Gemini Spark is the most impressive and terrifying AI experience I’ve had yet
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International Mathematical Union endorses warning about tech industry influence.
I recently completed a 5-minute philosophical science fiction short film called The Robot Summit. The story takes place in a future where humanity has disappeared and intelligent machines gather to understand their origins, purpose, and the nature of intelligence itself. As the discussion unfolds, an unexpected human survivor challenges many of their assumptions. This project was developed over several months using a workflow that combined AI image generation, AI video generation, AI voice synthesis, original music composition, and traditional editing in Final Cut Pro. One of the biggest challenges was maintaining visual consistency and narrative coherence across dozens of AI-generated shots while still creating something that felt like a film rather than a technology demonstration. I'm particularly interested in feedback regarding: • Narrative flow and pacing • Visual continuity between scenes • Audio balance between narration and music • Whether the philosophical themes feel natural or overly explicit • Overall effectiveness as a short film I'm also happy to answer questions about the production workflow, tools used, and lessons learned during development. Film: https://www.youtube.com/watch?v=pMeJ7h734vE submitted by /u/renatobotto [link] [留言]
Google Photos and Google Play Books are also getting new AI-powered updates.
Microsoft’s OpenClaw-style agent appears in Teams, just like a human colleague, and automates your dull office tasks.
Layup Parts co-founder Zack Eakin has drawn on a motorsports background, and his experience working for Palmer Luckey and Elon Musk, to tackle making faster, cheaper, and better composites.
Sometime late last year a company called Logical Intelligence developed an EBM called Kona. What do people make of the company’s claims that they have a close to functioning EBM. And if true, what impact would this have on existing AI? submitted by /u/Treey1234 [link] [留言]
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Quantum computing is starting to get pulled into the same conversation as AI, semiconductors and national scientific computing. The federal government is supporting quantum through CHIPS-style incentives, national lab initiatives, and post-quantum cybersecurity regulation. Big tech is also still heavily involved through IBM, Google, Microsoft, Amazon, Nvidia and Honeywell/Quantinuum. But I’m trying to understand the real timeline. AI has immediate commercial demand. Data centers need GPUs right now. Power demand is visible right now. Quantum is different. The potential is huge, but broad commercial quantum advantage still seems uncertain. So is quantum a real near-term AI infrastructure theme, or is it more like a 5-10 year strategic bet? Where do people think the first real commercial use cases show up? Optimization? Chemistry/materials? Cybersecurity? Finance? Drug discovery? AI model training? National labs? Curious what people working closer to the field think. submitted by /u/CalebMitchell840 [link] [留言]
Another fusion startup has raised another a massive round to make this type of power a reality.
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Hey everyone, If you are deploying open-source models, you know the biggest headache is figuring out exact hardware requirements. You usually end up digging through Reddit threads to find out if a specific model fits on a single A10G, if you can squeeze it onto consumer cards, or if you have to jump up to a massive bare metal A100 cluster. Most of the "guides" out there are just static, out-of-date tables or dense walls of text. So, we published "Which GPU Runs Which LLM" on the AgentSwarms blog, but we engineered it completely differently. What makes this different: It is 100% interactive and gamified. Instead of reading a textbook on VRAM math, you actively engage with the hardware logic right on the page. You select the model size (8B, 32B, 70B, etc.). You tweak the quantization (FP16, 8-bit, 4-bit, GGUF vs AWQ). The interactive deck instantly calculates the VRAM constraints and visually maps out the exact GPU tiers you need to deploy. It gamifies the infrastructure planning so you build an intuitive understanding of token economics and hardware limits before you spin up expensive cloud instances. It is completely free to read and play with (no sign-ups required). If you are trying to optimize your AI infrastructure or just want to test your intuition on hardware mapping, click around the interactive guide and let me know how this format feels compared to a standard article (All AgentSwarms blogs and presentations are fully interractive) Link: agentswarms.fyi/blog/which-gpu-runs-which-llm-the-complete-guide submitted by /u/Outside-Risk-8912 [link] [留言]
In the social event planner’s first major move toward monetization, Partiful is getting ticketing directly in the app.
Board, the startup building what it calls "together tech" designed to bring people into the same room, has closed a Series A led by Union Square Ventures.
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Building a Thriving Package Marketplace: The Complete MarketHub Guide Introduction If you're building a platform where developers can discover, share, and monetize packages, you're tackling one of the most complex problems in the software ecosystem. From managing publisher reputations to handling analytics at scale, marketplace dynamics require careful orchestration across multiple user roles. Enter MarketHub — a comprehensive three-app marketplace system designed to handle exactly this challenge. Whether you're creating a plugin ecosystem, SaaS integrations hub, or package distribution platform, MarketHub provides a battle-tested architecture for managing the complete marketplace lifecycle. The Problem: Why Marketplaces Are Hard Building a marketplace isn't just about creating a catalog. You need to solve several interconnected problems simultaneously: Discovery : How do users find quality packages in a sea of options? Trust : How do you build confidence in unfamiliar publishers? Quality Control : How do you maintain standards without stifling innovation? Incentives : How do you motivate publishers to create excellent packages? Scale : How do you manage analytics, reputation, and community as the ecosystem grows? Most teams try to bolt these features onto a basic catalog — resulting in fragmented systems where reputation tracking doesn't align with analytics, and community features feel disconnected from the review process. MarketHub Architecture: A Three-App Approach MarketHub solves this by separating concerns into three distinct applications, each optimized for its audience: 1. Public Discovery App — The Storefront This is where users find packages. The discovery app features: Intelligent Search & Filtering : Search across package names, descriptions, and tags with category-based filtering Featured Packages : Curated collections to highlight quality and trending packages Smart Ranking Algorithm : Packages rank based on quality signals — not just download counts
Recently, I started building a website for a local car showroom. The budget? 800,000 Indonesian Rupiah (around $50 USD). At first, it sounded impossible. But when working with small businesses in Indonesia, budgets are often very different from what many developers in the US or Europe are used to. Instead of building a complex custom platform, I focused on solving the showroom's real problems. What the client gets Vehicle Management Add and edit car listings Manage prices Vehicle specifications Featured inventory Vehicle Search & Filters Visitors can filter cars by: Brand Model Year Price Condition Built-in CMS The showroom can publish: Car buying guides Automotive news SEO articles Promotions Lead Generation Every car listing includes direct WhatsApp contact buttons to maximize inquiries. Extra Services Included For the same price: Free maintenance for simple issues Free consultation and support 3 free blog articles during the first month AI-powered statistics assistant Why WordPress? Many developers immediately think about Laravel, React, Next.js, microservices, and other modern stacks. For this project, WordPress was the right tool. The client needed: A website they could update themselves Better Google visibility A simple inventory system More WhatsApp leads WordPress delivered all of that quickly. A Lesson I've Learned Small businesses rarely care about technology. They care about outcomes. They don't ask: "Does it use React?" They ask: "Will this help me sell more cars?" And honestly, that's probably the better question. What would you include in a low-budget car showroom website?
Japanese version available on note . Hi, I'm chatii @chatii . I recently attended Laravel Live Japan 2026. Here's what inspired me and what I took home from the conference. Profile Organizer of PHP Conference Kagawa Encountered PHP back in the 4.x era Freelancer English level: "Can read reasonably well," "Can write a little," "Can listen a bit," "Cannot speak at all." 5/23 PHP×Tokyo - Laravel Live Japan PRE-PARTY PHP×Tokyo - Laravel Live Japan PRE-PARTY - connpass (English follows Japanese) PHP×Tokyoは、PHPやLaravelが好きなエンジニアのためのインターナショナルなミートアップです。 日英のライブ翻訳付きなので、英語が得意でなくても大丈夫です!言語の壁を越えて、PHP/Laravelについて語り合いましょう! 登壇者も募集中です!登壇を希望する方はこちらからご応募ください。 登壇は日本語・英語どちらでも大丈夫です。 #### タイムテーブル * 13:00 - 13:30 受付 & ネットワーキング * 13:30 - 13:40 オープニング * 13:40 - 14:10 "Man... phpxtky.connpass.com I first participated in "PHP×Tokyo March 2026." It was my first time attending a meetup with international participants. I couldn't speak English, but I hoped to be able to communicate somehow. Back in March, David helped me immensely with translation, which made me feel a bit apologetic... At the PRE-PARTY, I took the plunge. During the networking session, I managed to approach Victor Ukam , who gave the talk "Manage AI Prompts as Versioned Files in PHP," and said in English, "I have a question...!" Well... communication after that relied on Google Translate, but I was able to overcome the "first hurdle." You could say I successfully executed <?= "Hello, World" ?> . Also, it was great to see Ivan again, who came from Russia. I first met him in March, and I was so happy he came over to say hello! 5/25 Eve of the Conference, Gyoza Restaurant Zumi organized an unofficial pre-party via the laravel-live-jp channel on the "Laravel Japan" Discord. Participating in these "fringe events" around a conference is always fun. I had booked a hotel from the day before, so I joined in. The real-time translation app that Albert Chen built was incredibly high-performance... 5/26 Day 1 ...Actually, I couldn't sleep at
When most people think about Java, they immediately picture enterprise applications, banking systems, massive backend services, or decades-old corporate software. While Java has earned its reputation in the enterprise world, that is only part of the story. Today, Java can run on devices as small as a Raspberry Pi, opening the door to hardware projects, edge computing, home automation, education, and hands-on learning experiences. Combining Java with Raspberry Pi creates a powerful platform for experimentation, learning, and building real-world solutions that go far beyond traditional enterprise development. Raspberry Pi teaches us about hardware. Java allows us to apply professional software engineering practices to that hardware. Together, they create a powerful platform for learning, prototyping, and building real-world IoT and edge computing solutions. Java Is More Than Enterprise Software Java's enterprise success has sometimes created the misconception that it only belongs in large organizations. In reality, modern Java offers: Excellent support for Linux and ARM architectures. High performance and low resource consumption. Modern frameworks such as Spring Boot, Quarkus, and Micronaut. Strong support for IoT and edge computing. Access to hardware through mature libraries. One of the largest developer ecosystems in the world. The Raspberry Pi highlights a different side of Java—one focused on creativity, experimentation, and direct interaction with the physical world. Instead of building another web application, you can build systems that sense, react, and interact with their environment. Java at the Edge One of the most exciting technology trends today is Edge Computing. Traditionally, devices send data to cloud services where processing and decision-making occur. Edge computing shifts part of that processing closer to where the data is generated. A Raspberry Pi running Java can: Process sensor data locally. Apply business rules before sending information to th
Opal, the company famous for making a fancy webcam, has pivoted to making other consumer electronics. Fueled by big investments from OpenAI and Samsung, it’s working on an audio gadget first.