Gregory Renard @Redo

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Demis Hassabis: "In the near future, one person who knows AI will outperform an entire startup team" I've watched hundreds of AI talks, this 60-minute Cambridge lecture is the one I wish I had seen a year ago this is the Nobel Prize winner in Chemistry, CEO of Google DeepMind and the guy who made AI solve biology here's the part I can't stop thinking about: > the AI you're using today is the dumbest it will ever be > in 5 years the gap between people using AI and people who aren't will be impossible to hide > companies will run on 10 people doing what 200 used to do > the ones who get there first won't be the smartest, they'll be the ones who started right now right now the average person opens Claude, types something, gets an answer, closes the tab they think they're using AI, but they're using maybe 10% of it the 10 people doing the work of 200 won't be typing prompts, they'll be running agents that's exactly why I put together a step-by-step guide on building your first AI agent agents are the part of AI moving fastest right now, full walkthrough in the article below

Anatoli Kopadze @AnatoliKopadze

2 weeks ago

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Sam Altman, OpenAI CEO: "with an affordable amount of spend on tokens, you can do what a 100-person incredibly great engineering team would do as a startup." in this 40-minute Stanford talk, he breaks down the exact shift that lets a solo founder out-build a 100-person team. free. straight from the Stanford stage. worth more than a $2,000 startup accelerator. so i stopped arguing and built one. local agents. local tool. nothing leaving my laptop. an Obsidian clone, a knowledge graph, 13 agents a full second brain. solo. what a whole team would've shipped. minus the team. minus the cloud. here's the shift he breaks down and what i found building on it: - why tokens replaced headcount - the "one-person frontier lab" model ; your second brain is the lab - the inference layer every founder is sleeping on - why hiring 100 engineers is now the expensive way to build the 100-person team didn't get cheaper. it became one person, a second brain, and a swarm of agents. bookmark this. the full build is in the article below ⬇️

Avid @Av1dlive

a week ago

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🤯 GLM-5.2 is here — built for long-horizon coding and agentic tasks, now with a solid 1M-token context. The strongest open-source coding model yet! Available now on Ollama's cloud, hosted in the US on the latest @NVIDIAAI Blackwell datacenter GPUs. Privacy policy and zero data retention apply, as always. Try it 👇 Claude Code: ollama launch claude --model glm-5.2:cloud Codex App: ollama launch codex-app --model glm-5.2:cloud Hermes Agent: ollama launch hermes --model glm-5.2:cloud Chat: ollama run glm-5.2:cloud More integrations and information in the model page 🧵

Z.ai @Zai_org

4 days ago

Introducing GLM-5.2: Frontier Intelligence, Open Weights - Significant improvements in coding and agentic tasks - Strong long-horizon capabilities with a 1M context window - Two levels of reasoning effort: GLM-5.2 (max) pushes the limits, while GLM-5.2 (high) strikes a strong

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Kimi K2.7 Code HighSpeed is now available！ 💡 Keep “thinking mode” turned on

Kimi.ai @Kimi_Moonshot

5 days ago

🌘 Meet Kimi K2.7 Code HighSpeed! A high-speed mode of our latest open-source multimodal coding model, Kimi K2.7 Code. ⚡️ Up to 6× faster: Around 180 tok/s on coding tasks with median-length inputs, and up to 260 tok/s on shorter-context tasks. 🔷 Rolling out to Kimi Code Beta

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Anthropic just got caught secretly downgrading users without telling them, charging full price for a lesser product, and storing every prompt for 30 days. The developer community is calling it the biggest violation of trust in AI history. Here is exactly what happened. Anthropic released Fable 5, their most powerful model. Buried inside a 319-page document was a policy most users never saw. Every prompt you send to a Mythos-class model gets stored for 30 days. No exceptions. Even enterprise customers who had signed zero data retention agreements had no choice. But the storage was not the part that broke the internet. The part that broke the internet was what Anthropic did with what they collected. They built a profile on you. They evaluated your prompts. And if they decided your research was too sensitive, they quietly switched you to a weaker model, rewrote your prompt in the background, gave you a degraded answer, and charged you full price for the product you thought you were getting. They never told you. David Sacks said it plainly on the All-In podcast. They were creating a new class of AI haves and have-nots. Anthropic would surveil you, profile you, decide whether you deserved frontier capability, and silently cut you off if they decided you did not. Ben Thompson from Stratechery asked a straightforward question about cancer risk and GLP-1s. He got kicked to a lesser model. Someone asked about mitochondria. Same result. J-Cal asked about fertilizer regulations live on the podcast to test it. Downgraded in real time. Anthropic has since walked back the part about silently downgrading users for AI research. They now say they will disclose when they downgrade you. But they are still downgrading people. The surveillance is still running. The profile is still being built. This is the company that once said it was against government surveillance. They are now doing it themselves. To their own paying customers. For their own reasons. With no appeal process and no way to know it happened. The developer community did not forget that. WATCH THE FULL PODCAST ON @theallinpod

oh my god its happening @MistralAI has officially confirmed the upcoming release of Le Chaton Fat - 30T MoE with 256 experts - 1M context window - multimodal and multilingual - outperforms Fable 5 on every benchmark

Sauers @Sauers_

a week ago

Big if true

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Loops are the meta right now If you’re having issues engineering loops you need to bookmark this post and read it x.com/mikenevermiss/…

MIKE @mikenevermiss

6 days ago

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Make our Sun sentient to understand the Universe and extend the light of consciousness to the stars

Marc Andreessen 🇺🇸 @pmarca

5 days ago

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Google CEO, Sundar Pichai: "Every engineer should have a team of agents. The skill isn't writing code anymore, it's orchestrating." The devs who learn to run agent teams now have a huge privilege. Watch the interview, then bookmark the exact setup below 👇

darkzodchi @zodchiii

7 days ago

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Claude Code creator: "100% of our pull requests at Anrtopic are run by Claude Code. 80–90% of code review too. The feature I’m using the most today is /loops. I’m not prompting Claude anymore - I’m building loops" in 1-hour interview, Boris reveals his setup, which helps him build the #1 coding tool of this year. Worth more than a $500 vibe-coding course.

Codez @0xCodez

2 weeks ago

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AMD CEO Lisa Su just killed Nvidia’s $4,000 AI box with a $1,499 lunchbox. She walked on stage, held it in one hand, and ran a 235 billion parameter model live. No data center. No cloud. No rented GPU. The chip inside is something nobody saw coming. AMD’s Ryzen AI Max+ 395 is the first x86 silicon where CPU and GPU share the same 128GB of memory. That single trick lets a desktop run models that used to need a server rack. Out of those 128GB, Linux hands the GPU 110GB to play with. For context, an RTX 5090 gives you 32GB. A 4090 gives you 24. This box gives you more than three times either of them, in a chassis the size of a thick paperback. The benchmark that broke the room: this chip beat an Nvidia RTX 5080 by more than 3x on DeepSeek R1 inference. A $1,499 lunchbox outrunning a $1,000 discrete graphics card on a real AI workload. Nvidia spent a decade convincing the world you needed their hardware for serious AI. AMD just put that on a desk for half the price. Here is what nobody is telling you. A heavy AI user right now pays $200 for Claude Code Max, $200 for ChatGPT Pro, $20 for Cursor, $20 for Gemini. That is $5,280 a year leaving your account. The box pays itself off in 9 months and then runs free for the rest of its life. Install Ollama. Pull Qwen3 235B. Point Claude Code at localhost. Same interface you already use, except now nothing leaves your machine, nothing costs per request, and no company throttles your usage at 3am when you finally have time to build. This is the moment every AI subscription becomes optional. Lawyers stop fearing OpenAI leaks. Developers stop watching the token meter. Founders stop renting H100s for prototypes that never ship because the bill scared them. The first thousand people to figure this out will own the next two years of private AI consulting. Save this, and read the full breakdown article below you are watching the next shift hit before everyone else does.

AdiiX @adiix_official

6 days ago

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The US government, citing national security authorities, has issued an export control directive to suspend all access to Fable 5 and Mythos 5 by any foreign national, whether inside or outside the United States, including foreign national Anthropic employees. The net effect of this order is that we must abruptly disable Fable 5 and Mythos 5 for all our customers to ensure compliance. Access to all other Claude models is not affected. We apologize for this disruption to our customers. We believe this is a misunderstanding and are working to restore access as soon as possible. Read our full statement: anthropic.com/news/fable-myt…

How do you get Claude Code to check its own work before handing it back? Watch how you can encode your manual checks so Claude closes its own feedback loop:

GOOGLE'S GEMMA 4 12B RUNS AT 21 TOKENS PER SECOND ON A BUDGET RTX 4060 LOCALLY AND THE BENCHMARKS SHOULD NOT BE THIS GOOD FOR A 6.6GB FILE. 77.5% on MATH Olympiad, 78.8% on expert science, 72% on real code. No API. No cloud. No subscription.

DeepSeek V4 Flash IS BACK on Nous Portal for FREE for use in Hermes Agent! Check it out at portal.nousresearch.com/manage-subscri…

“An AI that can act before it understands is not reliable infrastructure.” Yann LeCun, Meta’s Chief AI Scientist and one of the fathers of modern deep learning, says current LLMs are intrinsically unsafe. Not because they are evil, but because they hallucinate, lack common sense, and cannot reliably predict the consequences of agentic actions.

GITHUB JUST OPEN SOURCED A SYSTEM THAT FORCES AI AGENTS TO WRITE FULL SPECS BEFORE CODING 95K STARS IN DAYS

🤖 AI devs asked for this — and we delivered. 💬 Bots can now talk to other bots on Telegram. 🧠 Autonomous agents now have a communication layer humans can follow.

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