So where can we download these models?
Given that this is DeepMind and not some more open AI organization, I assume you cannot.
DeepMind’s new AI with a memory outperforms algorithms 25 times its size
41–50 of 141 posts
Re: DeepMind’s new AI with a memory outperforms algorithms 25 times its size
#42> Gebru, a widely respected leader in AI ethics research, is known for coauthoring a groundbreaking paper that showed facial recognition to be less accurate at identifying women and people of color, which means its use can end up discriminating against them. Surely this is a function of location? I understand the U.S.-English term “person o color” to be convoluted language for “not white”. One simple thing I notice i…
Completely not the focus of the article, and you've turned the result of an error rate of 0.8 percent for gender classification of light-skinned men and a 34.7 percent error rate for the same classifier on dark-skinned women - into some kind of google image search language game? I can only quote Joy Buolamwini on this: “To fail on one in three, in a commercial system, on something that’s been reduced to a binary clas…
The answer would probably be yes if that subgroup wasn't a large percentage of the dataset used for training and testing. Or if that subgroup wasn't a large percentage of the user base.
Come on, if you've worked at any large company using ML you know model performance is literally just taking the average accuracy/ROC/precision/etc over your training dataset plus some hold out sets. Then you track proxy metrics like engagement to see if your model actually works in production. At no point does race come into the equation. Naturally, if your choice of subgroup happens to not be a large proportion of either the dataset or the userbase then you don't see the poor performance on that subgroup show up in your metrics so you don't care to fix it.
Re: DeepMind’s new AI with a memory outperforms algorithms 25 times its size
#43If we point it at the horrendously bad scots wiki (some kid in the US decided he'd translate Wikipedia into what he thought was lowland scots/Doric.. it's a disaster) we might get entertainingly bad outcomes.
Oh wow, that's a fun rabbit hole: https://www.theguardian.com/uk-news/2020/aug/26/shock-an-aw-...
Re: DeepMind’s new AI with a memory outperforms algorithms 25 times its size
#44A neural net with access to wikipedia is faster than than a neural net that contains Wikipedia? Seems odd to call it AI with a memory though... unless I'm misunderstanding. It's more like AI with a decent memory and an understanding of how to use an encyclopedia.
I wonder what we can learn from AI models about how humans work.
Like, could we assume that for humans it's also faster to search for information on Wikipedia or would it be faster to recall from memory of already read Wikipedia? Although with humans stored information decay is present. (In a way a human form of garbage collection :P).
Re: DeepMind’s new AI with a memory outperforms algorithms 25 times its size
#45Earlier quoted context omitted.
Completely not the focus of the article, and you've turned the result of an error rate of 0.8 percent for gender classification of light-skinned men and a 34.7 percent error rate for the same classifier on dark-skinned women - into some kind of google image search language game? I can only quote Joy Buolamwini on this: “To fail on one in three, in a commercial system, on something that’s been reduced to a binary clas…
The answer would probably be yes if that subgroup wasn't a large percentage of the dataset used for training and testing. Or if that subgroup wasn't a large percentage of the user base. Come on, if you've worked at any large company using ML you know model performance is literally just taking the average accuracy/ROC/precision/etc over your training dataset plus some hold out sets. Then you track proxy metrics like e…
Obviously, but the question is, why were there no Black women in the data set, and what care can be taken to prevent racialized bias when selecting the data set in the future?
Re: DeepMind’s new AI with a memory outperforms algorithms 25 times its size
#46Earlier quoted context omitted.
I believe plenty of "quantum phenomenon" are utilized in humans' biochemistry[0]. Whether the brain "calculates" things using a method that is particularly similar to the methods used in today's quantum computers is...unlikely. It probably is "quantum" in other ways though. 0: https://www.the-scientist.com/infographics/infographic--quan...
Yes. It's unavoidably "quantum" in the sense that, as a physical machine in our universe it's subject to the rules, including quantum physics. However there is no apparent mechanism by which "thinking" could harness any interesting properties of quantum physics, it's just not happening at the right scale, like the way kids sand walls on the beach don't alter the world's tides.
That proportions in that analogy seem way off. Every single neuron of the human brain could be utilizing quantum mechanical effects at the same time. Not very much at all like a kid's sand castle against the world's tides. I don't think anyone really understand "thinking" and quantum mechanics well enough for the mechanisms to be apparent. I mean, squirrels convert forest detritus into general intelligence. I don't understand the strong certainty against the idea that there's some physics based piece of the puzzle that we're missing.
Re: DeepMind’s new AI with a memory outperforms algorithms 25 times its size
#47Earlier quoted context omitted.
The answer would probably be yes if that subgroup wasn't a large percentage of the dataset used for training and testing. Or if that subgroup wasn't a large percentage of the user base. Come on, if you've worked at any large company using ML you know model performance is literally just taking the average accuracy/ROC/precision/etc over your training dataset plus some hold out sets. Then you track proxy metrics like e…
Obviously, but the question is, why were there no Black women in the data set, and what care can be taken to prevent racialized bias when selecting the data set in the future?
Certainly you can ask these questions but these are business process issues, not technical ones. They're unrelated to AI.
My personal take is you won't see any tangible movement on this until black women (or whatever group you choose) comprise a tangible proportion of revenue generating users. Corporations operate for money and nothing else.
Re: DeepMind’s new AI with a memory outperforms algorithms 25 times its size
#48Earlier quoted context omitted.
The answer would probably be yes if that subgroup wasn't a large percentage of the dataset used for training and testing. Or if that subgroup wasn't a large percentage of the user base. Come on, if you've worked at any large company using ML you know model performance is literally just taking the average accuracy/ROC/precision/etc over your training dataset plus some hold out sets. Then you track proxy metrics like e…
Obviously, but the question is, why were there no Black women in the data set, and what care can be taken to prevent racialized bias when selecting the data set in the future?
I would assume these data sets are not manually selected but imported from some mechanism.
Other issues which are sure to arise is that the a.i. will have trouble with people who aren't smiling, and that the data set probably contains people who look better than average, and almost certainly excludes people who suffer from injuries or deformities in appropriate proportions.
Perhaps an interesting project is simply the compilation of a vast dataset of “world proportional pictures of people”. — It would be an interesting undertaking to realize such a dataset.
Re: DeepMind’s new AI with a memory outperforms algorithms 25 times its size
#49[deleted]
Re: DeepMind’s new AI with a memory outperforms algorithms 25 times its size
#50Earlier quoted context omitted.
Yes. It's unavoidably "quantum" in the sense that, as a physical machine in our universe it's subject to the rules, including quantum physics. However there is no apparent mechanism by which "thinking" could harness any interesting properties of quantum physics, it's just not happening at the right scale, like the way kids sand walls on the beach don't alter the world's tides.
That proportions in that analogy seem way off. Every single neuron of the human brain could be utilizing quantum mechanical effects at the same time. Not very much at all like a kid's sand castle against the world's tides. I don't think anyone really understand "thinking" and quantum mechanics well enough for the mechanisms to be apparent. I mean, squirrels convert forest detritus into general intelligence. I don't u…
I believe we've been able to model the processes behind neural firings for quite some time now, the issue is more mapping between that micro-scale understanding of how each individual piece in a 10^10 piece puzzle with 10^15 edges affects the macro-scale emergent properties of said puzzle. It's less a lack of understanding of the processes and more a complexity so great that it exceeds the grasp of our best modeling tools thus far.
We can barely model the humble nematode c. elegans with its 330 neurons.