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Category: Innovation at the Edge

Design, optimize, and deploy your edge AI

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

Find your best model using LEIP recipes

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

Reduce your AI/ML cloud services costs with Latent AI

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