An autoregressive model generates or predicts a sequence one element at a time, conditioning each new step on earlier elements. In a language model, the next token is selected from probabilities based on the prompt and tokens already generated; in time-series analysis, a future value may depend on previous observations. This structure supports flexible generation and variable-length output, but it creates sequential inference that can be slower than producing all outputs in parallel. Errors can also compound because later predictions depend on earlier generated content. Sampling strategy, context length, caching, and stopping rules strongly influence results even though the underlying model parameters remain unchanged.
AI-driven bots now generate more internet traffic than humans, according to a new report, highlighting the growing impact of automated systems online.
New research shows that telling AI models they are “experts” can reduce accuracy in tasks like coding and math, while improving safety and alignment outcomes.
Meta introduced four new in-house MTIA chips designed for AI training and inference as the company accelerates data center expansion. The chips aim to improve performance and reduce reliance on external hardware suppliers.
Google has rolled out Canvas in AI Mode to all U.S. users in English, enabling people to create documents, dashboards, and interactive tools directly within Search. The feature provides a dynamic workspace for planning projects and building simple applications.
Andrej Karpathy argues AI coding agents now fundamentally change programming workflows, enabling long-running autonomous tasks and redefining software engineering.
MSCI introduces AI connectors enabling access to its data via MSCI ONE, ChatGPT, and Claude, debuting IndexAI Insights to deliver conversational index analytics powered by large language models.
Google is rolling out Gemini 3.1 Pro across consumer, developer, and enterprise products, touting major gains in reasoning performance and benchmark results.
India’s AI Impact Summit in New Delhi delivered more than $250 billion in investment commitments, spanning data centers, AI infrastructure, and global expansion plans.
Fei-Fei Li’s World Labs secured a $200 million investment from Autodesk as part of a broader $1 billion round, deepening collaboration on AI systems that generate and reason about 3D environments.
Mistral AI CEO Arthur Mensch said more than half of today’s enterprise software could be replaced by AI, intensifying investor concerns about the future of SaaS business models.