TechTalk: Analyst Series With IDC, East (Marrch 7th)

If you have been ardently following the exciting developments and innovations happening in the AI conversational world, it is likely that you would have noticed the growing enthusiasm around OpenAi's ChatGPT in the last couple of months.

The AI-based chat system that uses the natural language processing (NLP) technique to stimulate human-like conversation is also capable of telling a story and responding to user queries. This AI tool has become especially relevant across brands whose focal point is maximum customer outreach in a more personalized as well interactive manner.

Since the release of ChatGPT in November, there has been much speculation about the possible killer application of advanced large language models (LLM).

A while back, there were reports that Microsoft will be integrating ChatGPT into its Bing search engine to get ahead of Google. There are also many discussions about something like ChatGPT replacing search altogether.

While I'm not sold on either of those ideas, I think that we're just beginning to explore the huge business potential of LLMs and other generative artificial intelligence technologies.

And Microsoft has the chance to become the big winner of this new wave of innovation that is about to be unleashed. Azure OpenAI Service, now generally available, can be Microsoft's winning card in the race to dominate the fast-growing market for generative AI.

The U.S. National Institute of Standards and Technology will publish the first iteration of its Artificial Intelligence Risk Management Framework Jan. 26.

The NIST described the voluntary standard as aiming to "improve the ability to incorporate trustworthiness considerations into the design, development, use, and evaluation" of AI offerings. A companion AI playbook containing suggested actions, references and documentation guidance is attached to the framework. Finalization follows a public comment period on the second draft of the framework released in September 2022.

As the pace of innovation in these areas accelerates, now is the time for technology leaders to take stock of everything they need to successfully leverage AI and analytics.

Topping the list of executive priorities for 2023-a year heralded by escalating economic woes and climate risks-is the need for data driven insights to propel efficiency, resiliency, and other key initiatives. Many companies have been experimenting with advanced analytics and artificial intelligence (AI) to fill this need. Now, they must turn their proof of concept into a return on investment. But, how?

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