The Next Era of Artificial Intelligence for Businesses
Microsoft, a leading tech giant, is encouraging enterprises to transition from proof of concepts (POCs) to developing their own AI models. With advancements like the RAG (Retrieval-Augmented Generation) approach and fine-tuning techniques, Microsoft believes that now is the perfect time for businesses to move forward and embrace AI technologies.
Rohini Srivathsa, the CTO of Microsoft India and South Asia, addressed the rapid innovation and agility in the AI landscape over the past year. While AI has been surrounded by hype, Srivathsa acknowledged that it is not a new phenomenon. From analytics to machine learning, deep learning, foundation models, and now generative AI, AI has continuously evolved. She emphasized that generative AI won’t be the last invention in this field.
Developing an Effective AI Strategy for Businesses
To build a successful AI strategy, it is crucial to have a clear understanding of the term “AI” itself. Srivathsa explained that AI models have evolved to the point where a large language model can solve mathematical problems. AI is no longer limited to backend processes; it has become an accessible user interface. As an example, Srivathsa mentioned ChatGPT, which millions of people can interact with.
These language models have acquired “emergent capabilities” as they are now trained on vast amounts of data. Srivathsa highlighted that these models exhibit reasoning abilities. They can analyze information from text and provide concise responses to prompts.
In order for businesses to harness the potential of AI, Dr. Srivathsa emphasized the importance of adopting the right approach. She stressed that companies should focus on their business needs and goals when considering AI adoption. This begins by selecting a specific use case, such as content generation, summarization, code generation, or semantic search. Then, companies can build a niche within that use case, like applying summarization in the legal or medical field.
Dr. Srivathsa emphasized the need for clarity regarding the business problem AI aims to solve. The problem and solution should be measurable. She also suggested taking a portfolio approach, as not one program or product can meet all business needs, and requirements may change over time.
When developing a technology strategy, many companies are faced with the decision of building custom models or fine-tuning existing ones. According to Gartner’s analysis, over 80 percent of companies are engaged in building pre-trained models. Dr. Srivathsa mentioned that the company’s data estate, scale, security requirements, and amount of data are key factors to consider when deciding on an approach.
AI and Microsoft
Microsoft is heavily investing in AI technologies, with Copilot being a significant part of their strategy. Copilot is being integrated into various Microsoft products, and it has already been integrated into the Microsoft Office suite. Furthermore, Microsoft is enhancing Bing to be a more effective search engine. The chatbot associated with Bing is designed to provide contextual information with relevant links, further enhancing search experiences.
In her discussion about Microsoft’s flagship search engine, Dr. Srivathsa highlighted that Bing is evolving to offer more than just search results. It now provides context, facilitates conversations, offers indices, and lists the sources of information.
Dr. Srivathsa concluded the conversation by emphasizing Microsoft’s dedication to AI responsibility. The company has closely examined existing laws and formulated policies to ensure the security of user data. Microsoft Research is fully committed to AI responsibility, consistently working on engineering and advancing these systems.
Editor’s Notes
It is evident that AI is rapidly transforming the business landscape, and Microsoft is playing a significant role in this transformation. The key takeaway from Dr. Srivathsa’s insights is the importance of businesses adopting a strategic approach when integrating AI technologies. By carefully selecting use cases, building niches, and measuring the impact, organizations can effectively leverage the power of AI to drive growth and innovation.
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