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Latent AI Senior ML Engineer Sarita Hedaya recently discussed the challenges and solutions surrounding edge AI implementations. AI developers, data scientists and ML engineers can spend months trying to find the optimal combination of model and device for their data. Our solutions let users skip the research and start training on their data in minutes, … Continued
Researching which hardware best suits your AI and data can be a time consuming and frustrating process that requires machine learning (ML) expertise to get right. LEIP accelerates time to deployment with Recipes, a rapidly growing library of over 50,000 pre-qualified ML model configurations that let you quickly compare performance across different hardware targets (CPUs, … Continued
Cloud computing offers more operational flexibility than privately maintained data centers. However, operational expenses (OPEX) can be especially high for AI. When deployed at scale, AI models run millions of inferences which add up to trillions of processor operations. It’s not just the processing that’s costly. Having large AI models also means more storage costs. … Continued
In a recent webinar, we 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. LEIP Recipes are flexible templates within the Latent AI Efficient Inference Platform (LEIP) that equip your team with the tools necessary to work with greater DevOps for … Continued
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