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.
In 2026, I hope AI will transition from being a tool for efficiency to a catalyst for scientific discovery.
My hope is that open AI continues to flourish and ultimately wins.
Coding apps moved beyond autofill-style code completion to agentic systems that manage a wide range of software development tasks.
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.
Enabling a pretrained large language model to process a data type other than text (say, images), possibly in a specialized domain (say, radiology), typically requires thousands to millions of examples that pair the other data (perhaps x-rays) with text.
OpenAI launched GPT-5.2 only weeks after its CEO Sam Altman reportedly issued a “code red” alarm in response to Google's Gemini 3.
Runway’s GWM-1 family of video-generation models respond to user input in real time while producing scenes that remain consistent regardless of the camera’s position.
Large language models often fail at puzzles like Sudoku, for which a solution includes multiple elements and a single mistake invalidates all of them. Researchers showed that a tiny network, by repeatedly refining its solution, can solve this sort of puzzle well.
Amazon raised the competitive profile of its foundation models and added services for custom model training and an agent platform for browser automation.
Claude Opus 4.5, the latest version of Anthropic’s flagship model, extends the earlier version’s strengths in coding, computer use, and agentic workflows while generating fewer tokens.
In factories, where teams of robotic arms work in tight spaces, their motions are programmed by hand to keep them from interfering with one another. Researchers automated this programming using graph neural networks trained via reinforcement learning.
Baidu debuted two models: a lightweight, open-weights, vision-language model and a giant, proprietary, multimodal model built to take on U.S. competitors.
Models that generate 3D spaces typically generate them as users move through them without generating a persistent world to be explored later. A new model produces 3D worlds that can be exported and modified.
Meta’s Segment Anything Model (SAM) image-segmentation model has evolved into an open-weights suite for generating 3D objects. SAM 3 segments images, SAM 3D turns the segments into 3D objects, and SAM 3D Body produces 3D objects of any people among the segments. You can experiment with all three.
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