LEIP
The majority of MLOps platforms are intricate. Because LEIP streamlines the process, developers of various expertise levels may create secure models incredibly quickly.
- 11.7 times faster inference speed because to NVIDIA Jetson Orin AGX optimisation.
- On NVIDIA Jetson Orin AGX, there is a 10x energy decrease per inference speed.
- 3x GPU RAM reduction on the NVIDIA Jetson Orin AGX.
Make it simple to deploy with assurance and model with certainty.
LEIP Design
AI that is always predictable and easy to use
Simple AI development software that assists you in selecting the ideal AI hardware and model and customising it to meet your requirements.
What is a recipe?
Recipes are tried-and-true setups that eliminate uncertainty when selecting the ideal model-hardware pairing for your project.
Recipes provide a quick and simple approach to get your AI models up and running for developers that need AI modelling tools that will enable them to quickly prototype and refine AI models for edge applications. You can find the ideal model and hardware for your application with the aid of recipes.
Benefits
At the edge, introduce dependable, user-friendly ML solutions.
Give each developer access
Regardless of ability level, create, optimise, and release models to your app.
Use AI models more quickly
Reduce development cycles by getting rid of the uncertainty around testing and evaluation.
Make sure your models are current
Rapid redeployment and retraining using a reliable MLOps pipeline.
Features
Create models that are ready for production quickly.
Easy and fast model design
Bid farewell to speculation! Finding the ideal model-hardware combination for your project is simple with Latent AI’s library of more than 1,000 pre-tested combinations.
- Select from recipes that have been benchmarked for memory footprint, inference speed, and on-device performance.
- You can easily hook your data into any formula.
- Make necessary ingredient additions, updates, and substitutions to your recipes to improve them.
Quick prototyping of any gadget
The robust recipe designer from LEIP Design gives you all the measurements you need to make prototyping simple.
- To satisfy your precise requirements, interactively examine the trade-offs between size, precision, and power.
- Aim for several hardware platforms without having to start the design process over.
- Prior to training, investigate options and confirm viability.
Reuse and retrain in minutes rather than hours
Use AI training software that expedites retraining and redeployment to keep your AI models current.
- Reuse your current workflow to quickly update and retrain your model with new data.
- Use a modular methodology to change hardware targets, swap models, and modify hyperparameters with ease.
- Update the model on edge devices without affecting hardware, applications, or dependencies.
Use LEIP Design to streamline your AI workflow
Latent AI machine learning engineer Sai Mitheran shows how LEIP Design streamlines the intricate process of creating and refining AI models in this video. Find out how to speed up your AI development with LEIP Design’s modular recipes, hardware optimisation features, and rapid prototyping capabilities.
LEIP OPTIMISE
Simplified optimisation of the Edge AI model
Intelligent tools that manage the difficult process of optimising your ML models’ hardware and software.
Presenting Forge
Use Forge to compile and distribute edge AI to a greater number of devices than previously possible.
LEIP Optimize’s core technology, Forge, is your go-to resource for streamlining the process of preparing your AI models for edge devices. It saves you time and effort by automating the challenging and time-consuming processes of quantising and building your models.
Benefits
Faster and device-neutral optimisation
Hasten the testing of hardware
Test and validate your model on additional hardware as soon as possible.
Remove the requirement for hardware knowledge
Regardless of your level of hardware expertise, optimise for a variety of hardware targets.
Obtain a single tool for both beginners and specialists.
Automation that is simple for novices and requires professional control.
Features
Optimise the model-hardware configuration instead of worrying about it.
Use Forge to automate optimisation
With Forge, deploying AI to the edge is simple and effective.
- target hardware without having a thorough understanding of or experience with it.
- Optimise the model and take use of acceleration on your target hardware to increase the performance of edge AI inference.
- Create a single portable file from a machine learning model.
- Create your own tools with Forge.
Support for agnostic models
Integrate your AI model with LEIP Optimise with ease.
- supports the majority of models with dynamic tensors, including transformers, as well as computer vision models.
- Ingest models, including most of the Hugging Face computer vision models, from well-known frameworks like as Tensorflow, PyTorch, and ONNX.
- smooth interaction with your existing machine learning environment to provide you with familiarity and flexibility in your tooling.
Quicken the prototyping process
simplified model-hardware optimisation that speeds up deployment and allows both novices and specialists to prototype quickly.
- Use hardware accelerators to optimise AI models for various target hardware.
- Utilise downsize to operate at lower bit precision (INT8) while maintaining accuracy and speed up model predictions through quantisation.
- tasks including script compilation and optimisation for automation and reusability.
Professional precision control
Tools that let professionals protect and optimise AI models for optimal performance.
- Use the direct graph manipulation tool to change and debug models that aren’t compatible with a particular piece of hardware.
- Investigate the design space for additional edge AI inference optimisation.
- Put watermarks on your models to keep them safe.
Using LEIP Optimise to compress AI models for edge deployment
Adnaan Yunus, a machine learning engineer at Latent AI, discusses the difficulties in implementing AI models on edge devices with limited resources in this video. He’ll demonstrate how LEIP Optimise can help you get past these obstacles by speeding up inference, compressing models, and power-efficiently optimising. See how LEIP Optimise works by watching the demo.
LEIP Deploy
Runtime standardisation for your edge devices
Obtain a standardised, safe runtime engine to provide seamless edge deployment.
Edge-powered AI models
The Latent Runtime Engine simplifies the deployment and administration of edge AI models.
Use a single runtime engine to update your built models, deploy to various hardware devices, and track performance. Without altering a single line of application code, you can adapt to real-world situations and handle a diverse hardware environment with a uniform, universal API.
Features
Use a lightweight, secure runtime designed for the edge to standardise the deployment of AI models.
Installation without friction
All of your devices should have a single runtime installed.
- Multiple hardware platforms, such as NVIDIA Jetson Orin and Xavier, Android Snapdragon, CUDA, ARM, and Linux-powered x86, can use the standardised runtime.
- Modify or swap out models without affecting your runtime engine.
- a single API for simple third-party application integration.
Integrated model security
With AI development software’s sophisticated safety measures, you can keep your models safe and secure.
- By using digital watermarking to prevent unauthorised usage or distribution, you may validate the provenance of models.
- Use an encrypted runtime to prevent models from being stolen or compromised.
- Maintain model integrity and guard against version tracking manipulation.
Track the generation of AI models
Use real-time diagnostics and extensive monitoring features from a single development platform to guarantee optimal model performance.
- Use real-time diagnostic metrics to assess performance during deployment in a seamless manner.
- Modify or swap out the model without altering your application.
- Models may be easily transferred across platforms to cross-hardware compatibility.
Use LEIP Deploy to streamline AI deployment
In this video, Latent AI embedded engineers Puru Saravanan and Natalia Jurado show how to use LEIP Deploy to quickly and simply deploy AI models to a variety of edge devices. Discover how to use LEIP Deploy to guarantee dependable performance, expedite inference times, and simplify the deployment process.
Benefits
Both novices and professionals will find it intuitive
Complex AI jobs are simplified by LEIP tools, which make it simple for novices to get started and for specialists to work effectively. The tried-and-true setups give you fine-grained control over each stage of the machine learning process and enable you to rapidly generate production models. You can build, test, and iterate without specialised hardware knowledge because everything is preset.
Create, evaluate, implement, and repeat
For machine learning programs to scale, repeatability is crucial. Because LEIP encourages reuse at every level, you may build a dependable pipeline for simple upgrades and retraining. You can easily track the settings applied to all model versions and hardware targets while saving, sharing, and modifying your workflows. Additionally, it standardised runtime engine guarantees a seamless redeployment when it’s time to release changes.
quickly adapts to your current configuration
LEIP minimises interruption and gives your development teams the ML tools they need to be successful by integrating easily into your current ML environment. You can utilise LEIP to develop ML solutions that suit your needs, regardless of whether you have a dataset to start with or an existing model in use. Additionally, LEIP’s versatile, modular tooling can be adjusted to meet your evolving demands if your configuration changes.