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GPUs help build smartest AI systems and startups

Want to build smart artificial intelligence systems or even an AI startup? Can you involve a graphics processing unit or GPU to meet your goal?

Yes, you can!

AI has been evolving at a higher pace. It is poised to become one of the most impactful technologies that humanity has ever created, boosting us, and also giving us the ability to solve problems that were  once thought to be unsolvable!

Intelligent AI systems are being built having innovative algorithms and models that predict and prescribe the outcomes accurately, which are powered by essential:

a) underlying HPC compute platform,
b) computes ability to interface and self-tune at device level,
c) associate and bind necessary built-in multi-matrix operations, and
d) effectively tweaking the run-time environments on the fly, for the desired outcome.

GPUs for AIPradeep Chakraborty | voicendata

GPUs help build smart AI systems.

GPUs and its closely-coupled platform plays a key role in building the smartest AI systems and successful AI startups!

While GPUs are equally important, its also essential to have the GPU platform associated with the underlying key components fulfilling all the dependencies, in order to expedite the AI startup journey toward success. Specifically, if the AI startups are empowered with the GPUs and the platform with the features mentioned below:

Key GPU and associated platform components for a successful AI startup:
* Instant access to the industry datasets from various repositories such as UCI, Kaggle and research institutes.
* Access to set of well-known ML algorithms to jumpstart the AI model development.
* Easy access to auto detect the relevant model applicable to the dataset of your interest.
* Platform to link the trained model to the end-customer through globally accepted protocols, such as REST and RPC.
* Customized and AI-based DevOps to manage the AI model lifecycle.
* Collaboration options to share the cost and simplified pricing through the AI model lifecycle.

Selecting appropriate mix of hardware platform, software mix, frameworks, access to the datasets, models and pipeline, along with simplified pricing for base models, industry models, customer model, and end-user models, is the key to being a successful AI startup.

— Shridhan Rokade, Founder and CEO, GPUONCLOUD.


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