Latent AI launches LEIP 3.0 to revolutionize edge computer vision design, deployment, and management

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Latent AI launches LEIP 3.0 to revolutionize edge computer vision design, deployment, and management
Latent AI launches LEIP 3.0 to revolutionize edge computer vision design, deployment, and management

LEIP 3.0 slashes time to deployment with built-in expertise to build and deploy high-performing computer vision models at scale.

“LEIP 3.0 marks a pivotal shift in how computer vision can be designed, trained, and deployed at scale on edge devices,” said Jags Kandasamy, co-founder and CEO of Latent AI.

SKILLMAN, NEW JERSEY, UNITED STATES, February 7, 2024 /EINPresswire.com/: Latent AI, a leader in solutions to design, deploy, and manage computer vision on the edge, today announced LEIP 3.0, the latest version of the Latent AI Efficient Inference Platform. LEIP 3.0 revolutionizes how both federal and commercial organizations can drastically reduce their computer vision time to deployment while also reducing the knowledge required to deliver effective models at scale.

AI is designed to work, but not necessarily on a specific hardware target. LEIP 3.0 accelerates time to deployment with Recipes, a rapidly growing library of over 50,000 pre-qualified model configurations that let you quickly compare performance across different hardware targets (CPUs, GPUs, FPLAs, etc.) to find the best combination of model and hardware for your data.

“LEIP 3.0 marks a pivotal shift in how computer vision can be designed, trained, and deployed at scale on edge devices,” said Jags Kandasamy, co-founder and CEO of Latent AI. “Instead of months of trial and error, users can now find their best model to use and understand how it will perform on their hardware before they even start training on their data.”

LEIP 3.0’s new and enhanced features include:
A groundbreaking, ultra-fast approach to designing AI models that lets users start training on their data in minutes
A database of over 50K pre-evaluated configurations for the latest state-of-the art models, including YOLOv8
The ability to design and build your own shareable and repeatable model configuration Recipes
Streamlined evaluation across various model families with consistent Python APIs
An enhanced runtime engine with services for analytics to improve performance and security to ensure data privacy
Support for both on-premise and private cloud for enterprises
built-in hardware and performance expertise that enables non-ML experts to succeed
A modular approach that lets you enter at any point of the MLOps workflow and integrate your existing tools and processes
An industry-first ability to calibrate int8 for precision and speed

LEIP 3.0 delivers faster time to deployment while also solving the most common challenges that ML practitioners face. Sek Chai, co-founder and CTO, said, “LEIP 3.0 lets you focus on development and performance, not hardware and configuration. Instead of wasting months and months building both an ML pipeline and solution, LEIP 3.0 gives you what you need to move your model to deployment far faster with well-qualified starting points for various system choices and the dedicated processes necessary to scale edge trust and performance.”

LEIP 3.0 is engineered to optimize and scale every aspect of edge ML development while also building in the processes necessary to manage and tune it. It’s DevOps for ML that casts computer vision design, deployment, and management into familiar software development cycles of reliable and repeatable processes.

With LEIP 3.0, users can fine-tune models based on their specific requirements, including how long a specific model on a specific hardware target will take to train, its necessary inference speed, and its memory and power usage. And it generates fast, accurate, and low-footprint model executables that are easy to scale and designed to work on the edge.

Join our webinar on February 29 at 2 p.m. EST to learn how you can deliver edge AI solutions faster than ever before with LEIP 3.0. Click here to register.

Also read“Fail Fast Learn Fast and Move On”

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