As we live in 2019, Data Science and Artificial Intelligence were taking on autopilot in various fields since data getting doubled up each coming years. Data Science reaching a point of becoming mandatory in every business to empower on its own.
Yet, the real side of Data age still in the transition period in the technology life cycle. There are many proven results on AI and Machine Learning making a business learn from the past to predict the future.
Why Artificial Intelligence on CPU important?
Artificial Intelligence has been revolving around a few applicative methods like Machine Learning Algorithms for the recommendation of a product(Amazon, Flipkart), Predicting Credit and Debit card usage by banks, AI cameras in latest phones and also for Vision-based systems for Auto Driving vehicles, Natural Language Processing in making sentiment analysis for customers favoritism and their support to liabilities like social media sentiment analysis.
But, these are more self-centered around the applicative usage of the business cycle. The Big data Analytics and building a predictive model over the years has started growing. The real side of the impact of all these data is found on the CPU where we process it. Since it is untapped. Here comes
Rapids, an open source community working on improving CPU in Artificial Intelligence as the performance of CPU over the years are heavily loaded.
Data Science on CPU will do wonders as proven in last year it doubles up speed by 50x.
HOW?
Python and NVIDIA developers collaborated to work on this as PyCon library have direct access to the BIOS and also a language for Data Science makes way for ease of access.
It provides a Data Science pipe on CPU enables Data Scientists to enforce data workload, data visualization in performance and also Machine Learning models over this will improve performance on autopilot.
What Can be Done?
There are real-time applications on this, as IRCTC websites server increases RAM and ROM based on a number of users logged in Automatically, even Google in the last tech meet expressed a view on never lag Android which is improving the OS on Artificial Intelligence based on Data Science Pipeline.
Cloud-based Architecture of systems will get empower over this solution.
With the growth of Data Science increasing rapidly in every possible way, RAPIDS by NVIDIA is another wing on its domain.
IF U LIKE TO ASK ANY QUESTIONS ---> https://forum.techiebouncer.com
Yet, the real side of Data age still in the transition period in the technology life cycle. There are many proven results on AI and Machine Learning making a business learn from the past to predict the future.
Why Artificial Intelligence on CPU important?
Artificial Intelligence has been revolving around a few applicative methods like Machine Learning Algorithms for the recommendation of a product(Amazon, Flipkart), Predicting Credit and Debit card usage by banks, AI cameras in latest phones and also for Vision-based systems for Auto Driving vehicles, Natural Language Processing in making sentiment analysis for customers favoritism and their support to liabilities like social media sentiment analysis.
But, these are more self-centered around the applicative usage of the business cycle. The Big data Analytics and building a predictive model over the years has started growing. The real side of the impact of all these data is found on the CPU where we process it. Since it is untapped. Here comes
Rapids, an open source community working on improving CPU in Artificial Intelligence as the performance of CPU over the years are heavily loaded.
Data Science on CPU will do wonders as proven in last year it doubles up speed by 50x.
HOW?
Python and NVIDIA developers collaborated to work on this as PyCon library have direct access to the BIOS and also a language for Data Science makes way for ease of access.
It provides a Data Science pipe on CPU enables Data Scientists to enforce data workload, data visualization in performance and also Machine Learning models over this will improve performance on autopilot.
What Can be Done?
There are real-time applications on this, as IRCTC websites server increases RAM and ROM based on a number of users logged in Automatically, even Google in the last tech meet expressed a view on never lag Android which is improving the OS on Artificial Intelligence based on Data Science Pipeline.
Cloud-based Architecture of systems will get empower over this solution.
With the growth of Data Science increasing rapidly in every possible way, RAPIDS by NVIDIA is another wing on its domain.
IF U LIKE TO ASK ANY QUESTIONS ---> https://forum.techiebouncer.com
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