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AI-native software engineering may be closer than developers think

CIO

Developers unimpressed by the early returns of generative AI for coding take note: Software development is headed toward a new era, when most code will be written by AI agents and reviewed by experienced developers, Gartner predicts. That’s what we call an AI software engineering agent.

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Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning - AI

This post presents a solution where you can upload a recording of your meeting (a feature available in most modern digital communication services such as Amazon Chime ) to a centralized video insights and summarization engine. Many commercial generative AI solutions available are expensive and require user-based licenses.

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Salesforce Ventures targets new $250M fund at generative AI startups

TechCrunch

The enterprise is about to get hit by the generative AI hype train, as Salesforce prepares to invest in startups developing what it calls “responsible generative AI.” Salesforce Ventures targets new $250M fund at generative AI startups by Paul Sawers originally published on TechCrunch

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

In this post, we explore a generative AI solution leveraging Amazon Bedrock to streamline the WAFR process. We demonstrate how to harness the power of LLMs to build an intelligent, scalable system that analyzes architecture documents and generates insightful recommendations based on AWS Well-Architected best practices.

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Reduce ML training costs with Amazon SageMaker HyperPod

AWS Machine Learning - AI

Training a frontier model is highly compute-intensive, requiring a distributed system of hundreds, or thousands, of accelerated instances running for several weeks or months to complete a single job. For example, pre-training the Llama 3 70B model with 15 trillion training tokens took 6.5 During the training of Llama 3.1

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Comprehensive data management for AI: The next-gen data management engine that will drive AI to new heights

CIO

The core of their problem is applying AI technology to the data they already have, whether in the cloud, on their premises, or more likely both. Imagine that you’re a data engineer. You export, move, and centralize your data for training purposes with all the associated time and capacity inefficiencies that entails.

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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

While organizations continue to discover the powerful applications of generative AI , adoption is often slowed down by team silos and bespoke workflows. To move faster, enterprises need robust operating models and a holistic approach that simplifies the generative AI lifecycle.