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While it may feel like we have been moving far and fast with AI, in reality we have been only exploring the foothills of this transformative technology. Now, we are on the edge of an era of Pervasive AI, when AI will become a core technology to everything, much like the Internet is today. In the 1990s, we saw glimmers of the internet’s potential, and now it underpins everything – how we work, consume entertainment, order goods and services, and every other aspect of business and society. This is the kind of impact that AI is about to have – only faster.
To date, organizations have used hundreds or even thousands of small models, each trained to perform a specific task. These small models are difficult to manage, expensive to maintain, and often do not work with each other. Large language models (LLMs) have made it possible for enterprises to use fewer models, each capable of replacing dozens of smaller models to reduce cost and complexity while also increasing their ability to generate valuable content. This capability is enabled by the sheer size of the models, which often contain tens of billions of parameters.
As we enter the era of pervasive AI, the accuracy demanded by enterprise tasks means that LLMs will need to have trillions of parameters. These models will be composed of hundreds of smaller models, all working together as a Composition of Experts model, which provides a high degree of modularity and extensibility. This will be the next generation of model architecture.
Today, a large language model will be capable of accurately summarizing a document such as a contract or reading and interpreting an image such as a medical scan, but they are limited in that as they become better in one function, such as finance, they lose capability in others, such as legal.
When models reach a trillion parameters, these limitations can be reduced or eliminated. The upside is that only a few of these very large models will be required for even the largest enterprise and they will be able to connect functions, such as finance, legal, operations, marketing, people ops, and more across the organization for unprecedented levels of efficiency.
AI will be multimodal, capable of ingesting and analyzing a broad range of data sources, including voice recordings, images, and text among others. It will be able to do this across a range of languages, a critical capacity for global organizations.
But delivering this capacity means that new capabilities are needed. Powering very large models across an enterprise organization requires a hardware platform that has been designed for AI at scale, so that the models can be run on a small, optimized footprint instead of ever-larger clusters of GPUs. That platform needs fully-integrated software that can optimize the models to run on the hardware and to manage and maintain the models. The models themselves will have to be open source, both to provide organizations with the explainability they will need to serve regulated industries, as well as to ensure that every company has the right to the IP they build in their own models. Finally, the platform will need to connect AI models to enterprise workflows in a seamless manner. Ultimately, this will require an integrated hardware-software, full stack platform, purpose-built for AI.
Today, there is such a system. The SambaNova Suite, the only full-stack, fully integrated platform, purpose-built for generative AI, and optimized for enterprise and government organizations. Available on-premises or in the cloud, SambaNova Suite is powered by the revolutionary SN40L chip and delivers state-of-the-art Composition of Expert models that can be adapted with customer data for greater accuracy.
Welcome to the era of pervasive AI!
