Foundation models are defined by their massive scale, which enables them to unlock insights trapped in unstructured data, in-context learning through powerful emergent capabilities with zero and few shot prompts, and high versatility with the ability to solve dozens of different tasks with a single model.

Conquering risk requires actionable signal from enterprise data. Discover how modern banks can extend the power of deep learning throughout the business, from customer experience to compliance.

With a model that’s multiple orders of magnitude smaller, the SambaNova GPT model outperforms the leading GPT-175b model in challenging low resource downstream settings, a common enterprise scenario where labeled data is hard to acquire.

Foundation models are defined by their massive scale, which enables them to unlock insights trapped in unstructured data, in-context learning through powerful emergent capabilities with zero and few shot prompts, and high versatility with the ability to solve dozens of different tasks with a single model.

Based on a series of podcast discussions led by Dan Faggella, Founder and CEO, of Emerj, this report highlights the impactful AI use cases discussed with industry leaders and examines the unique business dynamics taking place beneath AI adoption strategies.

Using the capabilities of the SambaNova DataScale® system, researchers at the U.S. Department of Energy’s Argonne National Laboratory and SambaNova partnered on a collaboration to advance state-of-the-art performance of Graph Neural Network (GNN) kernels.

One of the areas where SambaNova sees the biggest application for foundation models and deep learning is accelerating scientific research and discovery across domains like advanced medical research, complex multi-physics simulations, and large scale seismic analysis

Learn how Argonne National Laboratory is using SambaNova’s DataScale system to accelerate AI for science workloads, including large-scale imaging data and large language models.

Over the next ten years, successful banking organizations will evolve from being data-driven to becoming signal-oriented. This paper will look at the functionality that deep learning and foundation models will soon be capable of offering to banking and financial institutions and how this potential can be tapped to reimagine the customer experience.