คุณอาจชื่นชอบ
Lambda has raised over $1.5B in equity to build superintelligence cloud infrastructure. TWG Global, USIT, and existing investors led the Series E round to position Lambda to execute on its mission to give everyone the power of superintelligence. One person, One GPU. Press…
From bigger models to better intelligence: what @NeurIPSConf 2025 tells us about progress. In his latest piece, @chuanli11, Lambda’s Chief Scientific Officer, unpacks where the field is heading: shorturl.at/U3lOh
Multi-cloud isn’t a strategy so much as an outcome of constraints. GPUs are scarce, DC capacity is tight, and egress fees complicate moving training data. Here’s a blueprint for running training and inference reliably across multiple clouds: shorturl.at/pjESR
Congratulations to @nvidia on the launch of their open model Nemotron 3 Nano. Fast, simple, and production-ready. Run on Lambda:
NVIDIA releases a new model today: Nemotron 3 Nano, the first of 3 in the Nemotron 3 family! A slew of improvements compared to Nemotron 2, including hybrid reasoning, a mamba layer, and more. Here's a quick tutorial on how to deploy it on @LambdaAPI! docs.lambda.ai/education/larg…
#NeurIPS2025: Our biggest year yet. Six accepted research papers, highest workshop attendance, and an incredible booth presence. Thank you to everyone who stopped by and shared your thoughts with us on what’s next in superintelligence. We can’t wait to see what you build in 2026.…
Building superintelligence-scale AI factories takes more than just GPUs. Join Maxx Garrison and Johnson Eung in a webinar on Thursday, December 11th, at 10am PST, to learn how Lambda and @Supermicro solve the operational problems of modular, GPU-dense AI factories and validate…
Welcome aboard, @TheZachMueller! We are beyond thrilled :)
Secrets out. I’m happy to announce that I’ve joined @LambdaAPI as Head of Developer Relations! I’ve been using Lambda for a number of years, and especially after how warm and welcoming they were towards helping out with my course this year, it was a role that “Just Made Sense.”…
Today, Heather Planishek joins Lambda as Chief Financial Officer. Most recently, she served as Chief Operating and Financial Officer at Tines, the intelligent workflow platform, and has been @LambdaAPI’s Audit Chair since July 2025. Heather brings deep company insight to our…
AI can draw a dog and a cat side by side, no problem. But ask it for “one golden retriever half-hidden behind another,” and you’ll get a four-legged blob. Why? Because most layout-to-image models are tested on scenes where objects don’t touch. Real photos don’t work that way. In…
Day 3 at #NeurIPS: back to our research roots. NeurIPS is one of the few conferences still focused on real academic work, and that’s been Lambda’s home for the past twelve years. We spent the day meeting with founders who turn state-of-the-art research into products and…
LLM alignment typically relies on large and expensive reward models. What if a simple metric could replace them? In a new #NeurIPS2025 paper, Lambda’s Amir Zadeh and @chuanli11 introduce BLEUBERI, which uses BLEU scores as the reward for instruction following:…
AI can recognize objects, but it still struggles with simple spatial questions like “Is the water bottle on the left or right of the person?” or “Can the robot reach that?” One of our NeurIPS 2025 papers, co-authored by Lambda researcher @jianwen_xie, introduces SpatialReasoner…
Day 2 at #NeurIPS2025 was all about builders talking shop. AI research teams stopped by the Lambda booth to trade notes on multimodal inference for superintelligence, building AI factories, and what reliable NVIDIA GB300 performance looks like when workloads hit production. Real…
At the atomic scale, running millions of simulations on large-scale datasets is expensive. AI helps, but today’s models still spend most of their time performing heavy computations to ensure their predictions remain accurate regardless of how a molecule is rotated, using the…
#NeurIPS2025 opened with a full slate of talks and demos asking the hard questions: multimodal reasoning, training at scale, and what it takes to build systems that behave more like software than static models. "We're from the AI community, building for the community. That's why…
Achieve up to 10× inference speed and efficiency on Mixture of Experts models like DeepSeek-R1 with @nvidia Blackwell NVL72 systems on Lambda’s cloud: purpose-built for AI teams that need fast, efficient, and seamlessly orchestrated infrastructure at scale, and tightly integrated…
If your bottleneck is data rather than compute, you may want to rethink using standard LLMs. In this latest NeurIPS paper co-authored by our very own Amir Zadeh, “Diffusion Beats Autoregressive in Data-Constrained Settings,” we show that masked diffusion models: - Train for…
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