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The investigation involves at least some crashes where it appears drivers were using "forked" versions of Comma's software.

The startup says its automated system can change four tires in under 15 minutes.

LinkedIn is rolling out new verification tools that let members vouch for colleagues’ work experience and give companies more control over accounts that falsely claim to employ them.

Spotify is rolling out Taste Profile to Premium users in the U.S., letting listeners see how the streamer understands their tastes and use natural language to reshape their recommendations.

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In this cursed timeline, we have been gifted something so unfathomable that we could never have imagined it.

YouTube's AI feature can now help you compare products as you shop.

YouTube’s new custom feeds let users describe the videos they want to see in their own words, then use Gemini to build a personalized feed around the request.

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Many of these tools hinge on using generative AI to try out a variety of different tactics on a video to find what works best.

Other Made On YouTube announcements are also designed to help creators grow and engage audiences.

YouTube is adding new features to generate ideas and monitor the performance of thumbnails.

Eight Sleep said the new pod is now 20% faster than the previous generation

YouTube is adding new AI-powered features to YouTube Music that aim to make it easier for listeners to discover music, explore artists, and find podcasts they may otherwise miss. Announced at this year’s Made On YouTube event, the updates include “Ask Music,” a conversational tool for music and podcasts, and “Your Podcast Lineup,” a personalized […]

Creators will be able to use AI in a conversational chat interface to help them edit videos.

NVIDIA TensorRT Edge Model Optimization Modern Physical AI systems are distributed pipelines. The goal is not simply higher FPS; it is predictable latency, controlled memory use, reasonable power consumption, and reliable behavior. Architecture Sensors / Smart Glasses ↓ Kotlin / Flutter ↓ Network / Gateway ↓ NVIDIA Jetson ↓ ROS 2 / Isaac ROS ↓ NVIDIA AI Model ↓ Planner / Controller 1. Establish a baseline...

I like to learn SpikeForge by giving it a small job and keeping the moving pieces visible. This walkthrough uses the public toolkit, a short experiment and the event path that gained a real train/test split in the latest release cycle. Start with the SpikeForge repository and install the package in a fresh environment. Pick one of the example datasets already supported by the project. Keep the first run short. A small experiment that you can rerun is more useful than a large run that leaves...

Most AI writing tools have the same hidden tax. You stop writing, copy the text, open a chat window, paste it, explain what you want, copy the answer, then paste it back into the app where you were originally working. That is fine for a big draft. It is annoying for the tiny moments that happen all day: make this email less awkward finish this sentence shorten this Slack reply clean up this paragraph make this note sound less messy I wanted that help inside the Mac text f...

A few weeks ago I promised a technical write-up. Here it is. The two questions I get most are: how do you render tens of thousands of Jira issues in under 10ms? And how does the AI figure out how to group things? They're related, and the answer to both starts with the same principle — do less. The rendering problem Jira backlogs are large. A mature project might have 50,000 issues. Naively rendering 50,000 nodes in a browser canvas is slow, and no amount of JavaScript opti...

A Django concurrency story about read-then-mutate , silent no-ops, and why one fix is never enough. Section 1: The Bug That Didn't Announce Itself After I fixed the add_member race condition, I did what most developers do after a win: I closed the ticket and moved on. Then a small voice asked a very inconvenient question: If add_member had a race condition, what about change_member_role ? That question turned into an audit. And the audit turned into two more...

Running a Laravel application on a VPS usually means repeating the same routine: connecting via SSH, pulling latest changes, running composer updates, migrating the database, and clearing caches manually. It works, but it's repetitive and prone to human error. So I automated the boring part. In this guide, I'll walk through setting up a lightweight Continuous Deployment (CD) pipeline using: GitHub & GitHub Actions SSH Key Authentication A Linux VPS (Ubuntu) Larave...

If you have built a multi-agent AI system over the past two years, you have almost certainly encountered what we call the Supervisor Tax . The pattern usually starts with clean intentions: you have 3–4 specialized subagents (a researcher, an executor, an evaluator, and a reporter) coordinated by a central "Supervisor" or "Router" LLM. The supervisor inspects intermediate outputs, decides who gets called next, evaluates task completion, and synthesizes the final response. In local testing ...

see the beginning: How I Built a Personal Assistant with the Hardware I Already Had In short: the assistant got permanent personal memory and dreams, during which it goes through its personal history again. Concepts from cognitive psychology were used when creating the synthetic personality. It was found that the agent structures and complicates its personal memory on its own. An evolution of the models of self, world and time can be observed. The assistant demonstrates signs of cog...

Why 96% RTP Doesn’t Protect Your Bankroll: Simulating Gambler’s Ruin While working on my slot engine , I was experimenting with different mathematical models and game modes. One question kept coming up: if a game has a 96% return to player, what does that actually mean for someone playing with a limited bankroll? At first, 96% sounds like the player gets most of their money back. But winnings can be wagered again, and each new bet exposes the remaining balance to another possible loss. T...

When you hand an agent work with external effects, two worries always come up. First: when the process dies, what happens to the work in progress? An agent paused at an approval gate crashes — can it resume, or does everything restart from scratch? Second: when an LLM retries, does it execute the same side effect twice? Retrying a send or a data mutation carries a real double-execution risk. My previous article measured HITL approval, audit trails, and structured output across three...

A suspicious transaction starts an investigation. The harder part is deciding what evidence to gather, what remains uncertain, and which action is justified. We built Casework for the TigerGraph × HHGoa challenge to explore that problem. Casework is a fraud investigation application that connects graph evidence, document retrieval, a local language model, and policy rules. It follows a case from an initial trigger to a recorded recommendation, preserving the evidence and decisions al...

Gate Evidence collected What it cannot prove Record-only Expected TXT, MX, and address answers A receiving server accepted a message Outcome-first Record answers plus a controlled delivery receipt Every recipient's future delivery Short answer: For an edtech onboarding gate, choose outcome-first checks when the domain will send enrollment mail. Keep the record-only check as a fast diagnostic, not as proof that students can receive messages. A TXT lookup ca...

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