🤖 1X opens pre-orders for NEO, the AI-powered home robot

1X has officially started taking pre-orders for NEO, its autonomous household robot designed to handle daily chores and tasks.

🔸 Customers can either subscribe for $500 per month or buy NEO outright for $20,000, which includes a three-year warranty and premium support.
🔸 The robot operates fully autonomously, but if it encounters a task it can’t perform, a human operator can remotely teach it new skills in real time, though the company says this only happens when necessary.
🔸 Users can also control NEO remotely through a mobile app or VR headset from anywhere in the world.
🔸 Shipments are scheduled to begin in 2026.

1X envisions NEO as a practical step toward personal robotics not just a gadget, but a home assistant that learns, adapts, and evolves alongside its owner.

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🔔 Durov unveils Cocoon, a decentralized network for running AI models

Pavel Durov has announced Cocoon, a new decentralized computing platform designed for developers to run AI models without relying on centralized servers or cloud providers.

🔸 The network will draw its processing power from individuals who share their high-end GPUs such as Nvidia H200 cards in return for rewards paid in TON cryptocurrency.
🔸 Developers will be able to deploy and process AI tasks directly within Cocoon, which Durov says will offer both privacy and lower costs.
🔸 Telegram will be the platform’s first major client, using Cocoon to handle confidential AI requests.
🔸 The project is set to launch in November, and the team is already accepting applications from developers and GPU owners interested in contributing to the network.

Cocoon marks Durov’s move to merge decentralized infrastructure with AI, building a privacy-first alternative to traditional cloud compute.

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🎓 New AI agent takes over academic writing from essays to full theses

A new AI-powered assistant built for students can now research, write, and format everything from short essays to full academic papers.

🔸 The agent can search for academic articles on any topic, users simply provide a short intro paragraph and type the command /cite.
🔸 With /insert, it automatically adds properly formatted citations into the text.
🔸 Powered by Deep Research, it scans and analyzes thousands of scientific papers online, organizing arguments and generating structured, evidence-based writing.
🔸 It also formats outputs like real academic documents, offering instant exports to LaTeX, Word, or PDF.

For students, it’s not just an essay writer, it’s a full academic co-pilot that handles the research, writing, and formatting in one place.

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🛡 OpenAI releases free AI models for content moderation

OpenAI has launched two open-source moderation models, gpt-oss-safeguard-120b and gpt-oss-safeguard-20b, designed to detect harmful or inappropriate content online.

🔸 The models can flag toxic language, fake reviews, or unsafe material across websites and social platforms.
🔸 Developers can set their own policy rules, customizing how the system interprets and enforces moderation standards.
🔸 Like the base gpt-oss model, both versions can explain their reasoning, showing the decision path behind each moderation action.

By making these tools free, OpenAI aims to give developers transparent, controllable moderation systems that can scale with AI-era platforms.

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⚙️ A complete guide to fine-tuning neural networks for specialized tasks

A comprehensive new guide explains how to turn a general-purpose AI model into a domain expert without extra cost or computing power.

✅ What’s inside
🔸 Step-by-step instructions for preparing high-quality training data that shapes the model’s expertise.
🔸 Detailed walkthrough on how to fine-tune existing models for precision and reliability.
🔸 Methods to train a model in a new “profession” transforming it from a generalist into a specialist in areas like law, design, or data science.
🔸 Guidance on deploying a trained model, assigning it specific tasks, and integrating it into workflows.

This guide shows how to evolve a universal neural network into a focused professional, fast, free, and ready to deliver expert-level results.

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🛡 OpenAI launches Aardvark, an AI agent that hunts code vulnerabilities

OpenAI has introduced Aardvark, a new AI-powered security agent that scans, tests, and flags vulnerabilities in codebases, working like a tireless digital security analyst.

🔸 Aardvark connects directly to GitHub, continuously reviewing code for potential security flaws and weak spots.
🔸 Using advanced reasoning from GPT-5, it identifies risks, explains their severity, and suggests specific fixes, all without changing code automatically.
🔸 In early trials, the agent uncovered previously unknown bugs in open-source projects that later received official CVE classifications.
🔸 Currently in invite-only beta, Aardvark will expand access after further testing and developer feedback.

By automating vulnerability detection, OpenAI aims to speed up the security review process, turning code audits from a manual bottleneck into a proactive, AI-driven defense layer.

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🎵 MiniMax launches Music 2.0 with vocal generation

MiniMax has released Music 2.0, an upgraded AI model that can now create full tracks with vocals lasting up to five minutes.

The system supports multiple languages, including Russian, though vocal quality and pronunciation still need refinement.

It’s another step toward AI tools capable of producing complete, human-like songs from scratch.

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When you traded a 9 to 6 job for startup life 24/7.

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🎬 New prompt generator for Sora 2 helps create cinematic AI videos

A new free tool has appeared for Sora 2 users, a prompt generator designed to produce the highest-quality AI videos with professional detail and structure.

🔸 Includes 64+ premium presets covering camera angles, lighting, color grading, and post-processing.
🔸 Supports 6 video types from memes and ads to cinematic clips and music videos.
🔸 Offers a scene-by-scene builder to assemble prompts for perfectly sequenced shots.
🔸 Completely free to use.

A must-have for anyone looking to turn Sora 2 into a true AI film studio.

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🔔 Elon Musk predicts the end of smartphones, AI displays will take over

Elon Musk believes smartphones are on their way out. Within the next 5–10 years, he says, they’ll be replaced by AI-powered displays that act as direct interfaces between local and cloud-based large language models.

🔸 Instead of apps or operating systems, these handheld displays will generate personalized interfaces and content in real time.
🔸 Communication, media, and productivity will all flow through AI, no icons, no downloads, no screens full of apps.
🔸 The idea aligns with Musk’s broader vision of human-AI integration, blurring the line between digital and biological interaction.

If this future materializes, it won’t just replace the smartphone, it could erase the entire concept of a “device,” making AI the true operating system of daily life.

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✅ Hugging Face drops a free 200-page textbook on building neural networks from scratch

Hugging Face just released a comprehensive open textbook that teaches how to create and train AI models from the ground up, completely free.

🔸 The 200-page guide covers the full training pipeline, from core math and data preparation to backpropagation and model optimization.
🔸 It’s written in accessible language and packed with diagrams, making deep learning fundamentals understandable even for beginners.
🔸 The release fits Hugging Face’s mission of open AI education and transparency, lowering the barrier for anyone to learn how modern neural networks actually work.

In an industry dominated by closed systems and paid courses, Hugging Face just turned AI education itself into open-source infrastructure.

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🚀 The first Nvidia H100 GPU just went to space

A small satellite, roughly the size of a mini-fridge, has carried the first Nvidia H100 into orbit, part of an early experiment by Starcloud, a startup aiming to build gigawatt-scale data centers in space.

🔸 The satellite includes solar panels, radiators, and a single H100 GPU, designed to test how high-performance chips operate beyond Earth’s atmosphere.
🔸 Starcloud’s long-term goal is to create massive orbital data centers with millions of GPUs running on direct solar power.
🔸 Operating in a sun-synchronous orbit means the data center is always in sunlight, removing the need for batteries or nighttime power plants, a huge advantage in energy efficiency and cost.
🔸 A proposed 5-gigawatt orbital facility would weigh around 20,000 tons and cover 16 square kilometers, nearly half the total mass humanity has ever launched into space.

The concept hinges on launch economics: Starcloud’s plan assumes orbital costs of about $30 per kilogram, achievable only with SpaceX’s Starship. Until then, the company is testing power, cooling, and GPU performance in orbit, a first step toward making space the next frontier for AI compute.

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📈 AI is enriching investors while compressing wages

Artificial intelligence is accelerating wealth for investors even as it diminishes the value of human labor, creating a historic concentration of capital in tech stocks.

🔸 The seven largest technology companies now have a combined market capitalization exceeding $20 trillion, an all-time high.
🔸 These companies’ shares account for roughly 35% of the S&P 500, marking a level of concentration unseen even during the dot-com bubble in 2000.
🔸 While AI boosts productivity and profit margins, it simultaneously reduces the economic leverage of human workers, widening inequality.
🔸 Investors are reaping unprecedented gains, but the broader workforce sees limited upside from the same technological boom.

The rise of AI highlights a fundamental shift: the greatest beneficiaries of technological progress are increasingly shareholders, not employees.

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⚙️ Reduino lets you program microcontrollers entirely in Python

A new library, Reduino, makes Arduino-style projects accessible without learning C++, letting hobbyists and engineers code microcontrollers in native Python.

🔸 Simplified coding: Control LEDs, RGB strips, sensors, and other electronics using familiar Python syntax, loops, conditions, arrays, tuples, and even classes.
🔸 Automatic translation: Python code is converted behind the scenes into C++ system files, ensuring compatibility and stability.
🔸 Seamless deployment: The library can compile and upload code directly to devices, removing the traditional Arduino workflow friction.
🔸 No C++ required: Beginners can focus on logic and experimentation without learning Arduino’s programming language.

Reduino could reshape DIY electronics by making Python the universal language for microcontrollers, lowering the barrier for creators and innovators alike.

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💸 Fewer checks, bigger bets: early rounds now dominated by single investors

Peter Walker, Head of Insights at Carta, shared data showing a sharp shift in early-stage funding, lead investors are now taking nearly 100% of Seed and Series A rounds. The rest, a symbolic 1%, goes to angels.

🔸 The logic is simple: lead investors secure better terms today and tighter control tomorrow, while founders get a cleaner cap table and faster closes.
🔸 For follow-on rounds, a fully led seed signals conviction “if Fund X took the whole thing, they must’ve seen something.”
🔸 Angels and syndicates are getting edged out, but founders benefit from speed, clarity, and fewer competing opinions.
🔸 The trade-off: less investor diversity means fewer networks and viewpoints early on.

So what’s better — many small believers or one big backer?

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🥗 One photo, full nutrition: AI app counts calories from any meal

A new app called CalPulse can now identify the full nutritional breakdown of food from a single photo, whether it’s a café dish, delivery meal, or restaurant plate.

🔸 Snap a photo, upload it to CalPulse, and the app instantly analyzes calories, proteins, fats, and carbs.
🔸 It also recognizes menu items from restaurants and delivery services, matching them to verified nutritional databases.
🔸 Designed for precision tracking, it helps users log macros without manually entering ingredients.

AI is making calorie counting effortless, just point, shoot, and eat smarter.

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🎥 YouTube turns likes into mini-animations to boost engagement

YouTube has updated its like button, it now shows custom animations depending on the video’s theme. A car video gets a spinning wheel, a football clip a bouncing ball, and a travel vlog a plane taking off.

🔸 The like itself hasn’t changed, you still can’t “multi-like” or react with emojis, only one click but the visual effect now varies across content types.
🔸 Dislikes remain static with no animation added.
🔸 The goal is to make liking more fun and “convert better,” nudging users to click more often.

More likes mean richer engagement data for algorithms, longer average watch time (since people are less likely to quit videos they’ve liked), and deeper platform attachment through frequent interaction.

A small UI tweak but a clever psychological move to keep viewers watching longer.

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