Why Most AI Vendor Solutions Are Underwhelming: Insights from AWS Expo

I took a couple of days off because I was down at the AWS Expo in D. C. , which was absolutely rammed, as you can imagine, both with local businesses, government organizations, and also a bazillion vendors all trying to sell their stuff. And so why am I talking about this on the AI briefing? Well, in part because what I saw was quite underwhelming, I think, from an AI perspective.

And of course, there are a lot of vendors there all selling various bits and pieces that obviously tie into the AWS ecosystem, the data processing, data security, user security. A lot of different stuff. But the things I noticed was there was an awful lot of very underwhelming use cases for AI that don't necessarily actually add a huge amount of value to the stuff that you're trying to do as an organization. And maybe it's more just a play to try and get to upsell and try and add value to a product that already existed. Whereas actual fact, you could just do the same thing.

You know, manually for less cost might take a little bit longer to set up. There is a lot of stuff that's changed in the worlds of LLMs and AI and all that type of stuff. But at the same time, a lot of it's not that innovative. And the companies that make the billions, the cursors of this world or the anthropic, obviously, with their foundational model, are the ones that really do innovate. Obviously, Anthropic and OpenAI came sort of first.

So, you know, that makes sense. But then Cursor and building stuff over the top that truly adds value to a person or an employee or a user's workflow is something that will make a difference. And a lot of companies are leveraging AI, but does it actually make a difference? AI in general is still in its infancy. Things will change a lot over the coming months and years.

The way that we interact, like I said, so many times the people actually will win at AI. The people that stop having us use it as a chatbot and come up with novel ways of being able to interact with an LLM that doesn't involve me typing stuff into a computer because that is slow and inefficient. Anyway, that's it. If you want to get ahead with AI, think about the use cases and the way that you would use it, why you would use it. And I will be back soon with another AI briefing.

My name is Tom. Thank you for watching. I'll see you all again soon. Bye for now. Why hire when you can partner?

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