Machine Learning Research
Training Cars to Reason: Nvidia’s Alpamayo-R1 is a robotics-style reasoning model for autonomous vehicles
Chain-of-thought reasoning can help autonomous vehicles decide what to do next.
Machine Learning Research
Machine Learning Research
Retrieval Faces Hard Limits: Google and Johns Hopkins researchers show embedding models can’t search unlimited documents
Can your retriever find all the relevant documents for any query your users might enter? Maybe not, research shows.
Machine Learning Research
More Affordable Reasoning: Canadian researchers find capping context helps models better retrieve data
One way to improve a reasoning model’s performance is to let it produce a longer chain of thought. However, attending to ever-longer contexts can become expensive, and making that attention more efficient requires changes to a model’s architecture.
Machine Learning Research
Lingua Franca for Science Labs: SAIL’s Science Context Protocol helps AI Agents communicate about local and virtual experiments
An open protocol aims to enable AI agents to conduct scientific research autonomously across disciplinary and institutional boundaries.
Machine Learning Research
Teaching Models to Tell the Truth: OpenAI fine-tuned a version of GPT-5 to confess when it was breaking the rules
Large language models occasionally conceal their failures to comply with constraints they’ve been trained or prompted to observe. Researchers trained an LLM to admit when it disobeyed.
Machine Learning Research
Chatbots That Build Community by Sharon Zhou: Sharon Zhou of AMD on expanding chat to serve groups and connect us with other people
Next year, I’m excited to see AI break out of 1:1 relationships with each of us. In 2026, AI has the potential to bring people together and unite us with human connection, rather than polarize and isolate us. It’s about time for ChatGPT to enter your group chats.
Machine Learning Research
Multimodal Models for Biomedicine by Pengtao Xie: Pengtao Xie of UC-San Diego on why medical models need to visualize tiny chemicals and large organs
Over the past few years, we have seen rapid progress in models that jointly reason over text, images, sequences, graphs, and time series. Yet in biomedical settings, these capabilities often remain fragmented, brittle, or difficult to interpret.
Machine Learning Research
From Prediction to Action by Tanmay Gupta: Tanmay Gupta of the Allen Institute on building AI for long-horizon tasks
AI research in 2026 should confront a simple but transformative realization: Models that predict are not the same as systems that act. The latter is what we actually need.
Machine Learning Research
AI for Scientific Discovery by Adji Bousso Dieng: Adji Bousso Dieng, Princeton University Assistant Professor and AI Researcher, on optimizing models for the long tail
In 2026, I hope AI will transition from being a tool for efficiency to a catalyst for scientific discovery.
Machine Learning Research
Open Source Wins by David Cox: David Cox, VP for AI Models at IBM Research, on the need for open development in AI
My hope is that open AI continues to flourish and ultimately wins.
Machine Learning Research
Agents Write Code Faster, Cheaper: Software developers used more versatile AI-powered tools to write code
Coding apps moved beyond autofill-style code completion to agentic systems that manage a wide range of software development tasks.
Machine Learning Research
Thinking Models Solve Bigger Problems: Reasoning models, beginning with OpenAI’s o1 and DeepSeek’s R1, transformed the industry
Think step by step. Explain your reasoning. Work backwards from the answer. As 2025 began, models executed these reasoning strategies only when prompted. Now most new large language models do it as a matter of course, improving performance across a wide range of tasks.