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Favorite This post is co-written with Mark Ross from Atos. Organizations pursuing AI transformation can face a familiar challenge: how to upskill their workforce at scale in a way that changes how teams build, deploy, and use AI. Traditional AI training approaches—online courses, certification programs, and classroom-based instruction—are necessary, but
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Shared by AWS Machine Learning March 17, 2026
Favorite We’re expanding Personal Intelligence across AI Mode in Search, the Gemini app and Gemini in Chrome. View Original Source (blog.google/technology/ai/) Here.
Favorite Google is making new investments, building new tools and developing code security to improve open source security. View Original Source (blog.google/technology/ai/) Here.
Favorite Building and managing machine learning (ML) features at scale is one of the most critical and complex challenges in modern data science workflows. Organizations often struggle with fragmented feature pipelines, inconsistent data definitions, and redundant engineering efforts across teams. Without a centralized system for storing and reusing features, models
Read More Shared by AWS Machine Learning March 16, 2026
Favorite This post is cowritten with Ilija Subanovic and Michael Rice from Workhuman. Workhuman’s customer service and analytics team were drowning in one-time reporting requests from seven million users worldwide—a common challenge with legacy reporting tools at scale. Business intelligence (BI) admins faced mounting pressure as their teams became overwhelmed
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Favorite We thank Greg Pereira and Robert Shaw from the llm-d team for their support in bringing llm-d to AWS. In the agentic and reasoning era, large language models (LLMs) generate 10x more tokens and compute through complex reasoning chains compared to single-shot replies. Agentic AI workflows also create highly variable
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Favorite This is Part II of a two-part series from the AWS Generative AI Innovation Center. If you missed Part I, refer to Operationalizing Agentic AI Part 1: A Stakeholder’s Guide. The biggest barrier to agentic AI isn’t the technology—it’s the operating model. In Part I, we established that organizations
Read More Shared by AWS Machine Learning March 16, 2026
Favorite AI is moving fast, and for most of our customers, the real opportunity isn’t in experimenting with it—it’s in running AI in production where it drives meaningful business outcomes. This means building systems that run reliably, perform at scale, and meet your organization’s security and compliance requirements. Today at
Read More Shared by AWS Machine Learning March 16, 2026
Favorite This post is a collaboration between AWS, NVIDIA and Heidi. Automatic speech recognition (ASR), often called speech-to-text (STT) is becoming increasingly critical across industries like healthcare, customer service, and media production. While pre-trained models offer strong capabilities for general speech, fine-tuning for specific domains and use cases can enhance
Read More Shared by AWS Machine Learning March 14, 2026
Favorite This post shows you how to build a scalable multimodal video search system that enables natural language search across large video datasets using Amazon Nova models and Amazon OpenSearch Service. You will learn how to move beyond manual tagging and keyword-based searches to enable semantic search that captures the
Read More Shared by AWS Machine Learning March 13, 2026