On-demand GPUs, managed clusters to develop, train and deploy AI in one place. : https://xitter.cf/t.co/a69wnEBpKH

New York, NY
Joined August 2019
Lightning AI ⚡️ retweeted
👏 Congratulations to @LightningAI and @DellTech on a successful deployment of NVIDIA GB300 NVL72!
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Lightning AI ⚡️ retweeted
It's been amazing to work with @nvidia to bring GB300s to the market ⚡️. Thank you for the support!
👏 Congratulations to @LightningAI and @DellTech on a successful deployment of NVIDIA GB300 NVL72!
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Lightning AI ⚡️ retweeted
Since 2019 we have been helping companies train and own their own specialized models. Really enjoyed sharing how @LightningAI is becoming THE enterprise platform that helps you do that - now with our own 40k GPUs ⚡️
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Lightning AI ⚡️ retweeted
The first GB300s have landed at @LightningAI! Can't recommend working with @Dell enough.
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Lightning AI ⚡️ retweeted
25,000 H100s now available for on-demand! - instant startup - high availability - enterprise-grade reliability read why we are going to become the leading on-demand cloud lightning.ai/blog/lightning-…
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Lightning AI ⚡️ retweeted
Today, @LightningAI launched the Lightning Cloud: instant on demand H100s guaranteed for AI teams that are doing serious training and experimentation. Our platform and infrastructure teams were absolutely cooking on this one. - Instant H100 availability - All the tools you need for training and experimentation - Baremetal interconnect speeds for hero training runs - All on an enterprise grade managed platform Learn more here → lightning.ai/blog/lightning-…
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Lightning AI ⚡️ retweeted
Yesterday we saw a supply-chain attack on PyTorch Lightning (on Pypi, not our core repo). It's wild how it happened but it was caught and quarantined within 42 minutes thanks to the open source community. It's one reason why open source actually helps increase the security posture of projects. Thank you to @pypi and @SocketSecurity ⚡️ Summary: On April 30th, 2026, an attacker captured PyPI credentials and used them to push compromised versions of PyTorch Lightning (PTL). These versions were live for 42 minutes before PTL community members alerted us and PyPI quarantined the package. The PyTorch Lightning GitHub source code repository was never compromised. This affected those who installed PTL via PyPI between 12:45:20 and 13:27:30 UTC on April 30th, 2026. lightning.ai/blog/pytorch-li…
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Lightning AI ⚡️ retweeted
I think everyone forgot that PyTorch Lightning is massively popular for finetuning and pretraining LLMs... It's been quietly growing exponentially in the background now with 25 million downloads last month alone. When i left AI at Meta it only had 60k total downloads.
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Lightning AI ⚡️ retweeted
🚀 Sneak peek of Deepseek v4 Pro on @LightningAI - clearly our optimization team had a post 5pm espresso so you could try this out before your 7am espresso. Link below:
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Lightning AI ⚡️ retweeted
I vibe coded a Boltz-2 structure prediction app and deployed it on @LightningAI. Framework choices, real-time logging, CSS bugs in the write-up. Thanks @boltz_bio for the great open source tool. Link in replies.
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Lightning AI ⚡️ retweeted
NVIDIA has released Nemotron 3 Super, a 120B (12B active) open weights reasoning model that scores 36 on the Artificial Analysis Intelligence Index with a hybrid Mamba-Transformer MoE architecture We were given access to this model ahead of launch and evaluated it across intelligence, openness, and inference efficiency. Key takeaways ➤ Combines high openness with strong intelligence: Nemotron 3 Super performs strongly for its size and is substantially more intelligent than any other model with comparable openness ➤ Nemotron 3 Super scored 36 on the Artificial Analysis Intelligence Index, +17 points ahead of the previous Super release and +12 points from Nemotron 3 Nano. Compared to models in a similar size category, this places it ahead of gpt-oss-120b (33), but behind the recently-released Qwen3.5 122B A10B (42). ➤ Focused on efficient intelligence: we found Nemotron 3 Super to have higher intelligence than gpt-oss-120b while enabling ~10% higher throughput per GPU in a simple but realistic load test ➤ Supported today for fast serverless inference: providers including @DeepInfra and @LightningAI are serving this model at launch with speeds of up to 484 tokens per second Model details 📝 Nemotron 3 Super has 120.6B total and 12.7B active parameters, along with a 1 million token context window and hybrid reasoning support. It is published with open weights and a permissive license, alongside open training data and methodology disclosure 📐 The model has several design features enabling efficient inference, including using hybrid Mamba-Transformer and LatentMoE architectures, multi-token prediction, and NVFP4 quantized weights 🎯 NVIDIA pre-trained Nemotron 3 Super in (mostly) NVFP4 precision, but moved to BF16 for post-training. Our evaluation scores use the BF16 weights 🧠 We benchmarked Nemotron 3 Super in its highest-effort reasoning mode ("regular"), the most capable of the model's three inference modes (reasoning-off, low-effort, and regular)
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Lightning AI ⚡️ retweeted
Ready to get started? Nemotron 3 Super supports deployment across environments, from workstations to the cloud, and can be accessed through API, OpenRouter, or build.nvidia.com. It is now live and available on major inference platforms, packaged as NVIDIA NIM: 📥 Download the weights from @HuggingFace, launch an optimized instance through NVIDIA NIM, fine-tune with @UnslothAI, or start with the cookbooks from @lmsysorg and @vllm_project to get running in minutes. Super is also available through @baseten, @Cloudflare, @deepinfra, @FireworksAI_HQ, @friendliai, inference.net, @LightningAI, and @modal. 📗Read the Nemotron 3 Super technical report for the full details research.nvidia.com/labs/nem…
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Lightning AI ⚡️ retweeted
Okay... I did the analysis on using a mac-mini for OpenClaw/ClawdBot vs running on the cloud (via Lightning). There are pros and cons to both. Local access on a Mac mini is nice. But isolation, 24/7 uptime, collaboration, and free cloud hosting, gives strong reasons to run it in the cloud too. lightning.ai/blog/running-op…
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Lightning AI ⚡️ retweeted
Another (4th?) major cloud outage today... this is exactly why we now own our datacenters and allow customers to ALSO run on any cloud. Reliability is a feature for Lightning users ⚡️
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Lightning AI ⚡️ retweeted
OK community, I need your help. If you remember your experience when you were onboarding to @LightningAI, I'd love to hear: 1 thing that went well, and as many things as you remember that sucked. Trust me, you can't offend me.
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Lightning AI ⚡️ retweeted
Kimi K2.5 is now available on Lightning AI ⚡️. Apparently it's the best OSS coding model 🤯. lightning.ai/models/lightnin…
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Lightning AI ⚡️ retweeted
Set up Clawdbot/OpenClaw in under a minute. You don't need to buy a Mac mini, use a terminal, or worry about any config files. Here's what you can do: 1. Go to the OpenClaw Lightning environment 2. Click on "Clone." 3. Follow the simple guide I've shared below From there, you can connect it to WhatsApp or Telegram and control your assistant from your mobile. This turns 2 hours of installation and configuration into just 2 minutes. But there's something more important: This approach keeps everything secure sandbox environment, off your local machine. Clawdbot is fun and powerful, but I would never recommend giving it access to your main machine.
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Lightning AI ⚡️ retweeted
Run OpenClaw on the cloud instantly in one click with zero setup via Lightning AI ⚡️. With free credits 🤯 Link in the replies
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Lightning AI ⚡️ retweeted
Upcoming Super Data Science podcast episode coming soon! with @JonKrohnLearns
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