Assessing the choices for GenAI information integration together with considerations in your specific company
13 hours ago
While GenAI is super cool, there’s little doubt that the businesses getting essentially the most value out of GenAI have found a way to integrate their very own information with the AI model. What I don’t necessarily see, nevertheless, is a transparent option to take into consideration how an organization should approach its GenAI strategy. You may read things online about how Bloomberg found great value constructing its own large language model (LLM) from scratch, or you would possibly come across as the many social media posts about how great retrieval augmented generation (RAG) is. To be clear, each of those tactics is great in its own right, but as you’ll be able to imagine, there isn’t any one-size-fits-all approach.
That said, this blog post isn’t going to provide you a definitive answer in your company’s situation. Slightly, what our goal shall be is to offer you a framework for methods to take into consideration integrating GenAI together with your company’s information. This post is structured into two high level sections. In the primary section, we’ll give a general high level understanding of what each of the three distinct options there are, stopping wanting the nitty gritty technical details. Within the second section, I’ll provide quite a few specific considerations to take into consideration when choosing one among the choices outlined in the primary section.
Without further ado, let’s get into it!
At a high level, there are three distinct ways that you would be able to leverage your personal company’s data. These include…
- Constructing your personal model from scratch
- Fantastic tuning
- Retrieval augmented generation (RAG)
In the next subsections, we’ll go into more details about what each of those are together with a number of technical nuances for every.
Constructing your personal model from scratch
Similar to it sounds, that is the situation where you construct your personal GenAI model from the bottom up. These are…