NeurIPS Recap - The State of AI Research

We start 2026 with an evening that covers a range of topics at the frontier of AI - and please note that the topics below are "subject to change" depending on new model releases, etc...

Talks:
"Nested Learning; mHC/Engram and Sub-1bit Compression" - Martin Andrews
In his talk, Martin will outline several interesting recent works: (a) Nested Learning from Google (which follows on from their TITANS paper at NeurIPS); (b) mHC and Engram from DeepSeek, which may be foreshadowing an upcoming release; and (c) "LittleBit: Ultra Low-Bit Quantization" which had flown under the radar until NeurIPS itself... The goal is to explain a little of both the "why" and the "what" behind this research.

"The Big Shift: From "Bigger Models" to "Smarter Systems"" - Sam Witteveen
In this talk, Sam will go through some of the papers and topics covered at NeurIPS and in general research over the past few months that cover how in the race for AGI, research is moving to Agentic Systems rather than just Big Models

"EmergentDB: What if Your Database Learned Like an LLM?" - Rach Pradhan
In his lightning talk, Rach will describe his highly-rated entry into the recent DeepMind Gemini Hackathon held in Singapore. His "EmergentDB" is a proof-of-concept vector database that uses MAP-Elites (Quality Diversity) to automatically discover optimal index configurations. Instead of hand-tuning HNSW parameters or guessing at partition counts, the idea is that the database evolves configurations specific to your data with impressive speedups over alternatives.

FOOD UPDATE : Google has told us that there WILL BE pizza at the event

ALSO: Sign-ups are on MeetUp this time! Registration here should be FREE - if MeetUp requires you to sign up for a subscription somehow, let us know! (We haven't heard of this happening for registrations via their mobile app, FWIW).
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Talks will start at 7:10pm (entry at 6:45pm) and end at around 9:00pm, at which point attendees can come up to the front for a bit of a chat with each other, and the speakers.

As always, we're actively looking for more speakers - both '30 minutes long-form', and lightning talks. For the lightning talks, we welcome folks to come and talk about something cool they've done with keras, PyTorch, JAX and/or Deep Learning for 5-10mins (so, if you have slides, then #max=10). We believe that the key ingredient for the success of a Lightning Talk is simply the cool/interesting factor. It doesn't matter whether you're an expert or an enthusiastic beginner: Given the responses we have had to previous talks, we're sure there are lots of people who would love to hear what you've been playing with. If you're interested in talking, please just introduce yourself to Martin at one of the events.