Causal language modeling, abbreviated CLM, is a training objective in which a model predicts the next token from tokens that came before it. A causal attention mask prevents information from later positions from leaking into each prediction. Repeating this task across large text collections teaches an autoregressive model statistical patterns of language, knowledge associations, and ways to continue a sequence. At inference time, the model generates text token by token using the same left-to-right dependency. CLM differs from masked language modeling, which hides selected tokens inside a sequence and uses surrounding context on both sides. The objective supports open-ended generation but does not guarantee factual or intentional understanding.
Tolan has raised $30 million for its everyday AI companion. The startup says 70% of users are women as it balances wider access with computing costs.
Anthropic is discussing another $45 billion Nscale agreement for West Virginia computing capacity, adding to an existing commitment as Claude demand grows.
Mass General Brigham’s FAHR-Face analyzes facial photographs to estimate aging and cancer survival risk, but clinical benefit still needs testing.
DeepSeek has released DeepInfer, its production inference engine, with support for V4.1 Flash on Nvidia SM100 and Huawei Ascend 950 hardware. The public release covers offline inference.
Inception says Mercury 3 delivers 1,068 tokens per second with a million-token context window, bringing diffusion-based AI to fast agents, tutoring and customer support.
MiniMax has released M3.1 Flash for AI agents, coding and computer use, with API pricing from $0.15 per million input tokens and claimed speeds above 200 tokens per second.
Germany has signed a joint declaration with Nvidia to advance industrial AI models for robotics, manufacturing and autonomous systems through its Industry 4.0 network.
World has introduced a bank-facing World ID suite that lets financial firms request proof of humanity, presence or selected attributes as AI deepfakes and agents reshape trust online.
Anthropic says Claude-driven development pushed code changes past 30,000 a day, turning Git infrastructure into a bottleneck and leading to its new Scion source-control system.
Anthropic says its new Public Benefit Fund will begin with 5% of company shares and could grow with its valuation to support major grants and direct distributions.