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> They are referring to it as “fine tune models with specific purposes and glue them together with normal code”. > will be technically out competed by their co
by bob1029 3y ago
> They are referring to it as “fine tune models with specific purposes and glue them together with normal code”.
> will be technically out competed by their competitors because fine tuned models are better.
I disagree that fine tuning is the way to go. We spent a large amount of effort on that path and found it to be untenable for our business cases - not from an academic standpoint, but from a practical data management/discipline standpoint. For better or worse, we don't have super clean, structured data about our business. We also aren't big enough to run a full-time data science team.
Picking targeted feature verticals and applying few-shot learning w/ narrowly-scoped, dynamic prompts seems to give us a lot more value per $$$ and unit time. For us, things like the function calling API are fine-tuning, because we can now insist that we get a certain shape of response.
I have a hard time squaring an implied, simultaneous agreement with "supermodels are generally not the right approach" and "fine tuned models are better". These ideas seem (to me) to be generally at odds with one another. Few-shot learning is still the real magic trick in my book.
- lhnz 3y agoI think this is exactly the kind of issue that the startup Klu [0] is trying to solve. Not everybody should be building their own custom toolchains for finetuning/prompting AI models and there is really quite a lot of work involved in data management/evaluation. There's definitely a lot of value in adding some AI features into your applications, but if it's not your core business you shouldn't be spending a lot of your time building a toolchain to do so. [0] https://klu.ai https://klu.ai
- meiraleal 3y ago> and there is really quite a lot of work involved in data management/evaluation This is boring tech already, we have been doing it for the past 2 decades in the web with CRUD. It doesn't make sense to be an openAI + VC-backed tools wrapper
- lhnz 3y agoI don't agree. You should be collecting data, running experiments and A/B tests and finetuning your own models, but you shouldn't be building CRUD apps to automate this yourself, even if you have two decades of experience doing so. You shouldn't be building out this stuff yourself, unless you are a massive business that can afford to, or it's the core of your business.
- meiraleal 3y ago> You shouldn't be building out this stuff yourself, unless you are a massive business that can afford to, or it's the core of your business. I think there is space for both reasoning. What led me to start creating my own framework on top of Lit because what's is available with the tech I know the most (React) has become utterly garbage recently. I don't like the direction it is going and I would recommend most companies to reevaluate their usage of React and then all the CRUD and things around it. Reinventing the wheel is what prevents monopoly in software development.