
Compete, @coreweave (prev @positron_ai, @googlecloud, @nvidia) Fast fleets of secure agents for all. opinions=own;
San Fierro
Joined December 2017
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Barrett Woodside retweeted
I used Opus 5.5 to help make an explainer video for @coreweave Agent Lens (agent observability + insights on prod). It's ridiculously good at these kinds of videos!!
I also used CoreWeave sandboxes to farm out the rendering.
prompts / workflow in reply
Barrett Woodside retweeted
Cognition is the first customer running @NVIDIA Vera Rubin, powered by @CoreWeave!
Hopper in 2022. Blackwell in 2024. Now Vera Rubin:
On SWE-2 inference, the new chips deliver about 4.8x more token throughput than GB200 at the same decode speed.
More compute, better agents!
Barrett Woodside retweeted

CoreWeave@CoreWeaveSep 25
United States!
United StatesConnected via WebLocation may be affected by a proxy or VPN.Account-level information, not a live location or per-post device.
It's the final countdown. See you at #FullyConnected26 next week!
Still not registered? Last call: bit.ly/4xAeVUm
Barrett Woodside retweeted
Replying to @SemiAnalysis_ @vllm_project
Cool to see that you’re adding benchmarks for harness-inference co-optimization next. I wrote a bit about that here
TLDR all harnesses are basically the same because they all need to preserve the sacred KV cache hit rate of the proprietary models
BUT
what if you control the underlying infrastructure and use open models?
Then, instead of just using whatever harness you’re given, your harness and inference scheduler are aware of each other so…
There’s lots of infra optimizations that can be done :)
Session affinity is the obvious one but there’s a lot more
- speculative tool calling
- request priorities based on workload
- prefetch KV cache during tool calls
- colocate subagents and their tool calls
- prewarm tool calling sandboxes
the list goes on! I’m no expert here but know some folks that are (lmk if you’re interested in learning more)
Barrett Woodside retweeted
For my first post, I’m sharing a letter @NVIDIA signed on why open models matter.
AI will transform every industry, power every company, and be built by every country.
Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty.
The world needs both frontier closed models and frontier open models.
images.nvidia.com/pdf/Open-W…
Barrett Woodside retweeted

CoreWeave@CoreWeaveJul 21
United States!
United StatesConnected via WebLocation may be affected by a proxy or VPN.Account-level information, not a live location or per-post device.
The first-ever measured silicon numbers for @NVIDIA Vera Rubin NVL72 are in 😲
First measured performance shows 10x more tokens per megawatt than Blackwell.
No projections. Real results from live hardware.
Barrett Woodside retweeted
Replying to @JeffDean
Are you ReLU sure that's the best way to calculate it? Sounds taxing!
Barrett Woodside retweeted
Quantization update!
Transformers is now compatible with models quantized with llm-compressor library from @vllm_project or models in compressed-tensors format.
This means that you can also enjoy high quality quantized models from the @neuralmagic team!
Barrett Woodside retweeted
#GPT4V is magical…A machine that can textually explain an image representing its own operation, and then suggest a new way to visually represent itself. What a time to be alive.
Barrett Woodside retweeted
I just wrote a blog post on how we used mmap() to make LLaMA load faster, run in parallel, and use less memory. In this post you'll find all the facts. justine.lol/mmap/
Barrett Woodside retweeted
Announcing that Lambda has raised $44M to build the best cloud for training AI. (Lots of GPUs.)
youtube.com/watch?v=zsfd-GHI…
I'll be doing a Q&A on Twitter for the next hour. Just reply in this thread.
Barrett Woodside retweeted
✨ Calling all AI executives and professionals! ✨
We’re looking for your feedback on how AI will impact your business in 2023! Help us by completing a short survey.
Your contribution will be used in our upcoming report, coming in early 2023!
scl.ai/3iYoTOH
Barrett Woodside retweeted
How much better is OpenAI's newest GPT-3 model?
We evaluate davinci-003 across a range of classification, summarization, and generation tasks using Scale Spellbook, the platform for LLM apps → scale.com/blog/gpt-3-davinci…
Barrett Woodside retweeted
Large language models are magical. But using them in production has been tricky, until now.
I’m excited to share ✨Spellbook🪄✨— the platform for LLM apps from @scale_AI. 🧵
Barrett Woodside retweeted
🎙️ Up Next: @gdb - President, Chairman, and Founder, @OpenAI.
👉 Join this session with @gdb and @alexandr_wang, CEO and Founder of @scale_AI to learn how foundation models can enable businesses to benefit from the cutting-edge research from @OpenAI.
scl.ai/3M0Ajfv
Barrett Woodside retweeted
Scale is excited to welcome @DennisKCinelli as our first CFO! Learn more about why he joined Scale and how his leadership will enable us to build and scale our mission to accelerate AI across industries. bit.ly/3MLoLeR
Barrett Woodside retweeted
Get a peek behind the #lidar #data curtain with this case study by @scale_AI, outlining how #VelodyneLidar uses their Nucleus solution to find edge cases in 3D data & curate the most valuable data for #annotation.
scale.com/customers/velodyne
#datamanagement #AI $VLDR






















