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TLDR: TimeGPT-1 by nixtla is the most accurate and fastest among foundation models (closely followed by Google AI's TimesFM). 🚀🚀🚀 We heard you. And we now present a reproducible benchmark comparing different foundation and classical models on 30K unique series. We

Meet nixtla, a Microsoft for Startups startup revolutionizing predictions with Time GPT, announced at #MSBuild! 🌊 Using Azure ML, they're creating models that forecast everything from ocean tides to financial markets with incredible accuracy. ⬇️

"Microsoft for Startups has helped us a lot. It has opened doors." 🔑 Discover how nixtla is transforming time series forecasting with Azure ML and how our support is making an impact: msft.it/6010YU3ye

We’re excited to introduce @ChaiDiscovery and release Chai-1, a foundation model for molecular structure prediction that performs at the state-of-the-art across a variety of drug discovery tasks We're releasing inference code, weights & a web interface: chaidiscovery.com/blog/introduct…

Rayyyk THORChain Flipside 📈 nice dashboard 🔥 amazing to see that you can also bring flipside data into OpenBB out of the box with website widget 👇 - Flipside 📈: circulation info - THORChain: whitepaper manually uploaded - DefiLlama.com: TVL info - nixtla: 120d forecast of thorchain TVL

⏰ 5 ways companies can use time series forecasting Much of the data your company has is already time-stamped. It’s probably sitting in Excel spreadsheets, brimming with potential. Recent advances in AI, such as foundation models, make it possible for smaller companies to

📣 👑 New release of Hierarchical Forecast! 👑 📣 HierachicalForecast offers different reconciliation methods that render coherent forecasts across hierarchies. New release v0.4.3 adds the following features: 🌟 Sparse middle-out reconciliation via MiddleOutSparse:

🔥 🧠 New release of NeuralForecast! 🧠 🔥 NeuralForecast offers a large collection of neural forecasting models focused on their usability, and robustness. The models range from classic networks like MLP, RNNs to novel proven contributions like NBEATS, NHITS, TFT and other

My favorite book for forecasting, now Pythonic! (and its free!) Let's dig into it: - A practical, modern approach to time series forecasting. - Fully reproducible Python code and examples Two new chapters covering recent advancements: - Neural Networks: introduces deep learning

This isn’t just about algorithms—it’s about rewriting how industries predict everything from server loads to stock trends. Will your organization lead or lag? #GDAI2025 #TimeSeriesAI #ZeroShotForecasting #FoundationModels #AIRevolution #DataInnovation #TechLeadership #Future

Today we're announcing that Eventual has raised $30M in Seed and Series A funding from CRV and Felicis as well as Y Combinator, M12 - Microsoft's Venture Fund and Citi and others. The AI era needs data infrastructure built for AI, not retrofitted. 🧵