Unpopular Opinion

Depends on where you live I suppose. Irrational AI hate is something I only really encounter online. Then again my country has pretty good worker protections, so there's less reason to be afraid of AI.

I don’t know, there’s plenty of anti-billionaire sentiment, fuck_cars is basically anti-capitalist, and most of the environmentalists get to the same conclusion pretty quickly too.

The realists (and cynics in some cases) just know that it’s going to take a huge process to shift us away. I’m a realist and am opting for a progressive takeover that leads to taxing billionaires, carbon/pollution, and dangerous vehicles (among other clear hazards) out of existence.

But when I’m feeling cynical, I get worried that it’s going to take a war to happen, and I hope for my son’s sake that doesn’t happen.

If used correctly newer generation AIs could be an absolute game changer In fields like medicine, finances, computing, public transport, customer services etc.

But what they'll actually be used for is to make more money.

If you take capitalism out of the equation they could be an amazing force for good. But under our current system they won't.

because AI is just a tool.

it could be used for good.

Because when greed and money aren't in the equation, AI is pretty useful and for most people it isn't costing them anything.

Mhmm. Here's the uncensored anti-woke AI Elon tried to create answering Twitter blue subscribers questions:

Or

Or

Yeah, so horribly biased and terrible...

Yes, the only two genders: capitalist economy and communist government.

If the means of production are collectively owned, and thus directed towards the good of society, job elimination isn't as much of a problem.

Socialists are huge proponents of automation, because instead of being used to cut jobs for profit, dirty and hard jobs can be eliminated.

Job elimination is a problem in capitalism because workers need jobs to survive. In a socialist society, job elimination can be a good thing, as it allows us to either increase access to resources or reduce how much time people need to work without dispossessing the people whose jobs were eliminated.

The difference is that, in capitalism, workers only survive by proving their usefulness to capitalists making money. Automation is thus a threat to worker bargaining power. If the means of production were socially owned (through for example government run utilities or worker coops), worker bargaining power is then through a vote or through ownership. It is possible to by default distribute the spoils of automation rather than concentrate them in the hands of capitalists.

LLMs real power isn't generating fresh content it's their ability to understand language.

Using one to summarise articles gives incredibly good results.

I use Bing enterprise everyday at work as a programmer. It makes information gathering and learning so much easier.

It's decent at writing code but that's not the main selling point in my opinion.

Plus they are general models to show the capabilities. Once the tech is more advanced you can train models for specific purposes.

It seems obvious an AI that can do creative writing and coding wouldn't be as good at either.

These are generation 0. There'll be a lot of advances coming.

Also LLMs are a very specific type of machine learning and any advances will help the rest of the field. AI is already widely used in many fields.

https://www.sciencedaily.com/releases/2023/12/231205144405.htm

Can you prove that human intelligence isn't an overhyped plagiarism machine?

Furthermore, simple probability calculations indicate that GPT-4's reasonable performance on k=5 is suggestive of going beyond "stochastic parrot" behavior (Bender et al., 2021), i.e., it combines skills in ways that it had not seen during training.

• https://arxiv.org/abs/2310.17567

Do these networks just memorize a collection of surface statistics, or do they rely on internal representations of the process that generates the sequences they see? We investigate this question by applying a variant of the GPT model to the task of predicting legal moves in a simple board game, Othello. Although the network has no a priori knowledge of the game or its rules, we uncover evidence of an emergent nonlinear internal representation of the board state.

• https://arxiv.org/abs/2210.13382 (replicated here and here (with chess))

So you already have research showing that GPT LLMs are capable of modeling aspects of training data at much deeper levels of abstraction than simply surface statistics of words and research showing that the most advanced models are already generating novel and new outputs distinct from anything that would be in the training data by virtue of the complexity of the number of different abstract concepts it combines from what was learned in the training data.

Like - have you actually read any of the ongoing actual research on the field at all? Or just articles written by embittered people who are generally misunderstanding the technology (for example, if you ever see someone refer to them as Markov chains, that person has no idea what they are talking about given the key factor of the transformer model is the self-attention mechanism which negates the Markov property characterizing Markov chains in the first place).

instead of an overhyped plagiarism machine first.

If I paint an Eiffel Tower from memory, am I plagiarizing?

If it's not plagiarism when humans do it, it's not plagiarism when a machine does it.