Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Artificial Intelligence: The Revolution Hasn’t Happened Yet (2018)

medium.com

Post reply on HN
Print view View original

41–50 of 92 posts

Re: Artificial Intelligence: The Revolution Hasn’t Happened Yet (2018)

#41

Post by WeylandYutani »

Animats wrote: post #6

This is a common sentiment, and pundits have been making similar remarks for decades. This author writes "Sixty years later, however, high-level reasoning and thought remain elusive." That's the wrong problem with AI. The trouble with AI is that it still sucks at manipulation in unstructured situations and at "common sense". Common sense can usefully be defined as getting through the next 30 seconds of life without a…

Automation only happens when it's cheaper than the human counterpart. In the US there are plenty of immigrants whom cost peanuts to employ. I don't expect the robotic future to come from North America.

Re: Artificial Intelligence: The Revolution Hasn’t Happened Yet (2018)

#42

Post by stuntkite »

bagels wrote: post #32
machina_ex_deus wrote: post #31

I suspect biological brains have a pretty groundbreaking hack to solve the long-term short term learning problem. Maybe involving sleep. What I mean by that is that AIs, the way they are currently built, need to learn very slowly on short term inputs or they overfit. Whereas humans can learn something just by explanation short term and don't have overfitting problems. I suspect this is solved by sleep, and I haven't…

How is sleep involved? There are a lot more differences than sleep.

https://www.med.upenn.edu/csi/the-impact-of-sleep-on-learnin...

Re: Artificial Intelligence: The Revolution Hasn’t Happened Yet (2018)

#43

Post by WeylandYutani »

pjc50 wrote: post #35
bravura wrote: post #19

Earlier quoted context omitted.

Imagine if the immediate outcome of AI is not that we replace taxi drivers, dishwashers, and factory workers, but instead we displace most knowledge-worker white collar jobs, like quant and software engineer? There's an old (and sometimes forgotten) idea in AI that perhaps things we think are simple, like vision and control (robotics), are actually incredibly complicated and took millions of years to evolve. Whereas…

I'm not sure that people appreciate how even the highly technical white collar jobs have large social elements in them. You might be able to get the AI to write the code, but can you get it to attend the meetings? And it's understanding what the right thing is to build that's the critical challenge in programming.

True but that won't save men. Already women are better suited for jobs that involve communication and empathy. I was in a hospital last week: almost a full female staff.

Re: Artificial Intelligence: The Revolution Hasn’t Happened Yet (2018)

#44

Post by DebtDeflation »

machina_ex_deus wrote: post #31

I suspect biological brains have a pretty groundbreaking hack to solve the long-term short term learning problem. Maybe involving sleep. What I mean by that is that AIs, the way they are currently built, need to learn very slowly on short term inputs or they overfit. Whereas humans can learn something just by explanation short term and don't have overfitting problems. I suspect this is solved by sleep, and I haven't…

That's an interesting take. I'll have to sleep on it and get back to you.

Re: Artificial Intelligence: The Revolution Hasn’t Happened Yet (2018)

#45

Post by twelvedogs »

evrydayhustling wrote: post #2

This is one of my favorites. So much of industrial AI is about replacing labor (usually cheaper but lower quality). In a way, AGI is only slightly more ambitious. We should be setting higher goals for AI, including helping individuals be superhuman, and helping organizations coordinate betteele.

the way people are learning to interact with stable diffusion is incredibly interesting to me, almost learning a new language via prompts to get it to produce desired results. i feel like that may be the key to the next step in ai, realising that human directed ai fills huge gaps in talent at both ends

Re: Artificial Intelligence: The Revolution Hasn’t Happened Yet (2018)

#46

Post by carlmr »

data_maan wrote: post #34
Animats wrote: post #6

This is a common sentiment, and pundits have been making similar remarks for decades. This author writes "Sixty years later, however, high-level reasoning and thought remain elusive." That's the wrong problem with AI. The trouble with AI is that it still sucks at manipulation in unstructured situations and at "common sense". Common sense can usefully be defined as getting through the next 30 seconds of life without a…

> Current hardware is easily up to the task. I don't think so. If you want to model a single synapse in full to capture all effects that might lead to "learning", you have a system of ordinary differential equations. Solving that is very hard, and solving that for 10 million neurons is impossible. On current hardware can only implement but a poor caricature of a real neuron.

While this is true, the complexity perspective misses something more fundamental.

1) Our brains, and moreso those of animals, come with a really good pretraining at birth. This is collective genetic knowledge of millions of generations distilled into your brain.

2) Our brains have a lot of sensors and actuators to interact with the world. We only learn by reading as adults when our brains can already do the synesthesia of translating words into thought. But even as adults, most of us learn better if we do something, write something, engage in dialog, instead of passively listening, reading, or watching.

Passive data can never replicate the rich environment our brains grow up in.

Re: Artificial Intelligence: The Revolution Hasn’t Happened Yet (2018)

#47

Post by te_chris »

pydry wrote: post #38
te_chris wrote: post #28

Earlier quoted context omitted.

I think there's a lot of truth to this. I'm new to ML, still going through the ropes on some online courses, but already I can see that, once I get a bit of muscle memory in setting up models etc, there's a whole lot of power and efficiency to be unlocked by using simple models - specifically in CS/X and Marketing. Obviously model quality matters, so you have to have proper monitoring etc, but this stuff is low hangi…

In a lot of these cases - maybe most, in fact - the sludge in the data pipeline makes makes the low hanging fruit hang high. I've worked on a number of projects where it looked simple to automate from the outset and impossible in retrospect.

Agree entirely, I wouldn’t want to build a saas startup around it due to data quality, but if you have control of your pipeline it’s easier.

Re: Artificial Intelligence: The Revolution Hasn’t Happened Yet (2018)

#49

Post by geysersam »

Animats wrote: post #6

This is a common sentiment, and pundits have been making similar remarks for decades. This author writes "Sixty years later, however, high-level reasoning and thought remain elusive." That's the wrong problem with AI. The trouble with AI is that it still sucks at manipulation in unstructured situations and at "common sense". Common sense can usefully be defined as getting through the next 30 seconds of life without a…

> A squirrel has around 10 million neurons.

I don't believe this is correct. It's too low.

It's more like 400 million.

> somebody ought to be able to build something with 10 million of them

Build them, sure, but they need to be connected in the right way.

Re: Artificial Intelligence: The Revolution Hasn’t Happened Yet (2018)

#50

Post by mkaic »

data_maan wrote: post #34
Animats wrote: post #6

This is a common sentiment, and pundits have been making similar remarks for decades. This author writes "Sixty years later, however, high-level reasoning and thought remain elusive." That's the wrong problem with AI. The trouble with AI is that it still sucks at manipulation in unstructured situations and at "common sense". Common sense can usefully be defined as getting through the next 30 seconds of life without a…

> Current hardware is easily up to the task. I don't think so. If you want to model a single synapse in full to capture all effects that might lead to "learning", you have a system of ordinary differential equations. Solving that is very hard, and solving that for 10 million neurons is impossible. On current hardware can only implement but a poor caricature of a real neuron.

I think this requires the assumption that modeling the complexity of biological synapses is required for general intelligence, when we don't know that to be the case. Personally, I believe that it's not a requirement at all and that the first AGI will be strikingly non-neuromorphic. Just my two cents though.
Post reply on HN