A Technology Broker and Management Company Specializing in KM Systems
Favorite Organizations commonly rely on A/B testing to optimize user experience, messaging, and conversion flows. However, traditional A/B testing assigns users randomly and requires weeks of traffic to reach statistical significance. While effective, this process can be slow and might not fully leverage early signals in user behavior. This post
Read More
Shared by AWS Machine Learning March 18, 2026
Favorite Moving AI agents from prototypes to production surfaces a challenge that traditional testing is unable to address. Agents are flexible, adaptive, and context-aware by design, but the same qualities that make them powerful also make them difficult to evaluate systematically. Traditional software testing relies on deterministic outputs: same input,
Read More Shared by AWS Machine Learning March 18, 2026
Favorite Large language models (LLMs) have transformed how we interact with AI, but one size doesn’t fit at all. Out-of-the-box LLMs are trained with broad, general knowledge and improved for a wide range of use cases, but they often fall short when it comes to domain-specific tasks, proprietary workflows, or
Read More Shared by AWS Machine Learning March 18, 2026
Favorite With a wide array of Nova customization offerings, the journey to customization and transitioning between platforms has traditionally been intricate, necessitating technical expertise, infrastructure setup, and considerable time investment. This disconnect between potential and practical applications is precisely what we aimed to address. Nova Forge SDK makes large language
Read More Shared by AWS Machine Learning March 18, 2026
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
Read More 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
Read More Shared by AWS Machine Learning March 16, 2026
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
Read More Shared by AWS Machine Learning March 16, 2026