Reading up on Groq

Jensen Huang's GTC keynote reveals his strategy of 'manifesting the future' through category coronation to shape industry belief systems and drive demand for Nvidia's AI compute.

SRAM-centric chips outperform GPUs on memory-bound AI inference workloads, particularly decode, by placing memory near compute for faster bandwidth.

A developer built a sub-500ms latency voice agent by co-locating and aggressively pipelining STT, LLM, and TTS stages. Commenters debate trade-offs vs. end-to-end models, endpoint detection alternatives, and the difficulty of human-like turn-taking.

By piping Deepgram Flux, Groq's LLM, and ElevenLabs TTS with geographic optimization, the author achieved ~400ms end-to-end voice agent latency, beating Vapi by 2x.

Faster AI coding models, even if less intelligent, are more productive for quick mechanical code edits than slower, smarter models, especially for users with short attention spans.