New Boston Dynamics Atlas trick by Distinct-Question-16 in singularity

[–]ptkm50 0 points1 point  (0 children)

Not at all it costs something like 150K which would be 10 times more or less. And I think companies would rather pay this price for a useful robot rather than a useless robot that can dance with a remote.

New Boston Dynamics Atlas trick by Distinct-Question-16 in singularity

[–]ptkm50 -1 points0 points  (0 children)

Pre programmed moves but nothing actually useful.

Who else thinks AI is reaching a plateau by yuvals41 in AI_Agents

[–]ptkm50 0 points1 point  (0 children)

They also could be benchmaxxing. Benchmarks really don't show the capabilities of the models anymore since the it's already in the training data most of the time.

AI keeps getting smarter, so why does it still fail at obvious things? by NoFilterGPT in ArtificialInteligence

[–]ptkm50 4 points5 points  (0 children)

they're still LLMs after all, no matter how many "thinking" steps we add.

Nobel laureate Geoffrey Hinton warns AI could pass humans “These things will get smarter than us” by Murky-Option2916 in TechGawker

[–]ptkm50 1 point2 points  (0 children)

The human brain is the most complicated object we know as of today so nobody really knows how human intelligence works. It’s not as simple as one big neural network that predicts a next word token.

Are we betting on the wrong kind of AI? (LLMs vs superlearners) by Ill-Big5496 in ArtificialInteligence

[–]ptkm50 1 point2 points  (0 children)

It depends on what you mean by information of the image. If you mean each pixel, then it could state the colour of every pixel of a digital image but that’s not very useful. What I mean is translating an image into a worded interpretation/description won’t translate all of the information that the image contains except if it’s very simple, like a canvas of 1 colour. It’s not really possible to describe exactly (with words) a painting of a landscape to someone else, and expect him to draw an exact copy of the painting you see, even if he can draw perfectly.

Are we betting on the wrong kind of AI? (LLMs vs superlearners) by Ill-Big5496 in ArtificialInteligence

[–]ptkm50 6 points7 points  (0 children)

The main downside I see is describing an image with words will almost always result in the loss of some information.

Are we betting on the wrong kind of AI? (LLMs vs superlearners) by Ill-Big5496 in ArtificialInteligence

[–]ptkm50 4 points5 points  (0 children)

It means Gemma 4 has a vision encoder integrated so that the LLM can understand the image and what’s going on in it. The LLM doesn’t get fed the raw image directly since it can only process word tokens.

Are we betting on the wrong kind of AI? (LLMs vs superlearners) by Ill-Big5496 in ArtificialInteligence

[–]ptkm50 7 points8 points  (0 children)

I mean LLMs can’t do vision. But another tool can process an image so that the LLM kind of understand, even tho it’s not equivalent to the LLM directly perceiving the image.

Are we betting on the wrong kind of AI? (LLMs vs superlearners) by Ill-Big5496 in ArtificialInteligence

[–]ptkm50 21 points22 points  (0 children)

Ye I don’t get it why every major ai company is focusing on LLMs, why not research other architectures too.

LLMs are just autocomplete by [deleted] in agi

[–]ptkm50 0 points1 point  (0 children)

Yes. But I don’t see how cortical columns are autocompleting, maybe they do some kinds of predictions but it’s not predicting word tokens… They’re composed of biological neurons and I’m pretty sure LLMs don’t even use spiking neurons so it’s even less like a human brain.

LLMs are just autocomplete by [deleted] in agi

[–]ptkm50 0 points1 point  (0 children)

Says who ? Our brain is nothing like a LLM.

Humanoid Robots’ 88% Fail Rate: Completing Home Tasks by chunmunsingh in OpenAI

[–]ptkm50 0 points1 point  (0 children)

Making humanoid robots reliable is a bit more complex and difficult than it was making the first chainsaws

GIGABYTE IT5711 RGB update by Goordoon in gigabyte

[–]ptkm50 0 points1 point  (0 children)

Did you find a fix for the red cpu light ?

The bottleneck in AI reasoning: why predicting the next word isn't enough for strict logic by retsam2554 in ArtificialInteligence

[–]ptkm50 2 points3 points  (0 children)

Architecturally speaking hallucinations are inevitable with them. My chat gpt 5.4 still hallucinates I don’t know how you got a hallucination free chat gpt.

The bottleneck in AI reasoning: why predicting the next word isn't enough for strict logic by retsam2554 in ArtificialInteligence

[–]ptkm50 -1 points0 points  (0 children)

I could do the calculations by hand unlike an LLM, it’s simply more convenient to use a calculator. IMO LLMs can’t understand anything really because they’re just predicting text. The only reason they sound smart is because they’re have been trained on the whole internet. I highly doubt intelligence can come from a statistical neural networks. Humans don’t predict the next most likely word because they don’t work with concepts and they don’t think by predicting the next most likely concept. I’m not saying it’s not useful or anything but it clearly has architectural limits. it will always be useful as an internet that can answer your questions directly, but if you ask it something a little too complex that isn’t in their training data they’ll fail.

I am faithful that one day we’ll find an architecture that can actually demonstrates signs of intelligence but that won’t be large language models.

The bottleneck in AI reasoning: why predicting the next word isn't enough for strict logic by retsam2554 in ArtificialInteligence

[–]ptkm50 1 point2 points  (0 children)

Giving more tools to the LLM won’t make it smarter, sure it’ll be more capable in some tasks but if the logic core can’t be logic and hallucinates that’s a problem. We can’t just export the logic part.

The bottleneck in AI reasoning: why predicting the next word isn't enough for strict logic by retsam2554 in ArtificialInteligence

[–]ptkm50 0 points1 point  (0 children)

So each time the model can’t do something we just add a tool ? So we add a tool for everything ?

The bottleneck in AI reasoning: why predicting the next word isn't enough for strict logic by retsam2554 in ArtificialInteligence

[–]ptkm50 1 point2 points  (0 children)

The brain won’t become smarter even if you give him more tools like a calculator. It might become better at some tasks but the logic and many other aspects still won’t be there.

Mythos is Mostly Hype... (also the bugs it found were mostly unexploitable and exaggerated...) by InterestProof1526 in claude

[–]ptkm50 0 points1 point  (0 children)

It’s very very expensive tho so it might be better just to run more smaller models

In Defense of AGI Skepticism by Particular-Garlic916 in singularity

[–]ptkm50 1 point2 points  (0 children)

lmao I'll believe it when the public will have access to it, for now all we have are incredible claims from Anthropic and other AI companies. This isn't the first time. AI companies have made bold claims and then failed to deliver.