The Superintelligence Cloud
San Francisco, CA
Joined July 2012
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Lambda retweeted
We’re launching NVIDIA Minerva to bring end-to-end observability to AI factories at scale.
The NVIDIA Minerva AIOps platform connects infrastructure and workload telemetry across GPUs, networking, storage, and schedulers, using AI to surface root causes and reduce alert noise across factories with hundreds of thousands of GPUs.
Read the news from #NVIDIAGTC Berlin: nvda.ws/4yD3tbb
Doing frontier research in finance, robotics, healthcare, AI agents, or anything in between? The program accepts applications on a rolling basis.
Request a research grant: lambda.ai/research?utm_sourc…
Every insight in this report came from a researcher running experiments on Lambda compute.
The Lambda Research Grant Program has distributed $1.3M+ in cloud credits. That compute powered 150+ published papers at ICML, NeurIPS, CVPR, and other top venues, across hundreds of institutions.
Read the report: lambda.ai/voices-of-ai-resea…
The mismatch: funding reviews take months. Architectures and baselines shift in weeks.
By the time compute is approved, the experiment is outdated. So researchers spend their time writing proposals instead of running the experiments they trained for years to run.
“Compute is the bottleneck between having a research idea and being able to test it at the scale the data demands.”
Davide Romelli, Trinity College Dublin
Lambda retweeted
NVIDIA introduces the OpenShell Reference Architecture to help businesses run AI agents under control.
The open design combines accelerated compute for agents with hardware-isolated security for deployment at scale.
Announced at GTC Berlin: nvda.ws/4zBujkE
Lambda retweeted
Scale AI securely across global infrastructure while maintaining full control of your models and data.
At #NVIDIAGTC Berlin, we’re introducing Confidential Bare Metal with NVIDIA Confidential Computing, enabling model builders to run sensitive AI workloads on dedicated third-party infrastructure securely.
@googlecloud is extending Confidential Bare Metal support to A4X Max instances, and @cohere plans to integrate it into Cohere Model Vault. ➡️ nvda.ws/4ixVneZ
ALT NVIDIA Confidential Computing Expands, Enabling Frontier Model Builders to Securely Scale Across Global Infrastructure
Featured in the #NVIDIAGTC Berlin keynote: 19 NVIDIA HGX B200 nodes running in the power budget of 16 with NVIDIA DSX MaxLPS. We're glad we got to build this proof of concept with @NVIDIA.
Find us at booth 7022 all week. Book a time with the team: lambda.ai/gtc-berlin-book-a-…
That's Lambda in the NVIDIA GTC Berlin keynote.
We're building with @NVIDIA on secure, efficient AI infrastructure, including an NVIDIA DSX MaxLPS proof of concept, plus support for Confidential Bare Metal and the NVIDIA OpenShell Reference Architecture.
#NVIDIAGTC
Heading to @stacresearch Summit NYC on Oct 21? Lambda's a platinum sponsor this year.
Catch Jessica Nicholson and Devina Jain at 10:20 a.m. for "FSI at Lambda: research at the edge, performance in production." Then Quinn Kennedy gives the five-minute version of how Lambda got here at 2:25 p.m.
We'll have our audited STAC-AI LANG6 results with us. Find us between sessions.
Book time with the team: lambda.ai/stac-ny-book-a-mee…
Three weeks of Build-a-Claw hackathons across Europe, and today the winners took the stage in Berlin.
Congrats to Sebastian Kwiedor and HOAIclaw, an AI advisor for German SMEs that keeps company data local and completed 3,200+ scheduled jobs with zero failures in production.
And to Pasha Abdulaev and Kautionskralle, which helps German renters recover their deposits by tracking deadlines and drafting objection letters.
We’re glad to support a community building with agents, open models, and physical AI.
Moving from prototype to production? Lambda is at @NVIDIA GTC Berlin 2026, booth 7022.
Our team is there all week to talk about scaling compute infrastructure for ML workloads. If you're working through capacity, deployment, or production-readiness decisions, book a time with us.
lambda.ai/gtc-berlin-book-a-…
Lambda retweeted
🚀 Introducing Next-Concept Modeling (NCM): our new paradigm for fast, parallel, coarse-to-fine text generation.
Compared to strong diffusion language models (DLMs) at similar parameter size, NCM achieves:
⚡ Up to 31× faster generation on downstream tasks like summarization and machine translation with comparable or better quality.
🏎️ 10–21× faster unconditional generation across TinyStories, LM1B, and OpenWebText, with comparable or better generative perplexity and using 3–5× fewer training tokens.
🧩 Better performance on reasoning tasks like Sudoku, outperforming both AR and diffusion baselines with fewer sampling steps.
With @ishanskhare, @IddahMlauzi, @ekellbuch, @simran_s_arora, @Azaliamirh, and @HazyResearch.
More details in the thread 🧵👇