Kili and Latent AI have partnered to make edge AI easier to implement by combining high quality data with faster training, prototyping, and deployment. By combining approaches, we can forge a path toward AI solutions that not only overcome current deployment and scalability hurdles but also lay a solid foundation for the future of AI development … Continued
Our recent webinar shed light on the potential of LEIP Recipes to accelerate meaningful results, enhance model optimization, and minimize the time and effort invested in machine learning projects. Recipes are customizable templates within the Latent AI Efficient Inference Platform (LEIP), a comprehensive software development kit (SDK) to simplify and expedite your AI development. By streamlining DevOps for ML through specialized … Continued
Part 1: Optimizing Your Model with LEIP Optimize The Latent AI Efficient Inference Platform (LEIP) SDK creates dedicated DevOps processes for ML. With LEIP, you can produce secure models optimized for memory, power, and compute that can be delivered as an executable ready to deploy at scale. But how does it work? How do you … Continued
The Latent AI Efficient Inference Platform (LEIP) creates specialized DevOps processes for machine learning (ML) that produce ultra-efficient, optimized models ready for scalable deployment as executable files. But how does it work? How does AI actually go from development to deployment to a device? In this series of blog posts, we’ll walk you through the … Continued
Instant decision-making and processing is critical in missions where the slightest delay can have significant consequences. Consider search and rescue (SAR) teams entering disaster zones with limited and incomplete information. As the crisis unfolds, situations can change rapidly. This would require the team to quickly adapt their classifications by also accommodating entirely new elements. Without … Continued
We previously explained Latent AI technology and how it delivers optimized edge models quickly and reliably by comparing it to the Iron Chef competitive cooking show. We’ve talked about how Iron Chef and Latent AI Recipes can be modified to meet regional tastes or specific hardware, respectively. We also touched on what it means to … Continued
Booz Allen Hamilton has selected Latent AI to support the Chief Digital and Artificial Intelligence Office (CDAO) on programs to help build scalability, security, and repeatability into edge AI model development and deployment. As the largest provider of AI services to the Department of Defense, Booz Allen leverages Latent AI to simplify and accelerate traditional … Continued
Latent AI was recently selected by Thales to participate in their upcoming AI@Centech program and recognized as a startup whose AI innovations align with their own market and business opportunities. We are honored to have been chosen out of hundreds of applicants and stand with our fellow three innovators and participants. Thales has successfully executed three seasons of AI@Centech to date, … Continued
Latent AI research regarding dynamically throttleable neural networks was recently accepted for publication by the prestigious Machine Visions and Applications Journal (MVA). Part of the problem with AI has been its inflexibility, especially regarding computing power. Neural networks runtime either fully fire, or not at all. Latent AI research shows how Adaptive AI can respond to its unique environment … Continued
