A Technology Broker and Management Company Specializing in KM Systems
Favorite A common challenge in AI-powered research workflows is depth versus context. If your agent reads ten web pages, its context window (the amount of text a large language model (LLM) can process at once) gets filled with raw content. If it also runs data analysis code, chart-generation logic competes
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Shared by AWS Machine Learning June 15, 2026
Favorite When your AI agent fails in production, knowing that it failed is only the beginning. The harder question is why it failed and what to fix. Traditional evaluation tells you “this agent scored 60 percent on goal completion,” but leaves you manually reviewing execution traces to understand what went
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Favorite Today, we are announcing the availability of the Gemma 4 family on Amazon Bedrock. Built by Google DeepMind and released under the Apache 2.0 license, Gemma 4 is a family of open-weight models designed with a focus on intelligence-per-parameter across a broad range of deployment scenarios. The family includes
Read More Shared by AWS Machine Learning June 15, 2026
Favorite Google has announced a $1.5 billion investment for 2026 and 2027 to expand its data center campus in Jackson County, Alabama. Operating since 2019 on a repurposed former… View Original Source (blog.google/technology/ai/) Here.
Favorite Frontier teams are not just using AI to code faster. They’re redesigning how software gets built. The result is 4.5x productivity gains, in some cases more than 10x. Six engineers. Seventy-six days. A project scoped for 30 developers over 12 to 18 months, delivered within a quarter. That is
Read More Shared by AWS Machine Learning June 12, 2026
Favorite Extracting structured data from unstructured documents such as invoices, contracts, tax forms, and enrollment applications is a common automation goal for organizations. Achieving high extraction precision remains a key challenge. Accuracy degrades when documents diverge from expected templates, formats vary across vendors, or scan quality is poor. With Amazon
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Favorite AWS Professional Services (AWS ProServe) compressed engagement timelines from months to days, not by adding artificial intelligence (AI) tools to an existing process, but by fundamentally rebuilding how we deliver from the inside out. The shift mirrors what my colleague Swami Sivasubramanian outlined in How Frontier Teams Are Reinventing
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Favorite Organizations process millions of documents daily, from insurance claims and invoices to legal contracts and medical records. While traditional optical character recognition (OCR) solutions extract text, they can’t understand context, relationships, or meaning embedded within complex documents. This limitation creates bottlenecks that require manual intervention, increasing processing time and
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Favorite Amazon Quick and Cisco Webex MCP servers can turn meeting prep and follow-up into a single conversational workflow. Instead of switching between Webex meetings, Vidcast videos, transcripts, recordings, and message spaces, users ask one assistant to gather the context they need. This post shows how to build a custom
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Favorite Rocket Close is a Detroit-based title agency and appraisal management company within Rocket Companies that provides title insurance, property valuation, and settlement services. As demand for mortgages and loans grew, title operations became a bottleneck in the homebuying process. Time-intensive, state-specific title examinations, combined with manual research and fragmented
Read More Shared by AWS Machine Learning June 12, 2026