A New York-based startup called Flourish has raised $500 million to pursue one of AI’s most ambitious goals: building an artificial intelligence system that works like the human brain. Steven Levy reports for WIRED that Jeff Bezos led the early funding after reading a two-page pitch document, eventually contributing tens of millions of dollars and …
A new simulation by enterprise AI startup Emergence AI tested what happens when AI models run a society. Jake Angelo reports for Fortune that each of five AI models governed its own 15-day simulated world, with strikingly different outcomes. The simulation featured over 40 locations, real-time weather data synced to New York City, access to …
A new startup called Trajectory is building a platform that helps AI products improve continuously by learning from real user interactions. Maxwell Zeff reports for WIRED that the company was founded by researchers who previously worked at Google DeepMind, Apple, and OpenAI, and has raised a $15 million seed round at a $115 million valuation. …
Researchers have developed a lightweight memory module for AI agents that retains information across long interactions without expanding the context window or relying on external retrieval systems. Called delta-mem, the system adds just 0.12% of additional parameters to a base language model while outperforming much larger alternatives on memory-intensive tasks, Ben Dickson reports for VentureBeat. …
A newly released language model called “talkie” offers a striking glimpse into what artificial intelligence looks like when trained exclusively on historical text. The model, described as a 13-billion-parameter system built on data from around 1930, produces responses that blend period-accurate knowledge with confident factual errors. The official announcement explains that the project presents talkie …
Google Research has released TurboQuant, a new compression algorithm designed to reduce the memory demands of large language models. The company says it can shrink a model’s key-value cache by at least six times and speed up a core processing step called attention computation by up to eight times, all without retraining the model or …
The development of large language models has undergone fundamental changes in 2025, marked by new training methods and surprising capabilities that reveal a fundamentally different form of intelligence than expected. AI researcher Andrej Karpathy writes on his blog about six major shifts that defined the year. The most significant change involves a new training technique …
Two major tech companies are tackling one of artificial intelligence’s most persistent problems: getting AI systems to stop making things up or hiding their mistakes. OpenAI and Amazon have each developed distinct approaches to make large language models more honest and reliable. OpenAI’s thruth serum OpenAI researchers introduced a technique called “confessions” that functions like …
Researchers at the University of Zurich and Cologne University are creating large language models trained solely on historical documents up to specific dates. The team, led by Daniel Göttlich, Dominik Loibner, Guohui Jiang, and Hans-Joachim Voth, describes their project on GitHub. The models, called Ranke-4B, contain four billion parameters and are trained on 80 billion …
Researchers at New York University have created a new AI architecture that generates higher-quality images more efficiently. Ben Dickson reports for VentureBeat that the model, called Representation Autoencoders or RAE, improves an AI’s understanding of image content, which leads to better results. The new method challenges common practices in building diffusion models, the technology behind …