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Hacker News Ask

I have an interesting idea to reduce the output tokens almost by fifty percent

Most token-saving tools focus on input tokens, but output tokens are usually priced higher, and edit-heavy agent sessions waste a lot of them on a specific pattern: to safely edit a file, the agent has to output the old code block plus the new code block, just so the harness can match and swap it in. That's safe (content-based matching means line drift doesn't cause a bad edit), but it means half the tokens going out are just the agent restating content it already read. Plain line-range edits ("

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AWS Machine Learning Blog

Build a serverless image editing agent with Amazon Bedrock AgentCore harness

This post walks through building a serverless image editor where users upload a photo, describe an edit in plain English, and receive the result in seconds. The agent runs on AgentCore harness without custom orchestration code. We deploy the full solution, including authentication, encrypted storage, three image editing tools, and a React frontend, with a single deployment command. The infrastructure is defined using AWS Cloud Development Kit (AWS CDK).

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AWS Machine Learning Blog

Monitoring discriminative ML models using Amazon SageMaker AI with MLflow

Implementing a data and model monitoring solution is necessary to maintain prediction accuracy and help achieve the best outcome for your machine learning use case. This post shows how you can use open source Evidently together with Amazon SageMaker AI to generate monitoring reports, organize and compare the results in MLflow, scale through pipelines, and trigger drift notifications.

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AWS Machine Learning Blog

Build an AI-powered AWS support companion with Amazon Bedrock AgentCore

In this post, you build an AWS Support Companion using Amazon Bedrock AgentCore. The agent uses Strands Agents as the orchestration framework and connects to AWS services through the Model Context Protocol (MCP). By the end, you have a working agent that can analyze CloudWatch logs, search AWS documentation, query community knowledge from AWS re:Post, and create support cases, all from a single conversational interface. The solution deploys with a single script using AWS CloudFormation and inclu

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The Hacker NewsSecurity

Rogue Agent Flaw Could Have Let Attackers Hijack Google Dialogflow CX Chatbots

A critical flaw in Google's Dialogflow CX could have let an attacker with edit rights on one Code Block-enabled agent compromise other Code Block-enabled agents in the same Google Cloud project. From there, they could read live conversations, steal the data users shared, and make the bots send attacker-written messages, including requests to re-enter a password. Security firm Varonis found it

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Rogue Agent Flaw Could Have Let Attackers Hijack Google Dialogflow CX Chatbots
Towards Data Science - Medium

A Production RAG Pipeline for PDFs: Relational Parsing, TOC Retrieval, Typed Answers

Enterprise Document Intelligence [Vol.1 #9A] - Same paper, same question as Article 1. One upgraded contract per brick: document parsing, question parsing, retrieval, generation The post A Production RAG Pipeline for PDFs: Relational Parsing, TOC Retrieval, Typed Answers appeared first on Towards Data Science .

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TechCrunch AIBusiness

Claude Cowork expands to mobile and web

With this update, users can start a task from their desk, get status updates on their phone, and pick up the finished output later — even if their laptop is closed.

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VentureBeat

Box survey: Why enterprise AI leaders are outperforming their peers

Presented by Box Content access, governance, and platform flexibility are emerging as the dividing lines between AI leaders and laggards, according to the new State of AI in the enterprise report from Box, which surveyed 1,640 IT decision makers across the US, UK, France, and Japan. One of the report's major findings is the speed of the shift: the combined share of organizations describing themselves as advanced or leading edge soared from 8% to 64% just over the past year, while the share calli

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Box survey: Why enterprise AI leaders are outperforming their peers
r/MachineLearningResearch

TorchJD: Training with multiple losses in PyTorch [P]

<!-- SC_OFF --><div class="md"><p>Hi everyone! I wanted to share some recent progress on <a href="https://github.com/SimplexLab/TorchJD">TorchJD</a> that might be useful to the machine learning community.</p> <p>When training models with multiple losses (multiple tasks, constraints, auxiliary losses, regularization terms, etc.), you typically have two options:</p> <ul> <li>Scalarization: Various ways to combine those losses into a single loss (e.g. average them or combine them with trainable wei

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Simon WillisonLLMs

github-code Web Component

<p><strong>Tool:</strong> <a href="https://tools.simonwillison.net/github-code-component">github-code Web Component</a></p> <p>An experimental Web Component built using GPT-5.5 and <a href="https://gist.github.com/simonw/0e3db21947b5ae7e29e8a4f69a0b0617">the following prompt</a>:</p> <blockquote> <p><code>let's build a Web Component for embedding code from GitHub</code></p> <p><code><github-code href="https://github.com/simonw/sqlite-ast/blob/437c759129154f05296324a7f82aa1246340dd14/sqlite_ast/p

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Hacker News OpenClaw

OpenClaw/Hermes Article on agent memory options

Article URL: https://yolo-auto.com/news/memory-options-for-agents Comments URL: https://news.ycombinator.com/item?id=48819916 Points: 2 # Comments: 0

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Hacker News Ask

Ask HN: Are LLMs slowly making companies dysfunctional?

LLMs are great. They can quickly one-shot plausible solutions for many problems. This makes companies push hard to offload rising cognitive demands to LLMs. It doesn't make much sense to invest effort into verifying a plausible-looking throwaway solution that is reviewed and smoke-tested by an LLM, with a quick glance from a tired human. This results in complexity creep everywhere: decisions, communication, code, documentation, etc. On par with cognitive debt, as thinking and decision refinement

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The DecoderBusiness

China eyes export curbs on its top AI models, and Europe is caught in the middle

According to Reuters, Chinese authorities are looking into restricting foreign access to the country's most powerful AI models. Alibaba, Bytedance, and Z.ai would all be affected. The move means both superpowers now treat AI as a strategic asset. For Europe, the convenient shortcut of relying on cheap Chinese open-source models could close much faster than expected. The article China eyes export curbs on its top AI models, and Europe is caught in the middle appeared first on The Decoder .

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China eyes export curbs on its top AI models, and Europe is caught in the middle
Hacker News FrontTools

Show HN: Rowboat – Open-source, local-first alternative to Claude Desktop

Claude’s desktop app is brilliant, but for our own daily work we kept wanting it to be less like a chat app and more like a full-fledged work app. Rowboat is our attempt at that, including the ability to build your own work surfaces inside Rowboat (more below). Our repo is https://github.com/rowboatlabs/rowboat , and there’s a demo video here: https://www.youtube.com/watch?v=et5yQABJ3xI In a previous startup, we built a deep-learning product for enterprise support reps, including teams supportin

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VentureBeat

Anthropic brings Claude Cowork to mobile and web as usage data shows most users aren’t coding

Anthropic on Tuesday launched Claude Cowork on mobile and web , expanding a tool that has quietly become the company's bridge between the developer-centric world of AI coding agents and the far larger market of knowledge workers who never open a terminal. The rollout, which begins in beta with Max subscribers before expanding to additional plans, marks a strategic inflection for Anthropic. It transforms Cowork from a desktop-only agent into a cross-device platform where tasks can start on a lapt

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Anthropic brings Claude Cowork to mobile and web as usage data shows most users aren’t coding
Product Hunt — The best new products, every day

agents-cli

<p> The CLI your coding agent uses to ship agents </p> <p> <a href="https://www.producthunt.com/products/agents-cli?utm_campaign=producthunt-atom-posts-feed&utm_medium=rss-feed&utm_source=producthunt-atom-posts-feed">Discussion</a> | <a href="https://www.producthunt.com/r/p/1190389?app_id=339">Link</a> </p>

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Product HuntTools

Miora

<p> Scale your creativity on editable canvas with agent memory </p> <p> <a href="https://www.producthunt.com/products/miora-2?utm_campaign=producthunt-atom-posts-feed&utm_medium=rss-feed&utm_source=producthunt-atom-posts-feed">Discussion</a> | <a href="https://www.producthunt.com/r/p/1190387?app_id=339">Link</a> </p>

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ByteByteGo

ChatGPT vs Gemini vs Claude: How They Differ

In this article, we will look at the various architectural forks the teams building these models encountered and the decisions they took.

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ChatGPT vs Gemini vs Claude: How They Differ