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Whereas GenAI is tremendous cool, there’s little doubt that the businesses getting essentially the most worth out of GenAI have discovered a method to combine their very own info with the AI mannequin. What I don’t essentially see, nonetheless, is a transparent approach to consider how an organization ought to strategy its GenAI technique. You would possibly learn issues on-line about how Bloomberg discovered nice worth constructing its personal massive language mannequin (LLM) from scratch, otherwise you would possibly come throughout because the quite a few social media posts about how nice retrieval augmented era (RAG) is. To be clear, every of those ways is great in its personal proper, however as you’ll be able to think about, there isn’t any one-size-fits-all strategy.
That stated, this weblog submit isn’t going to provide you a definitive reply on your firm’s scenario. Reasonably, what our aim will probably be is to give you a framework for a way to consider integrating GenAI together with your firm’s info. This submit is structured into two excessive degree sections. Within the first part, we’ll give a common excessive degree understanding of what every of the three distinct choices there are, stopping wanting the nitty gritty technical particulars. Within the second part, I’ll present plenty of particular concerns to consider when choosing one of many choices outlined within the first part.
With out additional ado, let’s get into it!
At a excessive degree, there are three distinct methods that you could leverage your individual firm’s information. These embrace…
- Constructing your individual mannequin from scratch
- Effective tuning
- Retrieval augmented era (RAG)
Within the following subsections, we’ll go into extra particulars about what every of those are together with just a few technical nuances for every.
Constructing your individual mannequin from scratch
Similar to it sounds, that is the scenario the place you construct your individual GenAI mannequin from the bottom up. These are…
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