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Toto: Time Series Optimized Transformer for Observability
Datadog’s new AI model, Toto, marks a major leap in time series forecasting for observability. Designed with a focus on accuracy,...
Google DeepMind Taught an AI to Tame a Star: Here's What It Means for the Future...
A team from Google DeepMind and the Swiss Plasma Center published their work on using a Reinforcement Learning (RL) agent to contr...
Senators Reaffirm Commitment to Market Structure Bill After Meeting with Coinbas...
Senate Democrats and Republican lawmakers have ended separate roundtable meetings focused on the Crypto Market Structure Bill. The...
Wall Street Grammar: How the Way CEOs Speak Moves Billions Before You Notice
Markets react not only to meaning but to form. The Syntactic Authority Index reveals that specific sentence structures—like “must,...
The Importance of Disentanglement: SAGE Outperforms Unified VQ-VAE Baselines in...
This article presents an ablation study confirming that disentangling motion latents into upper and lower halves significantly enh...
How the Crypto Market Could React to the Next Fed Meeting on October 29?
The crypto market has, for a while now, been pricing a potential 25 basis points (bps) rate cut at the October 29 Fed meeting. Thi...
Toto AI Model Sets New Benchmark for Time Series Forecasting
Toto, a pre-trained time series foundation model, delivers state-of-the-art performance across Long Sequence Forecasting (LSF) and...
Quantitative and Qualitative Results: SAGE Outperforms SOTA in Full-Body 3D Avat...
This article presents the quantitative and qualitative results for the SAGE model across three evaluation settings
JUST IN: Ethereum Foundation Moves Entire $650M+ Treasury To Safe Multisig
The Foundation has completed the migration of its full treasury, over 160,000 ETH worth approximately $650 million to Safe. Safe i...
Fixing Web3 Marketing: What Channels Actually Work in Web3
Web3 marketing can’t rely on hype or a single platform. To succeed, projects need a multi-channel strategy combining X/Twitter for...
Quantifying Motion Accuracy: MPJRE, MPJPE, and Consistency Metrics for HMD-based...
This article outlines the evaluation metrics used to benchmark 3D avatar reconstruction models on the AMASS motion capture dataset...
Temporal Refinement in Stratified Motion Diffusion: Utilizing GRU for Smoothed F...
This article describes the online inference stage of the model, which predicts 3D avatars in a frame-by-frame manner using a slidi...
