IBM Fast Tracking Enterprise GenAI By Using Their Own Enterprise

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Francis is a well known and established technology industry expert, thought leader and influencer. He has a proven track record of helping clients develop impactful, pragmatic and effective business and product strategies and messaging based on in depth analysis of the current technology, business, economic and geopolitical environment and trends.

OpenAI ChatGPT Opens The Door For You To Make Money By Easily Devising Income-Producing GPTs Based On What You Know Or What Others Want To KnowOver the last century, IBM also known as International Business Machines ushered in an era of productive, practical and most importantly, profitable computing in the business world, changing the way we do business forever.

While the elements for current GenAI capabilities have been in existence since the 1960s when Joseph Weizenbaum developed the first chatbot named ELIZA, it wasn’t until 2017 when transformer networks were introduced that modern GenAI started to take shape. Late 2022 ushered in the dawn of GenAI mass adoption with the release of ChatGPT but most of these early use cases are centered around consumer applications.

However, when an enterprise is one of the most established enterprises in the modern computing era, like IBM is, what better way to rapidly develop and test enterprise class solutions and receiving firsthand knowledge of what works, what doesn’t work, and required bug fixes and enhancements than first using them internally? This is exactly what IBM is doing with their development of enterprise GenAI solutions, and in so doing, has been able to effectively minimize the number of cycles required...

Given that IBM itself is a large-scale enterprise similar to the customers for whom they are developing these solutions, they are organized in similar ways and have identical needs of their potential customers. Consequently, they are able to use internal teams as substitutes for the external alpha, and sometimes beta customers, to reduce the number of development cycles and streamlining the process required for moving from product ideation to general availability.

Tirias Research tracks and consults for companies throughout the electronics ecosystem from semiconductors to systems and sensors to the cloud. Members of the Tirias Research team have consulted for IBM, Nvidia, AMD and other companies throughout the server, AI and Quantum ecosystems.

 

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