Episode

2/17/26: Approximately Aligned Decoding with Daniel Melcer

Podcast
Boston Computation Club
Published
Feb 18, 2026
Duration seconds
2939
Processing state
not_requested
Canonical source
https://podcasters.spotify.com/pod/show/bostoncc/episodes/21726-Approximately-Aligned-Decoding-with-Daniel-Melcer-e3f81q5
Audio
https://anchor.fm/s/5eee01ac/podcast/play/115655941/https%3A%2F%2Fd3ctxlq1ktw2nl.cloudfront.net%2Fstaging%2F2026-1-18%2Ff585dd16-8419-3cad-5f6f-f7c172abecc5.m4a
JSON
/v1/public/podcasts/boston-computation-club-4031660/episodes/2-17-26-approximately-aligned-decoding-with-daniel-melcer
Markdown
/podcast/boston-computation-club-4031660/2-17-26-approximately-aligned-decoding-with-daniel-melcer.md

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Summary

Daniel Melcer is a PhD student at Northeastern University, where he researches formal methods, reinforcement learning, and large language models, among other things. Daniel also has the most colorful hair in the business (bright red for this talk, other colors for other occasions). Today he joined us to talk about some really exciting work he completed at Amazon, and to expand on his general vision of where constrained inference problems are heading in the future.