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Exabyte scale infrastructure requires specific features that extend beyond the core #objectstore. That’s why we’re introducing the MinIO Enterprise Object Store. Designed for commercial customers, the #EnterpriseObjectStore includes features that span observability, key management, S3 data firewall, data catalog, caching service and a new global console. Stay with us...

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MinIO

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45,343 görüntüleme • 2 yıl önce •via X (Twitter)

EğitimHaberler & PolitikaBilim & Teknoloji#objectstore#EnterpriseObjectStore
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Benzer Videolar

One of the challenges faced by our largest clients is the inability to search and query their namespace efficiently, a critical capability for organizations managing hundreds of billions of objects. The #objectstorage world needed a simple, powerful solution to this problem. That is why we built the MinIO #EnterpriseObjectStore Catalog feature. Go deeper here:
0:30

One of the challenges faced by our largest clients is the inability to search and query their namespace efficiently, a critical capability for organizations managing hundreds of billions of objects. The #objectstorage world needed a simple, powerful solution to this problem. That is why we built the MinIO #EnterpriseObjectStore Catalog feature. Go deeper here:

MinIO

428,384 görüntüleme • 2 yıl önce

Announcement: GPU Rentals with Third-Party Storage Integration Today we introduce a new feature for our GPU rental service: one-click integration with third-party storage services. This enhancement allows users to quickly sync and backup data. Currently, we support AWS and Google storage services. Key Features: • Easy Integration: One-click connection to third-party storage. • Regular Syncing: Ensures your data is always secure. • Flexible Sync Modes: Choose between adding new data or overwriting existing data to suit your needs. A detailed operation video below is available to guide you through the process. Ready to experience the new feature? Head over to our website and try the latest feature today:
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Announcement: GPU Rentals with Third-Party Storage Integration Today we introduce a new feature for our GPU rental service: one-click integration with third-party storage services. This enhancement allows users to quickly sync and backup data. Currently, we support AWS and Google storage services. Key Features: • Easy Integration: One-click connection to third-party storage. • Regular Syncing: Ensures your data is always secure. • Flexible Sync Modes: Choose between adding new data or overwriting existing data to suit your needs. A detailed operation video below is available to guide you through the process. Ready to experience the new feature? Head over to our website and try the latest feature today:

NetMind.AI

64,645 görüntüleme • 2 yıl önce

Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.
1:21

Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.

Aaron Levie

91,863 görüntüleme • 10 ay önce

Microsoft has launched a powerful new data analysis tool! Introducing Data Formulator, a 100% open-source LLM-powered, no-code tool that transforms data in a snap and creates stunning visualizations. Key features include: 🤖 AI-powered data transformation 🖱️ Interactive drag-and-drop UI for visualizations 💬 Seamless blend of UI & natural language inputs But that’s not all: You can even create charts beyond your initial dataset. Data Formulator automatically identifies extra computation needs, generates fields for you, and outputs the final visualization. Find the GitHub repo in the next tweet! _____ Find me → Akshay 🚀 ✔️ For more insights and tutorials on AI and Machine Learning.
0:24

Microsoft has launched a powerful new data analysis tool! Introducing Data Formulator, a 100% open-source LLM-powered, no-code tool that transforms data in a snap and creates stunning visualizations. Key features include: 🤖 AI-powered data transformation 🖱️ Interactive drag-and-drop UI for visualizations 💬 Seamless blend of UI & natural language inputs But that’s not all: You can even create charts beyond your initial dataset. Data Formulator automatically identifies extra computation needs, generates fields for you, and outputs the final visualization. Find the GitHub repo in the next tweet! _____ Find me → Akshay 🚀 ✔️ For more insights and tutorials on AI and Machine Learning.

Akshay 🚀

280,449 görüntüleme • 1 yıl önce

The creative industry is being challenged right now. Demand for content is skyrocketing, budgets are shrinking, and timelines are tighter than ever. And while we all know AI is here to help, not all AI is actually helping. Most AI isn’t built for enterprise level creative work because it requires the precision and control that your average AI just can’t provide. That’s why today, we’re introducing Stability AI Solutions: A new offering designed to help enterprises scale creative production with generative AI.
2:58

The creative industry is being challenged right now. Demand for content is skyrocketing, budgets are shrinking, and timelines are tighter than ever. And while we all know AI is here to help, not all AI is actually helping. Most AI isn’t built for enterprise level creative work because it requires the precision and control that your average AI just can’t provide. That’s why today, we’re introducing Stability AI Solutions: A new offering designed to help enterprises scale creative production with generative AI.

Stability AI

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The next evolution of the OptimAI Core Node is coming, and it’s bringing one of our most powerful innovations yet: The Data Mining Agent. Become an OptimAI Node: 🔍 What is the Data Mining Agent? A fully autonomous agent running on your Core Node that: + Scans, retrieves, and indexes real-time public web data + Transforms raw information into actionable intelligence + Powers faster, smarter, adaptive Persona AI systems 💡 Why It Matters: Agentic AI is only as strong as the data it can access. Centralized APIs are slow, expensive, and limited. With the Core Node + Data Mining Agent, every contributor turns their desktop into a data supernode, accelerating AI evolution and giving our community a massive edge. ⚡ We’re not just building tools - we’re architecting the global backbone of Agentic AI, powered by you. Stay tuned for teasers, and get ready to upgrade your node. The future is decentralized. The future is agentic. And you are a key part of it. 💪 The more you contribute, the more you earn. Let’s BUIDL the future of AI together.
0:31

The next evolution of the OptimAI Core Node is coming, and it’s bringing one of our most powerful innovations yet: The Data Mining Agent. Become an OptimAI Node: 🔍 What is the Data Mining Agent? A fully autonomous agent running on your Core Node that: + Scans, retrieves, and indexes real-time public web data + Transforms raw information into actionable intelligence + Powers faster, smarter, adaptive Persona AI systems 💡 Why It Matters: Agentic AI is only as strong as the data it can access. Centralized APIs are slow, expensive, and limited. With the Core Node + Data Mining Agent, every contributor turns their desktop into a data supernode, accelerating AI evolution and giving our community a massive edge. ⚡ We’re not just building tools - we’re architecting the global backbone of Agentic AI, powered by you. Stay tuned for teasers, and get ready to upgrade your node. The future is decentralized. The future is agentic. And you are a key part of it. 💪 The more you contribute, the more you earn. Let’s BUIDL the future of AI together.

OptimAI Network

50,424 görüntüleme • 10 ay önce

The Everywhere Edition is here: If you are on Shopify, you are everywhere your customers are shopping. This Edition features some key updates to Agentic Storefronts, Catalog and UCP because we want to be clear that if you want on Shopify you are everywhere by default. Every Edition is intentionally overwhelming. It’s a celebration of the progress we’ve made each season and serves as a complete list of features for those who want to pay attention. To make it easier to parse, I broke down some of my favorite features among the 200+ and explained some of the ambition behind them.
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The Everywhere Edition is here: If you are on Shopify, you are everywhere your customers are shopping. This Edition features some key updates to Agentic Storefronts, Catalog and UCP because we want to be clear that if you want on Shopify you are everywhere by default. Every Edition is intentionally overwhelming. It’s a celebration of the progress we’ve made each season and serves as a complete list of features for those who want to pay attention. To make it easier to parse, I broke down some of my favorite features among the 200+ and explained some of the ambition behind them.

Vanessa Lee

13,833 görüntüleme • 1 ay önce

Introducing the new UNESCO 🏛️ #Education #Sciences #Culture 🇺🇳 Sites Navigator—a powerful new digital platform designed for the exploration, analysis, and monitoring of UNESCO-designated sites worldwide. This interactive tool provides verified, geospatial data on #WorldHeritage properties, #BiosphereReserves, and #GlobalGeoparks. With advanced cartographic features, users can explore site boundaries and information, measure and annotate directly on the map, import/export shapefiles, and access reliable data to support research and conservation. Funded by the Flanders, the platform is strengthening capacities for effective and sustainable heritage management globally. Discover how geospatial technology is transforming heritage conservation. Start exploring today: Flanders DFA #47WHC
1:53

Introducing the new UNESCO 🏛️ #Education #Sciences #Culture 🇺🇳 Sites Navigator—a powerful new digital platform designed for the exploration, analysis, and monitoring of UNESCO-designated sites worldwide. This interactive tool provides verified, geospatial data on #WorldHeritage properties, #BiosphereReserves, and #GlobalGeoparks. With advanced cartographic features, users can explore site boundaries and information, measure and annotate directly on the map, import/export shapefiles, and access reliable data to support research and conservation. Funded by the Flanders, the platform is strengthening capacities for effective and sustainable heritage management globally. Discover how geospatial technology is transforming heritage conservation. Start exploring today: Flanders DFA #47WHC

UNESCO 🏛️ #Education #Sciences #Culture 🇺🇳

11,590 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

🚀 Massive News for Backrush Databases: Introducing TablesDB! We just revolutionized how you work with data: ➡️ New Relational API Layer All new database features will now ship through the powerful TablesDB API. ➡️ Spreadsheet-Like UI in Console Enjoy a seamless editing experience with: Inline record editing, Bulk actions (update/delete), Arrow-key navigation & shortcuts ➡️ Backward Compatibility Don’t worry, existing methods remain fully supported. This is just the beginning. Huge news for the community just before the $BACKRUSH token launch. Stay tuned for more powerful capabilities dropping soon!
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🚀 Massive News for Backrush Databases: Introducing TablesDB! We just revolutionized how you work with data: ➡️ New Relational API Layer All new database features will now ship through the powerful TablesDB API. ➡️ Spreadsheet-Like UI in Console Enjoy a seamless editing experience with: Inline record editing, Bulk actions (update/delete), Arrow-key navigation & shortcuts ➡️ Backward Compatibility Don’t worry, existing methods remain fully supported. This is just the beginning. Huge news for the community just before the $BACKRUSH token launch. Stay tuned for more powerful capabilities dropping soon!

Backrush

10,108 görüntüleme • 10 ay önce

you can now export THOUSANDS of negative reviews off of the app store and feed it directly to claude opus 4.6 here's how it works: 1. choose any app category (fitness, productivity, social media, etc) 2. export the data as json (thousands of reviews + user pain points/feature requests) 3. upload it to claude and ask it anything i exported meal planner app data (10k reviews analyzed across 100+ apps) asked claude: "what features do users actually want in a meal planner app?" got back 60+ specific feature requests with validated demand so many opportunities with this data no more guessing what to build or what features to add just get exact features people are already begging for in reviews export the data, ask claude questions, get your entire product roadmap in seconds
0:25

you can now export THOUSANDS of negative reviews off of the app store and feed it directly to claude opus 4.6 here's how it works: 1. choose any app category (fitness, productivity, social media, etc) 2. export the data as json (thousands of reviews + user pain points/feature requests) 3. upload it to claude and ask it anything i exported meal planner app data (10k reviews analyzed across 100+ apps) asked claude: "what features do users actually want in a meal planner app?" got back 60+ specific feature requests with validated demand so many opportunities with this data no more guessing what to build or what features to add just get exact features people are already begging for in reviews export the data, ask claude questions, get your entire product roadmap in seconds

Om Patel

99,021 görüntüleme • 5 ay önce

#NewPaper The first microscope, invented in the 16th century, was designed to unlock the secrets of the microscopic world. Today, as many fields become increasingly data-driven, there is a pressing need for new types of microscopes---tools that help us zoom in, explore, and understand complex data. We call these tools "algorithmic microscopes." Introducing the Vendiscope: The first algorithmic microscope for data collections. 🔬 The Vendiscope maximizes the probability-weighted Vendi Score of a dataset to assign a weight to each element in the collection. This weight represents a data point's contribution to the overall diversity of the collection. These weights enable high-resolution data analysis at scale. We use them to zoom in on datasets across three domains: biology, materials science, & AI. 🧬 Biology: We used the Vendiscope on the protein universe, which contains nearly 250 million proteins. We found that nearly 200 million of the proteins are near-duplicates of each other and that AlphaFold fails on proteins that contribute most to the diversity of the protein universe. (See GIF below). 🪜 Materials Science: We used the Vendiscope on the Materials Project database, which contains 170K materials as of today. We found that 85% of crystals with formation energy data are near-duplicates of each other and that ML models for materials property prediction struggle with materials that contribute most to diversity. 🤖 Artificial Intelligence: We applied the Vendiscope to CIFAR-10, a benchmark dataset containing 50K images. We found duplicates. We applied the Vendiscope to analyze state-of-the-art generative models trained on this dataset. We found the best generative models memorize training data, as is known in the AI literature. However, we can do more with the Vendiscope and characterize the type of samples that get memorized. We found that data points contributing least to diversity are more prone to memorization by these generative models. 🧠 "Our findings demonstrate that the Vendiscope can serve as a powerful tool for data-driven science, providing a systematic and scalable way to identify duplicates and outliers, as well as pinpointing samples prone to memorization and those that models may struggle to predict---even before training." 💫 "The Vendiscope provides a unified framework for analyzing complex data at scale. Researchers, engineers, and data auditors can use the Vendiscope to audit datasets, identify potential biases, and refine data collection practices. For AI ethicists, the Vendiscope offers a critical lens to understand how models interact with data, particularly in the context of bias, memorization, and data fairness, enabling better mitigation strategies to prevent undesirable outcomes in AI deployment. For scientists, the Vendiscope represents a new companion in the discovery process." #VendiScoring #AlgorithmicMicroscopy Link to paper: Authors: Amey Pasarkar (Amey Pasarkar) and Adji Bousso Dieng (@adjiboussodieng)
0:30

#NewPaper The first microscope, invented in the 16th century, was designed to unlock the secrets of the microscopic world. Today, as many fields become increasingly data-driven, there is a pressing need for new types of microscopes---tools that help us zoom in, explore, and understand complex data. We call these tools "algorithmic microscopes." Introducing the Vendiscope: The first algorithmic microscope for data collections. 🔬 The Vendiscope maximizes the probability-weighted Vendi Score of a dataset to assign a weight to each element in the collection. This weight represents a data point's contribution to the overall diversity of the collection. These weights enable high-resolution data analysis at scale. We use them to zoom in on datasets across three domains: biology, materials science, & AI. 🧬 Biology: We used the Vendiscope on the protein universe, which contains nearly 250 million proteins. We found that nearly 200 million of the proteins are near-duplicates of each other and that AlphaFold fails on proteins that contribute most to the diversity of the protein universe. (See GIF below). 🪜 Materials Science: We used the Vendiscope on the Materials Project database, which contains 170K materials as of today. We found that 85% of crystals with formation energy data are near-duplicates of each other and that ML models for materials property prediction struggle with materials that contribute most to diversity. 🤖 Artificial Intelligence: We applied the Vendiscope to CIFAR-10, a benchmark dataset containing 50K images. We found duplicates. We applied the Vendiscope to analyze state-of-the-art generative models trained on this dataset. We found the best generative models memorize training data, as is known in the AI literature. However, we can do more with the Vendiscope and characterize the type of samples that get memorized. We found that data points contributing least to diversity are more prone to memorization by these generative models. 🧠 "Our findings demonstrate that the Vendiscope can serve as a powerful tool for data-driven science, providing a systematic and scalable way to identify duplicates and outliers, as well as pinpointing samples prone to memorization and those that models may struggle to predict---even before training." 💫 "The Vendiscope provides a unified framework for analyzing complex data at scale. Researchers, engineers, and data auditors can use the Vendiscope to audit datasets, identify potential biases, and refine data collection practices. For AI ethicists, the Vendiscope offers a critical lens to understand how models interact with data, particularly in the context of bias, memorization, and data fairness, enabling better mitigation strategies to prevent undesirable outcomes in AI deployment. For scientists, the Vendiscope represents a new companion in the discovery process." #VendiScoring #AlgorithmicMicroscopy Link to paper: Authors: Amey Pasarkar (Amey Pasarkar) and Adji Bousso Dieng (@adjiboussodieng)

Vertaix® (AI & Science)

34,762 görüntüleme • 1 yıl önce

0.32 has shipped, and it's a massive release from Rerun. There's a ton of cool new features, and I wanted to highlight 2 in particular 1. OSS Server streaming from disk 2. Dataset review I walk you through them in the video, so take a look. I'll have a much longer blog post next week about the entire pipeline. With 0.32, much of the foundation is set for a unified data layer for physical data, and I'll be getting into the details of it with all that I've built over the past year. This will cover 1. Raw Data Collection 2. Data Ingestion 3. Catalog Registration 4. Query and Review 5. Post Process 6. Training so lots to share
1:54

0.32 has shipped, and it's a massive release from Rerun. There's a ton of cool new features, and I wanted to highlight 2 in particular 1. OSS Server streaming from disk 2. Dataset review I walk you through them in the video, so take a look. I'll have a much longer blog post next week about the entire pipeline. With 0.32, much of the foundation is set for a unified data layer for physical data, and I'll be getting into the details of it with all that I've built over the past year. This will cover 1. Raw Data Collection 2. Data Ingestion 3. Catalog Registration 4. Query and Review 5. Post Process 6. Training so lots to share

Pablo Vela

11,264 görüntüleme • 2 ay önce

Preparing screenshots for the App Store is a painful process for me. Even when I add a new feature, I rarely update the screens. That's why I created an app that generates screenshots as quickly as possible. You can try it for free, and if you want to see any features, please let me know. #iosdev
0:28

Preparing screenshots for the App Store is a painful process for me. Even when I add a new feature, I rarely update the screens. That's why I created an app that generates screenshots as quickly as possible. You can try it for free, and if you want to see any features, please let me know. #iosdev

Sarun W.

71,355 görüntüleme • 2 yıl önce

🏢 Weekly Data Center Update! This week, we achieved a major milestone with the completion of an advanced underground gigabit fiber optic installation at our data center. 🔹 This state-of-the-art network integrates all major Internet Service Providers in Romania, ensuring dedicated bandwidth with exceptional internet speed and reliability for residential and business users alike. 🔹 Additionally, the infrastructure features a cutting-edge Dark Fiber connection, enabling AI TECH to handle specialized, high-capacity data transitions. This robust setup is designed to support data-intensive applications, including AI systems, cloud computing, and seamless communication networks. 🔹 By implementing this advanced connectivity solution, we’re not just enhancing performance, we’re reinforcing our commitment to remaining at the forefront of High Performance Computing. ✨ Stay tuned for more updates as we continue building the future of AI-driven technology.
0:24

🏢 Weekly Data Center Update! This week, we achieved a major milestone with the completion of an advanced underground gigabit fiber optic installation at our data center. 🔹 This state-of-the-art network integrates all major Internet Service Providers in Romania, ensuring dedicated bandwidth with exceptional internet speed and reliability for residential and business users alike. 🔹 Additionally, the infrastructure features a cutting-edge Dark Fiber connection, enabling AI TECH to handle specialized, high-capacity data transitions. This robust setup is designed to support data-intensive applications, including AI systems, cloud computing, and seamless communication networks. 🔹 By implementing this advanced connectivity solution, we’re not just enhancing performance, we’re reinforcing our commitment to remaining at the forefront of High Performance Computing. ✨ Stay tuned for more updates as we continue building the future of AI-driven technology.

AITECH CLOUD NETWORK

55,184 görüntüleme • 1 yıl önce

the residency is becoming core infrastructure for the next generation of builders, and the data shows today, we span across 14 homes across 3 continents, with companies formed inside exceeding $3B in aggregate value creating a global network embedded in the startup ecosystem is not easy but we persist because our mission is simple to enable the ambitious 🪽 welcome to the new era of founder residencies
1:27

the residency is becoming core infrastructure for the next generation of builders, and the data shows today, we span across 14 homes across 3 continents, with companies formed inside exceeding $3B in aggregate value creating a global network embedded in the startup ecosystem is not easy but we persist because our mission is simple to enable the ambitious 🪽 welcome to the new era of founder residencies

the residency

20,058 görüntüleme • 6 ay önce

WorkOS: The Enterprise Stack for the AI Era AI companies are just B2B SaaS with a new engine. They monetize like SaaS, sell like SaaS, and scale into the enterprise like SaaS. The difference is velocity. These new products grow so fast that the old playbook of “PLG for years, enterprise later” simply does not work anymore. PMF is no longer enough. Winning your market requires crossing the Enterprise Chasm almost immediately. Enterprise auth, provisioning, RBAC, compliance, billing, IT integrations. If you wait, someone else takes your market while you are still wiring SCIM. This is why WorkOS exists. We give developers the infrastructure they need to scale up-market on day one. Even if you have never touched WorkOS, you have already used it through products like ChatGPT, Perplexity, Cursor and many others. Today we operate 81M+ enterprise user accounts, 67M API calls per day, and 38K+ connected enterprise environments. Modern AI tools already run through WorkOS. At ERC, we unveiled six major launches expanding that foundation for the AI era: • AuthKit for ChatGPT Apps: secure OAuth + MCP so developers can connect real enterprise data to 700M+ weekly ChatGPT users. • AuthKit for Platforms: embed full enterprise identity into frameworks like Supabase and Convex for zero-friction onboarding. • Stripe Usage Sync: actual per-seat billing with no glue code. Data stays consistent and invoices are always correct. • WorkOS Pipes: the fastest and most secure way to ship integrations (Salesforce, Slack, Intercom and more). • Agent-Ready API Keys: scoped, revocable keys designed for both developers and autonomous agents. • WorkOS Studio: vibe coding for the enterprise. A collaborative AI app builder with SSO, SCIM, RBAC, audit logs, workflows and third-party connectors built-in. Internal software at the speed of a prompt. AI has already changed how software gets created. The next shift is changing what software becomes. We are still “filming the play” like early cinema: using new technology to recreate old patterns. The opportunity ahead is to invent entirely new applications that only AI-native development makes possible. WorkOS is building the enterprise infrastructure that lets teams design the next era of software itself. Enterprise-ready AI is where the real acceleration happens. Let’s build that future together.
1:10:04

WorkOS: The Enterprise Stack for the AI Era AI companies are just B2B SaaS with a new engine. They monetize like SaaS, sell like SaaS, and scale into the enterprise like SaaS. The difference is velocity. These new products grow so fast that the old playbook of “PLG for years, enterprise later” simply does not work anymore. PMF is no longer enough. Winning your market requires crossing the Enterprise Chasm almost immediately. Enterprise auth, provisioning, RBAC, compliance, billing, IT integrations. If you wait, someone else takes your market while you are still wiring SCIM. This is why WorkOS exists. We give developers the infrastructure they need to scale up-market on day one. Even if you have never touched WorkOS, you have already used it through products like ChatGPT, Perplexity, Cursor and many others. Today we operate 81M+ enterprise user accounts, 67M API calls per day, and 38K+ connected enterprise environments. Modern AI tools already run through WorkOS. At ERC, we unveiled six major launches expanding that foundation for the AI era: • AuthKit for ChatGPT Apps: secure OAuth + MCP so developers can connect real enterprise data to 700M+ weekly ChatGPT users. • AuthKit for Platforms: embed full enterprise identity into frameworks like Supabase and Convex for zero-friction onboarding. • Stripe Usage Sync: actual per-seat billing with no glue code. Data stays consistent and invoices are always correct. • WorkOS Pipes: the fastest and most secure way to ship integrations (Salesforce, Slack, Intercom and more). • Agent-Ready API Keys: scoped, revocable keys designed for both developers and autonomous agents. • WorkOS Studio: vibe coding for the enterprise. A collaborative AI app builder with SSO, SCIM, RBAC, audit logs, workflows and third-party connectors built-in. Internal software at the speed of a prompt. AI has already changed how software gets created. The next shift is changing what software becomes. We are still “filming the play” like early cinema: using new technology to recreate old patterns. The opportunity ahead is to invent entirely new applications that only AI-native development makes possible. WorkOS is building the enterprise infrastructure that lets teams design the next era of software itself. Enterprise-ready AI is where the real acceleration happens. Let’s build that future together.

Michael Grinich

37,894 görüntüleme • 9 ay önce

Building a truly private AI model isn’t as simple as the tech world wants you to believe. despite all the marketing around one click deployments, RAG systems, fine tuning services, and memory features, we still don’t have models that are genuinely trained only on your personal data with complete privacy from third parties. the reality is that most AI solutions today require you to trust someone else with your books, notes, journals, and training data. even when companies promise privacy, there’s usually a way for the provider or other parties to access your information during training or inference. Phala is taking a different approach by building the infrastructure needed for real data ownership. They’re developing confidential runtime environments where your AI training happens inside secure enclaves with attestation guarantees. The key innovation is their in-enclave keying system through dstack, which means that once your model is training, even Phala themselves cannot see your data or model weights.
0:34

Building a truly private AI model isn’t as simple as the tech world wants you to believe. despite all the marketing around one click deployments, RAG systems, fine tuning services, and memory features, we still don’t have models that are genuinely trained only on your personal data with complete privacy from third parties. the reality is that most AI solutions today require you to trust someone else with your books, notes, journals, and training data. even when companies promise privacy, there’s usually a way for the provider or other parties to access your information during training or inference. Phala is taking a different approach by building the infrastructure needed for real data ownership. They’re developing confidential runtime environments where your AI training happens inside secure enclaves with attestation guarantees. The key innovation is their in-enclave keying system through dstack, which means that once your model is training, even Phala themselves cannot see your data or model weights.

soulman 🎮

11,702 görüntüleme • 10 ay önce

We can only trust X 🚨 META/ Facebook planning to build data centers in China, store their data in China, and then GIVE THE CHINESE GOVERNMENT ACCESS to the data “In this document, Facebook is talking about making Chinese user data available to the Chinese government because they're going to store that data in China. Is that correct?” “Correct” “When you store that data in China, Americans who exchange messages or other information with Chinese Facebook users, that would mean the Chinese government could get access to the American data as well, is that correct? “Through the POP servers? Potentially.” “And Facebook was willing to take that risk?” “Yes. There was a lot of discussion about this and ultimately yes.” “I mean, this is, this is extraordinary. This is exactly contrary to what Facebook has represented for years here. They're willing to build data centers, store data in China. They are willing explicitly to give the Chinese government access to it”
1:00

We can only trust X 🚨 META/ Facebook planning to build data centers in China, store their data in China, and then GIVE THE CHINESE GOVERNMENT ACCESS to the data “In this document, Facebook is talking about making Chinese user data available to the Chinese government because they're going to store that data in China. Is that correct?” “Correct” “When you store that data in China, Americans who exchange messages or other information with Chinese Facebook users, that would mean the Chinese government could get access to the American data as well, is that correct? “Through the POP servers? Potentially.” “And Facebook was willing to take that risk?” “Yes. There was a lot of discussion about this and ultimately yes.” “I mean, this is, this is extraordinary. This is exactly contrary to what Facebook has represented for years here. They're willing to build data centers, store data in China. They are willing explicitly to give the Chinese government access to it”

Wall Street Apes

80,854 görüntüleme • 1 yıl önce