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Aptoide has become the first app store distributed inside Google Play under a judge's order.

Meta CEO Mark Zuckerberg has a lot to say about the idealized future he now envisions for humanity co-existing with artificial intelligence - his latest essay spans more than 6,500 words on the matter. The lengthy manifesto Zuckerberg published on Monday, titled "The Future is for Everyone," broadly lays out his beliefs about how the […]

Starting on Friday, August 28th, Apple will begin streaming Friday Night Baseball in immersive video on Apple Vision Pro. The stream will feature commentary from various analysts and reporters, and live graphics will be anchored around the viewers space during the game. After the games conclude, replays will be made available in the Apple TV […]

Building any intake pipeline, you'll hit the same problem eventually. Files arrive from multiple sources. Some you've already processed: re-uploads of the same document, copies from two different intake paths, items your worker errored on last run and re-queued. Call the anchoring API blindly and you end up with multiple proof records for identical bytes. The ProofLedger v1 API returns a duplicate_of field in its 201 response when it detects a hash it's already seen. But that's only half the solution. A network round-trip costs time and quota even when it comes back as a duplicate. Hash-based local deduplication is the other half. Here's how to build a worker that handles both layers. Hash Locally First The core pattern: compute the SHA-256 digest before making any API call. If you've seen this digest before, skip it. If you haven't, submit it. Two things you need: a persistent record of digests you've already anchored, and chunked hashing so large files don't blow memory. import hashlib import json from pathlib import Path SEEN_DB = Path ( " anchored_hashes.json " ) def load_seen (): if SEEN_DB . exists (): with open ( SEEN_DB ) as f : return json . load ( f ) return {} def save_seen ( db ): with open ( SEEN_DB , " w " ) as f : json . dump ( db , f , indent = 2 ) def hash_file ( path : str ) -> str : h = hashlib . sha256 () with open ( path , " rb " ) as f : for chunk in iter ( lambda : f . read ( 65536 ), b "" ): h . update ( chunk ) return h . hexdigest () 65536-byte chunks keep memory flat regardless of file size. The load_seen / save_seen pair gives you a persistent record that survives worker restarts. Submitting and Reading duplicate_of When duplicate_of appears in the API response, its value is the proof ID of the earliest anchor for that hash. That's the canonical ID. The new proof ID from this call is irrelevant. import requests API_URL = " https://proofledger.io/api/v1/proof " API_KEY = " sk_YOUR_KEY_HERE " def anchor_file ( file_path : str , seen : dict

Valve says a data breach may have exposed the personal information of customers who ordered its Steam hardware in Europe. In an email sent to users, Valve says its European shipping partner, CEVA Logistics, suffered a data breach that may have included customer names, addresses, phone numbers, and email addresses. The breach at CEVA occurred […]

You probably know just by looking at it if the Classic-TKL Underscore Edition is for you. Do you want a retro-looking wired keyboard without a number pad? Great. Do you care that it doesn't have wireless? Perfect. Do you want it preassembled? Buddy, you're in the right place. But Nathan, you might say, preassembled is […]

Following the latest twist in Google's legal battles with Epic, US Android users are now able to open Google's Play Store and download a third-party digital store with its own selection of apps. Aptoide, a store specializing in mobile games, is the first to become available. Third-party app stores have always been available on Android, […]

MIT Technology Review’s What’s Next series looks across industries, trends, and technologies to give you a first look at the future. You can read the rest of them here. Way back in the summer of 2017, AI researchers at Google put out a paper called “Attention Is All You Need,” in which they described a new…

The Infrastructure: Setting Up Jenkins on AWS The foundation of this project began by provisioning an Ubuntu EC2 instance on AWS. Setting up the environment meant defining strict networking rules (opening Port 22 for SSH and Port 8080 for the Jenkins UI) and structuring the Jenkins environment with clear access controls. In Jenkins, maintaining a secure and organized environment generally falls into two roles: Administrators: Responsible for managing the Jenkins cluster, installing necessary plugins, and handling data backups. Users: Focused purely on creating jobs to run their respective workflows. The Magic of Docker-out-of-Docker (DooD) One of the most critical architectural choices was deciding how to let Jenkins build Docker images without installing a heavy, nested Docker engine inside the Jenkins container itself. The solution was a Docker-out-of-Docker configuration. By running the following command, I spun up the Jenkins container while binding it directly to the host machine's Docker socket: docker run -p 8080:8080 -p 50000:50000 -d \ -v jenkins_home:/var/jenkins_home \ -v /var/run/docker.sock:/var/run/docker.sock \ -v $( which docker ) :/usr/bin/docker jenkins/jenkins:lts This single command did a lot of heavy lifting. It mapped port 8080 for the UI and 50000 for Jenkins agent communication. More importantly, mapping /var/run/docker.sock gave the Jenkins container the ability to pass docker build and docker push commands directly to the EC2 host’s Docker engine. (Just remember to ensure your jenkins user has the right permissions to access that socket!). Hitting the Wall: The Limitations of Freestyle Jobs Initially, I set up the application lifecycle running npm install , npm test , and npm pack using a standard Jenkins Freestyle job. Freestyle jobs are great for quick, isolated tasks. However, their limitations become glaringly obvious when you try to build a project with multiple automation steps. Orchestrating a complex workflow by chaining multiple Fr

Earlier this week, the Alaskan cruise ship Wilderness Legacy rescued a small skiff stranded near Farragut Bay after running out of fuel. But, according to tracking data reviewed by the Alaska Beacon and Halifax Shipping News, the closest vessel was actually Mark Zuckerberg's super yacht, Launchpad. Michael Love, a passenger on the Wilderness Legacy, posted […]

Welcome back to TechCrunch Mobility, your hub for the future of transportation and now, more than ever, the role AI is playing in it.

In 2018 I bet my reputation and self-worth on a huge crowdfunded game design project. It could have been a failure for many reasons, but the one I became most worried about was losing all of the work that was stored locally on my home-built PC - a scenario that would have left a lot […]

X is ending its controversial revenue-sharing program for content creators, which has seen numerous revisions under Elon Musk's reign. In its place, it's launching a new Original Content Rewards program on September 8th. To be eligible, creators must have at least 500 verified followers and at least 500,000 Home Timeline impressions from verified users in […]

Hi, friends! Welcome to Installer No. 139, your guide to the best and Verge-iest stuff in the world. (If you're new here, welcome, barbecue sauce, and also you can read all the old editions at the Installer homepage.) This week, I've been reading about Johnny Knoxville and Google Zero and the history of the bicycle, […]

A multi-agent system without an orchestrator is just a collection of agents. Each one is capable, but none of them coordinated. They might all be excellent at their individual jobs - searching the web, writing code, calling APIs - but without something deciding what gets done, in what order, by whom, and what to do when a result comes back wrong, the system does not behave like a system. It behaves like a group project with no project manager. The orchestrator is the project manager. Its job is not to do the work. Its job is to make sure the work gets done - and that is a harder, more subtle problem than it sounds. What an orchestrator is responsible for An orchestrator does four things, and only these four things: 1. Decompose the goal. Turn a high-level objective into a concrete set of subtasks. This is a planning problem, not an execution problem. The orchestrator decides what needs to happen, not how to do it. 2. Route tasks to the right workers. Match each subtask to an agent capable of doing it. This requires knowing what tools and capabilities each worker has - not in detail, but well enough to delegate correctly. 3. Manage state across the workflow. As workers return results, the orchestrator decides what those results mean for the remaining plan. Sometimes a result changes the plan entirely. Sometimes it confirms the next step. The orchestrator holds the full picture. 4. Synthesise the final output. Worker outputs are partial. The orchestrator assembles them into a coherent response and decides when the goal has been met. Notice what is absent: the orchestrator does not call APIs, does not run code, does not search the web. It reasons about work and routes it. The moment an orchestrator starts executing, it loses the focus that makes it good at coordination. Building one from scratch Here is a minimal orchestrator in Python. It plans upfront, delegates to type workers, and synthesizes results: import json def orchestrator ( goal : str , workers : dict ) ->

There's two things you should know about me, your intrepid reviewer: I hate the feature creep associated with modern power banks, and I love shaving grams off the gear I carry when backpacking, bikepacking, and trail running. So imagine my delight when Nitecore released a new generation of its ultralight NB10000 battery. After a few […]

Copernicus Browser adds wildfire visualization amid record wildfire season.

OpenAI says it is pausing "internal activities" around an in-development AI model, Astra, because it doesn't yet meet new security standards the company is putting in place. The announcement follows its recent disclosure that OpenAI models accidentally hacked Hugging Face. Anthropic and Meta have also since admitted that they had AI models that went rogue […]

Microsoft Edge is ending support for the Manifest V2 extensions platform, which will cut off the uBlock Origin adblocker and others like it, just like Google Chrome did earlier this year. According to Microsoft, there are only 58 extensions on the Edge Add-On Store "with any meaningful usage" that still use MV2, and only three […]

Gurman report claims OpenAI confirmed the speaker is not an Apple ripoff.