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AWS expanded its enterprise AI portfolio this week with a collection of new tools aimed at improving how AI agents operate across business environments. This includes how they understand data […] The post AWS Unveils New Tools Aimed at Making Enterprise AI Agents More Effective appeared first on AIwire.
Building AI systems at scale is demanding, requiring low-latency inference, fast vector search, strong GPU price-performance and infrastructure that can grow without multiplying operational complexity. NVIDIA’s latest work with Amazon Web Services (AWS) addresses each of those constraints. Across Amazon OpenSearch and Amazon EC2, NVIDIA AI infrastructure is giving enterprises more practical paths to deploy […]
Postquant Labs has finalized a decentralized network architecture that coordinates idle quantum processing hardware to actively safeguard $20 billion worth of vulnerable blockchain assets against early cryptographic failure vectors. According to Postquant Labs CEO Colton Dillion, the startup is launching…
AI coding agents are making it easier than ever to produce software. Ensuring that software is secure before deployment is another matter — one that AWS thinks AI should help with too. As enterprises adopt agentic development workflows, the volume of first-party code being created and modified is rising rapidly. Yet the process of validating vulnerabilities, determining whether they are exploitable, and fixing them often still depends on developers and security teams working through findings manually. AWS is aiming to address that imbalance with Continuum, a new service designed to continuously discover, investigate, and remediate vulnerabilities in enterprise environments, whether the code is their own or from third parties. Rather than simply generating alerts, the service is intended to help enterprises move findings through the entire remediation lifecycle, AWS VP of Security and Observability Chet Kapoor wrote in a blog post. For first-party applications, Continuum can analyze cod
AWS turned on AI traffic monetization inside AWS WAF on Monday, letting any site behind Amazon CloudFront charge AI agents per request in USDC through Coinbase's x402 protocol. It is the first time a hyperscale cloud has wired onchain settlement into its content-delivery edge.
For many developers, the hard part of building an AI application isn’t the model anymore. It’s keeping the application’s knowledge current. Retrieval-augmented generation (RAG) has become a popular technique for grounding AI applications in enterprise data, but it also introduces a steady stream of operational work, including tasks such as updating embeddings and indexes, synchronizing data sources, and tuning retrieval performance. AWS is seeking to remove much of that burden with Bedrock Managed Knowledge Base, a new managed service that automates the retrieval layer behind enterprise AI applications. “By default, the service automatically selects and manages a default embeddings model, re-ranker model, and foundational model on your behalf, so you can get up to speed quickly without needing to pick or maintain one yourself,” Daniel Abib, senior solutions architect at AWS, wrote in a blog post. In order to help maintain data pipelines without building and managing custom integrations
It is tempting to date cloud computing from the launch of Amazon S3 in 2006 and the rise of infrastructure as a service (IaaS) that followed. That was certainly the moment the market changed in a visible, irreversible way. But the truth is that cloud began earlier, in the 1990s, when software as a service (SaaS), application hosting, managed services providers, and various forms of remote subscription computing started to reshape how enterprises thought about owning and operating technology. Even then, the core value proposition was familiar: Let someone else run the infrastructure, abstract the complexity, deliver capability as a service, and allow the business to consume only what it needs. What AWS changed was the scale, accessibility, and precision of the execution. Amazon turned infrastructure into a programmable utility. It made compute and storage available in ways that were elastic, self-service, API-driven, and globally reachable. That was the breakthrough. Enterprises had out
Expanded collaboration enables customers to adopt and scale agentic AI as they modernize and run mission‑critical workloads on AWS NEW YORK, June 18, 2026 — Kyndryl, a leading provider of […] The post Kyndryl and AWS Expand Partnership to Accelerate Enterprise Agentic AI Adoption appeared first on AIwire.
AWS is in talks to sell its chips to other data centers. CEO Andy Jassy has said this represents a $50 billion opportunity for the company.
The EU probe could reshape cloud market dynamics, potentially enhancing competition and impacting AWS and Azure's strategic operations. The post Microsoft, Amazon Web Services face EU probe over cloud dominance appeared first on Crypto Briefing.
After helping turn cloud computing into essential infrastructure, Sivasubramanian is now leading AWS’s push to make agentic AI easier for companies to deploy at scale.
