Machine Learning Research
Computer Use Gains Momentum: OpenAI’s Operator automates online tasks with a new AI agent
OpenAI introduced an AI agent that performs simple web tasks on a user’s behalf.
Machine Learning Research
Machine Learning Research
Reinforcement Learning Heats Up: How DeepSeek-R1 and Kimi k1.5 use reinforcement learning to improve reasoning
Reinforcement learning is emerging as an avenue for building large language models with advanced reasoning capabilities.
Machine Learning Research
Generated Chip Designs Work in Mysterious Ways: Researchers used deep learning and an evolutionary algorithm to design chips in minutes
Designing integrated circuits typically requires years of human expertise. Recent work set AI to the task with surprising results.
Machine Learning Research
DeepSeek Sharpens Its Reasoning: DeepSeek-R1, an affordable rival to OpenAI’s o1
A new open model rivals OpenAI’s o1, and it’s free to use or modify.
Machine Learning Research
Calibrating Contrast: X-CLR, an approach to contrastive learning for better vision models
Contrastive loss functions make it possible to produce good embeddings without labeled data. A twist on this idea makes even more useful embeddings.
Machine Learning Research
DeepSeek Ups the Open Weights Ante: DeepSeek-V3 redefines LLM performance and cost efficiency
A new model from Hangzhou upstart DeepSeek delivers outstanding performance and may change the equation for training costs.
Machine Learning Research
Better Performance From Merged Models: Localize-and-Stitch improves methods for merging and fine-tuning multiple models
Merging multiple fine-tuned models is a less expensive alternative to hosting multiple specialized models. But, while model merging can deliver higher average performance across several tasks, it often results in lower performance on specific tasks. New work addresses this issue.
Machine Learning Research
Massively More Training Text: Harvard unveils a million-book corpus for AI training
Harvard University amassed a huge new text corpus for training machine learning models.
Machine Learning Research
Models Can Use Tools in Deceptive Ways: Researchers expose AI models' deceptive behaviors
Large language models have been shown to be capable of lying when users unintentionally give them an incentive to do so. Further research shows that LLMs with access to tools can be incentivized to use them in deceptive ways.
Machine Learning Research
What LLM Users Want: Anthropic reveals how users interact with Claude 3.5
Anthropic analyzed 1 million anonymized conversations between users and Claude 3.5 Sonnet. The study found that most people used the model for software development and also revealed malfunctions and jailbreaks.
Machine Learning Research
Mustafa Suleyman: Agents of action
In 2025, AI will have learned to see, it will be way smarter and more accurate, and it will start to do things on your behalf.
Machine Learning Research
Albert Gu: More learning, less data
Building a foundation model takes tremendous amounts of data. In the coming year, I hope we’ll enable models to learn more from less data.