Co-Founder and CEO at Libre AI | PhD in CS/ML | AI and Machine Learning for All! 🇸🇻

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Joined February 2008
eˣrnesto retweeted
NVIDIA releases Nemotron-3.5-Bolt-E4B, a new model that runs locally on 6GB RAM. 💚 Bolt-E4B can run on edge devices like phones and delivers top-tier performance for its size. Trained on Gemma 4, it supports vision. GGUF: huggingface.co/unsloth/NVIDI… Guide: unsloth.ai/docs/models/nemot…
Available now: NVIDIA Nemotron 3.5 Bolt E4B 4GB ⚡️ Our newest small open model is built for local assistants, interactive characters and robots that can carry on a conversation and use tools to get things done. Watch Reachy Mini chat and move, with Bolt handling conversation and NVIDIA Cosmos handling vision. Both models run locally on Jetson Orin Nano 8GB. Learn more: research.nvidia.com/labs/nem…
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Established companies will at best adapt to AI. Newly founded startups will be AI-native from the start. This is an interesting example of a company in the middle, which (by great effort) remade itself as an AI-native company.
We built a $150M ARR business twice. The first time took 8 years. The second took 2.5. Today, Podium crossed $150M in AI annual recurring revenue. Three years ago, we already had a great software business. Well over $100M in revenue, tens of thousands of customers, and a product we'd spent nearly a decade building. And we decided to start over. The business was performing well. But we believed AI was going to fundamentally change the software industry and make much of traditional software obsolete. As a founder, you pour your life into what you're building. An insane amount of time, sacrifice, and effort. The hard part is not getting too attached to it. When we started building our first AI agents, we had to confront the possibility that much of what we'd built might not be that valuable in the future. That's a tough pill to swallow. But we also realized those same 10 years had put us in a unique position to take advantage of what AI could do for our customers. Instead of protecting what we'd spent a decade building, we decided to bet the future of the company on AI employees that actually do the work for our customers. We massively underestimated what we'd signed up for. We ended up building entirely new operating systems for the industries we serve, from the AI agents all the way down to the systems of record. Now customers run their entire businesses on Podium. Reinventing our product wasn't even the hardest part. We had to reinvent how the entire company operated. When you've been running a company for over a decade, the operational inertia is incredibly powerful. We had to rethink how we build products, how we sell, how we serve customers, and how we run the business. We effectively started a second startup inside an already successful company. And we're still at the very beginning. Today, we have 20,000 AI agents working for our customers. They've helped generate more than $13 billion in revenue for those businesses. And we're barely scratching the surface of what AI will be able to do for them. And we've done all of this while becoming profitable and generating free cash flow. We're building Podium to be around for decades. Huge credit to our team for having the guts to make this bet and the ability to actually pull it off. We still have a long way to go and tons of problems to solve, but it's so damn fun to be winning when the opportunity ahead is this big. In the age of AI, you can either disrupt your own company or wait for somebody else to do it. I'd rather do it ourselves.
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The good news: you can mid-train yourself to the frontier! At a fraction of the cost! Without distillation! What we did: We took Qwen3.5 14B and mid- and post-trained it to beat every other open model and perform as well as the very best frontier models. This is no simple toy task or format fixing, we are training the model to understand and reason over DNA sequences. Bio is the next frontier for AI and universal access will be crucial to make progress. The fun part: because we train the model on both natural language and DNA sequences you can actually 'chat to your DNA': Ask it questions, ponder the impact of mutations, or ask it to generate a small sequence. We'll soon see the frontier labs move away from math and cyber towards bio. It already started, and we believe researchers should have access to capable models. We are releasing the full recipe, so you can do it, too! Model: huggingface.co/HuggingFaceBi… Blog: huggingface.co/spaces/Huggin…
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OlmoEarth v1.3 is out. 🌍 State-of-the-art embeddings from the same foundation model family, precomputed for every 10 m pixel on Earth. We’re excited to give you more ways to work with OlmoEarth, including a new browser tool to explore and customize maps. Full rundown in 🧵
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Wake up. Every profession deemed white-collar, the middle class dream, is about to be decimated by AI, at a much faster pace than anticipated, with monstrous social consequences.
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eˣrnesto retweeted
Run Flint locally on 24GB RAM via Unsloth Dynamic GGUFs! Flint is the strongest MoE model under 50B parameters. Recursive’s Apache-2.0 model has 39.8B parameters (2.5B active). Run at 125 t/s on Mac, 150 on RTX Spark GGUF: huggingface.co/unsloth/flint… Guide: unsloth.ai/docs/models/flint
Introducing Flint, @Recursive_SI’s first model: a fast local coding model built with our automated research system, the Eureka Machine. • Best-in-class fast local coding • Up to 2x faster than comparable models: 125+ tokens/sec on a MacBook Pro, 150+ on RTX Spark • Built from scratch in under 4 months Private, unmetered intelligence on your own machine. Open weights available now on @huggingface, run it locally on your favorite framework or try it for free on @opencode or @pidotdev.
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DeepSeek V4.1-Flash-1017 can now run locally! 🐳 We made 1-bit retain ~88.2% accuracy while shrinking size from 508GB to 250GB (−52%). Run on a 128GB+ RAM device. V4.1 Flash 1017 is the strongest open model to date Guide: unsloth.ai/docs/models/deeps… GGUF: huggingface.co/unsloth/DeepS…
🚀 DeepSeek-V4.1-Flash-1017 is here! Stronger benchmark performance, faster task completion, and shorter outputs than the previous version—a Pareto improvement in performance and cost. Now live on our website, app, and API. 🛠️ Optimized for @DeepSeekHarness, Tencent CodeBuddy, WorkBuddy, and more. Upgrade to DeepSeek Harness v0.2.1-rc.1 or later for the best experience with the new model. 1/4
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eˣrnesto retweeted
Someone asked what was the best way to get hired by a startup. I told him it was to start one and then hire himself.
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🚀 Introducing DeepInfer, our in-house inference framework, now fully open source! Powering DeepSeek-V4.1-Flash at scale with high throughput and low latency. We’re sharing our production stack to help the community lower compute costs, reduce energy use, and make AI more affordable. 🔗 github.com/deepseek-ai/DeepI… 1/4
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A few papers & benchmarks on LLM failure to follow instructions 🧵 I. Can LLMs Unlearn Stubborn Training Conventions? “LLMs often exhibit cognitive inertia, struggling when tasked with instructions that explicitly deviate from their training norms” arxiv.org/abs/2509.04292 1/
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Former Manchester City manager Pep Guardiola has urged the world not to forget Palestinians in Gaza. In a video with the UN agency for Palestinian refugees, UNRWA, he condemns the dehumanisation of victims and the suffering of children.
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The most built-upon model on the Hugging Face Hub isn’t Llama or Qwen. It’s FLUX.1-dev from Black Forest Labs, a German lab: 43k derivative models. Europe trained ~8% of the open-model compute on the Hub, but ~18% of what people build on top of it is European. Build or surrender? Build, and build open. See you at GTC Berlin this week
Should Europe leave frontier AI to the Americans and the Chinese? The idea has gained ground in Europe. It is a fundamental mistake. Build or surrender: for now, the choice is still ours. Full article below.
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Google has another banger 🤯 It’s called PaperBanana. It turns your methodology text into academic illustrations, helping you explain your research visually. 100% free.
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I personally think bears waiting for a lower bottom are on the wrong side of the trade. Capital flowing in/out of BTC bottomed August 9th 2026.
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Back when calculators were a little more controversial, v/@JonErlichman.
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BREAKING: At least 74,475 people have been killed and 175,517 wounded by Israel’s genocidal war on Gaza since October 2023, according to the enclave’s Health Ministry. 🔴 LIVE updates: aje.news/e9uqrl
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DeepSeek v4.1 Flash 1017 is basically GPT 5.6 Sol at home Incredible
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Another way the current administration is trapped in the ZERO-SUM FALLACY: The H-1B visa situation. + You are NOT taking a job from a citizen, rather creating jobs by increasing overal economic output. Plus these people (even vegetarians) SPEND locally. + The US has long been benefiting from other countries' brain drain; without it its edge wd collapse. Tesla, Von Braun, von Neumann, Fermi & Einstein did NOT each take the job of a citizen. + It the problem is anti-Indian racism, say it, don't play games.
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Today, @Meta is open sourcing the weights for Muse Spark Open, the most capable US open-weights model to date. It’s integrated with the PyTorch ecosystem: it ships with Helion kernels, and TorchTitan can be used to further tune the model. More in the blog: pytorch.org/blog/muse-spark-…
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Israeli spyware disguised as a digital advertising firm has targeted journalists’ devices at Al Jazeera and other companies. Here is what we know.
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