diablozzq

No true Scottsman fallacy.

My point still stands

The crux of my argument is Consciousness is irrelevant to any AI debates. It’s not necessary to perform tasks we previously deemed only humans could do.

I say clearly as at some point we reach proof by construction. As in, we already built intelligence because the system already completes tasks that require intelligence.

We are so far into what would have been science fiction five years ago and the goal posts have moved so far.

For anyone who disagrees, I challenge you to prove deep learning systems cannot solve <task with specific outcome humans can solve but not AI> given sufficient data and compute.

I think the strongest sign we have true intelligence already is no one has built any benchmark that AI cannot solve.

Yes, our current robotics lags AI, so we don’t have the equivalent of the human body to give our deep learning systems. Thus, it’s expected AI will be limited in physical scenarios.

Second, hallucinations are present in humans. We are highly biased to ignore all the misspoken words in everyday life as we have error correction built into normal conversations. How often do you have to have someone repeat or rephrase something?

It just doesn’t make sense to me.

It’s like there are people out there whose belief systems are incompatible with this tech existing.

Sure, it has limitations due to training data. It has limitations with no physical body. It cannot combine training and inference the same way a human does. But none of those are measures of intelligence or required to be intelligent.

EVs are fine,

yes they are still limited in some cases.

Most of the sections had no citations and anecdotes.

Like many who have predicted doom or ChatGPT can never do XYZ, anecdotes do not build a substantive argument.

Thanks for the articles!

I’ve read through them and they are timeless.

Also the finding cures pivot from CS was inspiring how I could start one problem space and pivot. Definitely a top computer scientist story.

DIY components is rough for basic dev.

Easy enough to code something in html and JavaScript and let tools translate. Obviously not that simple, but an example of why it might not be as hard in 2024.

It’s a bold claim, but they are executing and have benchmarks for validating the performance and features.

Lots of work left to do - but the speed aspect is where other frameworks who have tried similar tend to choke. If you look at the web framework benchmarks on tech empower and the web frameworks for react, dioxus is ahead of 95% today. And the ones that are ahead, don’t support deployment to desktop mobile and web.

Mobile, desktop, web, rust

They have an eye on performance up front which is where most previous attempts fail.

And rust gives them the security and performance foundation up front.

.5 was a huge leap, this looks like the polish that should make it viable.

Then goal posts were moved to logical reasoning such as the Winograd Schemas. Then that wasn’t enough.

In fact, it’s abundantly clear we won’t be satisfied until we’ve completely destroyed human intelligence as superior.

The current goal post is LLMs must do everything better than humans or it’s not AGI. If there is one thing it does worse, people will cite it as just a stochastic parrot. That’s a complete fallacy.

Of course we dare not compare LLMs to the worse case human - because LLMs would be AGI compared to that.

We compare LLMs to the best human in every category - unfairly.

With LLMs it’s been abundantly clear - there is not a line where something is intelligent or not. There’s only shades of gray and eventually we call it black.

There will always be differences between LLM capabilities and humans - different architectures and different training. However it’s very clear that a process that takes huge amounts of data and processes it whether a brain or LLM come up with similar results.

Someone should up with a definition of intelligence that excludes all LLMs and includes all humans.

Also while you are at it, disprove humans do more than what ChatGPT does - aka probabilistic word generation.

I’ll wait.

Until then, as ChatGPT blows past what was science fiction 5 years ago, maybe these arguments aren’t great?

Also - name one thing we have the data for that we haven’t been able to produce a neural network capable of performing that task?

Human bodies have so many sensors it’s mind blowing. The data any human processes in one days simply blows LLMs out of the water.

Touch, taste, smell, hearing, etc…

That’s not to say if you could hook up a hypothetical neural network to a human body, that we couldn’t do the same.

But we consider humans intelligent.

They are using race to preferentially treat higher risk groups of people.

Sounds like the way you should treat people - higher risk first. Very click bait title.

  Location: Omaha, NE
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  Résumé/CV: https://docs.google.com/document/d/1Jo9ZSbBmsr2EuZ3N7jA5_I0gQT_v1FdN5jVD7gyg9wM/edit?usp=sharing
  Email: morlandkc (at) gmail (dot) com

I'm a OSCP / CISSP holder currently obtaining a Masters in Computer Science at Georgia Tech. Working on developing Ghidra (java) reverse engineering plugins for malware analysis.

My career has mostly been automation / security in Infrastructure. But I've developed ReactJS websites w/ postgres, and done about everything you can do on a computer, from assembly, C, to networking and infrastructure.

I want hard, challenging problems to solve.