OpenAI has some big questions. It doesn’t have unique tech. It has a big user base, but with limited engagement and stickiness and no network effect. The incumbents have matched the tech and are leveraging their product and distribution. And a lot of the value and leverage will come from new experiences that haven’t been invented yet, and it can’t invent all of those itself. What’s the plan?
Read MoreHow far do LLMs give us a step change in how good a search and recommendation system can be? Do they let you build one without needing a vast user base of your own?
Read MoreWith every platform shift, we want to measure the growth but we’re confused about what to measure. That’s partly a problem of data and definitions, but it’s really a question about what this is going to be.
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Generative AI chatbots might be a life-changing transformation in the nature of computing, that can replace all software, but so far, most of its users only pick it up every week or two, and far fewer have made it part of their lives. Is that a time problem or a product problem?
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Software ate the world. Uber and Airbnb didn’t sell software - they disrupted and redefined markets. But what kind of disruption are we talking about ?
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It matters that Apple’s new Siri will be late, and it matters more that Apple didn’t realise. Is it more than that?
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OpenAI’s Deep Research is built for me, and I can’t use it. It’s another amazing demo, until it breaks. But it breaks in really interesting ways.
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Every week there’s a better AI model that gives better answers. But a lot of questions don’t have better answers, only ‘right’ answers, and these models can’t do that. So what does ‘better’ mean, how do we manage these things, and should we change what we expect from computers?
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A quarter century after ‘don't be evil’ a judge has found that Google is abusing its monopoly in search. But no-one knows what happens next, and whether this ruling will change anything. Will Apple build a search engine? Will ChatGPT change search? Does it matter?
Read MoreHundreds of millions of people have tried ChatGPT, but most of them haven’t been back. Every big company has done a pilot, but far fewer are in deployment. Some of this is just a matter of time. But LLMs might also be a trap: they look like products and they look magic, but they aren’t. Maybe we have to go through the slow, boring hunt for product-market fit after all.
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