... agents, device collaboration, security and new ways for computers and phones to share capabilities. GPU Borrow demonstrated one of those ideas: A device doesn't necessarily need to own a capability to temporarily use it. We demonstrated a real NVIDIA RTX 3050 Laptop GPU being exposed through Blink Bridge, discovered and requested by an AI orchestrator, explicitly authorized by the user, used for a bounded workload, verified, and then released. Since then, our experiments have gone further. Android ... ... demonstrated an Android device participating in a workflow where a data block travelled through Blink Bridge, was transformed using an NVIDIA

... about or indexed Kanverse GPU Borrow and Kanverse ProofStamp thanks to Product Hunt The part of GPU Borrow that matters most to me is the control model: Discover Ask Permission Borrow Execute Verify Release The demo uses a real NVIDIA RTX 3050 Laptop GPU across devices, with explicit human authorization before a bounded GPU workload is allowed to run. But the idea is not simply remote GPU access. It is part of a broader principle we are exploring at Kanverse ...

... When I was reading TechCrunch today, I came across Jensen Huang s (NVIDIA CEO) view that AI safety should be handled by companies through engineering and market pressure, rather than through new regulation. In my opinion, the power of consumers and the public is sometimes simply not strong enough to counterbalance large technology companies. That s why I believe governments sometimes need to step in and establish rules and regulations. Do you think AI should be regulated by governments ... ... move money, send emails, touch production systems) than rules scoped to the model itself. That also happens to be the layer where a small team can actually build good defaults - permission scopes, human approval steps, audit logs - versus

... deal is done. NVIDIA has officially agreed to acquire Hugging Face, the company known for its GitHub-like repository of open-source AI models, for $12.9 billion. What it means: NVIDIA

... agent that lives in your terminal instead of a browser tab. The idea started from being tired of switching between chat windows and my editor. So loomcode plugs into whatever model you already pay for Anthropic, OpenAI, Gemini, OpenRouter, NVIDIA NIM (free tier), or local Ollama and you can switch models mid-session with /models. No lock-in, your own keys. The part I'm most unsure about (and would love feedback on) is Loom Computer , a beta feature where ...

... between retrieval/evidence and the final answer and checks whether the available evidence actually supports the claims being produced. If support is insufficient, it can fail closed. I recently ran the same frozen black-box protocol against: AletheionAGI Guardrails AI NVIDIA NeMo Guardrails Patronus Lynx Final observed results: AletheionAGI 9 PASS 0 FAIL 1 SKIPPED 0 ERROR Guardrails AI 4 PASS 2 FAIL 4 SKIPPED 0 ERROR NVIDIA

... Moonshot : Kimi K3 2.8T params, largest open weights ever (Jul 16) ByteDance : Seedance 2.5 (Aug 3) MiniMax : H3 multimodal (Aug 3) Huawei : openPangu-2.0-Pro 505B total / 18B active, open source (Aug 1) Meituan : LongCat 2.0 (Jul 20) NVIDIA : Nemotron TwoTower (Jul 1) poolside : Laguna S 2.1 (Jul 21) thinkingmachines : Inkling (Jul 17), Inkling Small (Jul 30) Ant Group : Ling-3.0-flash (Jul 23) Kuaishou : KAT-Coder-Air V2.5 / Pro V2.5 (Jul 10) SenseTime : SenseNova U1.5 (Aug 3) That ...

... genuinely excited to share this one. Intrascope is now a member of the @NVIDIA Inception program. We started building Intrascope because our own team needed a better way to use generative AI across the company without losing control over access, context, models, usage, and costs. What began as an internal need has grown into a platform that helps teams connect leading AI providers, manage permissions, define shared company and project context, and understand how AI is being used across ... ... organization. Joining the NVIDIA

... pledged with Nvidia-backed Firebird to build "Data Center Valley" 100,000 GPUs, live by 2027, part of Kazakhstan's push to become a regional AI hub. Thoughts anyone? I'm personally a little confused about why they chose Kazakhstan as the new data center capital ...

... Wired or Integrating: FastAPI, React, Three.js, WebGL, Tailwind, Socket.io, Docker, Kubernetes, Terraform, Nginx, Redis, PostgreSQL, SQLite, Figma, Notion, Linear, Jira, Slack. COMPANIES & LABS WE WANT AT THE TABLE: OpenAI, Anthropic, Google DeepMind, Microsoft, Meta AI, xAI, Moonshot AI, NVIDIA, Mistral AI, Cohere, Stability AI, Midjourney, Runway, ElevenLabs, Replicate, Hugging Face, LangChain, Vercel, Cloudflare, Stripe, Shopify, Notion, Linear, Figma. FOR CONTRIBUTORS: Verified dev badge. Tiered system access. Fair credit/revenue distribution. Owners, devs, superusers, archival users everyone gets a seat. Distributed ...

... this problem. After testing similar apps for Windows, I realized that the goal of my app is maximum ease of use (modelled after Google s visual translation on Pixel devices). The app works as an overlay (similar to Nvidia Overlay) that sits in the system tray and can be launched with a hotkey. The architecture is designed so that you can change most settings in real time with minimal effort. Currently, the following core features are available: Overlay mode Text ...

... reasonable pick precisely because the market still prices them behind on AI despite owning the infrastructure and consumer reach to make Gemini sticky over time. Comment from Johnson Gill(@johnsongill): I've got some pretty strong contenders - Anthropic - Nvidia - But Google is at the top coz they never give up. Comment from Nika(@busmark_w_nika): @virko_kask  I think that it must be a collective using :D But Apple and Google gave me some profits :D Comment from ... ... biggest returns still in the AI model companies, or will the real winners be the smaller companies building profitable businesses on top of them? Comment from Sebastian(@sebxdev): I've been investing for a year now, I've google, nvidia

... something a lot of indie devs actually need. Finding real testers is honestly one of the hardest parts of early launch. How do you keep the feedback quality high, is there any incentive for people to give thoughtful ratings vs just quick swipes? Comment from Nolan Vu(@nolan_vu): @josephsskaf_hub  Really respect the honesty around the trust problem Joseph, that's the exact tension every discovery platform faces. Keeping editorial rankings independent while offering paid placement ... ... both of us Comment from Gaurav Singh(@gaurav_singh91): Building: adextract - one MCP server that connects AI agents to ad libraries (Meta, TikTok, LinkedIn, and more) For: Claude power users and AI agent builders who need programmatic access to competitor

... annual budget. Their COO admitted they can t justify the expense. Microsoft has revoked AI licenses from its own developers to control costs. Starbucks scrapped its AI inventory system after 9 months because it performed worse than human employees. NVIDIA s VP recently said that AI is costing more than human workers. So the question is (are): Will companies eventually find a way to significantly reduce the cost of AI? Or will we see a partial return to old-school ... ... human labour because it s still more reliable and cost-efficient in certain cases? What s your take on this? Comment from lknur B.(@bailknur): I don't think it will be a simple AI vs

... deploy. Paste a model ID, it scans your GPU, VRAM, OS, and serving libraries, gives you a Hardware Ready verdict and full memory breakdown (weights + KV cache + serving overhead). No surprises at runtime. Supports Apple Silicon (M1 to M5), NVIDIA (CUDA), AMD (ROCm), and serving libraries including Ollama, llama.cpp, SGLang, TensorRT-LLM, PyTorch and many more coming. It tells you why something won't work, not just that it won't. CPU support is something we're actively working through ... ... oneInfer-edge is part of the broader oneinfer.ai inference control plane, a platform built for teams shipping multimodal AI products at scale. oneInfer-edge brings that same infrastructure intelligence to your local machine so self-hosting is a genuine alternative

... deploy. Paste a model ID, it scans your GPU, VRAM, OS, and serving libraries, gives you a Hardware Ready verdict and full memory breakdown (weights + KV cache + serving overhead). No surprises at runtime. Supports Apple Silicon (M1 to M5), NVIDIA (CUDA), AMD (ROCm), and serving libraries including Ollama, llama.cpp, SGLang, TensorRT-LLM, PyTorch and many more coming. It tells you why something won't work, not just that it won't. CPU support is something we're actively working through ... ... oneinfer-edge is part of the broader oneinfer.ai inference control plane, a platform built for teams shipping multimodal AI products at scale. oneinfer-edge brings that same infrastructure intelligence to your local machine so self-hosting is a genuine alternative

... mostly about making local coding-agent setups less fragile. What changed: - Reworked the Launch / Profile flow so picking agent + profile + workspace + session is faster - Better bridge routing and model metadata for Codex / Claude-style launches - New provider profiles: xAI, NVIDIA NIM, and Mimo - Pi profile launches and direct Pi session support - Agent enable controls, bridge proxy controls, and an in-app release update indicator - Web Chat now surfaces context-compaction notices more clearly If you use multiple coding agents ...

... that involves the use of a laptop is going to disappear like lightning. Comment from Bengeekly(@bengeekly): @busmark_w_nika  Honestly, it wouldn't shock me, while we are all looking at white-collars being replaced. Tesla and Nvidia can tomorrow make a huge step with a robot and instantly change the game. What really surprise us right now are huge steps Comment from Bengeekly(@bengeekly): My prediction years ago was that humans would remain the most artistic ... ... everyone overnight - they ll just move much faster with fewer bottlenecks. Comment from Alper Tayfur(@alpertayfurr): I think white-collar work gets affected faster because most of it already lives inside software. But the real split is not blue vs

... person, it might be literally $0; for another, it might be $3k/mo till break-even. Break-even on another hand depends on the nature of business + market (whether you need to scale adoption vs start charging right away) So it depends on geo + situation + (most importantly) the nature of the startup. Comment from John Hammond(@supamrvl): We've shipped 28+ apps at MRVL. Here's what the numbers actually look like from the inside. The $100 build cost is real ... ... amazes me how much you can achieve today, even without big VC money. We've been bootstrapping out of Madrid, Spain (which is obviously easier to do than living in high cost of living cities) and have benefits from NVIDIA

... real-time multilingual communication. There s still a lot to improve, but seeing the system evolve like this is a great feeling. It also makes me appreciate how powerful the open-source AI ecosystem has become. Huge respect to NVIDIA, Google, Qwen, and all the teams pushing this space forward. A lot more coming soon for VertoX Comment from Nemo Shakhverdiev(@nemos): @lyshen  Right now, we re still actively optimizing the pipeline, but the goal is sub-second ...

... only danger is that if things take a radical new turn, he likely won't be able to match it as he doesn't come off aggressive like Satya or Steve but still overall feels strongly right given NVIDIA is the most valuable company right now. Comment from Vova Lavrik(@vova_lavrik): @itsluo  i bet in 5 to 10 years Johny Srouji will be the next CEO, as he stepping in the same possition ...

... useful on a personal level. Definitely worth listening to. Comment from Ghost Kitty(@ghost-kitty-9520627): Comment Deleted Comment from Ricky Singh, MBA(@xquest): Lenny is in the rotation, but the ones I reach for first are Acquired (the Nvidia trilogy is required listening if you build anything in tech), My First Million for raw idea volume, and The Knowledge Project with Shane Parrish when I want to slow my thinking down. Hidden gem: Founders with David Senra. He reads ... ... still works in today's AI world. Comment from Ghost Kitty(@ghost-kitty-9659431): Comment Deleted Comment from Hamid Khan(@get_map_leads): Solid picks, but Acquired is on another level. The depth they go into on companies like Nvidia

... looking for contributors to make it even better. PinchBench started as a side project of @realolearycrew . The goal was simple: create a real-world benchmarking tool to help developers choose the right LLM for @OpenClaw agents. Fast forward, @NVIDIA CEO Jensen Huang featured PinchBench in his GTC 2026 keynote as the definitive standard for evaluating the real-world performance of OpenClaw agents. Launched this week on Product Hunt, ranked in the Top Products ...

... Product Hunt! I built ClawBox a plug-and-play AI assistant box running on NVIDIA Jetson Orin Nano 8GB. The idea: you plug it in, scan a QR code, and in 5 minutes you have a local AI assistant that runs 24/7 at 15W. It connects to Telegram, WhatsApp, Discord, and can automate your browser. Specs: 67 TOPS AI performance 512GB NVMe SSD Carbon fiber case OpenClaw pre-installed (open source) NVIDIA

... LLMs locally on your #MacBook using full MPS (Metal Performance Shaders) acceleration. M1 through M5, your chip was built for this moment. We've been hearing this request since day one. We listened. We shipped. No cloud costs. No @NVIDIA required. No complex setup. Just: pip install modelforge-finetuning ...and you're fine-tuning on your Mac. At ForgeOpus, we're on a mission to democratize AI, and that means powerful tools that work for every builder, on every machine ...