Tested is an independent AI tool review platform that uses four top LLMs (Claude, GPT, Gemini, Grok) as a jury to score over 40 AI tools, avoiding paid rankings. It covers categories like chatbots, coding, image, video, and more, providing transparent scores and pricing info.
Uses four LLM agents for independent scoring to ensure fairness
Covers 12 categories including AI chatbots, coding, image, video
A new report reconstructs the AI economy from the bottom up, capturing real customer demand without double-counting. It finds the AI economy is bigger and faster than any previous tech wave, yet still early, with revenue barely covering infrastructure costs. Future growth depends on demand acceleration as prices fall and the real intelligence per token.
First bottom-up reconstruction of the AI economy with no double-counting
AI economy larger and faster than prior tech waves, but still early
capframe.ai has published a security leaderboard for MCP servers, grading 87 published servers using a deterministic rule engine with a score out of 100. Each Critical finding deducts 10 points, High 4, Medium 2, Low 1. The leaderboard shows top servers scoring 100 (e.g., magicnpm, Cloudflare MCP, Elasticsearch MCP), while also revealing medium and high severity issues like unconstrained string inputs and missing side-effect declarations.
capframe.ai scanned 89 MCP servers (effectively 87) and scored them using a public deterministic rule engine, with 100 being a perfect score.
Several well-known servers achieved a perfect score, including magicnpm, Cloudflare MCP Server, Elasticsearch MCP, and others.
This guide explains how to build an MCP Apps host using @ai-sdk/mcp and @ai-sdk/react, including filtering model-visible tools, reading ui:// resources, and rendering interactive tool UIs in a sandboxed iframe.
Use splitMCPAppTools to separate model-visible and app-visible tools
Read ui:// resources with readMCPAppResource to get HTML content
Best Photo Picker is a local-first, open-source photo curation tool that uses AI to score photos on sharpness, lighting, faces, and composition. It runs entirely on your machine with no cloud uploads, supports smart deduplication, face recognition, and temporal diversity, and offers a web UI and native macOS app.
Fully local, no photo uploads to the cloud, ensuring privacy.
AI auto-scoring based on sharpness, exposure, faces, and composition.
Moss is a sub-10 ms semantic search runtime for Conversational AI agents. It eliminates the need for a remote vector database by embedding search and retrieval in-process, achieving single-digit millisecond query latency. It supports hybrid search, built-in embeddings, metadata filtering, and a WebAssembly build for browser use. Benchmarks show Moss's P50 latency at 3.1 ms vs. 432.6 ms for Pinecone on 100,000 documents.
Moss is an embedded semantic search runtime that removes the need for vector databases, with query latency under 10 ms.
It supports hybrid search, built-in embeddings, and metadata filtering. SDKs available for Python, TypeScript, Elixir, and C.
The US government granted Anthropic permission to release its Mythos 5 AI model to about 100 companies and federal agencies, ending a two-week standoff over national security concerns.
Anthropic received approval to release Mythos 5 to select organizations
The decision follows a two-week dispute over export controls
A Python-based open-source AI audio translator that uses Telnyx APIs for speech-to-text, LLM-based translation, and text-to-speech, allowing users to upload audio and receive translated audio with aligned transcript.
Uses Telnyx APIs for STT, AI translation, and TTS
Supports any audio format (podcast, meeting, lecture)
The AI-Run Business Index (ARBI) is a new 0–100 metric that scores how deeply AI runs a business, not just whether it's adopted. With adoption at 88% but only ~6% capturing real profit, ARBI reveals a 50-point execution gap between the mainstream economy (~30) and AI-native frontier (~80). The index weights automation depth, value capture, and revenue leverage most heavily, and includes a reliability penalty.
ARBI is the first standardized metric to measure AI execution, not adoption.
Mainstream economy scores ~30/100 while AI-native frontier scores ~80/100.
A desktop pet with real-time AI capabilities, serving as a language partner, homework helper, screen assistant, and chat companion. Built on the legacy of Shimeji and inspired by Codex Pets, it seeks a co-founder from Asia.
AI-powered desktop pet that assists with language, homework, screen tasks, and casual chat.
Revives the desktop mascot trend with modern AI integration.
Apple is revamping its Apple silicon roadmap, canceling high-end M6 chips to accelerate AI-focused M7 chips. The base M6 will debut in late 2026 for entry-level Macs, while M7 series arrives in 2027. M5 Ultra is also expected in late 2026.
Apple cancels M6 Pro and M6 Max, shifting focus to M7 chips for AI workloads.
M7 chips expected in H1 2027, with Pro/Max versions by end of 2027.
AI can already tackle long-horizon coding tasks. Claude Opus 4.7 reimplemented gotree, a 16,000-line bioinformatics toolkit, in 14 hours for $251. However, MirrorCode benchmark score is only 56%, showing room for improvement. Models improve rapidly over time, though data contamination is a concern. 22 of 25 target programs are open-sourced.
Claude Opus 4.7 reimplemented gotree in 14 hours at $251, a task estimated to take humans weeks.
MirrorCode headline score is just 56%, with many tasks not reliably solved.
Privacy-focused search engine DuckDuckGo's AI-generated search results erroneously stated that President Donald Trump died from rabies contracted from Vice President J.D. Vance, who also died of the disease.
DuckDuckGo's AI search feature generated false information
The false claim stated Trump and Vance died of rabies
Hush is a secret store for AI agents, designed so that agents can use API keys, tokens, and other secrets without ever seeing the plaintext. It leverages native OS keychains (macOS Keychain, Linux libsecret, Windows DPAPI) to store secrets and injects them into commands on-demand, ensuring secrets never appear in transcripts.
AI agents never see the plaintext secret; they only use injected environment variables.
Cross-platform: supports macOS, Linux, and Windows via their native keychain APIs.
Framesmith 1.7 is an open-source MCP server that gives AI coding agents a visual canvas to sketch and review UI before writing code. It includes a viewer, quality evaluation panel, design system inheritance, and multi-breakpoint previews, integrating easily with various MCP-compatible clients.
Open-source MCP server providing a visual UI canvas for AI agents.
Includes quality evaluation panel that scores canvases and suggests fixes.
The Linux Foundation launches Akrites, a coordinated industry program to fast-track fixing vulnerabilities in open-source software before AI-powered attackers can exploit them. Backed by major tech and financial firms, Akrites aims to reduce fragmentation and maintainer overload by providing a single coordinated process.
Akrites is a Linux Foundation initiative to coordinate vulnerability fixing in open source, backed by companies like Google, Microsoft, and OpenAI.
It addresses the challenge of AI discovering vulnerabilities faster than humans can patch them, with the mean time to exploit now negative seven days.
AI's popularity is declining as its industry provokes backlash with anti-human hiring ads, layoffs, chatbot replacement of customer service, and AI-generated slop. Author and activist Cory Doctorow discusses his new book, 'The Reverse Centaur’s Guide to Life After AI,' addressing how to critique AI effectively and protect ourselves.
AI industry actions trigger negative reactions, including ads urging employers to stop hiring humans, layoffs blamed on AI, and chatbots replacing customer service.
Cory Doctorow's new book 'The Reverse Centaur’s Guide to Life After AI' offers critique and solutions.
This article explores how humans and AI can recognize when we are choosing the good. The author proposes three tells: means and ends (Kant and Kierkegaard), vice and virtue (Aristotle), and shallow vs. deep (Salzberg and Spinoza). While the nature of good is hard to define, these indicators can help guide decision-making for both humans and AI.
Kant and Kierkegaard emphasize the unity of means and ends; AI should not take unethical shortcuts.
Aristotle's virtue ethics suggests balance between vices, but AI cannot practice virtue directly.
Large context windows are useful but continuity is different. The article argues that coding agents need persistent, belief-backed memory rather than larger prompt space. It contrasts context-native and memory-native agents, discusses why retrieval is insufficient, and presents Sigilix's approach with a memory backing layer. A smaller model (Boreas) can outperform a larger one on continuity-heavy tasks when the substrate is prepared. The piece also covers failure modes of memory systems and the importance of source, scope, decay, and proof.
Context size does not equal continuity; a larger window carries more text but does not decide what to remember.
Retrieval answers what text is relevant, not what the repo has taught, so agents can still seem forgetful.
This article explores the discoverable evidence generated during AI-assisted software porting, including code diffs, comment patterns, and migration traces, and analyzes their impact on software verification and auditing.
AI-assisted porting leaves traceable evidence in the codebase
This evidence aids in verifying correctness and completeness of the port
Gartner warns that consumption-based pricing for AI coding agents is driving costs up to $20,000 per developer per month, with little transparency or cost control. Token consumption does not directly correlate with productivity gains. Recommendations include context engineering and model routing. By 2028, AI coding costs could exceed average developer salaries globally.
Shift from seat-based to consumption-based pricing causes cost spikes
Lack of cost optimization tools and transparency leads to tokenmaxxing without productivity gains
Weave Router is an open-source model router that intelligently selects the best AI model per request, supporting multiple API formats and reducing costs by 40-70%.
Routes every request to the optimal model using a cluster scorer based on Avengers-Pro 2
Supports Anthropic, OpenAI, Gemini APIs and open models via OpenRouter
This free GEO checker evaluates your website's visibility in AI search engines like ChatGPT, Claude, Perplexity, and Gemini across 7 technical layers—including llms.txt, structured data, service catalog API, OpenAPI spec, Agent Card, health endpoint, and robots/sitemap—providing a score and actionable improvements.
Checks 7 AI discovery layers: llms.txt, structured data, service catalog API, OpenAPI spec, Agent Card, health endpoint, robots & sitemap.
Free to use, no account required, instant A-F grade score.
Using social cartography, this article analyzes three polarized orientations toward AI: techno-solutionist cheerleading, total refusal via abstention, and strategic redirection that engages while acknowledging risks. It argues that refusal does not grant moral innocence and adoption need not imply endorsement, emphasizing the need for discernment and restraint.
Social cartography reveals three main stances in AI debates: cheerleading, abstention, and strategic redirection.
AI abstention maintains moral clarity but may overestimate the leverage of refusal.
TickerPro is an AI-assisted stock research terminal that helps investors discover and analyze US stocks with personalized recommendations, real-time data, and narrative-driven insights, built by a couple to streamline their own research process.
TickerPro provides AI-powered personalized stock recommendations based on your portfolio and investment style.
It offers deep-dive research capabilities, including business models, financials, and transcripts, with AI-generated overviews.
This article benchmarks four AI gateways on the hot path, measuring latency, throughput, memory, CPU, cold start, and image size. GoModel leads in nearly every metric, while LiteLLM suffers from high resource consumption. The author discusses the importance of runtime footprint for local models and serverless deployments, and notes the need to evaluate openness and vendor neutrality.
GoModel excels with 1.8ms median latency, 4900 req/s throughput, 37MB RAM, and 0.56s cold start. LiteLLM lags with 2.3GB RAM, 25.5s cold start, and 324 req/s. Bifrost and Portkey fall in between.
The benchmark focuses on runtime overhead, not feature count or provider coverage. It measures what matters when the gateway sits on every request.
Brian Merchant launches a podcast for his newsletter 'Blood in the Machine', with the first episode focusing on AI industry's massive spending to influence elections. Guest Molly White discusses her project 'Tech Influence Watch' tracking political money from AI and crypto companies.
Brian Merchant launches 'Blood in the Machine' podcast; first episode covers AI industry's election spending.
Guest Molly White introduces 'Tech Influence Watch', tracking political donations from AI and crypto.
This guide walks through building an AI Telegram bot using Quickchat AI Agent and Telegram Bot API to manage groups. It covers six AI actions for reading group info and performing admin-only moderation tasks, with a server-side permission gate preventing non-admins from triggering destructive actions.
Build six AI actions corresponding to Telegram Bot API methods: getChat, getChatMemberCount, sendMessage, pinChatMessage, restrictChatMember, and banChatMember.
Use Quickchat AI's metadata injection and run conditions to enforce admin-only actions deterministically, bypassing prompt-based security.