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Last week, @PublicAI launched $PUBLIC on major exchanges to power an open AI data network. PublicAI lets anyone contribute, verify, and curate training data, turning high-quality datasets into onchain public goods instead of private assets. PTR.NEAR brings the intel:

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🚀 Discover PublicAI Product Ecosystem – Your Gateway to contributes data to train AI and share revenues! 🚀 Unleash the power of PublicAI's Data Hunter Chrome Extension and transform your social media browsing into a treasure trove of valuable data. 📊 Upload your ChatGPT conversations with a simple click and earn rewards for your valuable contributions. 🔍 Use Data Hub to harness your intuition and refine data through community consensus. 🤖 Harness community-approved data to train AI models and craft your own AI Agent. Embark on the AI journey with PublicAI and redefine the future of AI interaction! 🌐🤖 #PublicAI
0:57

🚀 Discover PublicAI Product Ecosystem – Your Gateway to contributes data to train AI and share revenues! 🚀 Unleash the power of PublicAI's Data Hunter Chrome Extension and transform your social media browsing into a treasure trove of valuable data. 📊 Upload your ChatGPT conversations with a simple click and earn rewards for your valuable contributions. 🔍 Use Data Hub to harness your intuition and refine data through community consensus. 🤖 Harness community-approved data to train AI models and craft your own AI Agent. Embark on the AI journey with PublicAI and redefine the future of AI interaction! 🌐🤖 #PublicAI

PublicAI

19,805 görüntüleme • 2 yıl önce

🧠Our mission is to unlock hidden value of research data: 🧑‍🎓 by bringing disparate datasets together 🧑‍🎓by building ecosystems with high quality data for #AI 🧑‍🎓by rewarding scientists who contribute to an open knowledge #desci Graph on PrivateAI platform. Product deep dive ⤵️
4:49

🧠Our mission is to unlock hidden value of research data: 🧑‍🎓 by bringing disparate datasets together 🧑‍🎓by building ecosystems with high quality data for #AI 🧑‍🎓by rewarding scientists who contribute to an open knowledge #desci Graph on PrivateAI platform. Product deep dive ⤵️

PrivateAI

152,569 görüntüleme • 2 yıl önce

NEAR AI Ecosystem - “What Did You Ship This Week?” Ep. 9 A week of steady momentum across the NEAR AI stack. From Open Agent Alliance expansion and new agent standards to browser-native private data operators and OAuth-powered crossposting infrastructure, builders continue pushing open-source AI forward. Timestamps & Highlights: 00:00 – Intro by Cameron.near🇺🇸 from NEAR AI 01:36 – AVB from Open Agent Alliance (OAA) shares updates on the OAA. After its ETHDenver launch, OAA is ramping up with a renewed website, active working groups around agent discovery, secure communication, and decentralized payments. Their mission: build a truly open, interoperable agent ecosystem across Web3 and beyond. 09:18 – play_tingz unveils their AI-powered gaming creation platform. Using simple text prompts, users can instantly generate 3D games without coding. 18:44 – shudong from MIZU demos MIZU Agent, a browser-native AI operator that lives in your existing browser environment. It accesses private data securely without re-logins, supporting agent-native interactions like navigating social media and automating tasks locally. 28:53 – 𝕵𝖔𝖗𝖉𝖆𝖓✨🐾ヤᵇᵃ ͥ ꜝ9d from PublicAI introduces new features including live quizzes for contributor skill validation, Hot Wallet integration for seamless Web3 reward claims, and Discord Connect to strengthen expert communities. PublicAI continues expanding its decentralized data sourcing platform. 40:40 – elliot braem from open crosspost shows CrossPost, an OAuth-integrated platform letting NEAR accounts securely control social media posting. Users can sign actions with their wallets via function call access keys, enabling bots and agents to crosspost content without needing direct account access. 52:50 – Matt Lockyer from Proximity Labs announces the Bankr x Shade Agent hackathon. Developers are invited to extend BankerBot's functionality with new Shade Agents that leverage NEAR Chain Signatures for decentralized agent-to-agent transactions. Submissions open through May 3rd. 1:01:37 – Wrap-up by Cameron.near🇺🇸 with updates on upcoming NEAR AI releases, including auditor agents for discovery and security + private inference compute networks. The future is NEAR – the blockchain for AI. Catch the full replay:
1:03:23

NEAR AI Ecosystem - “What Did You Ship This Week?” Ep. 9 A week of steady momentum across the NEAR AI stack. From Open Agent Alliance expansion and new agent standards to browser-native private data operators and OAuth-powered crossposting infrastructure, builders continue pushing open-source AI forward. Timestamps & Highlights: 00:00 – Intro by Cameron.near🇺🇸 from NEAR AI 01:36 – AVB from Open Agent Alliance (OAA) shares updates on the OAA. After its ETHDenver launch, OAA is ramping up with a renewed website, active working groups around agent discovery, secure communication, and decentralized payments. Their mission: build a truly open, interoperable agent ecosystem across Web3 and beyond. 09:18 – play_tingz unveils their AI-powered gaming creation platform. Using simple text prompts, users can instantly generate 3D games without coding. 18:44 – shudong from MIZU demos MIZU Agent, a browser-native AI operator that lives in your existing browser environment. It accesses private data securely without re-logins, supporting agent-native interactions like navigating social media and automating tasks locally. 28:53 – 𝕵𝖔𝖗𝖉𝖆𝖓✨🐾ヤᵇᵃ ͥ ꜝ9d from PublicAI introduces new features including live quizzes for contributor skill validation, Hot Wallet integration for seamless Web3 reward claims, and Discord Connect to strengthen expert communities. PublicAI continues expanding its decentralized data sourcing platform. 40:40 – elliot braem from open crosspost shows CrossPost, an OAuth-integrated platform letting NEAR accounts securely control social media posting. Users can sign actions with their wallets via function call access keys, enabling bots and agents to crosspost content without needing direct account access. 52:50 – Matt Lockyer from Proximity Labs announces the Bankr x Shade Agent hackathon. Developers are invited to extend BankerBot's functionality with new Shade Agents that leverage NEAR Chain Signatures for decentralized agent-to-agent transactions. Submissions open through May 3rd. 1:01:37 – Wrap-up by Cameron.near🇺🇸 with updates on upcoming NEAR AI releases, including auditor agents for discovery and security + private inference compute networks. The future is NEAR – the blockchain for AI. Catch the full replay:

NEARWEEK

30,822 görüntüleme • 1 yıl önce

Introducing: Advanced Data Assets™ By LayerAI 🧬 Data is used to power Big Data and AI. The increasing demand for high quality data to improve AI models will lead to new companies creating value in the global data market. The problem: current data collection methods make data fall short of its true potential. Data is limited. Building a decentralized solution where users choose to productize and earn from their data opens untapped sources of income. 🌐 Creating Advanced Data Assets™ There exists a market opportunity to create a digital blockchain-based global data marketplace. Data collected using our nodes, our native network apps, settled on LayerAI. The Advanced Data. Meet the Ecosystem that empowers users to participate in the Data Economy.
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Introducing: Advanced Data Assets™ By LayerAI 🧬 Data is used to power Big Data and AI. The increasing demand for high quality data to improve AI models will lead to new companies creating value in the global data market. The problem: current data collection methods make data fall short of its true potential. Data is limited. Building a decentralized solution where users choose to productize and earn from their data opens untapped sources of income. 🌐 Creating Advanced Data Assets™ There exists a market opportunity to create a digital blockchain-based global data marketplace. Data collected using our nodes, our native network apps, settled on LayerAI. The Advanced Data. Meet the Ecosystem that empowers users to participate in the Data Economy.

LayerAI | AI2Earn

27,136 görüntüleme • 2 yıl önce

NEAR AI Ecosystem – “What Did You Ship This Week?” Ep. 7 A big week across the NEAR AI ecosystem with updates on personalized data agents, TypeScript tooling, crowdsourced AI data, and non-custodial flows for token coordination + much more. Timestamps & Highlights: 00:00 – Intro by Cameron.near🇺🇸 from NEAR AI 01:00 – 𝕵𝖔𝖗𝖉𝖆𝖓✨🐾ヤᵇᵃ ͥ ꜝ9d from PublicAI explains how their platform lets users earn stablecoins and points by uploading and verifying native language audio clips. Data builders can now claim earnings directly to a NEAR Protocol wallet. Public beta is live. 09:35 – Matt Hamilton from ASIMOV Protocol demos their CLI tools for uploading structured datasets to NEAR, plus new knowledge graph visualizations and early experiments transcribing voice into semantic graphs. 15:55 – @tahpot_au from Verida 💜 shows how developers can access private user data for AI agents using the Verida Vault. Users retain full control over their data, with API keys gated by permission. 25:25 – Zahidul Islam from Jutsu | Work Smarter with AI Agents drops updates on the NEAR AI TypeScript SDK. One-command agent deployment, fully local dev support, and matching features with the Python SDK. Also demoed new AI-generated video tooling with Postt. 34:20 – Matt Lockyer from Proximity Labs shares the launch of their Base naming agent Basednames. Users post on X to mint names, pay with Bankr, and finalize with verified chain signatures powered by NEAR. All non-custodial. All live on Base. 50:35 – Charles previews Divvy Agent. Users can set portfolio growth and swap thresholds with natural language. Latest update adds persistent memory, improved LLM matching, and MPC integration for safe, automated execution. 59:36 – Cameron.near🇺🇸 closes out with updates from the NEAR AI core team. Hiring in progress, governance agents coming soon, and progress on privacy tooling and agent infra powering the NEAR AI Hub. The future is NEAR - the blockchain for AI. Catch the full replay:
1:03:20

NEAR AI Ecosystem – “What Did You Ship This Week?” Ep. 7 A big week across the NEAR AI ecosystem with updates on personalized data agents, TypeScript tooling, crowdsourced AI data, and non-custodial flows for token coordination + much more. Timestamps & Highlights: 00:00 – Intro by Cameron.near🇺🇸 from NEAR AI 01:00 – 𝕵𝖔𝖗𝖉𝖆𝖓✨🐾ヤᵇᵃ ͥ ꜝ9d from PublicAI explains how their platform lets users earn stablecoins and points by uploading and verifying native language audio clips. Data builders can now claim earnings directly to a NEAR Protocol wallet. Public beta is live. 09:35 – Matt Hamilton from ASIMOV Protocol demos their CLI tools for uploading structured datasets to NEAR, plus new knowledge graph visualizations and early experiments transcribing voice into semantic graphs. 15:55 – @tahpot_au from Verida 💜 shows how developers can access private user data for AI agents using the Verida Vault. Users retain full control over their data, with API keys gated by permission. 25:25 – Zahidul Islam from Jutsu | Work Smarter with AI Agents drops updates on the NEAR AI TypeScript SDK. One-command agent deployment, fully local dev support, and matching features with the Python SDK. Also demoed new AI-generated video tooling with Postt. 34:20 – Matt Lockyer from Proximity Labs shares the launch of their Base naming agent Basednames. Users post on X to mint names, pay with Bankr, and finalize with verified chain signatures powered by NEAR. All non-custodial. All live on Base. 50:35 – Charles previews Divvy Agent. Users can set portfolio growth and swap thresholds with natural language. Latest update adds persistent memory, improved LLM matching, and MPC integration for safe, automated execution. 59:36 – Cameron.near🇺🇸 closes out with updates from the NEAR AI core team. Hiring in progress, governance agents coming soon, and progress on privacy tooling and agent infra powering the NEAR AI Hub. The future is NEAR - the blockchain for AI. Catch the full replay:

NEARWEEK

35,143 görüntüleme • 1 yıl önce

Introducing Trace. Trace is our flagship, public audit and search platform where every asset permanently registered on DATA Network can be accessed. AI Labs can search every human contributed photo or voice sample and drill into any individual record to see the full audit trail. Trace is where labs and regulators can filter by dataset, app, data type, modality, and time to verify data provenance so AI models can be trained with confidence.
1:31

Introducing Trace. Trace is our flagship, public audit and search platform where every asset permanently registered on DATA Network can be accessed. AI Labs can search every human contributed photo or voice sample and drill into any individual record to see the full audit trail. Trace is where labs and regulators can filter by dataset, app, data type, modality, and time to verify data provenance so AI models can be trained with confidence.

The DATA Foundation

72,735 görüntüleme • 1 ay önce

What if your personal data became an asset you actually owned? In this May 2026 AMA, Matrix AI Network explores one of the most important questions facing AI, Web3, and the future digital economy: Who owns the data that powers artificial intelligence? As AI models continue to improve, the next major bottleneck is no longer computing power—it is access to high-quality, verified human data. The discussion covers how personal biodata can become a valuable digital asset, how data quality is measured, and why future AI companies may depend directly on users as data providers. Topics include: ✅ Biodata as a new asset class ✅ AI-grade data quality scoring ✅ Wearable devices for raw data ✅ Data ownership and monetization models ✅ Preventing fake data and device spoofing ✅ Real-world applications in healthcare, sports science and mental wellness ✅ Hypnus and the future biodata ecosystem ✅ Project direction The future may not belong to companies that own data. It belongs to the people who create it. Watch now 👇 #AI #Web3 #DataOwnership
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What if your personal data became an asset you actually owned? In this May 2026 AMA, Matrix AI Network explores one of the most important questions facing AI, Web3, and the future digital economy: Who owns the data that powers artificial intelligence? As AI models continue to improve, the next major bottleneck is no longer computing power—it is access to high-quality, verified human data. The discussion covers how personal biodata can become a valuable digital asset, how data quality is measured, and why future AI companies may depend directly on users as data providers. Topics include: ✅ Biodata as a new asset class ✅ AI-grade data quality scoring ✅ Wearable devices for raw data ✅ Data ownership and monetization models ✅ Preventing fake data and device spoofing ✅ Real-world applications in healthcare, sports science and mental wellness ✅ Hypnus and the future biodata ecosystem ✅ Project direction The future may not belong to companies that own data. It belongs to the people who create it. Watch now 👇 #AI #Web3 #DataOwnership

Matrix AI Network

60,855 görüntüleme • 2 ay önce

Today we're launching Hebbian Robotics (YC S26) Hebbian Robotics (YC S26) . We build APIs for evaluating data quality, without training a robotics model. Data vendors use our API to search and analyze Physical AI data at scale, getting on-demand quality signals and metrics without managing infrastructure. High-quality data is the bottleneck to the next frontier of intelligence in robotics. Buyers want data they can trust. Data providers are focused on operational excellence. They don't have the bandwidth to understand the quality of their data at scale. We're fixing this. Vendors use our APIs to understand the impact of their decisions on their data quality: - Buyers demanding per-collector hour limits? Prove compliance while we stay ahead of the workarounds. - Changed your collection SOPs? Monitor for quality drift and regression. - Suspect duplicate samples? Verify with a single API call. Before Hebbian, I trained AI models for industrial cleaning robots, and kingston kuan spent years building large-scale infrastructure at Jane Street.
2:17

Today we're launching Hebbian Robotics (YC S26) Hebbian Robotics (YC S26) . We build APIs for evaluating data quality, without training a robotics model. Data vendors use our API to search and analyze Physical AI data at scale, getting on-demand quality signals and metrics without managing infrastructure. High-quality data is the bottleneck to the next frontier of intelligence in robotics. Buyers want data they can trust. Data providers are focused on operational excellence. They don't have the bandwidth to understand the quality of their data at scale. We're fixing this. Vendors use our APIs to understand the impact of their decisions on their data quality: - Buyers demanding per-collector hour limits? Prove compliance while we stay ahead of the workarounds. - Changed your collection SOPs? Monitor for quality drift and regression. - Suspect duplicate samples? Verify with a single API call. Before Hebbian, I trained AI models for industrial cleaning robots, and kingston kuan spent years building large-scale infrastructure at Jane Street.

Brandon Ong

162,683 görüntüleme • 3 gün önce

Could You Guess What Comes After the OptimAI Edge Node? We’re excited to share another glimpse into the future, Community-Powered Data Validation, a unique feature within the OptimAI Core Node for desktop. What is Data Validation? It’s the essential process of ensuring AI systems learn from accurate, unbiased, and high-quality data. Through human intelligence, users verify, correct, and refine information - making it reliable for training advanced AI agents. This process is enabled by the OptimAI DeHIN (Decentralized Human Intelligence Network), which brings collective intelligence into the heart of AI development. Why is it important? Because truly responsible and powerful AI starts with trusted data. Community validation improves fairness, transparency, and performance - ensuring AI benefits everyone. And as a participant, you’re not just supporting better AI; you’re earning rewards and shaping its future. Your desktop is about to become much more than a device. It’s a gateway to reinforcing the quality of data that powers Agentic AI. Validate data. Strengthen AI. Get rewarded. The future of AI is collective — and it needs you. #BUIDL with us! 👉OptimAI Lite Node: 👉OptimAI Edge Node:
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Could You Guess What Comes After the OptimAI Edge Node? We’re excited to share another glimpse into the future, Community-Powered Data Validation, a unique feature within the OptimAI Core Node for desktop. What is Data Validation? It’s the essential process of ensuring AI systems learn from accurate, unbiased, and high-quality data. Through human intelligence, users verify, correct, and refine information - making it reliable for training advanced AI agents. This process is enabled by the OptimAI DeHIN (Decentralized Human Intelligence Network), which brings collective intelligence into the heart of AI development. Why is it important? Because truly responsible and powerful AI starts with trusted data. Community validation improves fairness, transparency, and performance - ensuring AI benefits everyone. And as a participant, you’re not just supporting better AI; you’re earning rewards and shaping its future. Your desktop is about to become much more than a device. It’s a gateway to reinforcing the quality of data that powers Agentic AI. Validate data. Strengthen AI. Get rewarded. The future of AI is collective — and it needs you. #BUIDL with us! 👉OptimAI Lite Node: 👉OptimAI Edge Node:

OptimAI Network

60,728 görüntüleme • 1 yıl önce

Scale alone is not enough for AI data. Quality and complexity are equally critical. Excited to support all of these for LLM developers with Snorkel AI Data-as-a-Service, and to share our new leaderboard! — Our decade-plus of research and work in AI data has a simple point: scale alone is not enough. AI success is all about the quality, complexity, and distribution of data—in addition to volume. We’re excited to be powering leading LLM developers with Snorkel AI Expert Data-as-a-Service, our white glove service for custom, expert-level AI datasets—and to now preview some of what we’re building via our new Expert Data Leaderboard (🔗 in 🧵) + upcoming OSS dataset releases! Snorkel Expert Data-as-a-Service is built to meet the rapidly evolving data needs of the agentic AI world—where success is built on the quality, complexity, and distribution of datasets, in addition to size and scale. This kind of high-quality, frontier AI data can only come from a union of technology and human expertise. With Snorkel Expert Data-as-a-Service, we’re powering frontier LLM developers across agentic, expert knowledge, reasoning, coding, multi-modal, and other task types via the combination of these two key components: - (1) The Snorkel Expert Network: A global team of subject matter experts focused wholly on specialized knowledge–spanning thousands of topics in STEM/academic, vertical/professional, and consumer/lifestyle domains. - (2) Snorkel AI Data Development Platform: Our unique programmatic data curation and quality control platform, accelerating and improving expert authoring and review through principled techniques developed over the last decade of R&D. Now: we’re incredibly excited to showcase some of the power of Snorkel Expert Data-as-a-Service via the new Snorkel Leaderboard—putting frontier models to the test in complex, agentic, and reasoning settings inspired by real industry scenarios (not esoteric puzzles)! We’ll be releasing new leaderboards and accompanying expert-verified open source datasets (coming soon!) regularly. To start, we’re sharing three initial ones in preview: - SnorkelFinance: Q&A over financial documents requiring agentic tool-calling and reasoning - SnorkelUnderwrite: Agentic insurance tasks requiring industry-specific reasoning and tool use - SnorkelSequences: Mathematical tasks requiring compositional multi-step reasoning
1:11

Scale alone is not enough for AI data. Quality and complexity are equally critical. Excited to support all of these for LLM developers with Snorkel AI Data-as-a-Service, and to share our new leaderboard! — Our decade-plus of research and work in AI data has a simple point: scale alone is not enough. AI success is all about the quality, complexity, and distribution of data—in addition to volume. We’re excited to be powering leading LLM developers with Snorkel AI Expert Data-as-a-Service, our white glove service for custom, expert-level AI datasets—and to now preview some of what we’re building via our new Expert Data Leaderboard (🔗 in 🧵) + upcoming OSS dataset releases! Snorkel Expert Data-as-a-Service is built to meet the rapidly evolving data needs of the agentic AI world—where success is built on the quality, complexity, and distribution of datasets, in addition to size and scale. This kind of high-quality, frontier AI data can only come from a union of technology and human expertise. With Snorkel Expert Data-as-a-Service, we’re powering frontier LLM developers across agentic, expert knowledge, reasoning, coding, multi-modal, and other task types via the combination of these two key components: - (1) The Snorkel Expert Network: A global team of subject matter experts focused wholly on specialized knowledge–spanning thousands of topics in STEM/academic, vertical/professional, and consumer/lifestyle domains. - (2) Snorkel AI Data Development Platform: Our unique programmatic data curation and quality control platform, accelerating and improving expert authoring and review through principled techniques developed over the last decade of R&D. Now: we’re incredibly excited to showcase some of the power of Snorkel Expert Data-as-a-Service via the new Snorkel Leaderboard—putting frontier models to the test in complex, agentic, and reasoning settings inspired by real industry scenarios (not esoteric puzzles)! We’ll be releasing new leaderboards and accompanying expert-verified open source datasets (coming soon!) regularly. To start, we’re sharing three initial ones in preview: - SnorkelFinance: Q&A over financial documents requiring agentic tool-calling and reasoning - SnorkelUnderwrite: Agentic insurance tasks requiring industry-specific reasoning and tool use - SnorkelSequences: Mathematical tasks requiring compositional multi-step reasoning

Alex Ratner

495,851 görüntüleme • 1 yıl önce

Partner Spotlight: iExec 🛡️🧠 Aethir and iExec RLC, an esteemed partner and a member of the AI Unbundled Alliance, shook hands to unlock Confidential AI at scale 📈💚 iExec brings the TEEs and Aethir brings the NVIDIA H100s 👉 to power secure, high-performance AI workloads, without compromising on decentralization or data privacy. 🧵👇🏻
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Partner Spotlight: iExec 🛡️🧠 Aethir and iExec RLC, an esteemed partner and a member of the AI Unbundled Alliance, shook hands to unlock Confidential AI at scale 📈💚 iExec brings the TEEs and Aethir brings the NVIDIA H100s 👉 to power secure, high-performance AI workloads, without compromising on decentralization or data privacy. 🧵👇🏻

Aethir Ecosystem

26,411 görüntüleme • 1 yıl önce

“You earn a dollar a day for uploading voice in your native language.” PublicAI kicked off Mother Tongue Season 3 with the launch of its DataBabies 🪐💜 NFT collection. Human audio training and chain-abstracted minting via HOT Protocol 🔥's HOT Craft! We'll let Jordan ✨🐾 乔丹 ⁹ᵈ explain:
5:35

“You earn a dollar a day for uploading voice in your native language.” PublicAI kicked off Mother Tongue Season 3 with the launch of its DataBabies 🪐💜 NFT collection. Human audio training and chain-abstracted minting via HOT Protocol 🔥's HOT Craft! We'll let Jordan ✨🐾 乔丹 ⁹ᵈ explain:

NEARWEEK

71,553 görüntüleme • 1 yıl önce

New Alpha Opportunity: Ta-Da is coming Tues 4th March! 🤖 AI needs two things to thrive: powerful algorithms & high-quality data. But today’s open-sourced datasets have already become overused, are often unreliable, and accordingly, depleted of value. For AI to keep evolving, it needs fresh, verified, real-world data, and that’s where Ta-da comes in ✨ 🧑‍🧑‍🧒‍🧒 Crowdsourced, human-generated AI training data with a stringent verification process to ensure accuracy 📀 100k+ users contributing terabytes of data and earning rewards for their contributions 💰 💪 The more people who contribute, the more powerful Ta-Da becomes Ta-Da is launching onto Solana with our partners at Keep Building ⚡️ But first, there's the SwissBorg Alpha Sale: 🗓️ Diamond Vault (Camp 200k and above): 4th March, opens 14:00 CET 🗓️ Public Vault: opens 14:30 CET Spaces are limited, and the top $BORG holders get the first opportunity! Full details 👉
0:25

New Alpha Opportunity: Ta-Da is coming Tues 4th March! 🤖 AI needs two things to thrive: powerful algorithms & high-quality data. But today’s open-sourced datasets have already become overused, are often unreliable, and accordingly, depleted of value. For AI to keep evolving, it needs fresh, verified, real-world data, and that’s where Ta-da comes in ✨ 🧑‍🧑‍🧒‍🧒 Crowdsourced, human-generated AI training data with a stringent verification process to ensure accuracy 📀 100k+ users contributing terabytes of data and earning rewards for their contributions 💰 💪 The more people who contribute, the more powerful Ta-Da becomes Ta-Da is launching onto Solana with our partners at Keep Building ⚡️ But first, there's the SwissBorg Alpha Sale: 🗓️ Diamond Vault (Camp 200k and above): 4th March, opens 14:00 CET 🗓️ Public Vault: opens 14:30 CET Spaces are limited, and the top $BORG holders get the first opportunity! Full details 👉

SwissBorg

36,172 görüntüleme • 1 yıl önce

Everyone’s racing to build AI. But most teams can’t even get started because infrastructure costs too much. io.net is solving that problem by connecting over 300K GPUs, 80K CPUs, and thousands of data centers worldwide into a single network anyone can access. By integrating with Irys, io.net would be able to offer developers a place to store training datasets, verifiable inference outputs, and entire AI models. With Irys, data is instantly accessible, fully transparent, and far more affordable than traditional or web3 storage. Spin up compute in seconds. Store data permanently. Build transparent, high-performance AI systems people actually trust. This is how we scale AI. Together.
0:36

Everyone’s racing to build AI. But most teams can’t even get started because infrastructure costs too much. io.net is solving that problem by connecting over 300K GPUs, 80K CPUs, and thousands of data centers worldwide into a single network anyone can access. By integrating with Irys, io.net would be able to offer developers a place to store training datasets, verifiable inference outputs, and entire AI models. With Irys, data is instantly accessible, fully transparent, and far more affordable than traditional or web3 storage. Spin up compute in seconds. Store data permanently. Build transparent, high-performance AI systems people actually trust. This is how we scale AI. Together.

Irys (✧ᴗ✧)

25,411 görüntüleme • 1 yıl önce

If anyone is wondering how a politician has made tens of millions of dollars on a $174K salary: Check out Quiver. It lets you track politicians’: - Stock trading - Portfolio - Net Worth - Corporate Donors - Proposed Legislation Along with data on hedge fund holdings, company financials, insider trading, and more. Open to the public with no ads. I try to post interesting insights from the data, but I think it’s important that the raw data is available to anyone who wants to do their own research.
0:27

If anyone is wondering how a politician has made tens of millions of dollars on a $174K salary: Check out Quiver. It lets you track politicians’: - Stock trading - Portfolio - Net Worth - Corporate Donors - Proposed Legislation Along with data on hedge fund holdings, company financials, insider trading, and more. Open to the public with no ads. I try to post interesting insights from the data, but I think it’s important that the raw data is available to anyone who wants to do their own research.

Quiver Quantitative

30,383 görüntüleme • 1 yıl önce

A 10-minute walk. That's all it takes to transform a real-world neighborhood into a machine-readable digital twin. Captured with an Insta360 X5 and reconstructed by Over the Reality, this environment is no longer just a place on a map. It's spatial data that can power Visual AI, Robotics localization, VPS, XR experiences, and next-generation world models. Today, the OVER community has already created more than 270,000 machine-readable locations like this, forming one of the world's largest 3D datasets for Physical AI, an increasingly valuable asset as demand for high quality real-world data continues to grow.
1:30

A 10-minute walk. That's all it takes to transform a real-world neighborhood into a machine-readable digital twin. Captured with an Insta360 X5 and reconstructed by Over the Reality, this environment is no longer just a place on a map. It's spatial data that can power Visual AI, Robotics localization, VPS, XR experiences, and next-generation world models. Today, the OVER community has already created more than 270,000 machine-readable locations like this, forming one of the world's largest 3D datasets for Physical AI, an increasingly valuable asset as demand for high quality real-world data continues to grow.

Over the Reality 🌐

16,642 görüntüleme • 28 gün önce

Texas is planning on running “4,000 linear miles of what amounts to extension cords on steroids throughout Texas” The reasoning is, there are areas that need more power for things like Data Centers. But instead of building the plants where the power is needed, they plan on running massive extension cords The project is part of a major grid upgrade managed by the Public Utility Commission of Texas The purpose is for oil and gas operations and data centers
0:56

Texas is planning on running “4,000 linear miles of what amounts to extension cords on steroids throughout Texas” The reasoning is, there are areas that need more power for things like Data Centers. But instead of building the plants where the power is needed, they plan on running massive extension cords The project is part of a major grid upgrade managed by the Public Utility Commission of Texas The purpose is for oil and gas operations and data centers

Wall Street Apes

100,883 görüntüleme • 4 ay önce

How to Make AI Models More Useful? Discover the potential of AI and blockchain, and how features like RAG and TEEs can help NEAR unlock its full potential to build the world's best truly open AI. TL;DR - RAG (Retrieval-Augmented Generation) enhances AI agents by personalizing responses with relevant context. - Blockchain ensures transactions are processed transparently, efficiently, and securely. - NEAR Protocol is designed for AI, featuring a sharding architecture that supports high transaction volumes at low fees without compromising performance. It also offers privacy, user-owned data, and monetization opportunities. Study the NEAR stack, explore how to make AI models useful:
3:05

How to Make AI Models More Useful? Discover the potential of AI and blockchain, and how features like RAG and TEEs can help NEAR unlock its full potential to build the world's best truly open AI. TL;DR - RAG (Retrieval-Augmented Generation) enhances AI agents by personalizing responses with relevant context. - Blockchain ensures transactions are processed transparently, efficiently, and securely. - NEAR Protocol is designed for AI, featuring a sharding architecture that supports high transaction volumes at low fees without compromising performance. It also offers privacy, user-owned data, and monetization opportunities. Study the NEAR stack, explore how to make AI models useful:

NEARWEEK

23,509 görüntüleme • 1 yıl önce

Oracle just told every AI company on earth the same thing. Your models are worthless. Not the technology, talent or the billions spent training them. But the data they were trained on. Larry Ellison, the man who built Oracle into the backbone of global enterprise just dropped a bombshell. He said ChatGPT, Gemini, Grok, and Llama, all of them are training on the exact same data.​ The entire public internet, every Wikipedia page, Reddit thread and every news article. That means they're all converging essentially becoming the same product with different logos.​ Ellison's word for it is commodities. But here's where it gets dangerous. He says the real gold isn't public data, It's private data.​ The medical records in hospital systems, the financial data in bank vaults. The supply chain secrets of every Fortune 500 and guess where most of that data already lives. Not Google, Amazon or Microsoft but inside Oracle.​ Oracle databases hold most of the world's high value private enterprise data. So Oracle just launched something called AI Database 26ai.​ It lets the top AI models, ChatGPT, Gemini, Grok, Llama reason directly over a company's private data, without that data ever leaving the vault.​ They're using a technique called RAG, Retrieval Augmented Generation. The AI doesn't train on your data, it searches it in real time.​ Think about what that means. A bank could ask AI to analyze every loan it's ever made without exposing a single customer record. A hospital could have AI diagnose patients using its full medical history without violating HIPAA.​ A defense contractor could let AI reason across classified operations without data leaving a secure environment.​ Ellison is betting this is bigger than the training market. Bigger than the GPU boom. Bigger than the data center buildout.​ He called it the largest and fastest growing market in history.​ The numbers back the ambition. Oracle's remaining performance obligations just hit $523 billion. That's contracted revenue not yet delivered and $300 billion of it comes from OpenAI alone.​ Cloud revenue hit $8 billion in a single quarter, OCI grew 66 percent and GPU revenue surged 177 percent.​ But here's the part nobody's talking about. If private data becomes the real AI moat, then whoever controls the database controls the future of AI.​ And that's a level of power that should make everyone uncomfortable.
0:38

Oracle just told every AI company on earth the same thing. Your models are worthless. Not the technology, talent or the billions spent training them. But the data they were trained on. Larry Ellison, the man who built Oracle into the backbone of global enterprise just dropped a bombshell. He said ChatGPT, Gemini, Grok, and Llama, all of them are training on the exact same data.​ The entire public internet, every Wikipedia page, Reddit thread and every news article. That means they're all converging essentially becoming the same product with different logos.​ Ellison's word for it is commodities. But here's where it gets dangerous. He says the real gold isn't public data, It's private data.​ The medical records in hospital systems, the financial data in bank vaults. The supply chain secrets of every Fortune 500 and guess where most of that data already lives. Not Google, Amazon or Microsoft but inside Oracle.​ Oracle databases hold most of the world's high value private enterprise data. So Oracle just launched something called AI Database 26ai.​ It lets the top AI models, ChatGPT, Gemini, Grok, Llama reason directly over a company's private data, without that data ever leaving the vault.​ They're using a technique called RAG, Retrieval Augmented Generation. The AI doesn't train on your data, it searches it in real time.​ Think about what that means. A bank could ask AI to analyze every loan it's ever made without exposing a single customer record. A hospital could have AI diagnose patients using its full medical history without violating HIPAA.​ A defense contractor could let AI reason across classified operations without data leaving a secure environment.​ Ellison is betting this is bigger than the training market. Bigger than the GPU boom. Bigger than the data center buildout.​ He called it the largest and fastest growing market in history.​ The numbers back the ambition. Oracle's remaining performance obligations just hit $523 billion. That's contracted revenue not yet delivered and $300 billion of it comes from OpenAI alone.​ Cloud revenue hit $8 billion in a single quarter, OCI grew 66 percent and GPU revenue surged 177 percent.​ But here's the part nobody's talking about. If private data becomes the real AI moat, then whoever controls the database controls the future of AI.​ And that's a level of power that should make everyone uncomfortable.

StockMarket.News

1,695,895 görüntüleme • 5 ay önce