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This is probably why Google or Meta will "win" over OpenAI in the end. They have all the data, and no one else even comes close.
Microsoft has plenty of data too. In Microsoft Teams, LinkedIn posts and messages, and Outlook emails.
> We firmly believe the moat for AI application is in the data and the data engineering today. At some point, the process of building custom LLMs might get so fast and easy that we’ll all return to building our own models. That simply isn’t the case today. Customized small models will outperform larger general models for your specific use case.
No they wont. Any model you train now will be beat by GPT5 easily
While it's possible the gap between GPT5 and 4 is as big as between 4 and 3, it's unlikely. The gap between 2 and 3 was much larger as the one between 3 and 4 (and similarly between 1 and 2).
Also, it's not clear that GPT5 will do this in an *economical way* once the spigot of investor money stops.
It's more than data. Steven Jobs used to tell the founders of the Segway that their secret technologies would leak sooner or later, even if they set up their factories in the middle of a desert in Nevada. His advice to the founders was that they needed to build a product that users couldn't get away from even if all the competitors had the same technology (or so I remember). That could be a process, an ecosystem, market penetration with an amazing supply chain (think about the largest seller of straws in the world. The unit price of a single straw is close to 0, which is really hard to achieve), and etc.
To me, data will just be one key component of the moat but not all. The moat of AI is the same ol' entire ecosystem: an infrastructure that is so efficient that the company can keep driving down the unit price of hosting the AI models; a fabulous culture to enable the company to keep churning out improvements; an extensive data platform and the associated process and sources that keeps provisioning quality data, a number of killer applications...
“What that also means is that you don’t need to be an AI genius to succeed in building applications. With thoughtful software engineering and a focus on customer data, you’ll build a moat over time.” This sounds encouraging at first glance, but even more demoralizing when you think about it. It doesn’t matter how clever or smart you are over your competitors. If you don’t have the data, you don’t stand a chance. And…
I don't see it that way. If you build a genuinely novel application then the critical data doesn't exist yet (IMO almost by definition). Sometimes it's easier for a startup to do this rather than for an incumbent who's trying to shoehorn the application into a preexisting framework (technical, operational, whatever).
Whatever thing people build, will be based on data that exists, not data that will be created afterwards. And guess what, you don't have that data.
> We firmly believe the moat for AI application is in the data and the data engineering today. At some point, the process of building custom LLMs might get so fast and easy that we’ll all return to building our own models. That simply isn’t the case today. Customized small models will outperform larger general models for your specific use case.
But small customized models seem to perform close to as well as large general ones.
Earlier quoted context omitted.
I don't see it that way. If you build a genuinely novel application then the critical data doesn't exist yet (IMO almost by definition). Sometimes it's easier for a startup to do this rather than for an incumbent who's trying to shoehorn the application into a preexisting framework (technical, operational, whatever).
If the data doesn't exist, you can't train an (neural network) AI as they exist today. Whatever thing people build, will be based on data that exists, not data that will be created afterwards. And guess what, you don't have that data.
This is probably why Google or Meta will "win" over OpenAI in the end. They have all the data, and no one else even comes close.
Microsoft has plenty of data too. In Microsoft Teams, LinkedIn posts and messages, and Outlook emails.
Earlier quoted context omitted.
Microsoft has plenty of data too. In Microsoft Teams, LinkedIn posts and messages, and Outlook emails.
Nobody has explained how they could use that data without producing a model that would emit private information.
Microsoft does seem active in this, e.g. https://microsoft.github.io/presidio/
This is probably why Google or Meta will "win" over OpenAI in the end. They have all the data, and no one else even comes close.
Microsoft has plenty of data too. In Microsoft Teams, LinkedIn posts and messages, and Outlook emails.
Unlike googles victims (individuals) corporations can and do fight back when someone plays it fast & loose with their confidential coms