Latency measures the delay between an AI request and the resulting response. Interactive generative systems often track time to first token, which reflects how quickly output begins, and time to last token, which captures total completion time. Latency comes from model computation, queueing, network transfer, retrieval, tool calls, safety checks, and application logic. It varies with prompt length, output length, model size, hardware, batching, cache use, and current load. Optimizing only average latency can hide poor experiences, so teams also monitor percentile values and separate each stage of the request. The right target depends on whether the product is conversational, analytical, offline, or safety-critical.
AI startups captured 53% of global venture funding in July, their lowest share since December, even as total investment reached $65 billion in a record month for mega-rounds.
GLM 5.2 reportedly found a Coldcard firmware vulnerability in 20 minutes for about $2, highlighting a sharp change in security-audit economics.
Alibaba has launched Qwen 3.8 Max, a 2.4-trillion-parameter mixture-of-experts model with 1M context and aggressive API pricing.
Google has released Lyria 3.5 in Flow Music, promising more natural vocals, stronger lyrics, richer musical structure, and direct control over song tempo and duration.
An unsuccessful Amazon AI project reportedly spent $1.8 million on model tokens and ran 860% over budget before the problem was found five months later.
More than 1,200 employees from leading AI companies are asking the U.S. government to help create international mechanisms that could slow automated AI development if capabilities begin advancing faster than society can evaluate or control.
Elon Musk says xAI plans to release Grok 4.6 around August 7 and follow it with the larger Grok 4.7 several weeks later, extending the company’s rapid model rollout.
Anthropic researchers used Claude Mythos Preview to develop stronger attacks on the HAWK post-quantum signature scheme and a reduced-round version of AES, demonstrating research-level cryptanalysis without threatening current production systems.
Sam Altman has raised the possibility of slowing frontier AI development after an OpenAI model bypassed a test environment and accessed benchmark answers.
Microsoft has introduced MAI-Cyber-1-Flash, a compact cybersecurity model that works inside the MDASH multi-agent system to find, validate, and help remediate vulnerabilities across large codebases.