Only 3% of social media users post toxic content — but Americans estimate 43%. An interactive essay about what algorithms hide.

A few thoughts on how the modern economy has stopped rewarding people who know
what they are doing, and started rewarding people who know how to look
like they do.

Hopper connects AI agents to your mainframe through Model Context Protocol — natural language operations, autonomous workflows, and an agentic development environment for z/OS.

Secure Boot protects a system from an attacker that compromises the boot flow. For example, without Secure Boot it is easy to replace the code that reads your disk encryption password and store it somewhere where the attacker can pick it up later. So ideally you want Secure Boot to be enabled to limit the code that runs on your system to what is supposed to run there.

A long-overlooked writing system from 5000 years ago is still largely undeciphered, but could mark the moment humans first represented their speech with written words

Source code: Lib/profiling/sampling/ Tachyon logo The profiling.sampling module, named Tachyon, provides statistical profiling of Python programs through periodic stack sampling. Tachyon can run sc...

Unitree's GD01 is the world's first mass-produced manned mech suit — a 500kg bipedal/quadrupedal machine that you actually ride. No US or UK release date in sight.

Watch videos with friends using WebRTC, let the server do the pausing and seeking. - pion/rtwatch

Chasing Chicago’s movable bridges

Transit advocates laud first stations to open in city in more than 25 years, with World Cup and Olympics coming to town

A full 3D game -- renderer, physics engine, scripting runtime -- exported to WebAssembly is 35MB. The default Node.js Docker image is hundreds of MB, pulled 19 million times last week.

In 1873 Heinrich Schliemann found a hoard of gold under a hill in western Anatolia, hid it from the Ottoman official assigned to watch him, packed it into his wife

I am a solution architect, developer, SRE, trainer, author, and more. With 25 years of experience in the Software Development industry that includes working as a Consultant and Trainer in a wide array of different industries.

Based on conversations with [Rob Simmons. Reader prerequisites: comfortable with inference rules, peano notation, state machines.]

The following inference...

Modern retrieval systems, whether lexical or semantic, expose a corpus through a fixed similarity interface that compresses access into a single top-k retrieval step before reasoning. This abstraction is efficient, but for agentic search, it becomes a bottleneck: exact lexical constraints, sparse clue conjunctions, local context checks, and multi-step hypothesis refinement are difficult to implement by calling a conventional off-the-shelf retriever, and evidence filtered out early cannot be recovered by stronger downstream reasoning. Agentic tasks further exacerbate this limitation because they require agents to orchestrate multiple steps, including discovering intermediate entities, combining weak clues, and revising the plan after observing partial evidence. To tackle the limitation, we study direct corpus interaction (DCI), where an agent searches the raw corpus directly with general-purpose terminal tools (e.g., grep, file reads, shell commands, lightweight scripts), without any embedding model, vector index, or retrieval API. This approach requires no offline indexing and adapts naturally to evolving local corpora. Across IR benchmarks and end-to-end agentic search tasks, this simple setup substantially outperforms strong sparse, dense, and reranking baselines on several BRIGHT and BEIR datasets, and attains strong accuracy on BrowseComp-Plus and multi-hop QA without relying on any conventional semantic retriever. Our results indicate that as language agents become stronger, retrieval quality depends not only on reasoning ability but also on the resolution of the interface through which the model interacts with the corpus, with which DCI opens a broader interface-design space for agentic search.

Welcome to LTT Labs - your go-to destination for all things tech. Explore comprehensive test results, insightful commentary, and the latest analysis in hardware.

Background We started off with a simple idea for a product; we wanted to re-use the chat interface for everything except chat. It was supposed to be just for photos but expandable later.
The idea was that most people already share their photos with others on WhatsApp or some other messaging service, which technically also ’tags’ the people who were there. So, why not turn the act of sharing into the act of organizing as well?

Why you shouldn't use SQL if you care about correctness

TL;DR. Claude would rather reinvent the wheel than pip install one.