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8 Predictions for the Era of Continual Learning
Scaling up Continual Learning — Ronak Malde, Trajectory
Memory and Continual Learning: Engram's Dan Biderman and Jessy Lin
Yu Su - Intelligence + Continual Learning = Expertise
Understanding Regularisation Methods for Continual Learning @ICML CL Workshop
Razvan Pascanu - Continual learning for deep learning and deep reinforcement learning
Mark Ring’s Continual Learning Workshop Introduction
Intelligence + Continual Learning = Expertise — Yu Su, NeoCognition
Continual Learning in Claude Code
Mathematics of Continual Learning - Liangzu Peng René Vidal - CoLLAs 2025
The Most Expensive “Almost” in AI
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Last Updated: September 18, 2026
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Full episode: youtu.be/n1E9IZfvGMA Me on twitter: x.com/dwarkesh_sp Dario Amodei thinks we are just a few years ... We have models that pass the bar exam and write functional code in seconds. But if you actually use them for real work, you ... Lex Fridman Podcast full episode: youtube.com/watch?v=EV7WhVT270Q Thank you for listening ❤ our ... Read the essay here: dwarkesh.com/p/era-of- Scale on policy self distillation to trajectories with a hundred tool calls and the model collapses into hedging. The tokens it learns ... Dan Biderman and Jessy Lin, co-founders of Engram, are building a neolab around memory and I will talk about three concepts-- intelligence, expertise, and how Most recent version of paper: arxiv.org/abs/2006.06357 Code at: github.com/freedbee/continual_regularisation. Recorded at the ML in PL 2019 Conference, the University of Warsaw, 22-24 November 2019. Razvan Pascanu (Google ... Watch CEO of CogitAI, Mark Ring, at the Scheduling a meeting is not finding a shared slot on everyone's calendar. It is a constraint optimization over authority, priority, and ... Get started for free on Tripo3D: ...