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With so many AI models out there, which ones will last? Check out this 17-second clip to see how Grass’s Live Context Retrieval (LCR) engine can give models a unique edge through access to real-time, unbiased web data.

Grass

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348,115 Aufrufe • vor 1 Jahr •via X (Twitter)

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AI companies are racing to build better models. The ones that actually win will have better access to reality. 700K+ nodes. 150+ countries. Real-time signal from the edge - not a data center. That's the Perceptron advantage. #PerceptronNTWK #NodeAndProud #AI #DecentralizedAI #ATEOV

AI companies are racing to build better models. The ones that actually win will have better access to reality. 700K+ nodes. 150+ countries. Real-time signal from the edge - not a data center. That's the Perceptron advantage. #PerceptronNTWK #NodeAndProud #AI #DecentralizedAI #ATEOV

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There are so many models that it can get confusing so today we launched an auto-router - you get the best answers from any of the top models. At the same time, we have AI experts and model enthusiasts who will enjoy access to 10 new models we just added including: ✅ GPT-4.1 ✅ o3 & o4 Mini ✅ Grok 3 ✅ Llama 4 Maverick & Scout We're also sunsetting some older models that just can't keep up anymore.

There are so many models that it can get confusing so today we launched an auto-router - you get the best answers from any of the top models. At the same time, we have AI experts and model enthusiasts who will enjoy access to 10 new models we just added including: ✅ GPT-4.1 ✅ o3 & o4 Mini ✅ Grok 3 ✅ Llama 4 Maverick & Scout We're also sunsetting some older models that just can't keep up anymore.

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A new era for Nodepay has begun. Bandwidth has been powering our real-time data retrieval infrastructure from day one. Now, that foundation has delivered something bigger: The Intelligence Engine — a living network of structured, real-time insights, powered by you. - Your predictions become real-time signals - Your insights become knowledge - Your bandwidth collects data for our AI - $NC becomes the fuel This is AI combined with collective intelligence. Why It Matters: - Users get rewarded for their insights, not just engagement - Projects gain direct access to real-time, validated community sentiment - Everyone saves time, earns more, & makes smarter decisions First access is reserved for $NC holders ⚠️ The next wave of users will be onboarded following the upcoming snapshot 📸 Soon, you’ll all be able to contribute insights, unlock smarter rewards, and tap into real-time sentiment and conviction that gives you the edge. The Intelligence Engine is live — and you’re getting paid to power it.

A new era for Nodepay has begun. Bandwidth has been powering our real-time data retrieval infrastructure from day one. Now, that foundation has delivered something bigger: The Intelligence Engine — a living network of structured, real-time insights, powered by you. - Your predictions become real-time signals - Your insights become knowledge - Your bandwidth collects data for our AI - $NC becomes the fuel This is AI combined with collective intelligence. Why It Matters: - Users get rewarded for their insights, not just engagement - Projects gain direct access to real-time, validated community sentiment - Everyone saves time, earns more, & makes smarter decisions First access is reserved for $NC holders ⚠️ The next wave of users will be onboarded following the upcoming snapshot 📸 Soon, you’ll all be able to contribute insights, unlock smarter rewards, and tap into real-time sentiment and conviction that gives you the edge. The Intelligence Engine is live — and you’re getting paid to power it.

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OpenAI's Deep Research is getting a run for its money. Deep Lake was just released, and it's a different take on an AI system that can do deep research on your own data. You can use Deep Lake to build AI search with reasoning on your private and public data. (Look at the attached videos to get an idea of how it works.) If you want to research proprietary and sensitive data, Deep Research won't help you because it's limited to public data. Deep Lake, however, will allow you to use your private data. On top of that, Deep Lake supports multi-modal retrieval from the ground up. It uses vision language models for data ingestion and retrieval so that you can connect any data (PDFs, images, videos, structured data, etc.) You can even use mixed-data queries! Deep Lake can search your data from S3, Dropbox, and GCP. It learns from your queries over time, making the results as relevant to your work as possible!

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Hey I just want to put it out there, anyone want to give me another chance? I've improved a lot since many of you last saw me, would love if you could give me another shot and check out my Twitch streams/vods Maybe you'll like what you see and will wanna join us degenerates 💙

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⚙️ Attention n8n Builders: Time to Upgrade Your Crawlers. If you are running web scraping or data retrieval workflows on n8n, it is time to flip the switch. Stop relying on fragile datacenter proxies that get blocked every five minutes. Try UpRock. As a verified n8n integration, UpRock gives your workflows access to a global network of real devices for: → Live Web Crawling → Deep Research → Semantic Video Search → Real-Time Intelligence Retrieval No more building separate stacks for crawling, research, video understanding, and web intelligence. One node. One workflow. One global swarm. Want a Cheeky Credit Boost? We want to see what you are building. If you transition an active data-gathering workflow over to the UpRock node this week, reach out directly to our dev team. Drop a message or reply below with your use case, and we will hook you up with custom API testing credits to supercharge your swarm infrastructure. Get Started on n8n: Search for Scraper - UpRock Crawler in your n8n Nodes panel or grab the package directly on npm!

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What if a network could deliver AI results closer to where data is created, instead of sending it to far‑off data centers? In collaboration with NVIDIA and Decart, we’re making that a reality by bringing GPU‑powered computing to the network edge — closer to homes and businesses — so AI applications respond in real-time. This is how we're laying the foundation for the next generation of AI‑driven services:

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Depth Any Video with Scalable Synthetic Data AI physicists and chemists continue to make strides in depth estimation from video. Check out this new paper featuring some impressive examples. See the thread for more details (unfortunately no code yet). Abstract: Video depth estimation has long been hindered by the scarcity of consistent and scalable ground truth data, leading to inconsistent and unreliable results. In this paper, we introduce Depth Any Video, a model that tackles the challenge through two key innovations. First, we develop a scalable synthetic data pipeline, capturing real-time video depth data from diverse game environments, yielding 40,000 video clips of 5-second duration, each with precise depth annotations. Second, we leverage the powerful priors of generative video diffusion models to handle real-world videos effectively, integrating advanced techniques such as rotary position encoding and flow matching to further enhance flexibility and efficiency. Unlike previous models, which are limited to fixed-length video sequences, our approach introduces a novel mixed-duration training strategy that handles videos of varying lengths and performs robustly across different frame rates 0 - even on single frames. At inference, we propose a depth interpolation method that enables our model to infer high-resolution video depth across sequences of up to 150 frames. Our model outperforms all previous generative depth models in terms of spatial accuracy and temporal consistency.

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Today, we're excited to announce a partnership with Manta Network (🔱,🔱), the Modular L2 solution that is transforming the landscape of ZK. Nesa is bringing private AI inference to the Manta ecosystem through a specialized collaboration. For the first time, developers on Manta can access Nesa's full library of AI models on-chain, and enjoy lightning fast, end-to-end private AI inference without ever leaving the Manta ecosystem. This means that dapps and protocols can now fuse with AI via smart contract on Manta. This integration is set to redefine the future of decentralized technology with AI. Stay tuned for more updates on how Nesa and Manta Network will be shaping the future of crypto together.

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Remember when we as football fans had to rely solely on paper draft guides, sports radio rumors, and gut feelings to predict draft day decisions? Excited that fans now have access to the NFL's Draft IQ powered by Amazon Web Services ( – the most sophisticated tool yet for following the NFL draft and your favorite team's strategy. Draft IQ is built on Amazon QuickSight, our cloud business intelligence service that makes it easy to analyze and visualize massive amounts of data. QuickSight processes real-time data to give fans unprecedented insight into team decision-making, updating the entire draft landscape every five minutes. You can explore team needs, draft capital, and front office tendencies through personalized team dashboards, plus get AWS-powered machine learning predictions about potential trades and picks. During draft week, fans can track picks, prospects, and Next Gen Stats in real-time. We're also introducing Amazon Q Business integration, our generative AI-powered assistant. Q Business leverages large language models to understand and respond to natural language queries, allowing fans to ask detailed questions about draft prospects, team strategies, and historical draft data. It can provide AI-generated insights based on the same historical Next Gen Stats research data that powers Draft IQ, giving fans a new way to engage with the draft experience (check out the example below). Can't wait to see what stories the data tells us as teams make their selections and excited to dig into the Giants' data myself :)

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Andy Jassy

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