Transform Your Data Privacy with SambaNova Systems

Posted by Keith Parker on May 29, 2024

As enterprise and government agencies strive to power more innovation, drive operational efficiency, and differentiate through transformative insights, many are leveraging cloud-based  AI models. To derive valuable insights from these  models, an organization must use its private data for training. This process poses challenges to data security, privacy, governance, and ownership. Mitigation of these challenges is especially critical for organizations in heavily regulated industries.

According to Deloitte, in January 2024, “41% of leaders reported their organizations were only slightly or not at all prepared to address governance and risk concerns related to generative AI adoption.”  Organizational leaders should take the following challenges into consideration when selecting the best generative AI solution for their needs.

Public Access to Private Corporate Data

When leveraging a cloud-based model, restricting data access is a persistent challenge. Once an organization’s private corporate data gets into a public model, any user can view it, or leverage new insights from it. Additionally, since the organization does not own the model that has been trained by its data, a competitor could  acquire the model—and, consequently, the proprietary information on which the model has been trained. Both scenarios expose the organization to significant data privacy risks and compromise its competitive edge.

Some cloud-based model providers offer safeguards, such as making a dedicated instance of the model available to customers. However, the fact that private corporate data is being sent to a third party will likely violate corporate data governance policies. To be clear, this is not the same as moving to a private cloud, it is moving the data to someone else’s private cloud.

Further compounding the issue for enterprise organizations is the ability to maintain data governance within the organization. In any large enterprise there is a need to maintain control over sensitive information, even internally. With traditional data systems this is handled through access controls. Cloud-based AI models do not have a method of controlling access to data so anyone with access to the model can access any data within it.

Unwanted Restrictions as You Grow

With cloud- based model providers, even when a model is trained on an organization’s private data, the provider owns the model, virtually locking the customer into that vendor relationship. The more an organization uses the model, the more customized it becomes, further enforcing a commitment that may not suit an organization’s long-term needs.

Conquer Data Privacy Hurdles with SambaNova Solutions

As the leading generative AI solution of its kind, SambaNova helps enterprises and government agencies address these common data privacy hurdles in several critical ways.

Own Your Data and Your Model

With the SambaNova solution, you retain exclusive ownership of the model that has been trained on your data and the data itself. It remains private and legally your intellectual property. This approach enables the model to function like an investment. Organizations can reap long-term benefits as the model learns your business, your customers, and your processes—allowing it to increase in value organically and exponentially over time.

Role-based Access Controls

The unique nature of Samba-1, the trillion parameter model from SambaNova based on a Composition of Experts architecture, provides role based access controls to maintain existing data governance policies. This ensures that only those with the proper permissions have access to sensitive data.

Experience an ROI that is Ten Times Greater than its Competitors

SambaNova is distinguished by its full stack solution. SambaNova empowers organizations with the flexibility to deploy the model in the cloud or on-premises, so data never has to leave the customer environment.

The solution optimizes performance for greater speed, operational efficiency, and a smaller footprint. Whether it be diagrams, images, charts, or content from various sources within an organization, SambaNova can efficiently analyze both your structured and unstructured data with ease. These features, combined with the small footprint of the SambaNova platform  and the inference efficiency of Samba-1 enable SambaNova to consistently deliver an ROI 10 times better than its competitors.

Learn more about how SambaNova delivers the first generative AI platform with enterprise grade data privacy and security.

Topics: business, Blog