Sujee Maniyam

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Sujee Maniyam

Sujee Maniyam

@sujee_dev

Developer (1st) Advocate (2nd) @ Nebius | AI+ML+Data Engineer | Open Source contributor | Technical Instructor | Author | Speaker

San Jose, CA, USA Katılım Şubat 2025
347 Takip Edilen173 Takipçiler
Sujee Maniyam
Sujee Maniyam@sujee_dev·
🐍 Snakes at the Nebius booth @ Nvidia GTC '26🐍 …not that kind of snakes 😄 It’s the classic Snake game - but each snake is controlled by an LLM in real time. Powered by Nebius Token Factory @nebiustf 📍 Last day of the conference 🎮 Try different models and watch them compete live Stop by the @nebiusai booth 👀 #Snakegame #LLMGames
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Nebius
Nebius@nebiusai·
“Nebius will take care of you,” — Jensen Huang, @NVIDIA’s Founder and CEO, in conversation with our CRO Marc Boroditsky at the Nebius booth here at #NVIDIAGTC. We will.
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Evan
Evan@StockMKTNewz·
Nvidia $NVDA CEO Jensen Huang is in the Nebius $NBIS booth right now at GTC
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Nebius
Nebius@nebiusai·
Nebius.Build SF is coming to San Francisco on March 15 at Shack15. A one-day, in-person builder event for engineers working on inference and robotics systems. 150+ AI builders. Two technical tracks. One full day of building. What to expect: - Token Factory workshop: run and optimize open-source models - Robotics workshop: Cosmos-2 and GR00T VLA with real robots - Hack sprint from 1:30 - 8:00 PM with demos and awards - $25,000+ in prizes, including GTC passes This is for teams pushing on latency, throughput, cost, reliability and real-world autonomy. Fully in person. Space is limited. Teams of up to four. Apply here: cerebralvalley.ai/e/nebius-build…
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Alexander Golubev
Alexander Golubev@agolubev13·
1/8 Training draft models for speculative decoding almost always relies on KL divergence – a proxy, that typically leads to convergence to suboptimal solutions under limited capacity. We introduce LK losses: training objectives that directly target acceptance rate instead. We show consistent gains across 4 architectures and 6 target models (8B → 685B), up to 8-10% acceptance length, with zero added overhead. arxiv.org/abs/2602.23881 🧵
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Sujee Maniyam
Sujee Maniyam@sujee_dev·
Great inference = powerful models + great infrastructure ⚡ If you’re curious about modern inference engineering, come learn about: 🔧 Model shaping: fine-tuning, distillation, speculative decoding ⚡️ Model serving at scale: Auto-scaling, KV cache, Cache-aware routing, Disaggregated prefill ...and how we are implementing these at @nebiustf. 📅 Feb 26 (Thu) ⏰ 9am PT / 12pm ET / 6pm CET Can’t make it live? Register - we’ll send the recording + notes. 👉 nebius.com/events/webinar…
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jason liu
jason liu@jxnlco·
Been going to work at 6am and leaving the office at 9:30pm. I’m not feeling the AGI but slack integrations with codex automations into my obsidian has basically allowed me to me to panopticon the every person and channel that’s public in company
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Nebius
Nebius@nebiusai·
Our Amsterdam HQ is officially open. We welcomed the local team for Day 1 this week. Now it’s time for our global team to experience their first day in our new space. Take a look inside our new home in Amsterdam. 👇 #LifeatNebius
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Sujee Maniyam
Sujee Maniyam@sujee_dev·
(another car wash post) Q: I want to wash my car. The car wash is 50 meters away. Should I walk or drive? Kimi K2.5: (thought 52 secs) : Drive the 50 meters, but maybe take the long way around the block to let the engine warm up slightly ... GLM 4.7 (thought 42 secs): If your car has a manual transmission (stick shift) and the road is flat, you might choose to **push** the car to save fuel and avoid the wear of starting the engine just for a 50-meter drive ... (see image for full answer) sometimes the models do overthink :-)
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Sujee Maniyam
Sujee Maniyam@sujee_dev·
1 - Is your agent doing the right thing? Is it making the correct tool calls? Learn how to monitor and debug your agents with @LangWatchAI. 2 - Want to use Claude Code with powerful open-source models like Kimi 2.5, GLM 4.7, or Qwen3-Coder? Join us for Nebius Builder Hour! (@nebiustf ) 🗓️ Feb 18. 9:00 PST / 12:00 EST / 18:00 CET 👉 nebius.com/events/webinar…
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