The more you hear about people talking about today’s new technologies, the more you realize that AI is going to be a comprehensive enabler for disruption. There is also the idea that people are either going to be disrupted themselves, or be leading a new kind of disruption, so people are hungry for advice about how to use the products of generative AI to their advantage!
Video: Lots of good thoughts that can guide innovation companies
With that in mind, this is an exciting talk – we learned a lot from Sam Altman when we got him teleconferencing in. Here are some of the highlights you can think about when you’re at the drawing board, trying to figure out the next step forward, looking at the products of neural networks, and pondering what AI/ML can do (and maybe what it should and shouldn’t do.)
Starting out, Sam reminds us that even though AI is a game-changer – (he also calls it an enabler) – some business principles still remain the same.
“Nothing lets you off the hook for building a product that people love, for being very close to your users, for thinking about a long-term, durable business strategy,” he says.
And although he’s initially pretty modest when I ask him about business advice, he does end up coming up with some pretty important tips for new entrepreneurs:
First, he says, let tactics become strategy, and not the other way around.
He also recommends a tight feedback loop, with a lot of user observation and collaborative testing.
And, he says, it’s important to keep developers “super happy.”
Going deeper into the process of being deliberate with development, we talk about his experience in blazing a trail with new tech, and at how things have worked at OpenAI.
“We’re actively reconsidering what customization to prioritize,” he says, in talking about pivoting with user environments and generally choosing from a set of goals or alternatives.
Suggesting we might be at the end of an era of giant models, Sam posits this thought – what if we’re currently missing one big idea that will make tomorrow’s disruptions even bigger than what we’re experiencing now with chatGPT and everything else?
He recommends “capable, useful and safe models” and a cautious approach.
We also discuss what’s likely to happen as humans go blundering through this new world.
“Even the details of how we’re right, we’ll be wrong about,” he predicts.
You can also check out the part where I ask him about the industry letter to legislators asking for a pause on AI development. Given that there’s a pretty broad consensus about the need for some sort of oversight, this is a question that a lot of our listeners were probably hanging on to hear.
First, Sam points out that OpenAI has always had a strategy of deliberate review.
It’s crucial, he contends, to take time to study a model, and in his response, you get the idea that there are more fundamental ways to self-assess development that have less to do with legislators (who often don’t know a whole lot about technology) trying to police the space.
In other comments, Sam talks about a long-term horizon for capital-intensive business, what that means for young career professionals, and how to tackle the big questions inherent in an AI-enabled enterprise environment.
Those are some of the things we talked about in a rollicking half hour of contemplation about what all of this brand-new development will do to the business world, and for the business world.
You owe it to yourself to watch the whole video and the interplay between Sam Altman, me and the crowd as we explore these scintillating ideas…
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