Toto 2.0: Time series forecasting enters the scaling era
For the first time, a time series foundation model gets reliably better with scale—five open-weights sizes from 4m to 2.5B parameters, trained from a single recipe.
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For the first time, a time series foundation model gets reliably better with scale—five open-weights sizes from 4m to 2.5B parameters, trained from a single recipe.
ARFBench is a time series question-answering benchmark built from real Datadog incidents to evaluate how well AI models can reason about anomalies.
Learn how Datadog verifies AI-generated systems at scale using deterministic testing, formal methods, and observability-driven feedback loops.