Greg Howe (also a former MVer, now shifted to AI as I have for the most part) posts frequently in LinkedIn on this topic and offers related consultation and services. I encourage everyone to check out his posts there, learn from a colleague, and translate his tips into your applications for fun and profit.
From my point of view, here is the rough evolution that I think people go through with this:
- ChatGPT : The Hello World of chatbot applications and OpenAI's gateway drug to the realm.
- CustomGPTs : Entry-Level opportunity for people to create a custom knowledge bot or creative agent with optional code interface. (My wife and I create these for fun.)
- Completion API : First Hello World stop for all developers to code an exchange with a LLM.
- Assistant API : First step beyond "wow, that was cool". Essentially Custom GPTs via API and without the UI.
- Embeddings : Next step toward "how do I use this with my own data" ... On-ramp for databases and knowledgebases.
- RAG : Serious developers' paradigm for really using the tools interactively with data and logic.
- Agents : Pro stuff - making it look intelligent without it actual AGI. Workflow, decisions, async processing : Borg Collective.
- Multi-modality - Enhancing UIs with audio I/O, image I/O, now video I/O, and more...
"AI" is still just a Marketing buzzphrase. All it is now is text-processing, predicting which word should come next in a sentence. There's no "intellegence" at the application level.
The current technology only looks smart with RAG and Agent architectures. In a year or two it will be different with AGI, and the average person might be a little closer to separating one concept from another. Where it is now, it's still relatively easy to hop on the train, and if your clients will pay for that, there should be no objections to providing it.
Most of the products that claim AI these days are based on some variation of the Completion API. As Dawn said, the serious players soon realize that there is much more to this, and they move forward. I saw the LLM interface in Informer some months ago at Dawn's invitation, and it was truly impressive. I encourage everyone to take a look - it will only get better. If you want to offer your clients the letters "A.I." and you don't want to have to write code, definitely look into what Entrinsik is doing with Informer and "smart" reporting.
In my past life here I would be talking about AI with MV. Today, I
note that there's near zero mention of the topic anywhere in the MV industry, which is exactly why I had to shift away. That continues to be painful and I wish it were different. On the bright side, as with all other tech
that we have encountered over these decades, I just want to convey that this is yet another technology that absolutely can work with any MV-based application. Just do your market
research to identify demand and cost-justification, then use the same
techniques that I've talked about over the years.
For all of us who have trouble figuring out where to hop on the train and what to expect, as always I'll be direct. This one isn't easy by a long shot - but it's still do-able. The APIs and capabilities of all of this stuff are rapidly changing. It's tough to keep up because New becomes Old within weeks. Best Practices and Design Patterns are evolving very quickly - as soon as you catch on to "this is how it's done" it changes, and there are suddenly better ways to do things and more platforms that claim to be better suited. For example, Fine-Tuning was the defacto practice for data-enabling a LLM, until the disadvantages were quickly and commonly recognized. Embeddings became popular, and now as people shift away from the LLM (and GPT) as being the main focus of all of their attention, multi-LLM environments with are common to support even small applications. RAG just means "data integration" and it's becomming a sub-industry in its own right. Most people aren't into agents yet. It's very complex and too new - there's a high investment time/cost, and because it changes so quickly it's difficult to get a stable and durable solution into production quickly that will provide ROI for the next cycle.
If you feel a sense of encouragement and discouragement, keep up with Greg. He can help to guide management and technical staff.
HTH
T