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I often wonder how much AI hype is driven by a company’s inability to correctly set wages for and value the output of useful ML.
For example, you drop $1mm on an AI hire and expect them to produce a thing that can predict something it’s never seen before.
For example, you drop $1mm on an AI hire and expect them to produce a thing that can predict something it’s never seen before.
They of course can’t do this but you spent $1mm on them and because you couldn’t value the output correctly you most likely also aren’t going to manage the situation and part ways with them or readjust expectations.
So, you generate more intangible value via marketing (which has huge spend anyway) and hence hype is born. Now, the AI hire is incentivized to go along because the alternative is to engage with the misalignment of comp and output.
Then, the tragic part of it slowly manifests as what the AI hire did deliver actually can help the business. It just needed engineers to unlock it by getting data pipelines into a workable state.
So now you’re reaping more benefit than you spent on the hire but not in a way you recognize.
So the company doesn’t learn from the situation and the only person who sees clearly is the one doing ops on the pipeline. But no one will recognize their opinion for another 5-10 years
So the company doesn’t learn from the situation and the only person who sees clearly is the one doing ops on the pipeline. But no one will recognize their opinion for another 5-10 years
By that time they will already be raising a seed round and building a solution that has a slim to no chance of making it in the broad market.
Because remember, companies don’t know to shop for it and the new founders are bad at selling.
Because remember, companies don’t know to shop for it and the new founders are bad at selling.
Then again...maybe the hype is just too real...who knows!?!?!?!?
