AI witnessed to reach an inflection point

#AItechnology has loomed over the horizon and it is here to stay. When someone thinks about the history of computing, we have always been trying to reduce the complexity of our ideas in order to communicate them to a machine and Silicon Valley has been pretty influential in how the algorithmic web we know today was born. But will it also be crucial in how A.I. businesses evolve in the future of technology?

Even when we write a search query, we’re simplifying, we’re reducing or we’re writing in shorthand so that the search engine can understand what we want. The year 2023 is going to be the year that we will expect acceleration of real-world use of AI and machine learning and there will be an even broader range of acceleration chips entering the market and a correlating increase in performance and efficiency.

There is a need to make it simpler to share data between clouds so that training and inferencing activity can be distributed. In fact, it is estimated that by 2025, 88% of servers for AI workloads deployed at the edge will be used for inferencing and the distribution of not just data, but also the AI/ML processing of that data is already underway.

Organizations that ride the second wave of AI will see a distinct competitive advantage as AI becomes able to better perceive, learn and reason – and give developers and data scientists more freedom to deliver applications and outcomes.

Organizations can enhance productivity and efficiency, lower power requirements, and accelerate multi cloud and edge strategies. As the industry matures, AI will also become more democratized as open-source AI becomes prevalent and accessible to larger communities.

AI technology is at an emerging and evolving juncture. India, a growing economy and the second-most populous nation, has a tremendous opportunity to carve its need-specific and robust AI ecosystem. AI can be used both for harnessing information and knowledge and in turn improving

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