Introducing Commenting in Bolt. Click anything in your preview, leave a comment, and send it straight to Bolt to build. No more screenshots, Slack threads, or Loom videos someone has to turn into fixes. Try it now → bolt.new

Today we’re launching @frontier1_ai . Frontier/1 is the security-first AI cloud for open-weight and proprietary models. Built for companies to secure their IP and intelligence, on dedicated NVIDIA hardware, in the country of their choice. AI is moving beyond the chat. It is moving into science, biotech, robotics, healthcare, defence and critical national infrastructure. In every one of those industries, the model is not the most valuable part. The work is. The promise I care most about: your models, your weights and your results stay yours.  We secure all of it, the model included. Every model is scanned, signed and verified before it runs. Every request is inspected on the way in and on the way out. Were backed by both Silicon Valley and British investors, including @SethGB at @SusaVentures, @dropalltables at SNR Ventures, @stopman Former VP of Engineering at @Yelp , and Imran Lone Co-Founder and CTO at @Augur. Secure AI that you control. That's the Frontier. frontierone.ai

What BitTorrent did for files, we want to do for AI inference. Antseed lets anyone buy and sell access to AI models, on their own terms. The Antseed Foundation has raised $2.4M in a token round led by Spark Capital to help make that happen.

Introducing Incredible The personal AI assistant that learns by watching you do your work. Hold a key, say the task in your own words, and Incredible clicks and types in the apps and browser you already use. Talk, Don't write prompts. Download today ↓

Today we're repositioning Zernio. Agents won't just build the product. They'll run how it reaches customers. That's not a theory but it's already happening. We started with social integrations. Now it's ads, WhatsApp, messaging, and calls. Same API. So we're calling it what it is: marketing infrastructure for products and agents.

Today we're repositioning Zernio. Agents won't just build the product. They'll run how it reaches customers. That's not a theory but it's already happening. We started with social integrations. Now it's ads, WhatsApp, messaging, and calls. Same API. So we're calling it what it is: marketing infrastructure for products and agents.

DEJA DE PAGAR $3.000 POR UNA LANDING PAGE. CON UN PROMPT LO TIENEN EN SEGUNDOS Agencias cobrando miles de dólares por páginas que un modelo de lenguaje puede generar en menos de un minuto. Sin código. Sin diseñador. → Copias el prompt con la estructura de tu producto → Lo pegas en Claude, ChatGPT o el modelo que uses → Te devuelve HTML + CSS completo, listo para publicar → Secciones, copy, CTA, diseño responsivo todo generado → Lo ajustas con más prompts si algo no te convence Lo que antes costaba semanas de ida y vuelta con un diseñador, ahora es una conversación de 5 minutos. El prompt os lo dejo en el primer link

CURSO COMPLETO: BOT DE TRADING CON CLAUDE FABLE 5 EN 31 MINUTOS Una trader china lo montó desde cero, paso a paso. Y lo compartió totalmente gratis. Subtitulado en inglés y español. 🔖 Guárdalo, ya me lo agradecerás

ENCONTRÉ UN SITIO CON MILES DE SKILLS Y PLUGINS GRATUITOS PARA CLAUDE Y ES UNA MINA DE ORO La mayoría de la gente usa Claude como un chatbot. Los que saben lo conectan con skills especializadas que lo convierten en un agente con superpoderes para su área. → Skills de ventas y marketing listas para usar → Plugins de contenido y programación → Automatización, trading y mucho más → Todo gratuito, todo compatible con Claude Code → Miles de opciones, instalación en segundos La diferencia entre usar Claude y usar Claude bien es exactamente esto. os dejo el enlace en el primer comentario

ENCONTRÉ UN SITIO CON MILES DE SKILLS Y PLUGINS GRATUITOS PARA CLAUDE Y ES UNA MINA DE ORO La mayoría de la gente usa Claude como un chatbot. Los que saben lo conectan con skills especializadas que lo convierten en un agente con superpoderes para su área. → Skills de ventas y marketing listas para usar → Plugins de contenido y programación → Automatización, trading y mucho más → Todo gratuito, todo compatible con Claude Code → Miles de opciones, instalación en segundos La diferencia entre usar Claude y usar Claude bien es exactamente esto. os dejo el enlace en el primer comentario

Introducing Griffin, the first model to pass the video Turing test. 48% of people who talked to it live thought it was a real human. Previous systems have had a pass rate <3%. It is #1 on NVIDIA's benchmark for full-duplex AI video. It’s the first Human Interaction Model (HIM).

BREAKING: Today, we witnessed the future of marketing. Introducing Citation Outreach A profitable company can add +$3M/month by ranking in ChatGPT and Claude. 12 months ago nobody believed AI search could drive this much revenue. This is absolutely insane.

After 9 years. 16K+ family homes. 500M sqft inside real homes covered, we know home robots are being built in wrong order. So we built Matic the way nature grows a child. Finally, sharing our vision: 1.⁠ ⁠Why robots get stuck at the demo 2.⁠ ⁠Why labs can't ship robots 3.⁠ ⁠Why we started with eyes, not hands 4.⁠ ⁠The 99.999% rule in robotics 5.⁠ ⁠Where Matic is going next 1. Why most robots get stuck at demos Robot demos look brilliant in a room arranged around its limitations: familiar lighting, predictable furniture, nothing troublesome on the floor. A family’s home makes no such accommodations. There are cables, toys, shifting rugs and, occasionally, dog poop. Yes, humanoids will need to avoid that too. Repeating a task under familiar conditions of uncluttered floors is not the same as handling an unfamiliar home with all its chaos. 2. Why labs can't ship robots SLAM (Simultaneous Localization and Mapping) is how a robot maps its surroundings and locates itself within them. Ask most academics and they'll tell you it's a solved problem. But real homes are the most chaotic spaces that exist. There are glass doors that look like open doorways, mirrors, stairs, rugs, charging cables, and Legos placed all around. So ask yourself: if indoor mapping and navigation is "solved," where are the robots? Why aren't airports, hotels and grocery stores full of them? Calling it “solved” misses the question families actually care about: can I leave this thing alone and trust it? 3. Why we started with eyes, not hands Nature doesn't give birth to a fully working human. We took our cue from how nature develops humans: capabilities built on one another. Children learn to see before they learn to grab, and to grab before they learn to plan and handle the unexpected. Perception comes first. Manipulation follows. More complex responsibilities come after that. At every stage, the robot must earn the next job by doing its current one well enough. Before asking a robot to pick up a sock, we wanted it to understand where it was, where the sock was, and how to reach it. Most of the industry started at the top, with humanoids. We started at the bottom, with a robot whose job is to see and move through a home precisely with 1cm accuracy in any lighting condition. Floor cleaning gave that foundation an immediately useful job. It forced us to confront navigation, clutter, privacy and everyday reliability before reaching for more complex chores. The floor cleaner isn’t a detour from our larger ambition. It is how we’re building toward it. 4. The 99.999% rule in robotics At 90%, one in ten decisions is wrong, and a robot makes thousands in a single clean. That's the robot that bumps, gets lost, and falls down the stairs. Every extra nine is a new mountain. The failures get rarer, harder to find, and exponentially harder to fix. They barely even happen until they happen in your home. Matic's visual SLAM runs at 99.999% in 16K+ homes. We’re the ONLY unsupervised home robot at scale with pure vision-only full autonomy. If you ask us, the gap between 80% and 99.999% is where our 9 years of engineering went. We close that gap inside real homes. When Matic handles something imperfectly, it saves a short clip and keeps it on the device. It only leaves if the family chooses to share it. If they do, it gets labeled, fed back into the model, and every Matic gets smarter, including theirs. Families control what leaves their homes. We do the work of making the product better. Better robots earn trust > trust brings more homes > and more homes teach the robot more. 5. Where Matic is going next Phase one was perception and it's nearly done. Matic has covered 500 million square feet, 400K miles in thousands of real lived-in homes. Now phase two is going to be about manipulation. And our idea is to build a robot that doesn't just move through your home, but acts in it to eliminate even more chores. Each step must be useful today, not justified by something we promise tomorrow. The evolution of Matic is the revolution. The goal isn’t to put the most impressive humanoid in your living room. It’s giving your family time and energy back through robots that earn your trust, protect your privacy, and help without becoming another responsibility. More time for each other. Less work getting in the way. That’s Matic. Get yours today at maticrobots.com