Tired of GenAI as a buzzword. How do you cut through the noise to determine use cases where it TRULY outperforms traditional prompt engineering, offering unique, measurable value for sustainable differentiation?
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CEO in Software6 months ago
As any tech during its initial phases of adoption creates a lot of buzz, you are spot on with the thought that its difficult to create projects that offers tangible sustinable value. The cost to adopt new technology and overall risk profile of that investment vs value is high. Having said that gen-ai from its bare bones has gone up its value chain with iteration and products outside the openai chatprompt all of us are familiar with. In my opinion large vendors are already incorporating genai features into their products making it very use-case specific taking away the complexity of prompt engineering and thereby the value derived out of the system.
If one has to create a differentiator out of GenAI then I would say unique data and custom models with proprietary data training is the way to go. From simple implementation of customer support to depending on the industry one is in, very specific capabilities can be added. As a vendor we see many new products being asked to develop in the areas of media and conversational bots.
So to answer the question, the way is to do first a competitive analysis, key operational parameters, define ROIs for process improvement projects and execute agile with performance tracking. Micro experiments that leverages a data set that is trained and prompts abstracted to simple clicks would be the way to go along with some team training. You may want to also note that this is a new way or an evolving culture of doing business and the shift in culture if guided with some policies as well it will more align with org values and goals.
Managing Partner in Software6 months ago
It is hard to answer without considering the organization's scope, vertical, and other aspects of your business.But generally, look for repetitive work starting with tasks performed by entry-level personnel. This does not mean that GenAI-driven automation can not help elsewhere, but it's the most obvious place to start. Also, you can hire an AI Agency that will work with you on the discovery + design and could build out the technical solution for you.
To align the expectation, as of today, most of the shelf solutions can address only the most common and simple cases. But to achieve good reliability, accuracy, and value for more sophisticated use cases, a custom solution will probably be required.
Senior Data Scientist in Miscellaneous2 months ago
I am still focussing on the historical knowledge, which is collected in the vast amount of documents, and other data over the years / decades. A.t.m.h.o. this is an undiscovered treasure.
1.Apps engineering for ideation design,
Dev/ testing deploying and scaling.
2. IT operations from creating SOP’s to Auto resolutions.
3. Business Aps from SCM to CRM including corporate functions like finance and HR. You can create enormous business cases based on flows.
Reach out to me if you want to discuss.