutt with the Department of War, what do you think you would've told Dario and that team to do, maybe, differently to try to change some of this outcome and some of this perception?” Jensen: “The first thing that I would say about Anthropic is, first of all, the technology is incredible. We are a large consumer of Anthropic technology.” “The desire to warn people about the capability of the technology is also really terrific.” “We just have to make sure that we understand that the world has a spectrum, and that warning is good, scaring is less good because this technology is too important to us.” “I think that it is fine to predict the future, but we need to be a little bit more circumspect. We need to have a little bit more humility, that, in fact, we can't completely predict the future.” “And to say things that are quite extreme, quite catastrophic, that there's no evidence of it happening, could be more damaging than people think.” “And of course we are technology leaders.” “There was a time when nobody listened to us, but now because technology is so important in the social fabric, such an important industry, so important to national security, our words do matter.” “And I think we have to be much more circumspect, we have to be more moderate, we have to be more balanced, we have to be far more thoughtful.”

The All-In Podcast

57,581 просмотров • 5 месяцев назад

$ABCL CEO Carl Hansen explains the net negative overall value creation in biotech and how AbCellera plans to beat it: “I really think it can be beat because there’s a lot of mistakes that get made in where you allocate capital.” “If you’re a biotech and you start a company on a drug, and you go public and have a drug, and now the data is looking not that great, you just keep running that drug. … Because if you quit that drug, the company is done.” “So, because you’re so concentrated on one thing, you end up having blinders. It’s like a cult of a molecule. And even a real, practical, capital access problem that makes you continue to move things forward” ______________________________________ “Another problem is that many of the drugs that get started, get started by people who don’t understand the competitive or commercial landscape and have no intent of ever actually manufacturing it. … Because they know someone else is going to buy it. So then their framework is not ‘Am I making a drug that’s going to make a difference for people?’ The framework is ‘Can I make something that I think someone will take off my hands?’ And that happens a lot.” “There are many acquisitions where a big pharma company spends $10B, $20B, and it’s a complete bust. So really no value is generated for patients but someone was able to get a good exit on that because they anticipated what someone would want. And a lot of decision making gets done like that”. _______________________________________ “I’m not saying that we have this all solved. But what we’re trying to do is create a framework where we are able to take many bets so that we don’t fall in love with anything, or we don’t have to fall in love with anything. … And then always hold up very explicitly what we know and what we don’t know along the dimensions that matter. The dimensions that matter are - Will it work? That’s a science. - When it gets where will people care? - Is it differentiated? - Does it solve a big problem? In order to get it there, is there a path with our resources and expertise that would allow us to see it through?” “When you start to hold things up like that, you start to see where the mistakes are, where the uncertainties are, and you can be more rational in deciding ‘We’re going to run it to here because we get to flip the card and if the card goes the wrong way we’re going to kill it because we’ve got something else behind it.’” “I do think that if done right, and if you can pick the right opportunities, the success rate can be well higher than an order of magnitude better. … And there are examples of this… companies I’ve mentioned, you know, Regeneron, their success rate is at least 10x the industry in bringing programs forward and getting them approved. … So it’s… you can do it better that way”
3:50

$ABCL CEO Carl Hansen explains the net negative overall value creation in biotech and how AbCellera plans to beat it: “I really think it can be beat because there’s a lot of mistakes that get made in where you allocate capital.” “If you’re a biotech and you start a company on a drug, and you go public and have a drug, and now the data is looking not that great, you just keep running that drug. … Because if you quit that drug, the company is done.” “So, because you’re so concentrated on one thing, you end up having blinders. It’s like a cult of a molecule. And even a real, practical, capital access problem that makes you continue to move things forward” ______________________________________ “Another problem is that many of the drugs that get started, get started by people who don’t understand the competitive or commercial landscape and have no intent of ever actually manufacturing it. … Because they know someone else is going to buy it. So then their framework is not ‘Am I making a drug that’s going to make a difference for people?’ The framework is ‘Can I make something that I think someone will take off my hands?’ And that happens a lot.” “There are many acquisitions where a big pharma company spends $10B, $20B, and it’s a complete bust. So really no value is generated for patients but someone was able to get a good exit on that because they anticipated what someone would want. And a lot of decision making gets done like that”. _______________________________________ “I’m not saying that we have this all solved. But what we’re trying to do is create a framework where we are able to take many bets so that we don’t fall in love with anything, or we don’t have to fall in love with anything. … And then always hold up very explicitly what we know and what we don’t know along the dimensions that matter. The dimensions that matter are - Will it work? That’s a science. - When it gets where will people care? - Is it differentiated? - Does it solve a big problem? In order to get it there, is there a path with our resources and expertise that would allow us to see it through?” “When you start to hold things up like that, you start to see where the mistakes are, where the uncertainties are, and you can be more rational in deciding ‘We’re going to run it to here because we get to flip the card and if the card goes the wrong way we’re going to kill it because we’ve got something else behind it.’” “I do think that if done right, and if you can pick the right opportunities, the success rate can be well higher than an order of magnitude better. … And there are examples of this… companies I’ve mentioned, you know, Regeneron, their success rate is at least 10x the industry in bringing programs forward and getting them approved. … So it’s… you can do it better that way”

Jack Prescott

27,317 просмотров • 18 дней назад

Sam Altman's new interview: AI should not be designed to pursue goals that are disconnected from human needs. People must remain at the center of AI development. “I have no interest in building a super-smart AI that accomplishes some non-human goals. People should react. People should say, ‘Hey, this is what I want, and this is what I do not want.’ I do not think the issue is that we have failed to explain the benefits. We say, ‘AI is going to cure a bunch of diseases,’ and people say, ‘Okay, that is great, but that is not really my question. My question is: What is my role in the future? What is my economic future? What is my agency? How do I know that my kids and my family will still be able to have fulfilling, creative expression, struggle, drive the world forward, grow, and do this thing together in a way that has worked for a long time?’ When people in AI say, ‘Sure, there are going to be no jobs,’ or ‘50% of jobs are going to go away,’ or ‘90% of jobs are going to go away,’ and ‘AI is going to be smarter than you at everything,’ and ‘We will give you some basic income, but you are not really going to have a role,’ that is horrible. And by the way, if an AI company says, ‘Maybe we are going to destroy all the jobs, and we will be the most valuable company in the world,’ people should look at you like, ‘Yeah, that is a terrible message.’ I do not think the problem is that we have not articulated the upsides. I think people actually believe us. They hear, ‘AI may cure your cancer,’ and they think, ‘That sounds great.’ I think we, as an industry, have failed to explain how people stay in control of determining the future at every step, and how people can still have a meaningful life in all the ways we care about.” ---- From "CNBC Television" YouTube channel, (link in comment)
1:28

Sam Altman's new interview: AI should not be designed to pursue goals that are disconnected from human needs. People must remain at the center of AI development. “I have no interest in building a super-smart AI that accomplishes some non-human goals. People should react. People should say, ‘Hey, this is what I want, and this is what I do not want.’ I do not think the issue is that we have failed to explain the benefits. We say, ‘AI is going to cure a bunch of diseases,’ and people say, ‘Okay, that is great, but that is not really my question. My question is: What is my role in the future? What is my economic future? What is my agency? How do I know that my kids and my family will still be able to have fulfilling, creative expression, struggle, drive the world forward, grow, and do this thing together in a way that has worked for a long time?’ When people in AI say, ‘Sure, there are going to be no jobs,’ or ‘50% of jobs are going to go away,’ or ‘90% of jobs are going to go away,’ and ‘AI is going to be smarter than you at everything,’ and ‘We will give you some basic income, but you are not really going to have a role,’ that is horrible. And by the way, if an AI company says, ‘Maybe we are going to destroy all the jobs, and we will be the most valuable company in the world,’ people should look at you like, ‘Yeah, that is a terrible message.’ I do not think the problem is that we have not articulated the upsides. I think people actually believe us. They hear, ‘AI may cure your cancer,’ and they think, ‘That sounds great.’ I think we, as an industry, have failed to explain how people stay in control of determining the future at every step, and how people can still have a meaningful life in all the ways we care about.” ---- From "CNBC Television" YouTube channel, (link in comment)

Rohan Paul

79,111 просмотров • 2 месяцев назад

Sam Altman reveals building Codex was a "crazy kamikaze mission" to beat Claude Code and that most of the best coders he knows now use Codex. "We were way behind Claude Code, and it seemed like a kind of crazy kamikaze mission to try to beat them with a coding app." "The consensus is that this kind of thing never works, and you just move on to the next one. It's a fool's errand to try to win when someone else already has momentum in a particular product category." "But we decided we thought it was really important. We asked a team to do it, and they performed a legitimate, unbelievable, very rare in the history of business thing." "Now it is the product that most of the best coders I know use." "That felt like an impossible thing, but if we hadn't asked the team, hey, we have a really important but extremely hard mission for you, it just wouldn't have happened."
0:58

Sam Altman reveals building Codex was a "crazy kamikaze mission" to beat Claude Code and that most of the best coders he knows now use Codex. "We were way behind Claude Code, and it seemed like a kind of crazy kamikaze mission to try to beat them with a coding app." "The consensus is that this kind of thing never works, and you just move on to the next one. It's a fool's errand to try to win when someone else already has momentum in a particular product category." "But we decided we thought it was really important. We asked a team to do it, and they performed a legitimate, unbelievable, very rare in the history of business thing." "Now it is the product that most of the best coders I know use." "That felt like an impossible thing, but if we hadn't asked the team, hey, we have a really important but extremely hard mission for you, it just wouldn't have happened."

Fireside Alpha

1,261,432 просмотров • 25 дней назад

Maple is preparing for the release of a co-working agent. You install it locally and it works with your files, whether it's office work or building websites and apps. It's a turnkey solution, as easy as Claude Code, that keeps your data secure and private, no data sharing with closed AI labs. This is THE sovereign AI app for individuals and businesses who want powerful AI while retaining ownership of their information. Why build an agent into the Maple app when other agents already exist? Easy, we want to give you control over your work. We don't have a business plan that incorporates making money off our users' data. In the age of AI, your information, whether it's personal or company trade secrets, is the single thing that differentiates you from everyone else. We all have access to AI that can build a professional website for selling shoes. But your strategy and network for how you sell shoes should not be shared with your competitors. Sovereignty is the path to protecting what makes you, you. Maple sits at the intersection of Usability and Sovereignty. Maple gives you the best tools that are both easy to use and maintain your data sovereignty. Sovereign for one, sovereign for all. It has been a journey to get here. We brought to market the very first personal chatbot with end-to-end encryption using TEEs in late 2024. Prior to that there were proofs of concept but no full product offerings. Every other AI chat product on the market handled your data in plain text, either selling you a service to get your data or asking you to trust that they won't snoop on you. Quickly people found Maple and latched onto its open-source code and verifiable encryption. We didn't stop there. You may remember earlier this year we teased a product called "Maple Agent" and opened up a waiting list. That product is a mobile app that acts as your AI "friend", maintaining one long continuous chat, and getting to know you over time. I dislike using the word "friend" there, but it's the best way to convey the UX in a few words. AI is a tool, always has been, always will be. Any kind of friendly personality on top is just synthetic. In our testing, the UX of Maple Agent is really powerful for what it does. Think about the many short AI chats you have in your favorite app, whether it's looking up a historical fact or asking advice about a topic. With Maple Agent, those all go away in favor of the long-running chat with the friendly agent. It's like you have your own personal assistant who knows you so well and can look up anything for you. When I ask AI certain questions, I want to ask an expert who already understands my situation so I'm not repeating myself for the 100th time. That's the amazing value the personal agent brings to the table. We still see great utility for a personal agent like the "Maple Agent". Thousands of people on the waiting list, hoping to get their hands on it, agree that the concept is worth exploring and trying out. We were constrained in launching it due to a few circumstances, one of them being access to the scale of compute needed to power it. We have a clear path laid out for how to get there, but today is not the day to execute on that. It will be in the near future. Instead we have a different agent ready to go that we think is also incredible. We now have an agentic harness inside of the Maple Research app. This thing is a powerhouse. It even builds and publishes its own software releases. The agent in Maple Research works with your local filesystem, speaks to the largest open models running in TEEs, utilizes local models for certain tasks, is compatible with MCP tools, has an API for connecting to anything you need, and also supports the ACP protocol, which means it can be extended in the future to speak to other tools like Claude Code, Codex, and local models running on your own hardware. A big unlock for us was the Goose Development Kit, which powers the core of our agent harness. More on that to come as we publish articles and documentation later about the agent. The agent inside Maple Research doesn't have a name. At least not yet, not sure if it ever will. For now we call it "Chat Mode" and "Agent Mode". Think of this as the workhorse, the truck, the heavy lifter. Our other "Agent", the phone app, is your sidekick in your pocket, ready to help with quick things and ongoing conversations about life. I am incredibly excited about the Maple Research Agent. While I'm already seeing great results using it for internal work items, I'm especially thrilled about the personal health and wellness work it's doing for me. I know there are plenty of apps out there for compiling wellness data, but I'm having it build a tool tailored specifically for what I need, without the extra fluff. And none of my health data is being donated to the closed AI labs or sent to advertisers. I know that the AI logic is not being silently adjusted to fit the whims of a large corporation that has paid for product placement. It's me, state of the art AI, and my data. That's how I want it. Maple's new agent makes that possible. We can't wait for you to try it out. If you want early access, comment here, email us, reach out in some way. To those on the other agent waitlist, you're already in the queue. Thanks for reading this lengthy update. :)
0:49

Maple is preparing for the release of a co-working agent. You install it locally and it works with your files, whether it's office work or building websites and apps. It's a turnkey solution, as easy as Claude Code, that keeps your data secure and private, no data sharing with closed AI labs. This is THE sovereign AI app for individuals and businesses who want powerful AI while retaining ownership of their information. Why build an agent into the Maple app when other agents already exist? Easy, we want to give you control over your work. We don't have a business plan that incorporates making money off our users' data. In the age of AI, your information, whether it's personal or company trade secrets, is the single thing that differentiates you from everyone else. We all have access to AI that can build a professional website for selling shoes. But your strategy and network for how you sell shoes should not be shared with your competitors. Sovereignty is the path to protecting what makes you, you. Maple sits at the intersection of Usability and Sovereignty. Maple gives you the best tools that are both easy to use and maintain your data sovereignty. Sovereign for one, sovereign for all. It has been a journey to get here. We brought to market the very first personal chatbot with end-to-end encryption using TEEs in late 2024. Prior to that there were proofs of concept but no full product offerings. Every other AI chat product on the market handled your data in plain text, either selling you a service to get your data or asking you to trust that they won't snoop on you. Quickly people found Maple and latched onto its open-source code and verifiable encryption. We didn't stop there. You may remember earlier this year we teased a product called "Maple Agent" and opened up a waiting list. That product is a mobile app that acts as your AI "friend", maintaining one long continuous chat, and getting to know you over time. I dislike using the word "friend" there, but it's the best way to convey the UX in a few words. AI is a tool, always has been, always will be. Any kind of friendly personality on top is just synthetic. In our testing, the UX of Maple Agent is really powerful for what it does. Think about the many short AI chats you have in your favorite app, whether it's looking up a historical fact or asking advice about a topic. With Maple Agent, those all go away in favor of the long-running chat with the friendly agent. It's like you have your own personal assistant who knows you so well and can look up anything for you. When I ask AI certain questions, I want to ask an expert who already understands my situation so I'm not repeating myself for the 100th time. That's the amazing value the personal agent brings to the table. We still see great utility for a personal agent like the "Maple Agent". Thousands of people on the waiting list, hoping to get their hands on it, agree that the concept is worth exploring and trying out. We were constrained in launching it due to a few circumstances, one of them being access to the scale of compute needed to power it. We have a clear path laid out for how to get there, but today is not the day to execute on that. It will be in the near future. Instead we have a different agent ready to go that we think is also incredible. We now have an agentic harness inside of the Maple Research app. This thing is a powerhouse. It even builds and publishes its own software releases. The agent in Maple Research works with your local filesystem, speaks to the largest open models running in TEEs, utilizes local models for certain tasks, is compatible with MCP tools, has an API for connecting to anything you need, and also supports the ACP protocol, which means it can be extended in the future to speak to other tools like Claude Code, Codex, and local models running on your own hardware. A big unlock for us was the Goose Development Kit, which powers the core of our agent harness. More on that to come as we publish articles and documentation later about the agent. The agent inside Maple Research doesn't have a name. At least not yet, not sure if it ever will. For now we call it "Chat Mode" and "Agent Mode". Think of this as the workhorse, the truck, the heavy lifter. Our other "Agent", the phone app, is your sidekick in your pocket, ready to help with quick things and ongoing conversations about life. I am incredibly excited about the Maple Research Agent. While I'm already seeing great results using it for internal work items, I'm especially thrilled about the personal health and wellness work it's doing for me. I know there are plenty of apps out there for compiling wellness data, but I'm having it build a tool tailored specifically for what I need, without the extra fluff. And none of my health data is being donated to the closed AI labs or sent to advertisers. I know that the AI logic is not being silently adjusted to fit the whims of a large corporation that has paid for product placement. It's me, state of the art AI, and my data. That's how I want it. Maple's new agent makes that possible. We can't wait for you to try it out. If you want early access, comment here, email us, reach out in some way. To those on the other agent waitlist, you're already in the queue. Thanks for reading this lengthy update. :)

Mark

44,707 просмотров • 28 дней назад

Sam Altman says the AI infrastructure race is not about bigger chatbots. It is about shifting the planet's intellectual output from human brains to AI brains. "If people knew what we could do with compute, they would want way, way more." "The thing I am personally most excited about is to use AI and lots of compute to discover new science." "A recent cool example here is we built the Sora Android app using Codex... in less than a month." "You can imagine that way much further, where entire companies can build their products using lots of compute." Then he gives the scale: "Let's say that an AI company today might be generating something on the order of 10 trillion tokens a day out of frontier models." "We're going to have these models at a company be outputting more tokens per day than all of humanity put together, and then 10 times that, and then 100 times that." The bottleneck is moving from software talent to compute supply, inference speed, product integration, and where all that machine intelligence gets pointed.
3:31

Sam Altman says the AI infrastructure race is not about bigger chatbots. It is about shifting the planet's intellectual output from human brains to AI brains. "If people knew what we could do with compute, they would want way, way more." "The thing I am personally most excited about is to use AI and lots of compute to discover new science." "A recent cool example here is we built the Sora Android app using Codex... in less than a month." "You can imagine that way much further, where entire companies can build their products using lots of compute." Then he gives the scale: "Let's say that an AI company today might be generating something on the order of 10 trillion tokens a day out of frontier models." "We're going to have these models at a company be outputting more tokens per day than all of humanity put together, and then 10 times that, and then 100 times that." The bottleneck is moving from software talent to compute supply, inference speed, product integration, and where all that machine intelligence gets pointed.

Karl Mehta

16,619 просмотров • 1 месяц назад

Anthropic Technical Staff Jess Yan says the harness and the model cannot be pulled apart without giving up performance, though she flags her own bias. "I think I am quite biased but I also think that it is impossible to get the maximum possible performance without tying together the harness and the model." "Now the components of the harness and maybe the thickness of the harness will change over time as models get more and more capable." "However, when we test our models and when we are assessing their performance we always have to test it in conjunction with a harness." "And are we going to test it with all the different harnesses of the world? We're going to select the harnesses that we have built." "And so there is an aspect of the necessity of building models is that you have to be testing them with harnesses, and that sort of keeps them paired together."
0:46

Anthropic Technical Staff Jess Yan says the harness and the model cannot be pulled apart without giving up performance, though she flags her own bias. "I think I am quite biased but I also think that it is impossible to get the maximum possible performance without tying together the harness and the model." "Now the components of the harness and maybe the thickness of the harness will change over time as models get more and more capable." "However, when we test our models and when we are assessing their performance we always have to test it in conjunction with a harness." "And are we going to test it with all the different harnesses of the world? We're going to select the harnesses that we have built." "And so there is an aspect of the necessity of building models is that you have to be testing them with harnesses, and that sort of keeps them paired together."

Fireside Alpha

583,614 просмотров • 18 дней назад

“What I think SPX is, is a wake-up call. And I think for the normie, the average person, it literally is best described as being the next Bitcoin, because that's literally what it is. Bitcoin was a wake-up call to show people that value is subjective. And SPX is the next iteration of that. And once you get enough people to understand that the value of the dollar is subjective. It only has value because people believe in it. Bitcoin only has value because people believe in it. SPX has value because people believe in it. And the next step is Well, it's not just money that is subjective in value. It is literally everything is subjective. The entire universe is this subjective entity that is created from our own consciousness. And that's what Like, the purpose of this vehicle, yes, it's going to make a lot of people a lot of money, but the point of that is to wake people up to the fact that the entire universe is this subjective entity. It is not just this, like, empirical machine with interlocking gears and like this orderly machine that proceeds from just like the sum of its parts like no like we are literally the universe creating the universe and that's what spx is meant to wake people up to.” — Crypto Maxi 💹🧲
1:36

“What I think SPX is, is a wake-up call. And I think for the normie, the average person, it literally is best described as being the next Bitcoin, because that's literally what it is. Bitcoin was a wake-up call to show people that value is subjective. And SPX is the next iteration of that. And once you get enough people to understand that the value of the dollar is subjective. It only has value because people believe in it. Bitcoin only has value because people believe in it. SPX has value because people believe in it. And the next step is Well, it's not just money that is subjective in value. It is literally everything is subjective. The entire universe is this subjective entity that is created from our own consciousness. And that's what Like, the purpose of this vehicle, yes, it's going to make a lot of people a lot of money, but the point of that is to wake people up to the fact that the entire universe is this subjective entity. It is not just this, like, empirical machine with interlocking gears and like this orderly machine that proceeds from just like the sum of its parts like no like we are literally the universe creating the universe and that's what spx is meant to wake people up to.” — Crypto Maxi 💹🧲

Tanz Cho 💹🧲

12,294 просмотров • 1 месяц назад