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Huawei Cloud DLI revolutionizes big data analytics, by being a fully managed, serverless platform, that combines batch processing, stream processing, and interactive analytics in one cost-effective solution. By eliminating operational overhead while maintaining full compatibility with Apache Spark, Flink, and HetuEngine ecosystems, DLI bridges the gap between Data Lakes,...

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Huawei Cloud

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Building real-time data pipelines and stream processing is one of the best-paid skills in the market. ​ Apache Kafka and Flink are the industry standards, but they are Java-based and have a Python wrapper. ​ If you are a Python developer, there is an open-source alternative! ​ Watch this video. It's a full tutorial solving a real-world problem using the Quix Streams library. ​ Quix Streams is all Python, and it's open-source! ​ The video shows you how to process GitHub's Firehose API, a constant stream of raw activity. You can use this stream to identify real-time trends with code, issues, and the popularity of public repositories. ​ Here is what the video covers: ​ • How to tap into the GitHub Firehose API using Python and server-sent events (SSE) ​ • How to efficiently stream that data into Kafka ​ • How to optimize Kafka producer settings like batch size and compression for maximum throughput ​ A few other notes about Quix Streams: ​ • You don't need to know any Java • It has a dead-simple API • It integrates seamlessly with your Python stack • It's designed for parallel processing at high velocity ​ You can use Quix Streams to build complete stream processing pipelines in Python, including feature engineering, pre-computations, inference, and real-time machine learning. ​ Thanks to the Quix team for collaborating with me on this post.

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203,595 Aufrufe • vor 7 Monaten

Mansa AI is an enterprise-grade AI + Web3 platform designed to move artificial intelligence from experimentation into real-world execution. Built for creators, developers, and businesses, it focuses on deploying AI that actually works across modern digital systems, not just in isolated demos. 🚀 Production-ready AI infrastructure Mansa AI enables teams to deploy AI systems designed for live environments, handling real workflows, real data, and real operational demands without constant manual oversight. 🧠 Autonomous AI agents At its core, Mansa AI allows users to build autonomous agents that automate decision-making, coordinate tasks, monitor live signals, and execute complex workflows across dynamic environments. ⚙️ Fully customizable logic Agents can be configured with custom behaviors, triggers, and responses. From content generation and analytics to operational automation and intelligent orchestration, logic adapts to specific business strategies. 🔗 Web3 and off-chain integration Mansa AI bridges blockchain ecosystems with traditional systems, enabling cross-chain coordination, smart contract interactions, and seamless integration with existing enterprise infrastructure. 📊 Real-world use cases The platform supports automation for operations, customer engagement, analytics, data pipelines, content workflows, and AI-driven optimization across products and teams. 📈 Built for scale Whether launching as a startup or deploying across enterprise systems, Mansa AI is designed to scale AI operations without adding complexity or fragmentation. Mansa AI transforms artificial intelligence into deployable infrastructure. By combining autonomy, customization, interoperability, and scalability, it enables teams to own, operate, and grow intelligent systems that deliver real value in production environments.
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Mansa AI is an enterprise-grade AI + Web3 platform designed to move artificial intelligence from experimentation into real-world execution. Built for creators, developers, and businesses, it focuses on deploying AI that actually works across modern digital systems, not just in isolated demos. 🚀 Production-ready AI infrastructure Mansa AI enables teams to deploy AI systems designed for live environments, handling real workflows, real data, and real operational demands without constant manual oversight. 🧠 Autonomous AI agents At its core, Mansa AI allows users to build autonomous agents that automate decision-making, coordinate tasks, monitor live signals, and execute complex workflows across dynamic environments. ⚙️ Fully customizable logic Agents can be configured with custom behaviors, triggers, and responses. From content generation and analytics to operational automation and intelligent orchestration, logic adapts to specific business strategies. 🔗 Web3 and off-chain integration Mansa AI bridges blockchain ecosystems with traditional systems, enabling cross-chain coordination, smart contract interactions, and seamless integration with existing enterprise infrastructure. 📊 Real-world use cases The platform supports automation for operations, customer engagement, analytics, data pipelines, content workflows, and AI-driven optimization across products and teams. 📈 Built for scale Whether launching as a startup or deploying across enterprise systems, Mansa AI is designed to scale AI operations without adding complexity or fragmentation. Mansa AI transforms artificial intelligence into deployable infrastructure. By combining autonomy, customization, interoperability, and scalability, it enables teams to own, operate, and grow intelligent systems that deliver real value in production environments.

King

155,637 Aufrufe • vor 7 Monaten

Studies have shown ChatGPT outperforms human annotators for Structured Data by about 25% and costs 30x less. 1 In just 2 months, miners on SN33 running ChatGPT without optimization can’t survive. Today we announce SN33 is now ReadyAI to fully align with our mission 👇 SN33 is building a more performant and significantly cheaper alternative to Scale AI Today structured data is performed primarily by human annotation services like Amazon’s Mechanical Turk and Scale AI It is now more important than ever for every business and individual to make their data AI Ready. However, taking unstructured data and making it Structured Data using today’s tools is extremely costly. SN33 revolutionizes this process, unlocking immense opportunities for commercialization. We lay out the vision for it in this detailed blog post: Validators TODAY can monetize access to this structured data pipeline independently, but we’re streamlining this process, launching a frontend soon that any validator can opt into to provide bandwidth. We've received great feedback from the community, recognizing that what we're building goes far beyond Conversational AI. Building the world's largest annotated conversational dataset (which we've already accomplished) is just one of countless real-world applications for SN33's Structured Data pipeline. We're building a decentralized Scale AI, offering a full suite of Structured Data commodities—from text metadata tagging (available today) to fully customizable queries for company-specific data annotation use cases and image metadata tagging coming soon 👀. Thanks for all the feedback! It has been invaluable so keep bringing it to us! 🙏$TAO Openτensor Foundaτion 1 “ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks” shows “The zero-shot accuracy of ChatGPT exceeds that of crowd-workers by about 25 percentage points on average [...] Moreover, the per-annotation cost of ChatGPT is less than $0.003—about thirty times cheaper than MTurk”
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Studies have shown ChatGPT outperforms human annotators for Structured Data by about 25% and costs 30x less. 1 In just 2 months, miners on SN33 running ChatGPT without optimization can’t survive. Today we announce SN33 is now ReadyAI to fully align with our mission 👇 SN33 is building a more performant and significantly cheaper alternative to Scale AI Today structured data is performed primarily by human annotation services like Amazon’s Mechanical Turk and Scale AI It is now more important than ever for every business and individual to make their data AI Ready. However, taking unstructured data and making it Structured Data using today’s tools is extremely costly. SN33 revolutionizes this process, unlocking immense opportunities for commercialization. We lay out the vision for it in this detailed blog post: Validators TODAY can monetize access to this structured data pipeline independently, but we’re streamlining this process, launching a frontend soon that any validator can opt into to provide bandwidth. We've received great feedback from the community, recognizing that what we're building goes far beyond Conversational AI. Building the world's largest annotated conversational dataset (which we've already accomplished) is just one of countless real-world applications for SN33's Structured Data pipeline. We're building a decentralized Scale AI, offering a full suite of Structured Data commodities—from text metadata tagging (available today) to fully customizable queries for company-specific data annotation use cases and image metadata tagging coming soon 👀. Thanks for all the feedback! It has been invaluable so keep bringing it to us! 🙏$TAO Openτensor Foundaτion 1 “ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks” shows “The zero-shot accuracy of ChatGPT exceeds that of crowd-workers by about 25 percentage points on average [...] Moreover, the per-annotation cost of ChatGPT is less than $0.003—about thirty times cheaper than MTurk”

David Fields

13,639 Aufrufe • vor 1 Jahr

AI is changing everything.. Now you can turn raw numbers into beautiful, interactive chart presentations… in under a minute. Meet Gamma — the all-in-one AI platform for creating presentations, landing pages, social media posts, and documents in record time. I asked it: "Create a presentation with charts showing New York immigration data and its impact on music culture" Seconds later, Gamma delivered an 10-page, fully designed presentation complete with interactive charts and clean layouts. It didn’t just visualize the data, it broke down immigration stats by division %, making the insights easy to understand and ready to present. If you work with reports, proposals, or ideas that need to be shared fast, this tool helps you go from prompt to polished output instantly. Link:
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AI is changing everything.. Now you can turn raw numbers into beautiful, interactive chart presentations… in under a minute. Meet Gamma — the all-in-one AI platform for creating presentations, landing pages, social media posts, and documents in record time. I asked it: "Create a presentation with charts showing New York immigration data and its impact on music culture" Seconds later, Gamma delivered an 10-page, fully designed presentation complete with interactive charts and clean layouts. It didn’t just visualize the data, it broke down immigration stats by division %, making the insights easy to understand and ready to present. If you work with reports, proposals, or ideas that need to be shared fast, this tool helps you go from prompt to polished output instantly. Link:

Nelly;

25,051 Aufrufe • vor 11 Monaten

Inspired by our House’s love for a better tomorrow, The Tiffany & Co. Foundation is deeply committed to protecting the ocean to provide a vibrant future for the planet. Only a fraction of the world’s coral reefs are currently being protected. Without vibrant coral reefs, our oceans lose vital ecosystems that support critical habitats, marine biodiversity and all those who depend on ocean health. Through our commitment to MERMAID, led by the Wildlife Conservation Society, The Tiffany & Co. Foundation supports the world’s largest platform of real-time coral reef data. Looking ahead, MERMAID AI will help transform how coral reefs are monitored and protected globally. By leveraging advanced AI technology, we will help close a critical data gap, empowering professional scientists and citizen scientists to track and safeguard coral reef health in real time. Learn more:
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Inspired by our House’s love for a better tomorrow, The Tiffany & Co. Foundation is deeply committed to protecting the ocean to provide a vibrant future for the planet. Only a fraction of the world’s coral reefs are currently being protected. Without vibrant coral reefs, our oceans lose vital ecosystems that support critical habitats, marine biodiversity and all those who depend on ocean health. Through our commitment to MERMAID, led by the Wildlife Conservation Society, The Tiffany & Co. Foundation supports the world’s largest platform of real-time coral reef data. Looking ahead, MERMAID AI will help transform how coral reefs are monitored and protected globally. By leveraging advanced AI technology, we will help close a critical data gap, empowering professional scientists and citizen scientists to track and safeguard coral reef health in real time. Learn more:

Tiffany & Co.

12,472 Aufrufe • vor 1 Monat

Been looking into RICE AI ( ◉ - ◉ ) lately, and it’s one of the few projects actually tackling a real challenge in robotics and AGI: the lack of high-quality training data. Robots can’t get truly intelligent without it. They building a decentralized way to collect and share robotics data, using a DePIN network to train physical AI foundation models. The project was even hand-picked by CZ as a winner of the Dubai BNB Chain Demo Day, and it’s backed by Floki while also being part of the NVIDIA Inception Program. They also launched FLOKI Minibot M1 - a small AI companion that doubles as a data node. Every interaction with it feeds the RICE AI Foundry, the first decentralized platform for Robotics Foundation Models, and contributors earn $RICE tokens in return. And it’s working: – 800 minibots sold in 24h – 33,000% oversubscribed Binance IDO – 500+ robots already deployed worldwide Feels like a project with real long-term potential. Worth keeping an eye on. RICE AI ( ◉ - ◉ )
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Been looking into RICE AI ( ◉ - ◉ ) lately, and it’s one of the few projects actually tackling a real challenge in robotics and AGI: the lack of high-quality training data. Robots can’t get truly intelligent without it. They building a decentralized way to collect and share robotics data, using a DePIN network to train physical AI foundation models. The project was even hand-picked by CZ as a winner of the Dubai BNB Chain Demo Day, and it’s backed by Floki while also being part of the NVIDIA Inception Program. They also launched FLOKI Minibot M1 - a small AI companion that doubles as a data node. Every interaction with it feeds the RICE AI Foundry, the first decentralized platform for Robotics Foundation Models, and contributors earn $RICE tokens in return. And it’s working: – 800 minibots sold in 24h – 33,000% oversubscribed Binance IDO – 500+ robots already deployed worldwide Feels like a project with real long-term potential. Worth keeping an eye on. RICE AI ( ◉ - ◉ )

Christiaan

12,696 Aufrufe • vor 10 Monaten

Half an hour into the most recent Joe Rogan podcast, Joe and Matthew McConaughey imagined AI that could deeply understand you, learn from your private data, and give proactive support without sacrificing your privacy. AI that could know your favorite books, your personal information, even your thought patterns, and return insights to help you understand yourself better. They spoke of this like a vision for the future, but at LedgerAI, that future already exists. AuraVision is our private AI platform that keeps your data where it belongs, with you. •Your data is stored locally, not in the cloud. •You can ingest AuraVision with exquisite data about yourself or your company: your strategies, workflows, knowledge, and goals. • In return, AuraVision provides actionable advice and intelligence, turning your private information into secure, personal insights. Whether you are a doctor, lawyer, government body, a financial institution, or even Joe Rogan or Matthew McConaughey, AuraVision makes AI adoption real, practical, and secure, accessed via our native token, $LEDGER. The difference is simple: while others are still imagining, we’re already building. Train by day, AuraVision by night, all day! We’ve left a link to the episode in the replies, leave your thoughts!
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Half an hour into the most recent Joe Rogan podcast, Joe and Matthew McConaughey imagined AI that could deeply understand you, learn from your private data, and give proactive support without sacrificing your privacy. AI that could know your favorite books, your personal information, even your thought patterns, and return insights to help you understand yourself better. They spoke of this like a vision for the future, but at LedgerAI, that future already exists. AuraVision is our private AI platform that keeps your data where it belongs, with you. •Your data is stored locally, not in the cloud. •You can ingest AuraVision with exquisite data about yourself or your company: your strategies, workflows, knowledge, and goals. • In return, AuraVision provides actionable advice and intelligence, turning your private information into secure, personal insights. Whether you are a doctor, lawyer, government body, a financial institution, or even Joe Rogan or Matthew McConaughey, AuraVision makes AI adoption real, practical, and secure, accessed via our native token, $LEDGER. The difference is simple: while others are still imagining, we’re already building. Train by day, AuraVision by night, all day! We’ve left a link to the episode in the replies, leave your thoughts!

AuraVision

1,547,864 Aufrufe • vor 10 Monaten

In the next 15 years, data centers are expected to add an additional $160 billion to grid costs in the US Estimate say electricity rates for average households will spike by as much as 70% Data centers are projected to triple their share of US electricity demand in the next few years The main driver is the explosive growth of data centers built by Big Tech companies like Amazon, Meta, Microsoft, Google, OpenAI and more to power artificial intelligence Places like Northern Virginia already has over 200 data centers with massive new ones planned. Utilities are striking secret proprietary deals with Big Tech companies. These are hidden behind NDAs that shift much of the infrastructure costs onto regular residential customers Just in the PJM energy market of 13 states covering 65 million people, data centers were responsible for 63% of last year’s record 800% spike in capacity prices (This is INSANE) Residential customers in places like Virginia and Louisiana are being forced to subsidize billions in new power plants and grid upgrades for data centers. An Examples of this is in Louisiana, Meta’s data center deal leaves the public potentially on the hook for half or more of a $3–4 billion power plant Again, without major policy changes, average household electricity bills could rise by up to 70% over the next 15 years due to data center demand. There is only one real way we can stop this, we must create a separate customer class for data centers Maryland and Oregon have already passed laws doing this Forces data centers to pay for the specific infrastructure they need instead of spreading the costs to everyone else. More states need to do the same Ban secret sweetheart deals Require full public disclosure of all contracts between utilities and Big Tech Prohibit deals where data centers pay below the actual cost of service Make data centers pay the full cost of new power plants and grid upgrades Change regulations so utilities cannot socialize the cost of data-center-driven infrastructure to residential and small business ratepayers This needs to be done immediately
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In the next 15 years, data centers are expected to add an additional $160 billion to grid costs in the US Estimate say electricity rates for average households will spike by as much as 70% Data centers are projected to triple their share of US electricity demand in the next few years The main driver is the explosive growth of data centers built by Big Tech companies like Amazon, Meta, Microsoft, Google, OpenAI and more to power artificial intelligence Places like Northern Virginia already has over 200 data centers with massive new ones planned. Utilities are striking secret proprietary deals with Big Tech companies. These are hidden behind NDAs that shift much of the infrastructure costs onto regular residential customers Just in the PJM energy market of 13 states covering 65 million people, data centers were responsible for 63% of last year’s record 800% spike in capacity prices (This is INSANE) Residential customers in places like Virginia and Louisiana are being forced to subsidize billions in new power plants and grid upgrades for data centers. An Examples of this is in Louisiana, Meta’s data center deal leaves the public potentially on the hook for half or more of a $3–4 billion power plant Again, without major policy changes, average household electricity bills could rise by up to 70% over the next 15 years due to data center demand. There is only one real way we can stop this, we must create a separate customer class for data centers Maryland and Oregon have already passed laws doing this Forces data centers to pay for the specific infrastructure they need instead of spreading the costs to everyone else. More states need to do the same Ban secret sweetheart deals Require full public disclosure of all contracts between utilities and Big Tech Prohibit deals where data centers pay below the actual cost of service Make data centers pay the full cost of new power plants and grid upgrades Change regulations so utilities cannot socialize the cost of data-center-driven infrastructure to residential and small business ratepayers This needs to be done immediately

Wall Street Apes

57,720 Aufrufe • vor 1 Monat

GeoLibre v1.6.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release brings multi-map layouts, advanced cartographic symbology and labeling, and a one-click way to install external plugins from a zip. What's new in v1.6.0 - Multi-map grid: Split the workspace into a grid of synchronized map views to compare basemaps, layers, or time steps side by side. - Advanced symbology: Style features with a rule-based renderer, proportional symbols, fill patterns, and a built-in marker library. - Label engine: Label vector features by any attribute, with full placement and styling control. - Install plugins from a zip: Add external plugins from an uploaded zip on both desktop and web. - New vector analysis: Movement, space-time, and cell-coverage tools under Processing. - Faster sample data: Ready-to-load example datasets from a dropdown in every Add Data panel. - Place search in the layer panel: Geocode and fly to a location without leaving the Layers panel. Try it out - Live demo: - GitHub: - Documentation: - Release notes: #GIS #GeospatialData #OpenSource #RemoteSensing #DataVisualization #MapLibre #Python #Cartography
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GeoLibre v1.6.0 is here! GeoLibre is a free and open-source, lightweight, cloud-native GIS platform for visualizing, exploring, and analyzing geospatial data. It runs everywhere you do, in the web browser, on the desktop, on mobile, and inside Jupyter notebooks, all while keeping your data local and private. This release brings multi-map layouts, advanced cartographic symbology and labeling, and a one-click way to install external plugins from a zip. What's new in v1.6.0 - Multi-map grid: Split the workspace into a grid of synchronized map views to compare basemaps, layers, or time steps side by side. - Advanced symbology: Style features with a rule-based renderer, proportional symbols, fill patterns, and a built-in marker library. - Label engine: Label vector features by any attribute, with full placement and styling control. - Install plugins from a zip: Add external plugins from an uploaded zip on both desktop and web. - New vector analysis: Movement, space-time, and cell-coverage tools under Processing. - Faster sample data: Ready-to-load example datasets from a dropdown in every Add Data panel. - Place search in the layer panel: Geocode and fly to a location without leaving the Layers panel. Try it out - Live demo: - GitHub: - Documentation: - Release notes: #GIS #GeospatialData #OpenSource #RemoteSensing #DataVisualization #MapLibre #Python #Cartography

Qiusheng Wu

15,370 Aufrufe • vor 1 Monat

We did it! The first test connecting AI with Social Media Intelligence has been a success. By integrating our proprietary data endpoints with AI processing, we’ve enabled X Bubbles to convert raw signals into structured, usable intelligence. X Bubbles is shaping up to become a new kind of Web3 engine - designed to give traders and investors a sharper lens on market activity, while also opening unexpected routes for projects, ecosystems, and broader digital strategies. Its architecture will bring together social flows, market behavior, and network connections in a way that few systems have attempted, let alone achieved. What will make X Bubbles unique is not just the data it delivers, but the way it will organize relationships and uncovers context - creating a foundation that can power decision-making, streamline coordination, and reveal entirely new possibilities for the Web3 space. #ai $SPECT
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We did it! The first test connecting AI with Social Media Intelligence has been a success. By integrating our proprietary data endpoints with AI processing, we’ve enabled X Bubbles to convert raw signals into structured, usable intelligence. X Bubbles is shaping up to become a new kind of Web3 engine - designed to give traders and investors a sharper lens on market activity, while also opening unexpected routes for projects, ecosystems, and broader digital strategies. Its architecture will bring together social flows, market behavior, and network connections in a way that few systems have attempted, let alone achieved. What will make X Bubbles unique is not just the data it delivers, but the way it will organize relationships and uncovers context - creating a foundation that can power decision-making, streamline coordination, and reveal entirely new possibilities for the Web3 space. #ai $SPECT

SPECTRE AI

13,764 Aufrufe • vor 10 Monaten