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M 3.9 Experimental Explosion – 147 Km ENE of Ponce Inlet, Florida

2026-07-17 @ 00:45:05Points: 42Comments: 12

The Human-in-the-Loop Is Tired

2026-07-17 @ 00:21:09Points: 50Comments: 30

Lingbot-map: A 3D foundation model for reconstructing scenes from streaming data

2026-07-17 @ 00:07:49Points: 7Comments: 0

Show HN: Mojibake – A low-level Unicode library written in C

2026-07-16 @ 22:29:21Points: 45Comments: 7

It consists of only two amalgamation files: mojibake.h and mojibake.c. I've added all the most important Unicode algorithms, such as normalization, case conversion, segmentation, bidirectional text, collation, confusable, and others.

I regularly test it in these OSes: Linux, macOS, FreeBSD, OpenBSD, NetBSD, and Windows 11.

You can find a WASM demo on that site of all the public API functions and the documentation. If you want to participate, feel free to do it. Any kind of help is welcome. Check the CONTRIBUTING.md and API.md files in the GitHub repository for instructions on how to do it.

The Little Book of Reinforcement Learning

2026-07-16 @ 22:27:22Points: 73Comments: 10

CVE-2026-25089: FortiSandbox unauthenticated command injection added to CISA KEV

2026-07-16 @ 22:07:30Points: 28Comments: 0

'Likweli': A new monkey species discovered in the Congo Basin

2026-07-16 @ 22:00:00Points: 57Comments: 8

Ring-Zero: Scaling Zero RL to a Trillion Parameters for Emergent Reasoning

2026-07-16 @ 21:38:02Points: 40Comments: 14

Mathematics of Data Science

2026-07-16 @ 20:38:48Points: 113Comments: 3

Helium escaping from atmosphere of nearby rocky exoplanet in a habitable zone

2026-07-16 @ 20:24:02Points: 80Comments: 17

LM Studio Bionic: the AI agent for open models

2026-07-16 @ 20:18:15Points: 181Comments: 67

The privacy problems hidden in your period tracker

2026-07-16 @ 20:15:58Points: 78Comments: 42

$100 AI Music Video: Claude Fable 5 vs. GPT-5.6 Sol

2026-07-16 @ 20:03:23Points: 163Comments: 178

CD sales growth outpaced vinyl in the first half of 2026

2026-07-16 @ 17:19:16Points: 72Comments: 84

Adaptional (YC S25) Is Hiring

2026-07-16 @ 17:00:55Points: 1

Launch HN: Traceforce (YC S26) – Company-wide security monitoring for AI apps

2026-07-16 @ 16:52:16Points: 38Comments: 19

https://www.traceforce.ai/). Traceforce provides visibility and control over AI apps such as ChatGPT, Claude etc directly on all devices (laptops, sandboxes, virtual machines) by discovering not just which apps are being used but also how they are connected to other data sources via MCPs. We also have an open-source dynamic MCP pentesting tool https://github.com/traceforce/mcp-xray to detect vulnerable MCPs.

The purpose of Traceforce is to:

- Give a company’s employees a standardized way to ensure that AI software running on their device is operating safely

- Give the company’s security team visibility of the activities of AI software on the company’s devices, and to detect and prevent unsafe actions and security breaches as early as possible.

How Traceforce works

1. Traceforce is installed on each device as a lightweight binary and browser extension.

2. Within 30 minutes, the device is uploading live data to the company profile, displaying all the AI agents/apps running across all company devices on a dashboard.

3. Company security staff can monitor the activity of all the agents in real time, implement controls, and be alerted to any security risks as soon as they arise.

Here’s the video demo: https://youtube.com/watch?v=IdK2WKg7kaM

The inspiration for Traceforce came via Xia’s experience as Director of Engineering at a startup called Clumio (which was acquired by Commvault in Oct 2024). Being able to monitor how team members are using AI without slowing them down was a top priority at Clumio. After speaking with 50+ CISOs and CIOs, it became clear that this is a much-needed solution right now across industries. We keep hearing that new AI features are being adopted so quickly and so broadly that visibility and control just can't keep up.

Traceforce is transparent about what we monitor and collect. By default, Traceforce collects only metadata and telemetry about the AI applications, MCPs, and tools running on a device. Security teams can enable options to inspect tool calls for the purpose of detecting, warning on, or blocking predefined high-risk or potentially destructive actions. All content inspection happens locally on the device. User prompts are never stored unless explicitly configured by the organization's security administrators.

We work closely with end-users of the product, and once they understand what is being monitored/shared, they actually have great comfort that they have a powerful layer of protection on their device to prevent security incidents. It enables them to just focus on their work without worrying about what leaks and breaches may be happening under the hood without their awareness.

The Traceforce binary is built using Go and the browser extension is written in Node JS. The hardest part is building a complete connectivity graph between AI applications, MCPs, and tools, then identifying the vulnerabilities and attack paths introduced by those connections. Traditional security tools fall short: EDRs see processes, CASBs see network traffic, but neither has visibility into the application-level activity happening inside AI apps. The way we got it to work was by understanding the configurations and logs of each and every app. It’s a labor intensive process because every app is different and AI features change frequently.

Traceforce is currently deployed across more than 1,000 devices at 10 organizations. On average, we discover over 15 AI applications per device with each application connected to 5-10 MCPs. We've helped customers identify exposed plaintext secrets in MCP configurations, prevent API keys from leaking through AI-generated code, and warn developers before executing potentially destructive commands such as “DROP TABLE”. Our "warn and acknowledge" approach has been especially well received, giving developers the freedom to work while helping them avoid costly mistakes.

We're looking to work with security, IT, and AI platform teams at small to medium enterprises (200+ employees) that are rapidly adopting AI coding assistants, ChatGPT, Claude, and MCPs. If you're struggling to understand what AI tools people use to boost their productivity or need a practical way to reduce AI-related security risk without slowing folks down, we'd love to talk.

You can get started with a free trial at https://www.traceforce.ai or reach out directly to schedule a demo and discuss your environment.

Detecting LLM-Generated Texts with “Classical” Machine Learning

2026-07-16 @ 16:41:37Points: 167Comments: 114

Decoy Font

2026-07-16 @ 16:18:21Points: 438Comments: 105

NotebookLM is now Gemini Notebook

2026-07-16 @ 16:08:13Points: 265Comments: 134

Microsoft Comic Chat is now open source

2026-07-16 @ 16:06:27Points: 581Comments: 124

Immersive Linear Algebra Book with Interactive Figures (2015)

2026-07-16 @ 15:32:23Points: 180Comments: 26

How to Train a Gen AI Kick Drum Model on Your Old Linux Desktop with 6GB VRAM

2026-07-16 @ 15:13:00Points: 107Comments: 55

Kimi K3: Open Frontier Intelligence

2026-07-16 @ 14:46:05Points: 1273Comments: 800

https://www.kimi.com/en

Kimi K3 Intelligence, Performance & Price Analysis: https://artificialanalysis.ai/models/kimi-k3

Goes-19 weather satellite enters Safe Hold mode

2026-07-16 @ 13:30:00Points: 156Comments: 78

How Our Rust-to-Zig Rewrite Is Going

2026-07-16 @ 11:39:27Points: 429Comments: 231

Abstracting Effects with Continuations

2026-07-16 @ 10:41:39Points: 44Comments: 0

Pseudpocalypse

2026-07-14 @ 16:02:01Points: 94Comments: 52

Simulating everything, sort of: The promise and limits of world models

2026-07-13 @ 17:34:33Points: 15Comments: 0

Solod: Go can be a better C

2026-07-13 @ 16:38:21Points: 60Comments: 16

Show HN: Clx – Compile Lua to Native Executables Through C++20

2026-07-11 @ 12:40:24Points: 95Comments: 5

clx is an ahead-of-time compiler for standard Lua that generates C++20 and produces standalone native executables through GCC, Clang or MSVC.

The project started as an experiment to see whether modern C++ could be used as a portable compiler backend instead of LLVM or direct machine code generation. The generated code is then compiled and optimized by the host toolchain.

The latest release replaces the previous NaN-tagged value representation with a new shadow-types implementation, adds full int64 support, improves native arithmetic code generation and adds ARM64 macOS coroutine support.

Performance is typically much faster than the Lua interpreter and can outperform LuaJIT on some computation-heavy workloads while remaining fully ahead-of-time compiled.

The repository also contains graphical examples written in Lua, including a Pong game and a Mandelbrot explorer using a Sokol binary module (using the clx C++ API)

I'd be very interested in feedback on clx :)

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