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Kamal Arora
Kamal Arora

The convergence of AI and HPC is beneficial because: 1) HPC systems generate large amounts of data that AI can help make sense of. 2) There is increasing overlap between AI and HPC tools, workflows, and outcomes. 3) Momentum from previous data analytics and HPC convergence is driving further integration of AI capabilities.

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3 Reasons Why convergence of AI & HPC is the future of businesses PRESENTED BY TYRONE SYSTEMS
AI techniques are increasingly being used to digest this enormity of data and transform it into more human- friendly formats. In theory, you could do this AI processing as a separate operation on a separate system custom-built for AI workloads. HPC systems are generating more data, and AI is helping us make sense of the data.
Now with AI, even though we have practitioners on either side of the fence, there is more overlap than ever in terms of the tools, workflows and, most interestingly, outcomes. Momentum from HPC and data analytics convergence is leading the way for AI convergence.
Its somewhat debatable, but ML has had a greater adoption with enterprise users who are already familiar with the analytical techniques ML is based upon. DL, on the other hand due to its reliance on large sparse matrices and numerical algorithms has always had more in common with traditional HPC users. AI systems architectures are beginning to scale out.
Our Social Pages FACEBOOK www.facebook.com/tyronesystems TWITTER www.twitter.com/tyronesystems BLOG www.blog.tyronesystems.com When it comes to the HPC, we have over 20 years experience building the most complex HPC infrastructure Learn more: https://netwebcsp.com/hpc-on- cloud-service/

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  • 1. 3 Reasons Why convergence of AI & HPC is the future of businesses PRESENTED BY TYRONE SYSTEMS
  • 2. AI techniques are increasingly being used to digest this enormity of data and transform it into more human- friendly formats. In theory, you could do this AI processing as a separate operation on a separate system custom-built for AI workloads. HPC systems are generating more data, and AI is helping us make sense of the data.
  • 3. Now with AI, even though we have practitioners on either side of the fence, there is more overlap than ever in terms of the tools, workflows and, most interestingly, outcomes. Momentum from HPC and data analytics convergence is leading the way for AI convergence.
  • 4. Its somewhat debatable, but ML has had a greater adoption with enterprise users who are already familiar with the analytical techniques ML is based upon. DL, on the other hand due to its reliance on large sparse matrices and numerical algorithms has always had more in common with traditional HPC users. AI systems architectures are beginning to scale out.
  • 5. Our Social Pages FACEBOOK www.facebook.com/tyronesystems TWITTER www.twitter.com/tyronesystems BLOG www.blog.tyronesystems.com When it comes to the HPC, we have over 20 years experience building the most complex HPC infrastructure Learn more: https://netwebcsp.com/hpc-on- cloud-service/