Generative AI: The Race Where The 'Slowest' Wins

Responsibility, caution, transparency, checks and control could be the new set of criteria for winners in an otherwise pound-for-pound game. Why is Generative Al going to be a different race track in the enterprise Olympics and would everyone play ball?

At a packed hall of eager eyes and hungry ears at the TrailblazerDX conference, Sarah Franklin, President and CMO, Salesforce announced their own Al baby in the form of Einstein GPT. But she did not hesitate in explaining that: We want to build the future with Al in a way we are proud of. There are a lot of questions about control, about governance and who makes the algorithms. These are important to address along with the productivity gains expected. The same day a panel on Al Ethics talked deeply about how Salesforce is cognizant about issues like explainability, about the trade-off between speed and creativity with Al models and about customer's data.

At the time of writing this article, Sam Altman was heard speaking with the same caution. He appeared patient in his interviews, where he was commenting on an open letter (by Tesla CEO Elon Musk, Apple cofounder Steve Wozniak and other signatories) asking companies such as OpenAl to pause development of Al systems more powerful than GPT-4.

Altman gave an assurance that his team wants to deliver the most capable and useful and safe models. He also cited how the team had spent more than six months after it finished training GPT-4 before releasing it. Speed was kept on the back-burner and priority was given to time to really study the safety model, to get external audits etc.

IT'S A BOBSLEIGH

Close to the heels of these news bytes came news from Google's lair-when its Al appeared to have been able to translate an unfamiliar language (Bangla) with very little prompting in Bangla. In media reports, CEO Sundar Pichai acknowledged this black box aspect to Al.