51–60 of 136 posts
Anyone who does understand the underlying mechanisms are probably still trying to clean the data sets.
Earlier quoted context omitted.
I'm curious what people find is more likely given this evidence: - 100s of models were done incorrectly, and none even remotely correctly - there is no phenomenon to correctly model Both seem extremely unlikely. Not sure what the alternatives are.
> there is no phenomenon to correctly model COVID exists, it causes physical changes and affects the world outside the host. 100% it can be modelled somehow in theory. That being said, there are harsh rules against collecting data (for example, it would be extremely illegal to create a sample set by taking a random group of people and infecting half of them with COVID on purpose). So I expect actually getting trainin…
The entire premise of modelling something rests on the fact that the behaviour of what you're trying to model in the future depends on its behaviour in the past.
This is not true for all systems, it's not even true for most systems. John Kay differentiates between 'resolvable uncertainty' and 'radical uncertainty'. Modelling a volcano eruption is resolvable because it's a reasonably predictable system and you can make confident stochastic claims. Complex human systems are chaotic, have 'unknown unknowns', are simply subject to chance or non-linear behaviour that completely throws any prediction off.
You cannot model something that is subject to forces you cannot even know at the point of making the model, and this is true for any complex human system pretty much. Modelling Covid as if we have access to Hari Seldon's psycho-history was always a terrible idea.
Should have built AI tools to educate the ignorant populace and encourage them to get a vaccine. I know there have to be tons of adboys and girls out there whose only job is to persuade people to do something that could have knocked this out of the park. I see we are still at about 50% vaccination and Walmart is begging people to come get a free vaccine. I’m sorry my tone is negative but this is really getting me fru…
So maybe the real mistake was making it free. IF a company could make a few bucks for every vaccine administered, we would have seen the ad industry being its full might to bear to harvest as many people getting it as possible.
Earlier quoted context omitted.
(also frustrated) re: adboys and girls, the problem (at least in the US) is that vaccines are political, so persuading people to get them is seen as dangerously close to subverting democratic society. Same thing as taking action to counter foreign influence campaigns. see also: the leaks to project veritas about Facebook's counter vaccine hesitancy program.
Well, back when Harris and Biden both said they were hesitant to get a vaccine produced under Trump, they kinda set the stage for the dumpster fire we have today.
> Many unwittingly used a data set that contained chest scans of children who did not have covid as their examples of what non-covid cases looked like. But as a result, the AIs learned to identify kids, not covid. > Driggs’s group trained its own model using a data set that contained a mix of scans taken when patients were lying down and standing up. Because patients scanned while lying down were more likely to be se…
A client of mine wanted me to look into this dataset and help creating a model for detecting COVID. One of the doctors they where working with wanted to be able to submit pictures they took (from their point and shoot camera) of the CT scan. Good luck putting that variation in your dataset.
What ever happened to using AI to diagnose infections based on cough sounds? It seemed like a promising approach. https://news.mit.edu/2020/covid-19-cough-cellphone-detection...
By the time you experience symptoms you've already been contagious for a few days. It's like trying to detect fires by looking for piles of ash.
> “The models are so similar—they almost all use the same techniques with minor tweaks, the same inputs—and they all make the same mistakes,” says Wynants. “If all these people making new models instead tested models that were already available, maybe we’d have something that could really help in the clinic by now.” Sounds about right.
I'm curious what people find is more likely given this evidence: - 100s of models were done incorrectly, and none even remotely correctly - there is no phenomenon to correctly model Both seem extremely unlikely. Not sure what the alternatives are.
Given the fact that at that time there was still quite a lot of "if we all help we can beat the pandemic" positiveness going around. An easily run-able piece of small code that promised "results" was available and the fact that a lot of organizations wanted positive PR, you get these insultingly low quality "research" practices.
I looked at a lot of the initial papers and models and most were forks of COVID-Net or used an already established model like ImageNet and retrained it with the bad dataset. Presto! Paper out PR happy. Very few questioned the dataset or the approach in general. But they loved bragging about it on LinkedIn.
> “The models are so similar—they almost all use the same techniques with minor tweaks, the same inputs—and they all make the same mistakes,” says Wynants. “If all these people making new models instead tested models that were already available, maybe we’d have something that could really help in the clinic by now.” Sounds about right.
I'm curious what people find is more likely given this evidence: - 100s of models were done incorrectly, and none even remotely correctly - there is no phenomenon to correctly model Both seem extremely unlikely. Not sure what the alternatives are.
100s of wrong models doesn't sound extremely unlikely to me. It's really easy to train a model and test that it works on some dataset and then find it doesn't work on a different one. Setting up the inputs for training is difficult because of data privacy, there's intense pressure to publish, models have no expectation of explanability, lots of reasons for a wrong model that looks promising.
I've worked adjacent to people trying to solve problems with machine learning and it's rough going. When things work, ok nice, but when they don't, it's much harder to tweak than something based on heuristics (which, of course, don't always apply either).
Should have built AI tools to educate the ignorant populace and encourage them to get a vaccine. I know there have to be tons of adboys and girls out there whose only job is to persuade people to do something that could have knocked this out of the park. I see we are still at about 50% vaccination and Walmart is begging people to come get a free vaccine. I’m sorry my tone is negative but this is really getting me fru…
I would agree that stupid is winning, but I probably agree more with Kant on what Enlightenment means.