@maxrumpf: turbopuffer x SID An easy way to tell a good from a great AI researcher: how much do they think about infrastructure. I…
Summary
The tweet thread highlights the importance of infrastructure in AI research, exemplified by the collaboration between turbopuffer and SID AI to train the SID-1 agentic search model using large-scale RL, achieving 1.9x recall over RAG+rerank and 24x faster/99% cheaper than GPT-5.1.
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Cached at: 05/22/26, 03:52 AM
turbopuffer x SID An easy way to tell a good from a great AI researcher: how much do they think about infrastructure. Infra extends beyond what’s running on the GPUs: Slow environments will bottleneck your training steps. More parallel and powerful models make this problem worse. RL environment specifics are usually secret, but we shared some details in a recent post with our friends at @turbopuffer Training great models requires great infrastructure and we’re excited to be working with the best.
turbopuffer (@turbopuffer): SID-1 is an agentic search model by @SID_AI
→ 1.9x recall over RAG + rerank → 24x faster, 99% cheaper than GPT-5.1
trained using large-scale RL on turbopuffer at 1k+ QPS bursts over 10M+ document corpora across thousands of steps
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