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Showing 121–140 of 167 dossiers

Gemini 3.8 Flash raises agent capability at the same token price — but may use more tokens per task

Gemini 3.8 Flash keeps 3.7 Flash’s promotional per-token rate and Flash-tier latency, but early independent analysis suggests harder reasoning can increase tokens consumed per task. A separate 3.8 Flash Cyber model is available only through Google’s Fairwind defensive-security program.

OpenAI’s Jalapeño chip posts its first public inference results ahead of 2026 deployment

Jalapeño is now working first-party silicon rather than a roadmap item. OpenAI reports materially better latency and throughput per kilowatt than compared Blackwell systems across GPT-OSS, DeepSeek and Kimi workloads, while SemiAnalysis says it inspected the chip and benchmarked it with its open InferenceX suite.

ChatGPT Ads expands self-service globally as targeting, measurement and campaign tooling deepen

ChatGPT Ads is moving from beta inventory toward a global performance-ad stack. OpenAI has expanded self-service buying and says optimized bidding is now the majority of campaigns, while new audience, measurement and workflow controls increase both scale and attribution complexity.

Federal court blocks the Pentagon’s Anthropic supply-chain blacklist, removing one Claude procurement barrier

The Anthropic ruling is not merely a political dispute: a procurement classification that could prevent defense contractors from using Claude on Pentagon work has been struck down. Builders serving government customers still need to watch separate directives and appeals, but one material supplier-risk constraint is no longer enforceable under the current ruling.

NVIDIA Groq 3 LPX enters full production with 3,431-token/s long-context inference

Groq 3 LPX is moving from architecture announcement to manufactured infrastructure. Artificial Analysis measured about 3,400 output tokens/s at both 10K and 100K context on an NVIDIA-hosted private endpoint, but the single-concurrency benchmark does not yet establish public-cloud price, multi-tenant throughput or end-to-end agent speed.

Amazon SES can now switch open and click tracking per email request

The new request-level controls make email measurement a per-send decision: an application can keep one SES configuration set while disabling open or click tracking for recipients who should not be measured. The override wins over the configuration-set default and adds no separate feature charge.

Neon makes Functions and Object Storage branch with Postgres

Neon’s beta backend now combines Postgres branches with Node.js Functions and S3-compatible Object Storage that inherit branch semantics. For builders, that makes ephemeral preview/test environments more complete: database state, backend code and object data can move together instead of requiring separate production-adjacent services.

Google DeepMind is piloting double-blind frontier-model evaluations with confidential computing

The pilot attacks a persistent evaluation trade-off: labs do not want to reveal frontier-model internals, while evaluators do not want benchmark prompts leaking back to the model provider. DeepMind says a Singapore AI Safety Institute pilot kept both sides’ sensitive assets hidden during execution.

Microsoft Project Zenith turns 64GB-class Windows PCs into a standardized local-AI developer tier

Project Zenith is not a new model or another Copilot feature. It standardizes a developer-focused Windows experience and hardware floor for local AI work, with preconfigured tooling and OS settings intended to reduce setup friction and dependence on metered cloud inference.

Cloudflare links AI code scanning to live edge exposure before proposing a fix

The interesting part is not another AI scanner. Cloudflare is connecting source-code evidence to what is actually deployed and being attacked at the edge, validating findings outside the model, then preparing both a code patch and, where appropriate, a narrowly scoped WAF mitigation for customer review.

Funes gives coding agents a local memory that can follow you across tools and machines

Funes treats agent memory as user-owned data rather than a hosted account feature: retrieval and reranking run locally, provenance stays attached to recalled passages, and cross-machine sharing is optional. The main risk is that publishing session-derived memory can still expose secrets if redaction misses them.