Essays/linkedin/24-01-10 ai for everything
🧠 I am constantly bombarded by messages of companies throwing AI around to try to savage their products. But AI is not a magic wand that will give you whatever answer you need (or worse, it gives you what you want to hear...)
I have come across many pitches of companies building measurement instruments. Mostly for diagnosis, but also for quality control, and therapeutics.
Readout devices and sensing techniques have inherent limitations, and blindly believing AI will overcome whatever challenge is thrown at, it's an extremely risky business proposition.
It's like proposing an AI could identify a face after it was trained on medieval texts.
Generating data became so cheap, that it's too tempting to jump at wagon of 'let's try to train algorithms'. Sadly, little is discussed on whether the data has any insights on what is analyzed.
In startups is clearer. There's a high likelihood the AI expert and the data acquisition expert do not speak the same language.
Every time I see a new project popping up claiming that "AI will solve X problem" I become a bit skeptical. Not always, though.
Machine Learning and AI have been enabling progress in many fronts, but it's hard not to suffer from the shiny object syndrome.
Only time will tell how mistaken I was.
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