Neural networks can encode any computable function.
KANs have no advantage in terms of computability. Why are they a promising pathway?
Also, the splines in KANs are no more "explainable" than the matrix weights. Sure, we can assign importance to a node, but so what? It has no more meaning than anything else.
I am not sure it is useful to bring in something as nebulous as "intelligence" and hand wave everything else away, unless you are going to tightly define what intelligence means.
There are only two objective measurements needed:
-is it making progress towards its goal?
-is it able to acquire capabilities it didn't have previously?
I am not sure if even the first one is objective enough.
Dismissing the argument without stating why you aren't convinced just comes across as a form of AI ludditism.
Really? IMO capabilities can be enumerated as a set of challenges in the category of things you want done. We don't need to discuss if an IC is "intelligent" to agree that the original $5 Pi Zero is "more capable" at that than all of humanity combined.
Sure, you can also say that GPT-4's passing the Bar tells you it can pass the kind of questions in the Bar exam without that extending to the kind of questions actual lawyers need to do, Goodhart's law remains if that was your point?
Can you please not break the site guidelines when posting here? You did it twice in this thread unfortunately (the other place was here: https://news.ycombinator.com/item?id=41773709).
If you'd please review https://news.ycombinator.com/newsguidelines.html and make your substantive points thoughtfully and respectfully, regardless of how wrong someone is or you feel they are, we'd appreciate it.
Man, what a waste of the term "autonomous worlds." When I hear that, I think "game where the world evolves independently, with or without direct interaction from the player" which is EXACTLY the type of game that I love to play. But if you look up that term you just get a bunch of boring blockchain junk.
The chief emergent behavior will be the crypto-bros and college kids who join up because they follow the buzz added to EvE's existing reputation. There's no such thing as bad publicity.
>> On Monday, Wood told Brinkema that Google intentionally put itself in this position to "manipulate the rules of ad auctions to its own benefit," The Washington Post reported.
A better way to understand this is that Google allegedly forced publishers to use Google's ad server and ad exchange if they wanted traffic from Google ads. From [1]:
>> After buying DoubleClick, Google tied its control over advertising demand to publisher use of its software. As the DOJ put it in the complaint, "If publishers wanted access to exclusive Google Ads’ advertising demand, they had to use Google’s publisher ad server (DFP) and ad exchange (AdX), rather than equivalent tools offered by Google’s rivals." The result is that it acquired a monopoly across the entire industry, in the software publishers use and the matching engine for advertisers.
Isn't the party here that's getting hurt the "equivalent tools offered by Google’s rivals". I'm still not seeing how this hurts publishers. Or is this like, if you want to show google ads, you can't show ads from other ad providers.
What you are getting at is that for a single person, the chance of going bankrupt is high but for a population ensemble, the average wealth increases.
This is absolutely true. All it takes is to understand that for the single person, the model isn't ergodic but all expected value based models assume ergodicity.
This comment thread is strange. I think you both raise interesting points, but are also rather hostile. Why not just respond sincerely? You have interesting things to say.
My forcing function was external. I was getting randomized by a lot of tasks and I felt I wasn't getting anything done. So I started to break down my day into 30 minute chunks. This got the feedback loop of seeing things get done going.
I also started to take notes about projects, other teams' working, notes from internal documentation etc. This has allowed me to retrieve some things super quickly to the point my teammates have been amazed. Another way to get the dopamine hit going.
Long story short: my brain is a primate, it needs dopamine hits, find a way to make your intended behavior give you dopamine hits.
KANs have no advantage in terms of computability. Why are they a promising pathway?
Also, the splines in KANs are no more "explainable" than the matrix weights. Sure, we can assign importance to a node, but so what? It has no more meaning than anything else.
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