The impact of Artificial Intelligence in industries is huge. It has become one of the driving factors of modern technological development & advancement. Emerging technologies derived from artificial intelligence like robotics, big data, and IoT are enhancing the way of living.
Some of the Crucial Use Cases of AI are:
1. Language Processing: It uses the NLP framework for deciding the format of a sentence from a given set of words.
2. Recommendation Systems: This system filters information to recommend a product or service to a human by observing his/ her online activities.
3. Image recognition: It processes images to identify objects by dividing an image into multiple parts.
4. Language translation: This is used to translate text from one language to another.
5. Object detection: Used to locate a particular object from an image or video.
6. Automatic Speech recognition (ASR): It is used as a speech instruction application for guiding a chatbot. This can also transform audio into subtitles.
7. Speech processing or text-to-speech: It is used for producing human speech from a text
8. High-performance computing (HPC): It delivers a high amount of computing by processing applications in parallel.
First track AI
NVIDIA TAO is a model adaptation of AI. It is a basic structure that helps the AI application to become simple and accelerating. It works through CLI and GUI-based solutions. NVIDIA TAO has a great value for simplifying the time-consuming areas of deep learning workflow like data preparation training, data optimization, etc.
Pre-trained AI models
The NVIDIA NGC catalog offers a whole host of production-ready AI models which have been pre-trained to high accuracy for many domains like computer vision, conversational AI.
Nice and easy to adapt
To produce the customized and production-ready models in hours just adapt the pre-trained models with your data leveraging transfer learning.
Deployment optimization
We can optimize for deployment on the target GPU just by balancing latency and throughput. NVIDIA triton inference server provides you to select the optimal configuration deployment for Any model architecture on a CPU or GPU.
Features of NVIDIA TAO
Easy to train
One of the great advantages of NVIDIA TAO is that it provides easier training. You have to add art AI's state to your application. There is no need for AI frameworks expertise.
High level of accuracy
This is the feature that makes NVIDIA TAO different from others. There are purpose-built pre-trained models Which help to remove barriers and unlock higher network accuracy.
Best Throughput
NVIDIA TAO helps to reduce the cost of deployment. It can get a throughput of high inference.
Anytime and anywhere
The NVIDIA TAO provides the advantage to work on any infrastructure where we locate and compute the data.
Common AI tasks with pre-trained models-
Computer version pre-trained models-
- People detection-
This model helps to detect people, bags, faces in a crowded area, public transport, etc.
- License plate detection and recognition –
It helps to detect the license plate of cars, bikes.
- Action recognition –
It recognizes many common human actions like walking, running, and many more.
- Pose estimation-
It tells about the key joints of the human body.
- Gaze estimation –
It estimates a human's sight by examining their eyes.
- Facial landmark-
It detects a human face and also we can track them by their face shape.
- Vehicles detection and classification –
It points out vehicles and classifies them by their types.
- Human gesture –
It detects the human's hand gestures.
- Segmentation –
It identifies multiple objects in a frame
- Text recognition –
It recognizes a text from an image
- Object detection –
It identifies multiple objects from a frame and draws a boundary box around the object.
- Image classification –
It classifies images by their features.
Conversational AI pre-trained model-
- Speech recognition –
Automatic speech recognition(ASR) takes voices from humans and converts the voices to text. Which is readable.
- Natural language processing –
Natural language processing (NLP) takes texts, processes the text, and finally responds by order.
- Text to speech(TTS)-
It converts written texts to a suitable voice.
E2E GPU cloud provider:
E2E provides NVIDIA GPU cloud computing facilities. Companies and organizations can improve Autonomous Mobile Robots development by implementing Accelerated cloud computing. Hence, E2E cloud GPU servers can help your organization to achieve this task. E2E cloud supported by NVIDIA. Hence productivity can be enhanced in Machine Learning and Deep Learning tasks.
E2E GPU Cloud is powered completely with Tesla V100, NVIDIA T4, NVIDIA A30, NVIDIA A100, and RTX 8000 GPUs. Now, startups and businesses can access GPU with the support of NVIDIA and E2E at an affordable rate.
