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Today's must-reads

Models

Google is training AI on even more of your data now, unless you opt out - here's how

Google now uses your images, voice searches, and videos from search interactions to train its AI models. You can opt out to protect your privacy. Here's how.

  • Google uses media (images, audio, video) from search interactions to train its AI models.
  • Users are automatically opted in and must manually disable the setting.
In-site article

Nemotron Labs: How Open Models Give Enterprises and Nations AI They Can Trust, Control and Customize

Open models like NVIDIA Nemotron enable enterprises to build AI that uniquely addresses their business needs, offering full control, customization, and cost efficiency, driving the shift from AI adoption to AI ownership.

  • Open models provide enterprises with full control to customize, inspect, and improve AI for specific business needs.
  • Post-training and domain-specific tuning allow open models to achieve frontier-level accuracy at a fraction of the cost of closed models.
In-site article
Agents

Meta accused of using biased AI targeting for mass layoffs

A group of 26 former Meta employees is suing the company over claims that it used AI tools to unfairly target workers on leave with layoffs, as reported earlier by Reuters. Meta denies the allegations, saying workforce decisions are made by people, not AI.

  • 26 former employees sue Meta, alleging AI tools unfairly targeted workers on protected leave during May layoffs.
  • The layoffs cut about 10% of Meta's workforce, approximately 8,000 employees.
In-site article

Show HN: An open-source Claude skill that stops AI building the wrong app

An open-source Claude skill called vibe-check, created by a seasoned product manager, helps beginners go from a vague idea to a buildable blueprint, ensuring they build the right thing rather than just building it right. It includes problem discovery, idea validation, user experience mapping, tech stack recommendations, growth loop design, and produces a comprehensive plan document.

  • vibe-check is an open-source skill for AI coding tools that guides complete beginners from a vague app idea to a buildable blueprint.
  • Developed by Amer Arab, a 12-year product manager focused on 0-to-1 product discovery.
In-site article

Agent Shell – persistent AI dev boxes from shell host running since 2009

Agent Shell is a hardened Linux box you hand your AI agent root on, over SSH or browser. gVisor-sandboxed so even root inside cannot touch the host, preloaded with agents like borg, Claude Code, Codex, Gemini, and live monitoring. Built on infrastructure operated since 2009.

  • Hardened Linux server with root access for AI agents
  • gVisor sandbox isolates agent from host
In-site article

Accelerating software delivery with agentic QA automation using Amazon Nova Act – Part 2

This post extends the previous foundation to demonstrate how QA Studio addresses batch regression testing and pipeline integration through test suites that organize and parallelize execution, and a command-line interface that brings agentic testing into automated CI/CD pipelines.

  • QA Studio groups individual test cases into test suites, enabling parallel execution to reduce total testing time.
  • The CLI (qa-studio) integrates with CI/CD platforms like GitHub Actions, GitLab CI, and Jenkins.
In-site article

Scaling UX testing with Amazon Nova Act: A new approach to user flow analysis

Using generative AI enables parallel execution of comprehensive user flow testing at scale. This solution demonstrates how to build a cloud-deployed UX testing platform that automatically generates test scenarios from documentation, executes user flows at scale using the intelligent navigation capabilities of Nova Act, and provides actionable insights through automated analysis.

  • Amazon Nova Act uses vision to intelligently navigate interfaces, mimicking human testers.
  • Automated test scenario generation from documentation reduces manual script writing.
In-site article
Chips

TPU and GPU Clusters: The Anatomy of Collective Communication

This article explores the topologies of TPU and GPU clusters and the core collective operations used in transformer training and inference. It emphasizes ring algorithms for large-message communication and analyzes TPU's 2D/3D torus topology and bandwidth hierarchy.

  • TPU clusters use 2D or 3D torus topologies with chips connected via ICI.
  • Collective operations like All-Gather and Reduce-Scatter are fundamental to distributed training.
In-site article

Taiwan’s Second-Largest Chipmaker Hits Photonics Production Milestone

Taiwanese chipmakers are expanding manufacturing capacity to support growing AI infrastructure demand.

  • Taiwan's second-largest chipmaker achieves a milestone in photonics production
  • Expansion of manufacturing capacity to meet AI infrastructure demands
In-site article
Other updates (9)
Agents

Scaling medical content review at Flo Health with Amazon Bedrock – Part 2

In this post, we share how Flo Health’s engineering team turned a proof of concept (PoC) from the AWS Generative AI Innovation Center into a production-grade, AI-powered medical content review and generation system built on Amazon Bedrock. This system reduced review time by 60 percent and tripled content throughput without expanding the medical team.

  • Reduced medical review time by 60% and tripled content throughput without expanding the medical team.
  • Three-layer validation: internal guidelines, trusted external sources, and expert review.
In-site article

ScienceSoft’s HIPAA-compliant AI voice scheduler built on AWS

ScienceSoft has built a HIPAA-compliant AI voice scheduler on AWS using Amazon Nova Sonic and Amazon Bedrock Guardrails. The solution tackles healthcare scheduling inefficiencies by reducing booking times, increasing call capacity, and lowering costs while ensuring data privacy and responsible AI standards.

  • Integrates Amazon Nova Sonic with Amazon Bedrock Guardrails for compliant conversational AI.
  • Reduces appointment booking time by 40% and increases call processing capacity by 70%.
In-site article

Design as the Enterprise Supply‑Chain Moat

As AI and optimization become commoditized, traditional supply chain planning no longer provides competitive advantage. Research shows most organizations lack visibility into their Tier 1 suppliers. Based on an Emerj podcast series, this article explores how scenario-driven modeling, AI-accelerated scenario analysis, and unified design environments enable better decision-making under volatility.

  • Design, not planning, is the new competitive battleground; organizations must architect the decision environment rather than rely on AI-generated decisions.
  • Scenario-driven modeling allows evaluation of multiple future configurations, enhancing strategic flexibility.
In-site article

A Longitudinal Study of AI Adoption in an Enterprise

A longitudinal study of an enterprise '2x mandate' to double merged pull requests per engineer found that throughput eventually reached 2.09x the pre-mandate baseline, with gains linked to AI adoption and usage intensity. Code review was restructured, with automated review overtaking human review and reviewer load doubling.

  • In a panel of 802 developers and 196,212 pull requests, per-capita throughput doubled to 2.09x baseline.
  • Gain attributed to AI adoption and usage, not the mandate itself, via staggered difference-in-differences.
In-site article

How to Debug Coding Agents with LangSmith Traces

Use LangSmith to trace coding agents across Claude Code, Codex, Cursor, Copilot, and more. Inspect tool calls, subagents, errors, costs, and retries.

  • Coding agents are black boxes; LangSmith provides unified visibility across different agents.
  • Traces include model calls, tool calls, subagents, errors, timing, and costs.
In-site article

Celebrating 25 years of visual search innovation

Google Images turns 25 with new browseable home and image generation in AI Overviews, plus a look back at major milestones in visual search.

  • New browseable home for Google Images with dynamic, immersive gallery tailored to user interests.
  • Image generation in AI Overviews using Nano Banana model to create custom visuals from text.
In-site article
Research

The Ramanujan Challenge for AI

Researchers released a set of formulas for fundamental mathematical constants designed to evaluate AI mathematical skills. The problems include proven (temporarily encrypted) and unproven formulas, testing AI's reasoning capabilities.

  • New benchmark features formulas for constants like π, e, and Catalan's constant.
  • Some formulas have known proofs that are encrypted; others are unproven.
In-site article
Tools

Google Search will let you instantly generate AI images for free - here's how

With the latest update to Google Images, you can generate your own images directly inside the AI Overviews.

  • Google Images is getting two new features: image generation in AI Overviews and a real-time updating gallery with collections tabs.
  • Image generation will roll out in English over the coming weeks, using Google's Nano Banana model.
In-site article

The Google Images homepage will recommend photos even before you search

To celebrate its 25th anniversary, Google is overhauling the Google Images homepage, replacing the mostly blank search page with a dynamic, immersive gallery of images tailored to user interests. Users can also save images to collections. Additionally, Google Search's AI Overviews will soon generate images for visualizing ideas like home decor. The new homepage rolls out in the coming weeks to signed-in desktop users in the US.

  • Google Images homepage will feature a browseable, dynamic gallery with personalized recommendations before search.
  • Users can save images to collections that appear as tabs above the feed.