Abhi Venigalla @ml_hardware
Researcher @Databricks. Former @MosaicML, @CerebrasSystems. Addicted to all things compute. San Francisco, CA Joined October 2018-
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memory-bound gf, compute-bound bf
presenting: big jeff's trainium hell
Cerebras just beat NVIDIA Blackwell Last week: Blackwell hit 1,000 t/s on Llama 4. Today: Cerebras hit 2,500 t/s on the same model, same benchmarks by @ArtificialAnlys Blackwell smoked Groq, AMD, Google – everyone. Only Cerebras stands – and we smoked Blackwell.
Meet Phonic, the next-generation speech-to-speech platform focused on reliability We’ve all gotten stuck speaking on the phone to an AI that doesn’t understand you At Phonic, we’ve rethought the whole stack from model training to voice evals to compound systems for reliability
AMD 💕 @__tinygrad__ we are looking forward to working closely with @__tinygrad__ to help commoditize the petaflop geohot.github.io//blog/jekyll/u…
I've been using uv for a few months now and I've never felt better. I have more energy. My skin is clearer. My eye sight has improved.
Guy seeing the territory for the first time: "getting a lot of Map vibes from this"
CUDA 12.8 just dropped with Blackwell support. TensorCore 5th Generation Family Instructions: docs.nvidia.com/cuda/parallel-…
Our 5-month journey conducting independent analysis & benchmarking of AMD MI300X vs Nvidia H100 + H200 Detailed, open source low-level benchmarks performance vs TCO Comprehensive public recommendations It’s not just immature software, they need to change how they do development
Our 5-month journey conducting independent analysis & benchmarking of AMD MI300X vs Nvidia H100 + H200 Detailed, open source low-level benchmarks performance vs TCO Comprehensive public recommendations It’s not just immature software, they need to change how they do development
🚨Cerebras Systems + Sandia National Labs have demonstrated training of a 1 trillion parameter model on a single CS-3 system (!) This is ~1% the footprint & power of an equivalent GPU cluster.
Llama 3.1 405B is now running on Cerebras! – 969 tokens/s, frontier AI now runs at instant speed – 12x faster than GPT-4o, 18x Claude, 12x fastest GPU cloud – 128K context length, 16-bit weights – Industry’s fastest time-to-first token @ 240ms
🧵We’ve spent the last few months at @datologyai building a state-of-the-art data curation pipeline and I’m SO excited to share our first results: we curated image-text pretraining data and massively improved CLIP model quality, training speed, and inference efficiency 🔥🔥🔥
Scaling laws are still true because all the labs use Google Sheets and can't fit a sigmoid in that, just straight lines on log log plots. All the finance Excel bros freaking out because they can plot a sigmoid but don't know what that means.
🚨 Cerebras Inference is now 3x faster: Llama3.1-70B just broke 2,100 tokens/s - 16x faster than the fastest GPU solution - 8x faster than GPUs running Llama *3B* - It's like the perf of a new hardware generation in a single software release Available now at…
Olmo goes multimodal! We are launching Molmo, a open family of multimodal models that rival the best closed VLMs out there 🤯 We spent the last 9 months meticulously curating PixMo, a dataset of (a) high-quality image-caption pairs and (b) multimodal instruction data.
Are you a entrepreneur or early stage startup building GenAI products with databricks? Enter our new startup challenge to win $1M in prizes and opportunities for funding. Application Deadline: November 1, 2024 Finalists Announced: November 20, 2024 databricks.com/blog/unleash-y…

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