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The Verge

OpenAI is teasing new hardware… for Codex

OpenAI is releasing some sort of device related to its AI-powered coding tool, Codex, on July 15th. In a video posted to X on Monday, OpenAI shows a square-shaped device with several buttons, alongside the caption, "Your favorite Codex shortcuts are getting an upgrade." This isn't the mysterious AI-powered device OpenAI is working on with […]

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OpenAI is teasing new hardware… for Codex
Hacker News AILLMs

Why Your AI Agents Should Stop Speaking English

Article URL: https://thenewassociationwebmasters.blogspot.com/2026/06/the-language-trap-reset-base-margin-0.html Comments URL: https://news.ycombinator.com/item?id=48723465 Points: 3 # Comments: 0

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Dev.to

How to Stop LangChain Agents from Bankrupting Your API Budget

<p>In November 2025, an engineering team deployed a market research pipeline using four LangChain agents. Due to a logic failure, the "Analyzer" and "Verifier" agents got stuck in a recursive ping-pong loop. Because every individual API call was perfectly valid, the system appeared healthy on their dashboards.</p> <p>11 days later, they discovered a <strong>$47,000 API bill</strong>.</p> <p>This is the hidden cost of building autonomous AI: <strong>infinite hallucination loops</strong>. When an

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Dev.to

Why Your LLM Applications Crash in Production (and How to Fix It Under 15 Microseconds)

<p>If you're building applications with OpenAI, Gemini, or LangChain agents, you already know the pain: <strong>Large Language Models are unreliable.</strong></p> <p>You ask for a JSON response. You set up a strict parser like Pydantic or Marshmallow. But then:</p> <ul> <li>The LLM cuts off mid-sentence because it hit the token limit.</li> <li>The output has a missing closing bracket <code>}</code>.</li> <li>The LLM outputs Python-style single quotes (<code>'id'</code>) or <code>True</code> inst

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The Hacker NewsSecurity

Malicious Perplexity Chrome Extension Intercepted Searches and Address Bar Input

Microsoft has found a malicious Chrome extension that posed as the AI search engine Perplexity and quietly logged what people searched for. It routed every query and every character typed into the address bar through an attacker-controlled server before redirecting users to real results. Microsoft says Google removed it from the store after responsible disclosure. The extension was called "

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Malicious Perplexity Chrome Extension Intercepted Searches and Address Bar Input
OpenClaw Commits

fix(agents): stop recording accepted sessions_spawn launches as tool …

<pre style='white-space:pre-wrap;width:81ex'>fix(agents): stop recording accepted sessions_spawn launches as tool failures (#96851) * fix(agents): stop recording accepted sessions_spawn launches as tool failures * fix(agents): stop recording accepted sessions_spawn launches as tool failures * fix(clownfish): address review for live-pr-inventory-20260629T175323-001 (1) --------- Co-authored-by: openclaw-clownfish[bot] <280122609+openclaw-clownfish[bot]@users.noreply.github.com></pre>

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OpenClaw Commits

fix(google-meet): fall back to manual OAuth paste when callback port …

<pre style='white-space:pre-wrap;width:81ex'>fix(google-meet): fall back to manual OAuth paste when callback port is occupied (#96492) The Google Meet OAuth login binds a fixed localhost:8085 callback listener and let listener failures propagate, so meet auth login aborted entirely when port 8085 was already in use. The sibling Gemini CLI OAuth path already recovers by switching to the manual copy/paste flow on EADDRINUSE/listen errors; bring Google Meet to parity by catching listener errors and

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The DecoderBusiness

Amazon engineers are reportedly distilling Anthropic models to cut costs before new token-based pricing kicks in

Amazon engineers are already distilling Anthropic models into smaller, cheaper versions for internal use. Starting next year, Amazon will pay by tokens processed rather than compute hours, which could push costs up sharply. The company is also exploring alternatives like OpenAI. The article Amazon engineers are reportedly distilling Anthropic models to cut costs before new token-based pricing kicks in appeared first on The Decoder .

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Amazon engineers are reportedly distilling Anthropic models to cut costs before new token-based pricing kicks in
MIT Tech ReviewResearch

AI agents are not your “coworkers”

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Imagine coming in to work to learn that a new underling will report to you. The worker is not a person but an AI tool—one that your company nonetheless calls Alex, an…

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The DecoderBusiness

EU seeks AI independence as Austria proposes luring Anthropic to Europe

Austria's State Secretary for Digitalization, Alexander Pröll, is calling on the European Commission to explore bringing Anthropic to Europe. He's responding to the U.S. ban on advanced AI models from OpenAI and Anthropic for foreign users. The initiative is likely unrealistic, though. And the alternative floating in the background, Chinese AI models, would just trade one dependency for another. The article EU seeks AI independence as Austria proposes luring Anthropic to Europe appeared first on

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EU seeks AI independence as Austria proposes luring Anthropic to Europe
Hacker News AILLMs

Wall Street Bets Micron Is the Next Nvidia AI Winner

Article URL: https://www.techbuzz.ai/articles/wall-street-bets-micron-is-the-next-nvidia-ai-winner Comments URL: https://news.ycombinator.com/item?id=48722634 Points: 1 # Comments: 0

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AWS Machine Learning Blog

Pair Nova 2 Lite with Claude for cost-optimized document processing

In this post, we show how pairing Amazon Nova 2 Lite with Anthropic’s Claude Sonnet 4.6 delivers an efficient solution for digitizing scanned documents at scale. We built a two-model pipeline on Amazon Bedrock for digitizing scanned yearbook pages. Amazon Nova 2 Lite handles native multimodal extraction in a single call: detecting photos, extracting visible names with coordinates, and returning page-level metadata. Claude Sonnet 4.6 then performs spatial reasoning to match names to faces based o

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OpenClaw Commits

fix(chutes): bound OAuth token error response reads (#97808)

<pre style='white-space:pre-wrap;width:81ex'>fix(chutes): bound OAuth token error response reads (#97808) * fix(chutes): bound OAuth token error response reads * ci: re-trigger checks (fs-safe unhandled-rejection flake on prior run) Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> --------- Co-authored-by: Pick-cat <266665499+Pick-cat@users.noreply.github.com> Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com></pre>

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OpenClaw Commits

fix(compaction): count bashExecution and summary turns in pre-prompt …

<pre style='white-space:pre-wrap;width:81ex'>fix(compaction): count bashExecution and summary turns in pre-prompt overflow precheck (#97861) estimateMessageTokenPressure special-cased toolResult, tool, and assistant roles and otherwise read record.content. bashExecution stores its payload in command/output and branchSummary/compactionSummary store theirs in summary, so record.content was undefined and those turns scored as bare boundary overhead. The provider request expands them via convertToLl

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Hacker News: Show HN

Show HN: Crossbeam-CLI – Connect Claude to Crossbeam without the enterprise tier

I built crossbeam-cli, an open-source tool that connects Claude to Crossbeam so you can ask questions about your partners, overlaps, and account mapping in plain English. Crossbeam gates programmatic access behind its top Supernode tier. Even the official Claude connector starts around $4,800/year. crossbeam-cli works on any plan, free tier included, because it talks to the same internal API the web app uses. You log in with your own credentials and requests go straight from your computer to Cro

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The Robot ReportRobotics

BMW Group deploys Figure 03 humanoid after tests with previous version

The Figure 02 robot supported the production of more than 30,000 BMW X3 vehicles over 11 months in South Carolina. The post BMW Group deploys Figure 03 humanoid after tests with previous version appeared first on The Robot Report .

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BMW Group deploys Figure 03 humanoid after tests with previous version
AWS Machine Learning Blog

Multi-tenant LLM analytics with row-level security: How we built a secure agent on AWS

In this post, we show you how PAR built a production-ready multi-tenant LLM analytics system that enforces row-level security through a three-layer architecture: cryptographic request signing with AWS SigV4, semantic validation on Amazon Bedrock, and programmatic data isolation via Split-Plane SQL. We demonstrate how each layer operates independently to reduce the risk of cross-tenant data exposure, even when the LLM itself is compromised or manipulated.

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AWS Machine Learning Blog

Build an agentic AI healthcare claims pipeline with Amazon Bedrock and AWS HealthLake

In this post, we show you how to build an automated claims processing pipeline using two key Amazon Bedrock capabilities: Amazon Bedrock Data Automation for intelligent document extraction from healthcare claim forms, and Amazon Bedrock AgentCore for hosting an AI agent that validates and transforms the extracted data into FHIR (Fast Healthcare Interoperable Resources) resources in AWS HealthLake. You will learn how to combine these services to create an end-to-end workflow that reduces manual p

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Towards Data Science - Medium

How Far Can Classical NLP Go? From Bag-of-Words to Stacking on Spooky Author Identification

An end-to-end classical NLP experiment on Kaggle’s Spooky Author Identification task: from Vowpal Wabbit and TF-IDF/NB-SVM baselines to a tuned stacked ensemble, with a compact representation survey of Bag-of-Words, BM25, Word2Vec, and FastText for context. The post How Far Can Classical NLP Go? From Bag-of-Words to Stacking on Spooky Author Identification appeared first on Towards Data Science .

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AWS Machine Learning Blog

Debugging production agents with Amazon Bedrock AgentCore Observability

In this post, you learn how to debug production agent failures using built-in observability capabilities. We walk through common failure patterns, show how to analyze agent behavior with traces and metrics, and provide structured workflows for resolving issues such as infinite loops and tool invocation failures. This is Part 1 of a two-part series. Part 2 covers performance optimization and memory management.

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