An AI-powered hiring solution for talent acquisition teams managing hiring at scale, built on Amazon's hiring science. AI agents conduct structured voice interviews, administer evidence-based assessments, and score candidates consistently. Candidates interview 24/7 from any device; recruiters review scores, transcripts, and detailed evaluations the next morning. All candidate data is anonymized during AI evaluation, every competency is scored against a rubric with each score tied to specific interview evidence, and recruiters keep final decision authority. GA includes competency-based assessments, AI-led voice interviews with adaptive questioning, a brand-customizable mobile-first candidate portal, and admin onboarding tools.
Corretto 27, a Feature Release of the no-cost multi-platform OpenJDK distribution, is out for Linux, Windows, and macOS with support through April 2027. Notable features:
Kimi K3 is available on Amazon Bedrock for coding and knowledge work — the first open model to reach 2.8 trillion parameters, combining native vision with a 1-million-token context window. Suited to long-running coding sessions across large repositories, multi-document analysis, and extended agent workflows. Moonshot reports ~2.5x scaling efficiency over Kimi K2. It's also the first open-weight model on Bedrock with explicit prompt caching, cutting latency and input costs when reusing context across calls.
A new simplified flow for starting projects: instead of completing configuration tasks first, you begin from what you want to build.
Corretto 27 (post-quantum TLS, compact headers, G1 default) is a genuinely good reason to upgrade your JVM distribution, and Kimi K3 brings an open 2.8T-parameter model with explicit prompt caching to Bedrock — noteworthy if long-context, repo-scale coding is your workload.