The world has entered a new era of AI.
Twenty years ago, the emergence of machine learning ushered in the first era of modern AI and changed how AI systems operate, enabling them to learn how to make future predictions based on historical data. In the 2010s, the deep learning revolution launched the second era of modern AI, which was powered by digital transformation, the availability of exponentially larger datasets, and new types of AI hardware.
Now, the third era of AI has emerged, powered by foundation models. 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.
This combination of scale, versatility and accuracy enables organizations to reduce 1000s of legacy models to a single foundation model with the ability to deliver unprecedented value for organizations and enterprises, including:
Despite all of this impressive capability and business value potential, foundation models are also defined by their cost, complexity, and massive size, which is often hundreds of billions or even trillions of parameters. These challenges make it impractical for most organizations to train and deploy these models themselves.
To overcome these challenges and achieve the benefit of these state-of-the-art foundation models, organizations need to invest in AI technology that delivers value and innovation across the full AI stack: hardware, software, systems, and even pre-trained models.
At SambaNova, that is our singular focus: to deliver innovation at every layer of the AI stack to power the most accurate pre-trained foundation models, deployed anywhere, to help our customers make better decisions, save money, and fuel growth.
To learn how SambaNova delivers innovation that drives value, visit SambaNova.ai.