An exciting new approach for doing continual learning, using nested optimization for enhancing long context processing.
MACHINE LEARNING
-
ByteDance Ouro: Scaling Latent Reasoning in Language Models
By
–
New paper from ByteDance Seed: Scaling Latent Reasoning via Looped LMs This paper proposes Ouro, which reuse the same layers to think in latent space instead of dumping long chain-of-thought text 2-3x param efficiency + increased performance via iterative latent computation
-
Share insights on LLMs AI Agents and Machine Learning
By
–
If you found it insightful, reshare with your network. Find me → @akshay_pachaar For more insights and tutorials on LLMs, AI Agents, and Machine Learning!
-
SAIL-Embedding: Omni-modal Foundation Model for Recommendations
By
–
What if one embedding model could seamlessly understand text, images, user behavior, and item IDs—all while boosting real-world recommendation performance? Meet SAIL-Embedding: an omni-modal foundation model engineered for the messy realities of industrial AI. Unlike CLIP-style
-
Self Guide to Becoming a Data Analyst Professional
By
–
Self Guide to becoming a #DataAnalyst
Via @ingliguori #programming #DataScience #Python #MachineLearning #python #IoT #100DaysOfCode #CodeNewbie #reactjs #bugbounty #gamedev #BigData #Analytics #NeuralNetworks #Cloud #OpenSource #AI #SQL #Scala #DEVCommunity #codinglife #R #Java -
Major AI Releases Despite Resource Constraints in 100 Days
By
–
crazy how they just keep finding a way to do it with restricted resources look at this list for the major releases in the last ~100 days alone
-
Fei-Fei Li Wins Queen Elizabeth Prize for Engineering
By
–
This week, our co-founding director @drfeifei has been awarded the 2025 @QEPrize for Engineering, alongside @StanfordHAI Distinguished Fellows @geoffreyhinton & @Yoshua_Bengio
, acknowledging their role in shaping today's AI revolution. Congratulations! https://
hai.stanford.edu/news/fei-fei-l
i-wins-queen-elizabeth-prize-for-engineering
… -
Junior AI Scientist and Risk Report on Autonomous Scientific Exploration
By
–
Jr. AI Scientist and Its Risk Report Autonomous Scientific Exploration from a Baseline Paper
-
SAIL-RL: Guiding MLLMs Thinking with Dual-Reward RL
By
–
SAIL-RL Guiding MLLMs in When and How to Think via Dual-Reward RL Tuning
-
Moonshot AI Unveils Kimi K2 Thinking 1T-Parameter Model
By
–
Beijing-based Moonshot AI has unveiled Kimi K2 Thinking — a 1T-parameter Mixture-of-Experts model built for deep reasoning, coding, and web search. Performance Highlights: SOTA on HLE (44.9%), BrowseComp (60.2%), SWE-Bench Verified (71.3%) Matches or surpasses GPT-5