The funding backs continued innovation in production-grade forecasting, anomaly detection, and artificial intelligence.

Fuzzy time series forecasting models represent a versatile and robust class of predictive techniques that address uncertainty and non-linearity in data. By utilising fuzzy set theory, these models ...

Pre-trained foundation models are making time-series forecasting more accessible and available, unlocking its benefits for smaller organizations with limited resources. Over the last year, we’ve seen ...

In the wake of the disruptive debut of DeepSeek-R1, reasoning models have been all the rage so far in 2025. IBM is now joining the party, with the debut today of its Granite 3.2 large language model ...

OpenAI released a pair of new o-series models, the o3 and o4 mini, that the generative artificial intelligence company said are capable of producing useful and novel scientific ideas. The San ...

Sweden’s central bank, the Riksbank, is embracing a transformative shift in economic forecasting, as recent findings from its Monetary Policy Department reveal that artificial intelligence (AI)-based ...

1. Difference Equations -- 2. Lag Operators -- 3. Stationary ARMA Processes -- 4. Forecasting -- 5. Maximum Likelihood Estimation -- 6. Spectral Analysis -- 7 ...

Solargis’ Evaluate 2.0 platform uses more granular time series data. Image: Solargis. For years, the solar industry has relied on Typical Meteorological Year (TMY) data as the standard for PV ...