Specialized LLMs / LSTM

Specialized models that are tailored to specific domains and tasks combined with distributed (federated) data processing. These models can leverage domain-specific data and knowledge to achieve higher accuracy and efficiency than big LLMs. And, more important, these models can be more transparent and explainable, allowing users to trust and control them better. The user has control over the data used to train these models, makes sure that no IP is exposed and, used in a correct way, reduces generative introduced bias.

Smaller, but specialized models are AI models that are trained and fine-tuned on smaller amounts of data that are specific to a certain domain or task.

Federated Data Processing for LLMs

With Blossom Sky, users can benefit from the best of both worlds: the generality and scalability of LLMs and the specificity and interpretability of smaller, but specialized models. Blossom future-proofs any analytics architecture by separating data storage and processing, allowing it to better use best-of-breed BI apps now and in future. Blossom also delivers the efficiency and flexibility to expedite time to insight with high concurrency through federated cost-based query optimization.

LSTM models

LSTEnergy - Energy Consumption Forecast