Cluster magicians and GPU whisperers, come join us! We’re looking for supercomputing engineers to build the infrastructure behind real-time interactive models, Tinker, and large-scale training: scheduling, storage, networking, reliability, and distributed systems at scale.
SYSTEMS
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AI Coder Builds OS with Claude Code: Masterclass, Guide, and Free Repo
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This guy literally built an ENTIRE operating system with Claude Code 🤯
— Charly Wargnier (@DataChaz) 12 mai 2026
now he is showing you exactly how.
Nate just dropped the ultimate AI coding starter pack:
→ 2+ hour masterclass
→ Complete framework guide
→ Free GitHub repo to start building
bookmark this 👇 https://t.co/DwToTNzjwH pic.twitter.com/Atk3Nd4croThis guy literally built an ENTIRE operating system with Claude Code now he is showing you exactly how. Nate just dropped the ultimate AI coding starter pack: → 2+ hour masterclass
→ Complete framework guide
→ Free GitHub repo to start building bookmark this -
Optimizing AI Infrastructure via Intelligent Model Routing
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Most AI apps are still burning money by sending every prompt to the most expensive model.
— God of Prompt (@godofprompt) 12 mai 2026
That won’t last.
The real unlock is routing: cheap models for simple jobs, stronger models when it actually matters, fallback when providers break.
This is the infra layer everyone… https://t.co/mpM5L6tuwwMost AI apps are still burning money by sending every prompt to the most expensive model. That won’t last. The real unlock is routing: cheap models for simple jobs, stronger models when it actually matters, fallback when providers break. This is the infra layer everyone
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Optimizing AI Application Performance via Intelligent Model Routing
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0% markup + automatic model routing is the part people should pay attention to. The winner won’t be the app using the biggest model for everything.
It’ll be the one that knows when not to. -
NVIDIA GB200 Architecture Optimized for Large-Model Inference
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This NVIDIA remains the strongest platform for large-model inference at scale. Prefill/decode disaggregation, Blackwell-native quantization, custom kernels, and rack-scale NVLink turn GB200 into faster answers lower serving cost. Read the full paper here
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Technical analysis of neurosymbolic AI architecture
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it’s a klugey neurosymbolic system but its certainly neurosymbolic. it’s certainly NOT a pure neural networks, and certainly not a pure symbolic system. it is a blend. (and of course lots of symbolic systems are kluges)
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AI Systems Search and Build in Real-Time During Chat Interactions
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they are actually searching things and building stuff in realtime as you chat.
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AI labs’ ASI belief signaled by disbanding consulting, jobs safe
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You will know that the AI labs believe in ASI when they disband their newly formed consulting (sorry “forward deployed engineering”) groups. As long as people are required to figure out how AI is useful & do organizational change & systems integration, jobs seem to be pretty safe
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Human-AI Bandwidth Bottleneck in Modern ML Accelerators
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In modern ML accelerators, FLOPS have absolutely exploded. Often though, the bottleneck is not FLOPS but memory bandwidth. Similarly, model intelligence has exploded, causing the bottleneck to be humanAI bandwidth. At Thinky, we think that it’s important to solve this. 1/4 x.com/thinkymachines…
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AI Performance Leap: ‘Framemogged’ Realtime Capabilities Redefined
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I believe the kids call this "
@thinkymachines just brutally framemogged gdm and oai". basically everyone's definition of "realtime" just got a massive frciking upgrade