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Felipe Mattosinho Felipe Jordão A.P Mattosinho About If You're Not Studying for Retention, Just Use AI @felipe_japm · Aug 17, 2026 Studying used to buy you two things: access to knowledge, and knowledge in your head. AI…
AI (artificial intelligence) is rapidly impacting cybersecurity on both sides of the battlefield. As defenders harness AI to detect threats faster, attackers are deploying intelligent tools to breach systems, evade dete…
2026-02-26T08:00:00.0000000Z" pubdate title="Time posted: >2/26/2026 8:00:00 AM (UTC)">Feb 26, 2026 AI Hurtles Ahead When I was preparing to write my December memo about artificial intelligence, Is It a Bubble?, I gaine…
Research: smolmachines / smolvm as a sandbox for untrusted Python & JavaScript I tasked Claude Fable 5 running in Claude Code for web with the following research task: Put https://smolmachines.com through its paces as a fast secure sandbox. Explore what it would take to use this to run untrusted Python and JavaScript code in a way that is limited in what RAM and CPU time it can take up (protection against "while true") with no network access and filesystem access only to designated files Goal is to be able to use this to execute user-provided tasks for things like data transformations It quickly ran into a problem: the Claude Code for web environment can't run smol machines. Quoting the notes it wrote: This Claude Code container: Linux 6.18.5-fc-v20 (itself a Firecracker guest), 4 vCPU, 1…
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You are entering a world somewhere between 0 and 1. It is a world that feels unsettling, strange, and new. There are often hallucinations. Bugs are flying everywhere. Are you in the twilight zone? No. You are working in…
NFL fans did little to hide their confusion after Jason Kelce attempted to lead a pee drive as part of a bizarre ad campaign for his beer brand, Garage Beer, and canned water company Liquid Death. In a now-viral commerc…
My hypothesis is that there is a new opportunity for Extensible Software on the web. LLMs radically lower the cost of authoring extensions, and modern sandbox primitives lower the deployment cost and provide good security boundaries. We can build our app as a solid, accountable core, and allow users to safely extend it in many directions by having LLMs fill in the missing pieces. We can give our users super powers. — Jeremy Morrell, Extensible Software in the age of LLMs Tags: sandboxing, llms, ai, generative-ai
Stripe Inc. today said it has agreed to acquire artificial intelligence model routing startup OpenRouter Inc. in a deal reported at $7.5 billion or more. Neither company disclosed terms and the reported numbers do not agree. The New York Times said $7.5 billion, citing a person with knowledge of the terms. Axios put it above […] The post Stripe buys AI model router OpenRouter in reported $7.5B deal appeared first on SiliconANGLE.
Dear researchers: Is AI all you've got? - Austin Z. Henley Austin Z. Henley I build tools for people [email protected] @austinzhenley github/AZHenley Home | Publications | Teaching | Blog Dear researchers: Is…
Last week I recorded an episode of the Talking Postgres podcast with Claire Giordano on the subject of "How AI is changing software development". We had a really great conversation. Here are a couple of my highlights from a lightly edited transcript (prompt to Claude: "very minor edits to remove disfluencies"). This is the latest version of an argument I've been trying to build about why sometimes it does make sense to talk about lines of code as an indicator of productivity with coding agents, at 35:01: A lot of people will tell you it makes no sense to measure productivity in lines of code. I’d actually disagree, because there’s a hard limit. In the before-times, a software engineer could produce a few hundred lines of production-ready code per day — and 200 lines of working, debugged,…
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Web Search on Amazon Bedrock AgentCore now supports runtime domain and published-date filtering. New per-request filters give developers per-call control over which web sources their agents consult and how fresh those sources must be, all enforced server-side. This release also expands Web Search to the Europe (Ireland) and Asia Pacific (Tokyo) Regions.
Classifying, extracting, and validating high volumes of documents is a challenge across banking, insurance, healthcare, and the public sector. See how a mid-size mortgage lender automates its entire document intake pipeline, from email to validated data, using the AWS GAIIC IDP Accelerator and Amazon Quick Automate.
In this post, you learn three serverless patterns (task-token callback, direct service integration, and durable functions) for invoking Amazon Bedrock AgentCore agents asynchronously from AWS Step Functions pipelines, eliminating idle compute costs while your AI agent processes requests.
Uh oh! There was an error while loading. Please reload this page. Uh oh! There was an error while loading. Please reload this page. Notifications You must be signed in to change notification settings Fork 36.5k Star 119…
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Something of a trend has emerged this year, with the major AI labs going all-out to tell the world how The post “The opening stages of OpenAI’s unraveling”: OpenAI slows model training — not everyone is buying the explanation appeared first on The New Stack.
Apple’s AirPods could soon do more than play music, with a leaked video appearing to reveal a new model that uses built-in cameras to help Siri understand the world around its wearer. Cameras fitted inside wearable tech…
The move is a response to the Hugging Face hacking incident and other cybersecurity concerns about AI models. However, enterprises need to ramp up security protections regardless of the models they use.
forked from dexloom/vibe-kanban-indie Notifications You must be signed in to change notification settings Fork 0 Star 1 BranchesTags Open more actions menu Latest commit History 2,456 Commits 2,456 Commits Folders and f…
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Notifications You must be signed in to change notification settings Fork 1 Star 0 BranchesTags Open more actions menu Latest commit History 11 Commits 11 Commits Folders and files NameName Last commit message Last commi…
I saw this going viral, “AI;DR (AI; Didn’t Read):” I’ve been thinking about it ever since. Why? Because there is growing grumbling among everyone about AI writing. And it’s not just others; it’s me! I am getting to the…
A new study suggests that some AI models become far less willing to recommend a nuclear strike when they reason in Japanese instead of English, revealing that the language an AI ‘thinks’ in can intimately influence its…
Before you change a setting, decide what better retrieval means for your workload. The right document at rank one, more candidates for a reranker, lower latency, and a smaller memory footprint each favor different settings, so pick your goal first. If your labeled queries can’t detect the improvement you’re chasing, you won’t be able to tell whether a change helped. Some settings are there to verify correctness, not to tune performance. If a vector is unindexed, a sparse vector is missing the IDF modifier, or the BM25 average length is wrong, the results are invalid. Any benchmark or comparison you run after that will reflect a broken setup. This article shows you how to check each setting and what the correct state looks like.
Toolbay Stack · v0.2.0 An agent stack that tells you when it failed. 60 skills for Claude Code. 145 engines, and every single one carries its own test — an engine without one fails the suite rather than shipping. Free,…
AI inference infrastructure is becoming a system-level challenge as organizations move generative and agentic applications into production. Graphics processing unit performance remains essential, but storage latency, network bandwidth, data movement and power consumption increasingly determine the cost and speed of producing tokens. The requirements also vary by workload. Interactive chat prioritizes latency, batch inference emphasizes […] The post The AI inference race moves beyond GPUs to reshape data center infrastructure appeared first on SiliconANGLE.
Fanatics Betting and Gaming built a multi-agent customer support system on AWS to handle the complexity of sports betting: state-specific rules, real-time responsible gaming, and traffic spikes during major sporting events. This post walks through the architecture, the AWS services involved, and the patterns for your own multi-agent support solution.
KnowledgeForge mines resolved ITSM incident tickets into new knowledge base articles and automatically curates the existing library by deduplicating, quality-scoring, and improving content, using Amazon Bedrock, Amazon S3 Vectors, and AWS Step Functions in a multi-tenant, closed-loop pipeline.