Readit NewsSounds like a magical fantasy computer.
How would the input and output devices work without drivers? Does "no classical software at all" mean that the drivers are somehow within the neural net?
How would such a magical neural net computer be trained? Wouldn't it require observing countless inputs and outputs for a normal computer? How would the neural net being trained distinguish between good, wanted input/output combinations versus bad, error input/output combinations?
How would you program such a computer or load new software onto it? If the whole thing is a single neural net, wouldn't the neural net need to be replaced in order to add new functionality or correct errors/bugs? How would user data be persisted while upgrading the applications?
The questions you pose are interesting ones, for the sake of the experiment I think at least:
- Programming
- Loading new software
- Adding new functionality
- Persisting user data
Could all at least in principle be achieved without changing the network architecture, but rather just providing the relevant data at the inputs (eg the full bit stream of the install file of the new software being installed) and having that lead to adjustments in activations (not weights or architecture) across the network which lead to any future inputs to the network resulting in the outputs that would be expected in the presence of the new software. Same deal for the other examples.
As to whether this is practical or achievable at present - not even remotely close in my view. But it’s still an interesting idea, even if just to think about why it wouldnt work and what that implies for future development direction of multimodal networks etc.
If ops point was rather that “accident”/“luck” are uniquely human… I don’t agree. Luck is when probability works out in your favour - and that can happen all the time with any sort of probabilistic search, which is rife in ML.
I love how this story follows the magic pattern of so much of innovation and discovery - an accident. It's refreshingly human and not a mode of discovery that machine learning is going to completely take away from us.
That's a huge unsolved issue with the Carbon Tax AND Carbon Credits solutions. Your idea doesn't solve it.
In NZ we also have an effective system for recognising and incentivising certain classes of forest carbon removals (which I think are a legitimate and important class of credits - unlike avoided emission credits which I agree are junk).
New solar records are done until next summer but still interesting stuff happening. For example, California hit a new battery charging record a few weeks ago.
All the records and more real time information about US grid are here: https://www.gridstatus.io/records
It might provide a way to harvest the remaining gravitational potential energy of the rain (possible funnel being your roof and guttering) but the only upside is that you could concentrate the energy with something that’s already there (and hence harvest over a smaller area). The amount of energy (and hence value) available would be even lower - unless you had a really high roof.
This is also the reason I abandoned my high school scheme of hydro turbines at the bottom of downpipes.
As the comments below say - you need to be working at the scale of a few major geographic features as a funnel before it starts to get really interesting.
Total rainfall volume per m^2 is .025 m^3/hour. This is approximately 500,000 randrops/hour or about 14 drops/second. Each drop has 1/2 * m * V^2 = 25 mJ of energy.
So putting it all together, this is generating 25 mJ/drop * 14 drops/second = .35 W/m^2, and that's only when its raining. (Edit: and this is assuming 100% conversion efficiency, which....no. Don't know anything about this technology, but probably cut that number in half again).
Sounds a lot like Solar Freakin Roadways.
Edit: Just a sidenote; back in college the best course I took was billed as a "Renewable Energy" but was really just a weekly set of unit conversion problems like this that proved how absolutely stupid most energy proposals are.
We did focus a fair amount on real technologies like Wind and Solar (and analyzing the shortcomings like storage, which haven gotten better since ~2009). The professor took a lot of joy in shooting down ideas like this though.
I wasn’t sure about the droplet analysis so took your same numbers (25mm/h, 10m/s) and just worked out aggregate mass: 25mm over 1m^2 = 0.025m^3 = 25kg
0.5mv^2 => 1250J/h… so looks like we agree.
And to add a simple economic analysis of why this is such a dead-end idea:
Mawsynram, in India, is apparently the rainiest city in the world with roughly 10,000mm of annual rainfall - 10x the global average.
A given rain energy harvesting panel, deployed there, would generate 500,000J/yr… or 0.138kWh. That’s significantly less than what a typical rooftop 1m2 solar panel would generate in an hour on a sunny day. 0.138kwh is worth around 1.3cents at 10c/kWh.
A big roof might get you $1-$2/year. You couldn’t pay to clean your roof for that. You couldn’t even pay someone to answer an email enquiry about the install costs for your system for that. This solution would have to be VASTLY cheaper than paint to stand a chance of being viable.
There is a reason our existing systems to collect power from rainfall rely on vast existing landscapes and aggregation mechanisms (rivers) to concentrate the rainfall for us.
It is - in my view - a dead idea.
Which means something that's engineered is made better by successive improvements from previous work.
2nd this is failing to consider different environment conditions and applications may make gathering energy from the environment in creative ways practical and useful.
Not saying this particular technology will eventually be practical from a commercial standpoint, only wishing to state it's more than just 'will this technology easily solve global energy demands'.
I agree we should keep an open mind regarding creative ways of collecting energy from the environment. But we should also abandon those which are quickly demonstrated to have no meaningful potential even if we were to perfect them.
> And AI is a machine – is not going to come alive any more than your toaster will.
There have been claims that AIs are conscious. For example, Ilya Sutskever has suggested that LLMs may be slightly conscious.
It is possible that machine consciousness could be quite different from human consciousness. This idea aligns with the philosophy of Nonduality, which proposes that pure consciousness is the fundamental substratum of the universe. Our minds are able to reflect this pure consciousness, albeit in a limited way. If our human minds can reflect consciousness, perhaps artificial neural networks can as well, but in their own manner.
Ironically I think the whole article is motivated by the thing he claims to condemn - namely: he’s a bootlegger, who has an interest in freedom of ai development.
Part 2 is much more interesting. Part 1 was very very weak.