🚀 Qwen3.5-397B-A17B is here: The first open-weight model in the Qwen3.5 series.
🖼️Native multimodal. Trained for real-world agents.
✨Powered by hybrid linear attention + sparse MoE and large-scale RL environment scaling.
⚡8.6x–19.0x decoding throughput vs Qwen3-Max
🌍201 languages & dialects
📜Apache2.0 licensed
🔗Dive in:
GitHub: https://t.co/NzNdS9joAT
Chat: https://t.co/bg4tAU0Rhw
API:https://t.co/YiiyKTnHoU
Qwen Code: https://t.co/qqwj5nAger
Hugging Face: https://t.co/wFMdX5p5um
ModelScope: https://t.co/9NGXcId57a
blog: https://t.co/AW8UQStXaL
📢 Just 8 weeks until #CoLLAs2025!
Modern ML thrives in benchmarks but struggles in the wild. CoLLAs is where we tackle non-stationarity head-on: catastrophic forgetting, distribution shift, continual RL, online adaptation, and lifelong learning for ML.
📍 Aug 11–14 @Penn
🧠 Keynotes, Workshops, tutorials, posters & community
🔗 https://t.co/8Yyt33Ef8h
#ContinualLearning #LifelongLearning #AI #MachineLearning
🚀RL algorithms are shaping the post-training of LLMs, but how do their objectives connect? In this blog, I explore their relationships and provide a unified perspective through the Policy Gradient Theorem—the backbone of policy gradient methods.
Dive in: https://t.co/SQREPoqGH0
BREAKING: Amii Chief Scientific Advisor, Richard S. Sutton, has been awarded the A.M. Turing Award, the highest honour in computer science, alongside Andrew Barto! Read the official @TheOfficialACM announcement: https://t.co/JXDhdEsQv7
#TuringAward#AI#ReinforcementLearning
🚨 Call for Reviewers! 🚨
Want to contribute to advancing lifelong learning research? #CoLLAs2025 is looking for expert reviewers! 📝
Help shape the field by reviewing cutting-edge research in continual and lifelong learning.
🔗 Apply here: https://t.co/nP6oE2OwPl
#MachineLearning #LifelongLearning #ContinualLearning #AI #AcademicReview
Would you believe that deep RL can work without replay buffers, target networks, or batch updates? Our recent work gets deep RL agents to learn from a continuous stream of data one sample at a time without storing any sample. Joint work with @Gautham529 and @rupammahmood.
Our NeurIPS paper is now on arXiv:
We introduce Action Value Gradient (AVG), a novel incremental deep RL method that learns in real-time, one sample at a time — no batch updates, target networks or a replay buffer!
Co-authors @mhmd_elsaye@bellingerc@white_martha@rupammahmood
RLC will be held at the Univ. of Alberta, Edmonton, in 2025. I'm happy to say that we now have the conference's website out: https://t.co/ZjpvWi5jyV
We'll continue to update it, and the CFP will be out soon, but the relevant dates are already there.
@RL_Conference@UAlberta
📢 Exciting News! The Fourth Conference on Lifelong Learning Agents (CoLLAs 2025) will be held at the University of Pennsylvania (@Penn) in Philadelphia, USA 🇺🇸
🗓️ Important Dates:
Abstract Deadline: Feb 21, 2025
Submission Deadline: Feb 26, 2025
Conference Dates: Aug 11 - Aug 14, 2025
We invite submissions that present new theories, methodologies, applications, or insights into algorithms and benchmarks designed for non-i.i.d. and non-stationary settings. Accepted papers will be published in the Proceedings of Machine Learning Research (PMLR). 📚
Full CFP: https://t.co/S8MwjLbOAr
#CoLLAs2025 #AI #MachineLearning #ContinualLearning #LifelongLearning #ResearchConference #CallForPapers #NonStationaryLearning
A year later and our work on Loss of Plasticity is finally published, in Nature no less! The Nature version is totally rewritten and has many new results:
https://t.co/QImypXpqQl
Congratulations to the authors:
@s_dohare@JFernandoHG
@LanceLan3
@rahman_parash@rupammahmood
It’s a deep learning problem that was ‘hidden in plain sight:’ A new Nature paper by Amii researchers explores why continual learning models can all of a sudden stop working, and what to do about it: https://t.co/WJ4Rgb8qoe #AI#ContinualLearning#MachineLearning
I couldn't be prouder of my colleagues at the @UAlberta! The work led by @s_dohare, in collaboration w/ J. F. H.-Garcia, @LanceLan3, @rahman_parash, @rupammahmood, & @RichardSSutton on continual learning and loss of plasticity is now published at @Nature!
https://t.co/PaO8GPsVHq