Ahmad Farhan @_afarhan_
Half algorithm, half deity Joined March 2022-
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.@RichardSSutton, father of reinforcement learning, doesn’t think LLMs are bitter-lesson-pilled. My steel man of Richard’s position: we need some new architecture to enable continual (on-the-job) learning. And if we have continual learning, we don't need a special training…
~8 minutes in and i can already sense the difference in the abstraction layers at which Dwarkesh and Dr. Sutton operate
vibe coders, secure your systems with this tool in 1 easy step
Repetitive negative thinking is associated with cognitive decline. Stay positive.
Here’s an unedited 10-minute demo of pi-0.5 straight out of the box. We gave it just one instruction, “clean the table by putting items into the basket”, and let it run. It worked! No fine-tuning required: it handled multiple tabletop scenes robustly, with smoother and faster…
Here’s an unedited 10-minute demo of pi-0.5 straight out of the box. We gave it just one instruction, “clean the table by putting items into the basket”, and let it run. It worked! No fine-tuning required: it handled multiple tabletop scenes robustly, with smoother and faster… https://t.co/mA9DgrRVYI
π0.5 weights + fine-tuning code are now open-source! github.com/Physical-Intel…
π0.5 weights + fine-tuning code are now open-source! github.com/Physical-Intel…
Everyone is talking about this new OpenAI paper. It's about why LLMs hallucinate. You might want to bookmark this one. Let's break down the technical details:
What a crazy week in AI 🤯 - Krea AI Real Time Video - Ideogram Styles Presets - ChatGPT Branch Feature - Grok Imagine with Speech - Google’s EmbeddedGemma - Kimi K2 1T Parameter Model - Alibaba Qwen3-Max-Preview - Warp Code Top Coding Agent Here’s EVERYTHING you need to know:
Another impressive paper by Google DeepMind. It takes a closer look at the limits of embedding-based retrieval. If you work with vector embeddings, bookmark this one. Let's break down the technical details:
OpenAI's gpt-oss claims to be "natively" quantized to MXFP4. But I believe it is actually quantization-aware training (QAT). This quantization method differs from native FP8 as seen in DeepSeek, which adopts FP8 for both weights and computation during training
OpenAI's gpt-oss claims to be "natively" quantized to MXFP4. But I believe it is actually quantization-aware training (QAT). This quantization method differs from native FP8 as seen in DeepSeek, which adopts FP8 for both weights and computation during training
🚨: Scientists just created matter from pure light, proving Einstein's 90-years old theory E=mc², right in the lab!
EXPO is a new method for RL post-training of diffusion policies. With good pre-training, it’s both really stable and ~2x more efficient than the most efficient RL fine-tuning methods I know of. Paper: arxiv.org/abs/2507.07986
EXPO is a new method for RL post-training of diffusion policies. With good pre-training, it’s both really stable and ~2x more efficient than the most efficient RL fine-tuning methods I know of. Paper: arxiv.org/abs/2507.07986 https://t.co/SvMjFGsavG
not even a single $ has moved since the last 16 years peak self control wonder what he is doing these days
“Vibe Coding is the Punk Rock of Coding” - Rick Rubin
We also had some fun messing with the robot, to test how it reacts. :) (again, all environments/objects/furniture not seen in training!)
Discrete Mathematics Lecture, By MIT:
LLMs Get Lost in Multi-turn Conversation The cat is out of the bag. Pay attention, devs. This is one of the most common issues when building with LLMs today. Glad there is now paper to share insights. Here are my notes:
PyTorch Day France—the first-ever PyTorch Day—comes as the PyTorch Foundation expands into an umbrella foundation, now positioned to support a growing ecosystem of trusted, community-driven AI projects. Co-located with @gosimfoundation's GOSIM AI Paris 2025. 🎟️ Register now with…
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