Amazon Web Services made availability announcements for services including its enterprise AI assistant Q, which now becomes available on its entry-level SageMaker tier, and introduced some new products at the AWS Summit at New York City’s Javits Center this week. Notably, the App Studio development assistant has launched in public preview. Amazon is also highlighting new features to improve AI accuracy, including a guardrail that detects “hallucinations.” Overall, the event — one in a series of daylong summits held in key cities across the nation — emphasized the comprehensiveness of the company’s generative AI stack. Continue reading AWS Expands Q Availability, Adds Guardrails for Bedrock AI

Google has debuted Project IDX, an AI-enabled development environment for building full-stack web and multiplatform apps. Comparing app development that works across mobile, web, and desktop platforms to “building a Rube Goldberg machine” with a duct-taped tech stack, Google says Project IDX smooths the process of compiling, testing, deploying and monitoring apps. The browser-based Project IDX is built on the Google Cloud using the Codey family of AI foundation models built on PaLM 2. Currently, IDX supports the JavaScript and Dart languages, with plans for Python, Go and more. Continue reading Google’s Project IDX Offers Full-Stack Dev in a Web Browser

A new generation of cybersecurity solutions is gaining attention for merging corporate networks with security tools like malware protection into one system that can be centrally managed. Akamai, Cisco, Cloudflare, Zscaler, Palo Alto Networks and others have begun offering consolidated cybersecurity platforms that span IT, operations and security, leveraging resources and theoretically reducing costs through shared expenses. Having all eyes on traffic and workloads via a single framework may also make it possible for chief information officers and IT personnel to be more effective and focused. Continue reading Cloud Platforms Combine Security, Operations for Efficiency

Nvidia has issued a software update for its formidable NeMo Megatron giant language training model, increasing efficiency and speed. Barely a year since Nvidia unveiled Megatron, this latest improvement further leverages the transformer engine architecture that has become synonymous with deep learning since Google introduced the concept in 2017. New features result in what Nvidia says is a 5x reduction in memory requirements and up to a 30 percent gain in speed for models as large as 1 trillion parameters, making NeMo Megatron better at handling transformer tasks across the entire stack. Continue reading Nvidia Turbo Charges NeMo Megatron Large Training Model