TL;DR – Technical Takeaways Scaffold splitting trumps random splits for kinase inhibitor models—without it, your QSAR will lie to you. We built a Random Forest model on ChEMBL data, using RDKit descriptors and BRICS fragmentation. SHAP waterfall plots exposed which molecular fragments drive pIC50, linking structure to activity. The pipeline runs as a Kedro‑wrapped co‑scientist inside a container that a chemist can interrogate via a REST endpoint. We’ll share the top 5 predicted EGFR inhibitors our model surfaced—molecules never tested against EGFR in the training set. We’ve been burned before by a “world‑class” QSAR model that hit R² = 0.89 on random cross‑validation, only to crash to R² = 0.21 when we tested it on a new chemical series. The sin? Random splitting. In kinase‑centric projects like EGFR inhibitor discovery, random splits create artificially high performance by leaking close analogs across folds. That’s why we pivoted to a scaffold‑split QSAR method —a ...

TL;DR – Executive Summary Low latency voice takes a massive leap with gpt-realtime-2.1 and gpt-realtime-2.1-mini . Internal benchmarks show round-trip audio delay dropping below 200 ms (machine‑side) in production. Real‑time WebSocket connections now support chunked audio streaming and interrupt‑first semantics out of the box. We’ll walk through deployment‑ready YAML, raw curl commands, and two  💡 Pro Tips that saved us from falling back to pre‑recorded IVR trees. We still remember the first time we plugged a cloud STT‑LLM‑TTS pipeline into a customer‑facing phone line. The latency was so bad the caller thought the agent had hung up. Voice AI that stumbles isn’t artificial intelligence—it’s artificial rudeness. OpenAI’s new Realtime API 2.1 models finally let us treat voice as a first‑class modality, not a franken‑pipeline of independent services. The Latency Tax We’ve All Been Paying Before the Realtime API, assembling a voice agent meant stringing together a V...