Life comes at ya pretty fast...and so do changes in the AI space...

...or why you shouldn't skip this article...

I know - I’ve been sending out a lot of newsletters/issues/ posts this week so A) if you like it, don’t get too attached, I probably can’t keep this pace up and if you don’t like this volume of posts B) see A.

I just think this little article (Databricks launches DBRX, challenging Big Tech in the open source AI race) is important for a couple of reasons. First, I have this feeling that a lot of folks will just scroll past unless they’re really in the mix so I want to do my part to maybe argue why you shouldn’t skip it.

Second, the article really gets into why its important for leaders to build up their technical knowledge of how AI works. They don’t have to become ML data scientists but they need to know enough to ask relevant questions and be able to assess the answers. Here are a couple examples - this model “contains 132 billion parameters, outperforms leading open source alternatives like Llama 2-70B and Mixtral on key benchmarks measuring language understanding, programming ability, and math skills” and “while not matching the raw power of OpenAI’s GPT-4, company executives pitched DBRX as a significantly more capable alternative to GPT-3.5 at a small fraction of the cost.” Got it? Think about it this way. Does the person signing the purchase order for your new AI vendor understand the relative importance of the number of parameters or given what you want AI to do within your org, whether or not you need the power or GPT 4 or you can get by with something comparable to GPT 3.5?

Third, do you know who Databricks is as a company? Do you know who Snowflake is or at what stage are competing offers from Amazon, Google, and/or Microsoft? Knowing this things is not incidental - they are key to you being able to understand if this deal fits your needs at financial, technological, and risk levels.

So this post is not a recommendation for or against DBRX but rather how the article is a useful signal for the elements that need to be mastered inside your org to enable you to make the best possible decisions regarding AI. Also, and in conclusion, and just to wrap up….this is a GREAT example of how #LearningAndDevelopment could be leading their orgs by providing education on these topics as well as upskilling.