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AI is code, and now that AI can code, we can close the self-improvement loop. GV is proud to co-lead the early round for @recursive_si as they build systems that safely automate the scientific method to achieve superintelligence. Congrats @richardsocher & team!

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15,404 görüntüleme • 1 ay önce •via X (Twitter)

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AI researcher Prof. Roman Yampolskiy: 100% of code for the most powerful AIs is now written by AI, an early form of recursive self-improvement. He says it's a hyperexponential process that results in superintelligent AI, "machine gods", which we won't be able to control.
1:24

AI researcher Prof. Roman Yampolskiy: 100% of code for the most powerful AIs is now written by AI, an early form of recursive self-improvement. He says it's a hyperexponential process that results in superintelligent AI, "machine gods", which we won't be able to control.

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"To build a great company, you need to write code and talk to users." - Florian Juengermann (co-founder of Listen Labs) "AI agents can now write code, so what becomes important is building the right thing and having the right feedback." "That's what we are building: telling the AI what to do, what to build, and being the tastemaker."
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"To build a great company, you need to write code and talk to users." - Florian Juengermann (co-founder of Listen Labs) "AI agents can now write code, so what becomes important is building the right thing and having the right feedback." "That's what we are building: telling the AI what to do, what to build, and being the tastemaker."

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Now that AI has enabled designers to code, is "design in code" a thing? Can we drop Figma altogether? 👇
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Today we are proud to emerge from stealth as Collaborative Computing Inc. Our mission is to build collaborative computing environments for humans and AI that expand what we can achieve. Atelier is our first product.
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Today we are proud to emerge from stealth as Collaborative Computing Inc. Our mission is to build collaborative computing environments for humans and AI that expand what we can achieve. Atelier is our first product.

Austin Huang

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Mark Zuckerberg says the most exciting development is seeing early signs of model self-improvement, bringing superintelligence into view. He believes superintelligence could arrive within two to three years—and Meta is preparing for that. Meta’s goal is to deliver personal superintelligence—AI that empowers every individual. He emphasizes this approach is different from other labs, aiming to put power in people’s hands, not just centralized systems.
2:06

Mark Zuckerberg says the most exciting development is seeing early signs of model self-improvement, bringing superintelligence into view. He believes superintelligence could arrive within two to three years—and Meta is preparing for that. Meta’s goal is to deliver personal superintelligence—AI that empowers every individual. He emphasizes this approach is different from other labs, aiming to put power in people’s hands, not just centralized systems.

Wes Roth

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AI can now generate high-quality textures for 3D objects! The method is called Material Anything and can generate realistic materials which are UV mapped. Small AI driven game studios are going to be the future. Code below 👇
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AI can now generate high-quality textures for 3D objects! The method is called Material Anything and can generate realistic materials which are UV mapped. Small AI driven game studios are going to be the future. Code below 👇

Dreaming Tulpa 🥓👑

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Dario Amodei says Nobel-laureate-level AI (Superintelligence) by 2026–27 still looks surprisingly close - and the turbocharger is a feedback loop where AI writes code and accelerates AI research to build even better models. He thinks full end-to-end AI software engineering could be just 6–12 months away - meaning the pace might jump from “fast” to “holy shit.”
1:45

Dario Amodei says Nobel-laureate-level AI (Superintelligence) by 2026–27 still looks surprisingly close - and the turbocharger is a feedback loop where AI writes code and accelerates AI research to build even better models. He thinks full end-to-end AI software engineering could be just 6–12 months away - meaning the pace might jump from “fast” to “holy shit.”

Chubby♨️

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Nobody is writing 90% of their code using AI. Here's the uncomfortable truth: The real productivity gain from using AI to write code is closer to 10%, nowhere near the 90% people claim. Sundar Pichai said in 2024 that 30% of the new code at Google was AI-generated. However, he went on to admit, during Lex Friedman's podcast, that engineering velocity had only increased by about 10%. AI-generated code isn't free code. It still has to be reviewed, tested, and made production-ready. Optimizing a single step (code generation) doesn't boost output if bottlenecks shift elsewhere (code reviews). It doesn't matter how much code you generate if you can't keep up the review process. The solution: Automate as much as you can the review and verification of your code. I'm working with Sonar, who is sponsoring this post, and they will take care of the code quality and security analysis of your code: • They review over 300B lines of code every single day • They cover reliability, security, and maintainability for your code • You can integrate them into your CI/CD pipeline • You can install them in your IDE (I use their VSCode extension) • Support for more than 30 languages Here is a link so you can check them out:
4:42

Nobody is writing 90% of their code using AI. Here's the uncomfortable truth: The real productivity gain from using AI to write code is closer to 10%, nowhere near the 90% people claim. Sundar Pichai said in 2024 that 30% of the new code at Google was AI-generated. However, he went on to admit, during Lex Friedman's podcast, that engineering velocity had only increased by about 10%. AI-generated code isn't free code. It still has to be reviewed, tested, and made production-ready. Optimizing a single step (code generation) doesn't boost output if bottlenecks shift elsewhere (code reviews). It doesn't matter how much code you generate if you can't keep up the review process. The solution: Automate as much as you can the review and verification of your code. I'm working with Sonar, who is sponsoring this post, and they will take care of the code quality and security analysis of your code: • They review over 300B lines of code every single day • They cover reliability, security, and maintainability for your code • You can integrate them into your CI/CD pipeline • You can install them in your IDE (I use their VSCode extension) • Support for more than 30 languages Here is a link so you can check them out:

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Agentin AI (Agentin AI) is building AI agents that connect with CRM and ERP systems to automate the entire Order-to-Cash process, eliminating manual tasks, data errors, and payment delays for businesses. Congrats on the launch, Sankeerth Rao Karingula, Ph.D.!
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Agentin AI (Agentin AI) is building AI agents that connect with CRM and ERP systems to automate the entire Order-to-Cash process, eliminating manual tasks, data errors, and payment delays for businesses. Congrats on the launch, Sankeerth Rao Karingula, Ph.D.!

Y Combinator

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“Math is code. And code is math.” Carina Hong CEO Axiom on why that idea matters for AI: “For centuries, mathematicians reasoned in natural language. But because of the Curry–Howard correspondence, a proof can also be a program.” “You can translate natural-language math into formal code using systems like Lean. Lean is both a theorem-proving language and a programming language.” “That means you can generate solutions as code and then formally verify them. You can even use the same system to verify programs themselves.” “This creates a flywheel of generation and verification, where AI can both write solutions and prove that they’re correct.”
2:25

“Math is code. And code is math.” Carina Hong CEO Axiom on why that idea matters for AI: “For centuries, mathematicians reasoned in natural language. But because of the Curry–Howard correspondence, a proof can also be a program.” “You can translate natural-language math into formal code using systems like Lean. Lean is both a theorem-proving language and a programming language.” “That means you can generate solutions as code and then formally verify them. You can even use the same system to verify programs themselves.” “This creates a flywheel of generation and verification, where AI can both write solutions and prove that they’re correct.”

Forward Future

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Dario Amodei just announced the end of software engineering as a profession. The timeline is 6 to 12 months. Amodei: “I have engineers within Anthropic who say, I don’t write any code anymore. I just let the model write the code. I edit it.” Not a prediction. Current reality inside the frontier lab. The engineers who built the most advanced AI in the world have stopped writing code. They supervise. They edit. They manage architecture. The craft they spent careers mastering has been handed to the system they built. Amodei says models will do most, maybe all, of what software engineers do end-to-end within six to twelve months. Not assisting. Not autocompleting. Handling the entire development process independently. If you are learning syntax today, you are learning a dead language. Amodei: “Then it’s a question of how fast does that loop close?” The loop is this. AI writes code. Code builds better AI. Better AI writes better code. Faster. Without sleep. Without the cognitive limits that cap how quickly any human engineer can work. Once that loop closes, technological progress stops being constrained by human output. It becomes self-sustaining. Exponential. Operating at a pace no human workforce can match or direct. Software engineering isn’t ending. It’s becoming supervision. The developers who survive won’t be the best coders. They’ll be the best supervisors. The ones who can direct AI output, catch its failures, and architect what it builds toward. The skill that matters stops being implementation. It becomes judgment. Most developers are still optimizing for a skillset about to become as obsolete as stenography. While the people who built the systems replacing them already stopped doing the work themselves. The window to develop that judgment before the loop closes is exactly as long as Amodei’s timeline. Six to twelve months.
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Dario Amodei just announced the end of software engineering as a profession. The timeline is 6 to 12 months. Amodei: “I have engineers within Anthropic who say, I don’t write any code anymore. I just let the model write the code. I edit it.” Not a prediction. Current reality inside the frontier lab. The engineers who built the most advanced AI in the world have stopped writing code. They supervise. They edit. They manage architecture. The craft they spent careers mastering has been handed to the system they built. Amodei says models will do most, maybe all, of what software engineers do end-to-end within six to twelve months. Not assisting. Not autocompleting. Handling the entire development process independently. If you are learning syntax today, you are learning a dead language. Amodei: “Then it’s a question of how fast does that loop close?” The loop is this. AI writes code. Code builds better AI. Better AI writes better code. Faster. Without sleep. Without the cognitive limits that cap how quickly any human engineer can work. Once that loop closes, technological progress stops being constrained by human output. It becomes self-sustaining. Exponential. Operating at a pace no human workforce can match or direct. Software engineering isn’t ending. It’s becoming supervision. The developers who survive won’t be the best coders. They’ll be the best supervisors. The ones who can direct AI output, catch its failures, and architect what it builds toward. The skill that matters stops being implementation. It becomes judgment. Most developers are still optimizing for a skillset about to become as obsolete as stenography. While the people who built the systems replacing them already stopped doing the work themselves. The window to develop that judgment before the loop closes is exactly as long as Amodei’s timeline. Six to twelve months.

Dustin

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Databricks CEO and co-founder Ali Ghodsi joined Bloomberg Technology to discuss the launch of Genie Code, an autonomous AI agent built specifically for data teams. "Just six months ago, we were talking about autocompleting code — now agents automate the code. The new question is: how do we take the code that’s been written into production and make sure we're monitoring it?" Watch the full conversation
5:15

Databricks CEO and co-founder Ali Ghodsi joined Bloomberg Technology to discuss the launch of Genie Code, an autonomous AI agent built specifically for data teams. "Just six months ago, we were talking about autocompleting code — now agents automate the code. The new question is: how do we take the code that’s been written into production and make sure we're monitoring it?" Watch the full conversation

Databricks

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AI companies are racing to build superintelligent AI, despite its many risks. Let's take our future back. 📝 Sign the Superintelligence Statement and join the growing call to ban the reckless development of superintelligence, until it can be made safely. #KeepTheFutureHuman
2:56

AI companies are racing to build superintelligent AI, despite its many risks. Let's take our future back. 📝 Sign the Superintelligence Statement and join the growing call to ban the reckless development of superintelligence, until it can be made safely. #KeepTheFutureHuman

Future of Life Institute

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Today we're launching REVIEW.FAST, speeding up human review of AI generated code 3X. AI changed the world, sped up writing code, but shifted the bottleneck to review. If you can speed up code review, you can ship more. It's as simple as that.
1:37

Today we're launching REVIEW.FAST, speeding up human review of AI generated code 3X. AI changed the world, sped up writing code, but shifted the bottleneck to review. If you can speed up code review, you can ship more. It's as simple as that.

Louis Knight-Webb

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Let's face it: AI can check your code 100x faster and catch 10x more issues than you can. "Code reviews" as a widespread practice is not coming back. There are only two reasons we should consider code reviews today: 1. To transfer knowledge within a team. 2. To ensure AI didn't miss critical aspects in the code. We are getting closer to a point where manually reviewing code will be as relevant as punching holes in a punch card. Here is one idea for you:
0:40

Let's face it: AI can check your code 100x faster and catch 10x more issues than you can. "Code reviews" as a widespread practice is not coming back. There are only two reasons we should consider code reviews today: 1. To transfer knowledge within a team. 2. To ensure AI didn't miss critical aspects in the code. We are getting closer to a point where manually reviewing code will be as relevant as punching holes in a punch card. Here is one idea for you:

Santiago

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Can schools prepare students for the AI‑driven era? Huawei says yes. By turning complex code into hands‑on practice, students can build AI recognition, classification, and tracking systems that create real‑world impact. Discover the future of learning from MWC 2026 Barcelona.
1:42

Can schools prepare students for the AI‑driven era? Huawei says yes. By turning complex code into hands‑on practice, students can build AI recognition, classification, and tracking systems that create real‑world impact. Discover the future of learning from MWC 2026 Barcelona.

Huawei

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Announcing Agent Composer: AI that works when it actually IS rocket science. Technical teams can now automate the routine (but complex) tasks that used to take hours every week—root cause analysis, production planning, test code generation— and reduce them down to minutes, so you can get your real work done. Here's how we solved the AI context problem for hard engineering tasks (like rocket science 🚀) 🧵
2:19

Announcing Agent Composer: AI that works when it actually IS rocket science. Technical teams can now automate the routine (but complex) tasks that used to take hours every week—root cause analysis, production planning, test code generation— and reduce them down to minutes, so you can get your real work done. Here's how we solved the AI context problem for hard engineering tasks (like rocket science 🚀) 🧵

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OpenAI’s chief scientist says they want to build AI that can automate research. And to be honest, it doesn’t feel that far away.
1:35

OpenAI’s chief scientist says they want to build AI that can automate research. And to be honest, it doesn’t feel that far away.

Chubby♨️

33,631 görüntüleme • 8 ay önce

Dario Amodei says the spark was seeing engineers stop writing code and start supervising it. Inside Anthropic, Claude writes much of the software, and humans review like editors. The twist is meta: some of that code helps build the next Claude. That’s the self-improvement loop tightening, says Dario Amodei.
0:49

Dario Amodei says the spark was seeing engineers stop writing code and start supervising it. Inside Anthropic, Claude writes much of the software, and humans review like editors. The twist is meta: some of that code helps build the next Claude. That’s the self-improvement loop tightening, says Dario Amodei.

Wes Roth

87,585 görüntüleme • 4 ay önce

108 workflow templates you can use to build AI applications without writing any code. You can use these templates with n8n. I recorded the attached video to show you how it works. n8n is the workhorse behind an open-source, self-hosted AI starter kit you can install on your computer. They are sponsoring this post. Here is the link to the starter kit repository: And here is the spreadsheet with the 108 templates: Whatever idea you have, search for something similar in the list of templates, and you'll save a ton of time. Lately, I've talked to many non-coders who want to start using AI more seriously to build things. n8n is perfect for that.
5:36

108 workflow templates you can use to build AI applications without writing any code. You can use these templates with n8n. I recorded the attached video to show you how it works. n8n is the workhorse behind an open-source, self-hosted AI starter kit you can install on your computer. They are sponsoring this post. Here is the link to the starter kit repository: And here is the spreadsheet with the 108 templates: Whatever idea you have, search for something similar in the list of templates, and you'll save a ton of time. Lately, I've talked to many non-coders who want to start using AI more seriously to build things. n8n is perfect for that.

Santiago

78,133 görüntüleme • 1 yıl önce