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Showing 141–159 of 159 dossiers

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.

Anthropic’s Model Hardware Standard gives AI agents a shared interface for physical devices

MHS is an attempt to make microscopes, liquid handlers, robotic arms and other programmable hardware look like a consistent tool surface to AI agents. It is still a research preview, but the interoperability layer is already being tested with research institutions and hardware vendors.

AWS and NVIDIA plan 2 million more GPUs as their AI stack expands beyond accelerators

The scale of the AWS–NVIDIA expansion is the headline, but the builder consequence is broader: AWS is co-engineering more of the NVIDIA stack, from CPUs and interconnects to models, vector indexing and physical-AI infrastructure, rather than merely adding another GPU instance family.

AWS Security Agent can now hard-cap autonomous pentest spend and revalidate individual fixes

AWS’s agentic pentesting service can run multiple security tasks in parallel, so billable task-hours may exceed wall-clock test duration. New per-run task-hour limits stop a test gracefully at the ceiling and preserve findings, while targeted revalidation checks specific fixes without rerunning the entire pentest.

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.

Google is adding hard spend caps and commitment pricing for AI agent workloads

Google’s new agent FinOps model combines hard monthly spend caps that pause agent API calls, Flexible Savings Plans with one- or three-year commitments, pay-as-you-go Gemini Enterprise usage and planned deferred execution at up to half normal inference cost. The controls are useful, but commitment economics and task eligibility need to be modeled carefully.

Cloudflare Web Analytics can now change SPA pageview counts as it measures soft navigations properly

Cloudflare’s RUM measurement model now distinguishes hard navigations, native soft navigations and routing-API fallbacks. For React, Vue, Angular, Svelte and other client-routed sites, the immediate consequence is a metric discontinuity: pageviews and Core Web Vitals can shift without an underlying traffic change.

GitLab 19.3 turns plain-English process knowledge into runnable agentic flows

Custom Flows became generally available in GitLab 19.2; 19.3 adds the missing authoring layer. Flow Creator reads current Flow Registry docs, applies known failure rules and generates a runnable flow from plain English. Builders still need to review, register and govern the automation rather than treating generated YAML as trusted infrastructure.

Bun 1.4 rewrites the runtime in Rust and moves closer to Node.js 26 compatibility

Bun 1.4 combines an implementation-language rewrite with a larger built-in standard library and a substantial Node-compatibility push. For teams already running Bun, the practical task is to validate native addons, runtime behavior and workload-specific performance rather than treating this as a drop-in minor upgrade.

GitHub Spark is shutting down August 31 — export code now and replace broken `llm()` calls

GitHub Spark stops being available to existing users on August 31, 2026. Deployed apps are meant to keep running, but owners should export code to a repository now; Spark apps using `llm()` need a separate inference provider because the underlying GitHub Models service retired July 30.