My team is actively working on client projects within Azure, GCP, and AWS to create GenAI POCs. During client conversations, I’ve been surprised by a lack of competitor comparisons out there. Any insights into what others are actually seeing built in any of these platforms?

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Tools is one thing, what companies are running into issues with is molding GenAI to fit their needs/data. Enterprise GenAI adoption is hitting a wall due to value realization (or lack thereof). Databricks and Scale are trying to combat this through either cloud molding or data generation and T&E respectively but I personally think there will be a VERY robust GenAI consulting industry that will explode in the next 5 years (after data hygiene is first fixed at a lot of larger enterprises)

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Look at Snowflake, NVDIA, and Googles Gemini. There are more things out there, they aren't getting the press like chatgpt.

The difficulties are where and how you want to integrate them in your builds.

How often are they updating, how do you bridge the gaps of knowledge (subsets of datasets to feed it), growing their general knowledge between updates.

Lastly not all of them are great at all things. How do you balance over committing to a few for integration, with flexibility to shift away or add another as more come online.

Lots to consider.

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I need this too

Lack of? There is quite a bit of competition..

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