Research Library
Explore our research, benchmarks, and practical guides on enterprise AI and software.
- AI ModelsInsightSep 15
World Foundation Models: 10 Use Cases
Training robots and autonomous vehicles (AVs) in the physical world can be costly, time-consuming and risky. World Foundation Models offer a scalable alternative by enabling realistic simulations of real-world environments. These models accelerate development and deployment in robotics, AVs, and other domains by reducing reliance on physical testing. Explore how World Foundation Models work, their…
- AI ModelsInsightSep 15
Time Series Foundation Models: Use Cases & Benefits
Time series foundation models (TSFMs) are pre-trained models that forecast, classify, impute, and detect anomalies in time series data without requiring a separate model for every dataset or industry. TSFMs use transformer-based architectures and large-scale time-series datasets to generalize across domains such as finance, retail, energy, and healthcare. Discover the architecture, use cases, adoption in…
- AI in IndustriesInsightSep 15
Top 20 Sustainability AI Applications & 7 Tools
By applying generative AI to logistics optimization, demand forecasting, and waste reduction, companies can reduce emissions across their operations beyond the AI systems themselves. Discover 7 sustainability AI tools and 20 applications with real-world examples that leverage AI to build a smarter, more efficient, and more sustainable future. Google AI for Sustainability includes a set…
- GenAI ApplicationsInsightSep 15
10 Risks of Generative AI & How to Mitigate Them
With industries prioritizing generative AI for innovation and automation, its potential grows. However, risks of generative AI like accuracy and ethical concerns remain. Addressing these challenges is key to ensuring AI benefits humanity. Explore the top 10 risks of generative AI and steps to mitigate them: Generative AI tools like ChatGPT rely on large language…
- MLOpsInsightSep 15
Reproducible AI: Why it Matters & How to Improve it
Reproducibility is a core part of scientific research. It allows researchers and AI teams to check whether a result can be obtained again under clearly described conditions. An OECD report on AI in science argues that AI research has not escaped the broader reproducibility crisis. It cites evidence that reproducibility problems have appeared across image…
- AI ModelsBenchmarkSep 15
Compare Relational Foundation Models
We benchmarked SAP-RPT-1-OSS against gradient boosting (LightGBM, CatBoost) on 17 tabular datasets spanning the semantic-numeral spectrum, small/high-semantic tables, mixed business datasets, and large low-semantic numerical datasets. Our goal is to measure where a relational LLM’s pretrained semantic priors may provide advantages over traditional tree models and where they face challenges under scale or low-semantic structure.…