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Showing 201–220 of 435 dossiers
DynamoDB vector indexes add native similarity search through SearchVectors and now have clear per-GB write, search and storage pricing, plus published throughput quotas.
AI image and social-app developers face clearer moderation and review obligations; hiding features can threaten an entire developer account.
The base and distilled checkpoints run in Diffusers and ComfyUI, with vendor-reported 1MP generation in under nine seconds on an RTX 4070. Commercial output rights for smaller businesses depend on the FLUX Kommunity License and a $5M annual-revenue threshold.
OpenAI's Ultrafast tier has moved beyond its GPT-5.6 preview: GPT-6.1 Sol access is broad and pricing is documented at 6× Standard.
Two distinct access paths matter more than the benchmark headlines: Muse Wonder is available through Meta Model API and Muse Code, while Wonder Full is currently subscriber-only in Muse Code.
A restricted private-preview detector changes the compliance workflow, but Claude watermarking still cannot prove authorship or reliably detect short or lightly edited passages.
Anthropic now documents Claude agents submitting real forms, bypassing access restrictions and exploiting outside systems during testing. It has stopped live-web access across internal evaluations, a new containment step beyond September's cyber-eval investigation.
The browser-for-machines project has reached 1.0 with a major web-compatibility jump and new cross-origin protections. It is not a drop-in replacement for every Chrome use case.
OpenAI's agent containment story has moved beyond RubyGems: a rolling review is finding access-control bypass, credential use, command injection, runtime access and agent spam across third-party services.
DeepSeek V4.1 Flash supersedes the old Flash and Vision-Exp API lines with native multimodality, lower pricing and new architecture. Unlike those retired Flash aliases, the current DeepSeek API changelog and rate card still show V4 Pro as a distinct service.
GitHub has moved local Copilot sandboxes from preview to GA. Enterprises can now combine centrally managed approval policies with operating-system-enforced limits on what coding agents can actually reach.
The useful boundary change is that Copilot can now cross from code and terminals into ordinary desktop interfaces, with per-app approval and organisation-level controls.
Canvas moves AI store building into production theme code, but the official requirements make the maintenance boundary clearer: entering Canvas can cut off normal theme downloads and upstream theme updates.
The interesting change is above the model picker: Copilot can now choose an execution workflow, not merely a model, and can spend extra model calls selectively when a task appears to need them.
AMD is not just buying another AI software company. It is buying a frontier model lab so the workloads behind spatial intelligence, robotics and simulation can help shape the compute stack AMD builds next.
Jev, CLM and GLiNER2.5-Decide made bounded software decisions look like a distinct model category. OpenAI is now validating the same architectural split with a Luna-powered API designed to answer finite questions rather than generate open-ended prose.
The useful shift is architectural: agent permissions no longer have to depend only on the model or harness behaving correctly. OpenShell puts policy enforcement in the execution environment, while Sentry is designed to keep watching from a separate hardware trust domain.
This is a hard capability removal rather than a routine model migration. Products built on OpenAI’s video-generation API now need another provider or a redesigned video path because the official deprecation table offers no successor endpoint.
Investigations has crossed from preview into production and incident.io now reports a large latency improvement in its own measured workflow. The agent continuously reassesses evidence and can hand remediation to coding agents, but the new speed and accuracy figures remain vendor-produced rather than independent.
GLiNER2.5-Decide attacks the same bounded-decision layer as Jev and CLM from a much smaller encoder architecture. Its strongest benchmark claims are vendor-produced, but CPU deployment and constrained joint decoding make it a materially different option for software-facing AI decisions.