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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.

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.

Gemini 3.5 Transcribe gives developers separate live and file speech-to-text APIs at about $0.009 and $0.005 per minute

Gemini 3.5 Transcribe turns Google’s audio understanding into a purpose-built developer surface: low-latency live transcription costs roughly $0.009/minute at Google’s published assumptions, while file transcription is roughly $0.005/minute and supports richer metadata.

Cloudflare Workers replaces 3MB and 10MB compressed bundle caps with one 64MiB uncompressed limit

The change makes heavier frameworks and dependency trees deployable to Workers without plan-specific compressed-size ceilings, but it also changes what builders need to measure: the operative limit is now uncompressed Total Upload rather than the gzip number they may have optimized around.

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.

Railway Cloud Agents turn coding agents into persistent deployment-adjacent VMs

Railway Cloud Agents are managed, persistent development machines rather than a new model or harness. They reuse developers’ existing agent credentials, sleep when disconnected by default, retain disk state, and live inside Railway project environments—blurring the boundary between remote coding workspace and deployment platform.