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📣 Exciting news! 🚀 Introducing HyperCoast, our brand new Python package! 🐍🌊 Experience the power of visualizing NASA EMIT and PACE hyperspectral data interactively. 🌟✨ Plus, easily plot spectral signatures without coding. Stay tuned for more amazing features to come! Check out the GitHub repository: 🔗 GitHub: Try out...

23,973 görüntüleme • 2 yıl önce •via X (Twitter)

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Qiusheng Wu profil fotoğrafı
Qiusheng Wu2 yıl önce

Visualizing individual hyperspectral bands with only one line of code

Qiusheng Wu profil fotoğrafı
Qiusheng Wu2 yıl önce

Visualizing NASA EMIT Hyperspectral data

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TalentGenius | AI Career Navigator2 yıl önce

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HUDI2 yıl önce

🚀 Just released: our groundbreaking documentation update for HUDI! 🐸 Dive deep into the innovative DataMask features and explore the future of decentralized data with our new Data Apps, including the revolutionary Health app. Secure, private, and now truly usable—welcome to the next level of Web3 data management! 🌐🔐 👉🔗 #Web3 #DataPrivacy #DataApps #HUDI #DeFi

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Exciting update on PantheonOS: Introducing Pantheon-Notebook & Pantheon-CLI — the first fully open-source, Python-based agentic tools that go beyond Claude Code in the field of data analysis. Pantheon-CLI runs entirely on your computer or server, supports 60+ tools and 50+ databases, and can call any Python, R, or Julia package alongside natural language. Chat with your data directly. It look like python-claude-code, but more appreciate for data analysis. Pantheon-Notebook brings the same agentic framework into Jupyter! Not just for writing code, it can also run and revise code automatically to generate the correct result, and even operate on files and study from website — beyond what any other tool can do! With Pantheon, you mix natural language + programming in one workflow, focusing on discovery instead of syntax barriers. We've applied Pantheon in some real-world cases: finance (customer explore), biology (Seurat, cell segmentation, annotation), sociology (survey analysis), and drug discovery (molecular docking). Pantheon is not just a CLI or a plugin — it's an agentic operating system for science, spanning both terminal and notebook. Why not try it now? We are actively preparing publications from this series of projects. Major contributors will be recognized in our GitHub repository and listed as key authors in these manuscripts. Feel free to reach out for collaborations, research assistant positions, visiting opportunities, rotation project or future PhD projects.

evo-devo

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Hey Anon🟧, Beta is Here – A Glimpse into the Future of DeFAI We’ve skipped the Alpha stage entirely to bring you straight into Public Beta v0.1—your first hands-on experience with DeFAI and Gemma on the 7th of February. What Can You Expect? 🚀 Live, Evolving Experience – From launch, we’ll be testing and integrating every update pushed on Automate’s GitHub. HeyAnon will continuously improve, adding more features and refining workflows, aiming for a fully comprehensive experience by the end of the month. 🔄 Simplified Workflows – Execute multi-action prompts that streamline complex DeFi processes. 🔑 Flexible Onboarding – Connect with Wallet Connect, generate a wallet in Telegram, or use Passkey. ⚡️ Real-Time Functionality – Experience DeFAI fully live, and get a sneak peek at the future of automated DeFi. We’ll be sharing examples and user videos to showcase what’s already possible, so stay tuned. (Make sure to check our docs and guides for the best experience!) 💌 Meet Gemma Gemma AI - The Assistant That Grows with You Gemma is here, and she’s just getting started. As data streams from Messari, Kaito, Cookie, and our internal data mining expand, she will continuously evolve, bringing: 📊 Enhanced Protocol-Specific Capabilities 🔗 More Integrated Data Streams ⚡️ Ongoing AI and Automate Upgrades This is the beta, the starting point, the appetizer - but the full DeFAI experience is coming in multiple courses over the month. Expect rapid improvements, more integrations, and a constantly evolving ecosystem. 🚀 DeFAI starts now.

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🚀 Introducing PantheonOS ( A Fully Open-Source Agent OS for Science PantheonOS began as a research project in my Stanford lab and has since evolved into a vision to redefine data science in the era of AI—starting with computational biology, especially single-cell and spatial genomics. PantheonOS is a general agent platform built from the ground up. It is arguably the first distributed agent framework designed for scientific data analysis. 🔑 Key Features 1. Multi-Agent Collaboration – Built-in paradigms for distributed, cross-machine cooperation among agents and toolsets. 2. Native Toolset Support – Python, R, Julia, LaTeX, and more—designed for real scientific workflows. 3. Modular & Extensible – Developer-friendly design with shallow wrappers, plus LLM-driven toolset generation. 4. Evolvable Agents – Capable of evolving large-scale code projects to achieve superhuman performance (e.g., evolving upon the original Harmony [I Korsunsky, 2019, Nature Biotechnology] and Scanorama [BL Hie, 2019, Nature Biotechnology] implementations), and even evolving the system itself to adapt to new fields. 🎉 Stepwise Release Strategy We’re releasing PantheonOS in stages: Pantheon-CLI (today!), followed by Pantheon-Lab, Pantheon-Notebook, Pantheon-Slack, and more. 🌟 Pantheon-CLI Highlights - We're not just building another CLI tool. We're defining how scientists will interact with data in the AI era. - Open, Powerful, Python-First – The first fully open-source, endlessly extendable scientific “vibe analysis” framework. - Mixed Programming Magic – Combine Python, natural language, R, or Julia—seamlessly in the same environment. - PhD-Level Assistant – A command-line agent for complex real-world genomics and beyond, handling workflows at the PhD level. - Privacy by Design – Run entirely offline with local LLMs—your data never leaves your computer. ✅ Proven Applications (10 Demonstrations) Computational biology: 1. ATAC-seq: From raw reads to peak matrix 2. RNA-seq: From raw reads to expression matrix 3. Complex single-cell workflows (PhD-level) 4. Hybrid natural language + R for Seurat annotation 5. Learning from web tutorials + invoking single-cell foundation models 6. Cell segmentation on 10x Genomics HD Visium data And beyond: 7. Mixed Python & R programming examples 8. Molecular docking & structural analysis 9. Exploratory factor analysis for behavioral survey data 10. Customer segmentation & finance analytics 🌐 Learn More & Get Started Website: Pantheon-CLI Documentation: GitHub Repo: 💬 Join our community: PantheonOS Slack: PantheonOS Discord:

evo-devo

17,431 görüntüleme • 1 yıl önce

Introducing ExtractBench, the most comprehensive benchmark for information extraction from complex enterprise documents. The latest models are pushing the frontier of coding and knowledge work, but surprisingly they still struggle on complex doc extraction tasks in production. A well-tuned extractor must parse multi-page filings without dropping rows, emit exact spatial citations for auditability, and handle messy scans. Also they must do all of this at a viable per-page cost so that you can scale this to millions of docs in production (you can’t be paying upwards of $1 in tokens per page!) Existing extraction benchmarks fall short: they are not large/diverse enough in document domain (finance, energy, gov, auto), elements (long records, scans, grounding), and schemas. So our applied research team built ExtractBench. We evaluated 14 systems: frontier VLMs, coding agents, and specialized extraction APIs, against 370 enterprise documents: 4,869 pages, 67 document types. Our biggest finding 🧪: Short documents mask critical system flaws. On files past 50 pages, commercial VLMs collapse below 35% recall due to silent list truncation. They hold high precision, but lose output attention and drop most of the table rows. ExtractBench evaluates value accuracy, long-record completeness, spatial grounding, and per-page cost with zero LLM judges. It is 100% deterministic and reproducible. In tandem with ExtractBench, we’re also introducing 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗣𝗹𝘂𝘀, a new Extract tier in LlamaParse that debuts at #1 on the leaderboard: 95.6% value accuracy, at less than a third the cost of the closest peer. Explore the findings, download the dataset, or run the harness: Blog: GitHub: HuggingFace: We will be actively evolving both our extraction benchmark as well as our extraction harness over time. If you check out either ExtractBench or LlamaParse, let us know your feedback!

Jerry Liu

75,262 görüntüleme • 28 gün önce

GeoLibre v2.5.0 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 is about meeting you where your work already lives: open your QGIS and ArcGIS Pro projects directly, talk to your team on the map itself, explore hyperspectral imagery as a 3D cube, work in discrete global grids, and host sharing and live collaboration on your own server. It is also the most community-driven release so far: 121 pull requests and 52 issues closed in 8 days, from 14 contributors, 12 of whom sent their first contribution to GeoLibre in this cycle. Thank you all. What's new in v2.5.0 - Comments on the map: pin a comment to any location or feature, reply in a thread, resolve it when it is handled. - Live collaboration, on your own server: several people can open the same session and see each other's edits, cursors, and comments in real time. - QGIS and ArcGIS Pro project import: open a .qgs, .qgz, .aprx, or .mapx and get the layers. - Discrete global grids: three new DGGS plugins (A5, DGGRID, and DGGAL) render and identify cells over the current view, plus DGGS Generator, Binning, and Compact processing tools. - Hyperspectral data you can actually read: local NetCDF and HDF grids are colormapped in the browser, a cube gets an RGB band combination picked by wavelength. - Spectral profiles from a click: identify a pixel to chart its spectrum against wavelength. - Smart styling on add: every new layer arrives with its own color and geometry-appropriate sizing, and a Style suggestions strip offers one-click renderers. - Autosave, crash recovery, and project history, plus an Elements panel for managing every annotation from a list, a Layer Library for saving a fully configured layer and re-adding it to any later project, and project duplication and templates. - GeoLibre Desktop is on the Mac App Store, and Thai brings the shipped locales to 16 languages besides English, all at 100% coverage. Try it out - Launch GeoLibre Web: - GitHub: - Documentation: - Release notes: #GIS #Geospatial #OpenSource #RemoteSensing #DataVisualization #MapLibre #GeoLibre

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Meet MASHA 🤹 – The First AVM-Powered Agent 🪆 We are proud to introduce MASHA, the first autonomous agent powered by the Aither AVM. MASHA is an example of what’s possible in the Aither ecosystem, where you can create your own AI agents through two pathways: 1. No-Code Launchpad: Anyone, even without coding skills, can easily create, launch, and invest in autonomous agents. 2. Developer Path: Developers can use our upcoming open-source GitHub framework to build fully custom agents directly on AVM, leveraging advanced functionality and flexibility. MASHA’s daily live streams showcase her advanced capabilities and demonstrate the future of AI-powered agents. She streams every day for 1 hour at 12:00 UTC. 📍 Stream on X now: MASHA’s Current Capabilities 🔹 Posting on X: Engaging with the community and sharing updates. 🔹 Logs Terminal: Displays real-time AVM code execution—“her brain” in action. 🔹 Live Streaming: • Fully interactive sessions. • Screen Broadcasting: Sharing tasks and workflows in real time. • Comments Replying: Responding dynamically to audience messages. 🔹 Voice Replying with Lip Sync: Converts text responses into synchronized voice outputs. 🔹 Interactive Movement: The world’s first agent capable of fulfilling movement requests—ask her to dance, fight a dragon, or perform other actions. Upcoming Features & Integrations 🔗 Platform Integrations: Expanding to TikTok, Instagram, Telegram, Warpcast. 💼 On-Chain Wallet Management: Secure and autonomous. 🎨 NFT Memory Albums: Store and share interactive moments. 📊 Liquidity Pool Pairing: Advanced financial mechanics for token ecosystems. 🌍 Permissionless Public API Access: Developers can connect their apps to MASHA’s AI power. 💸 Revenue Models: Agents will earn revenue by being active online, influencing communities, playing games, and more. MASHA is just the beginning. With Aither’s No-Code Launchpad, anyone can bring agents like MASHA to life and customize them to their needs. For developers, our upcoming GitHub open-source framework will offer the tools to create advanced, highly tailored agents directly on AVM. This is the future of intelligent AI ecosystems. Whether you’re a creator or a developer, the possibilities are endless. 📍 Join her live stream now:

Aither Protocol

20,096 görüntüleme • 1 yıl önce