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a lot of these AI companies products are really terrible. Has anyone ever tried the AI API models from clarifai ? Just so unaccurate. It seems like a scam. I've also had a really bad experience with watson's speech to text apis.
I'm pretty sure it's all a big scam, at least the crap that comes out of IBM.
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The purpose of such a system should be to give leads for further research. If you treat them as leads and only leads, then bad leads don't matter much. Unless, the leads are so bad on average that too much effort is spent on vetting them that could be put to better use elsewhere.
I doubt that's how Watson is being marketed to customers, though. IBM tends to oversell and under deliver and have grown increasingly desperate with their shrinking market shares in both hardware and services.
Slightly unrelated, but I hope IBM doesn't ruin Red Hat and CoreOS. I would love to see the CoreOS tools to gain more adoption.
I'm a long time Fedora user. I love the sane defaults. It's just a solid workhorse. But I've been feeling pretty uneasy about using it lately...
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In my experience, IBM’s support is excellent, bordering on fanatical. It’s just that their hardware (in this case, Spectrum Scale and Power9) are preposterously overpriced. Same for their software, if not more so.
As a former IBMer I really like the POWER hardware. It is just a shame that it is made by IBM. Like you said IBM stuff is just too damn expensive.
Slowly, I am noticing that people are starting to question the abilities of machine learning systems and, in particular, seeing a lot of the transparent AI-washing that is now going on for systems that aren't AI at all. This is one of the most positive changes in the tech industry, honestly.
They're just good enough to, with insane amount of computing resources, churn out economically viable results, but in my opinion they're the biggest setback in actually developing intelligence or cognition in a long time.
There's very little insight to be gained from what they pick up, and they function purely in a stochastic sense. Even the best ML algorithm has no ability to reason at a high level or produce counterfactuals, it works purely by correlation and still, in those 1% edge cases, will be as helpless as anything else.
That might be good enough when selling advertisements, but in automated cars and healthcare treatment, this sort of failure is not an option.
I sincerely hope IBM's failures do not deter further progress in trying to innovate in healthcare technology. I believe healthcare vitally needs GOOD/USEFUL technology and AI applications because medical progress is not advancing quickly enough by several metrics. I hope IBM continues to fail and becomes a case study in the failure of massive bureaucracy.
We need to prove them wrong on both these accounts.
I sincerely hope IBM's failures do not deter further progress in trying to innovate in healthcare technology. I believe healthcare vitally needs GOOD/USEFUL technology and AI applications because medical progress is not advancing quickly enough by several metrics. I hope IBM continues to fail and becomes a case study in the failure of massive bureaucracy.
One failure by one company, even IBM, won't stop future attempts.
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The difference is the expectation of fallibility with human docs. Which is why checks are built into the system. I have zero trust in IBM to market their ML products correctly so that proper checks are maintained. Especially since technically, explainability is still an active area of ML research.
>I have zero trust in IBM to market their ML products correctly so that proper checks are maintained. That's a problem, yes, but it's not a new one. Vendor management has been around for decades, centuries, millennia maybe. If I contract out part of my job, it's still my responsibility to make sure the contractors are doing their job right. "But their marketing said..." or "but their sales guys said..." is not an exc…
Well as a doctor if I’m still ultimately responsible then nothing has fundamentally changed, this is just another tool, possibly one I’ll be forced to use by someone with not one day of medical training.
And medicine in the US is in a precarious position. Software engineers are generally not licensed, and they’re not sued (it’s virtually unheard of). It’s different for doctors. There’s a complex dynamic of removing autonomy from providers to ostensibly improve outcomes (and revenue cycle) while also still holding those same personally liable.
So much of what I do is indirectly dictated by wonks in IT and billing, but they have virtually no liability. And one wonders why burnout in medicine continues climbing with no end.
I sincerely hope IBM's failures do not deter further progress in trying to innovate in healthcare technology. I believe healthcare vitally needs GOOD/USEFUL technology and AI applications because medical progress is not advancing quickly enough by several metrics. I hope IBM continues to fail and becomes a case study in the failure of massive bureaucracy.
EconTalk from last week[1] shed some light on the convoluted world of drug pricing and pharmaceutical patents. While I agree with your point that AI could help with medical progress, I would also emphasize that we're being held back by meat-space institutions as well (in this case, drug patents). One of the key takeaways was looking at the return on marginal investment in gaming the patent system vs developing new dr…
That said, if you can make clinical trial reporting data collection more efficient, there's a LOT of money to be made.