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See John Hughlings Jackson, 1874, and subsequent work with certain aphasics and split brain patients, on two sources of words and phrases in our brains. David Shariatmadari has a good overview in his recent book, and Pinker discusses it a little in "The Language Instinct".https://twitter.com/tdietterich/status/1221211653695369217 …
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A careful review of GPT-2 by
@GaryMarcus.https://thegradient.pub/gpt2-and-the-nature-of-intelligence/ …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Rodney Brooks proslijedio/la je Tweet
Me: *sobbing through tears* "please stop... you can't just call any technology AI Tech startups: *points at something that could be replicated with 1800's technology* "AI powered"https://twitter.com/richdemuro/status/1214955597025538049 …
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Rodney Brooks proslijedio/la je Tweet
A cogent criticism of modern AI tools....http://blog.lareviewofbooks.org/provocations/neophobic-conservative-ai-overlords-want-everything-stay/ …
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Just published my 2nd of 32 annual reviews of my January 1st 2018 hype dampening predictions about self driving cars, AI & ML, and the space industry. My predictions had dates attached so you can evaluate how well I did. http://rodneybrooks.com/predictions-scorecard-2020-january-01/ …
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Yes, that computation is a misleading metaphor for how intelligence arises. Just like how computation would not be a good explanatory metaphor for how rockets work.https://twitter.com/dileeplearning/status/1210988764002054144 …
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For those of us who can't figure out where quantum computers really stand here is a great explanation by one of the key players in the field, Scott Aaronson, about how better to read various claims. [My interpretation: don't hold your breath.] https://www.scottaaronson.com/blog/?p=4447
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Rodney Brooks proslijedio/la je Tweet
It is extremely difficult to make precision nuts and bolts, and it is by no means "trivial". But the science of making nuts and bolts is not the science of making engines, and a community engrossed in the former will be limping on the latter.
#BookofwhyHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
A good review of tech failures in the 201x's from revolutionizing eating with fruit juices and soylent, to computers on our faces, to drone package deliveries, to vaping and others. The author politely did not include my own tech failure of the decade...https://www.washingtonpost.com/technology/2019/12/26/most-disappointing-technologies-decade-face-computers-space-tourism-juicero/ …
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I joined Stanford AI Lab in 1977, sharing space & PDP10 with Chowning’s CCRMA. During summers when I hacked through the night, by 6am the digital music students would arrive and over the digital PA we would hear their compositions grow. To 20 seconds or so each, by September.https://twitter.com/markoff/status/1209718758102618113 …
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Spent the last two days crisscrossing Mumbai for meetings. All those autonomous miles in Chandler, Arizona are easily going to generalize for AV roll outs here. Yeah, right.
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13/13 But if you do succeed please acknowledge this thread in your many award acceptance speeches. You are welcome.
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12/13 My prior is that there is a 50% chance that the above scenario is possible. The expected outcome for an invidual who tries it is close to zero however. Most likely you will fail. You have been warned.
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11/13 You will have invented a new engineering tool which will allow new progress in AI and Robotics. Other people will make a lot of money based on your work--and perhaps you will too if you are lucky.
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10/13 Bonus points if you exploit GPUs or even TPUs. Then start outperforming current DL and DRL on current data sets. You will become the next big thing. ALIFE conferences will explode with attendees. Life will never be the same.
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9/13 ... epigenesis, non-genetic inheritance, etc. Of course, like current DL and DRL perhaps an engineering answer does not need to include much similarity with biological systems.
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8/13 This will need innovations at the "genetic" level, but we have learned an awful lot in the last 30 years about mechansims in real genetics that we did not know existed--e.g. self repair, gene regulation,...
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7/13 Perhaps there is an opportunity to reinvent evolutionary computation and exploit the competition ready training sets and massive amounts of computation.
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6/13 e) DL and DRL are both showing sublinear performance improvement despite exponentially more computation available to researchers.
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5/13 d) Computation is now many orders of magnituds more available and there are countless competition ready data sets.
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