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Many in the AI field think the bigger-is-better approach is running out of road

economist.com

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Re: Many in the AI field think the bigger-is-better approach is running out of road

#181

Post by indigoabstract »

bemmu wrote: post #111
michaelteter wrote: post #63

Isn't the fundamental problem that LLM's don't actually understand anything (as greater concepts), but rather operate as complex probability machines? My 2 month active experience with ChatGPT-4 gave me the following takeaways: - when it's right, it's amazing; and when you, the operator, can recognize the niche use case where it performs really well, it can be a game-changer (although you could have programmed a tool…

I’m not convinced the language part of my brain isn’t just a complex probability machine, just with different trade-offs.

I am pretty sure that my understanding of something (or lack of) is not encoded into words and probabilities. It's more like a feeling of "I got this figured out" or "I haven't grasped this".

Words seem more like a protocol to express some internal model/state in the brain and can never capture the entire actual state, only a small part of it. But since we're not telepaths, we obviously need to use words to exchange information.

Re: Many in the AI field think the bigger-is-better approach is running out of road

#182

Post by flangola7 »

chaosjevil wrote: post #172
bemmu wrote: post #111

Earlier quoted context omitted.

I’m not convinced the language part of my brain isn’t just a complex probability machine, just with different trade-offs.

Nah. Human utterances convey purpose on a discursive level; including your comment or mine. We say stuff because we want to do something, like showing [dis]agreement or inform another speaker or change the actions of the other speaker. This is not just probabilistic - it's a way to handle the world. In the meantime those large language models simply predict the next word based on the preceding words.

> We say stuff because we want to do something, like showing [dis]agreement or inform another speaker or change the actions of the other speaker.

My LLaMA instance is absolutely capable of this. ChatGPT shows a very, very narrow range of possible LLM behaviors.

Re: Many in the AI field think the bigger-is-better approach is running out of road

#183

Post by siilikuin »

goldenshale wrote: post #157
ilaksh wrote: post #147

Earlier quoted context omitted.

Warning people about potential extreme risks from advanced AI does not make you a cultist. It makes you a realist. I love GPT and my whole life and plans are based on AI tools like it. But that doesn't mean that if you make it say 50% smarter and 50 times faster that it can't cause problems for people. Because all it takes is systems with superior reasoning capability to be given an overly broad goal. In less than fi…

A realist is someone who accepts reality as it is, not as they might be able to anxiously envision that it could be. Life is too short and attention too precious to fill the meme space with every dreamer's deepest concerns. None of these dramatic X-risk claims is based on anything but beliefs and conjecture. "Thinking dozens of times faster?" What do you even mean? These are models executing matrix multiplies billion…

Let's try to rewrite this in a somewhat more dispassionate style:

A pragmatic perspective requires one to accept the present reality as it is, rather than hypothesize an exaggerated potential of what could be. Not all concerns surrounding existential risks in technology are necessarily grounded in empirical evidence. When it comes to artificial intelligence, for instance, current models operate at a speed vastly superior to human cognition. However, this does not equate to sentient consciousness or personal motivation. The projection of human traits onto these models may be misplaced, as AI systems do not possess inherently human drives or desires.

Many misconceptions about reinforcement learning and its capabilities abound. The development of systems that can translate abstract objectives into detailed subtasks remains a distant prospect. There seems to be a pervasive certainty about the risks associated with these models, yet concrete evidence of such dangers is still wanting.

This belief system, one might argue, shares certain characteristics with a doomsday cult. There is a narrative that portrays a small group of technologists as our only defense against a looming, catastrophic end. These artificial intelligence models, which were engineered after extensive research, are often misinterpreted as inscrutable entities capable of outsmarting and eradicating humanity, while simultaneously being so simplistic as to obsess over trivial tasks.

Alternatively, these AI models could be viewed as valuable tools for knowledge compression and distribution, enabling the advancement of civilization. As a result, societal education levels could improve, and the cost of goods and services might decrease, which could potentially enrich human life on a global scale. While there seems to be a tendency to worry about every potential hazard, optimism about the future is not unfounded given the trajectory of human progress.

There are certainly different perspectives on this issue. Some adhere to a more fatalistic viewpoint, while others are working towards a brighter future for humanity. Regardless, once the present fears subside, everyone is invited to participate in shaping our collective future.

Re: Many in the AI field think the bigger-is-better approach is running out of road

#184

Post by thomasahle »

michaelteter wrote: post #63

Isn't the fundamental problem that LLM's don't actually understand anything (as greater concepts), but rather operate as complex probability machines? My 2 month active experience with ChatGPT-4 gave me the following takeaways: - when it's right, it's amazing; and when you, the operator, can recognize the niche use case where it performs really well, it can be a game-changer (although you could have programmed a tool…

> LLM's don't actually understand anything (as greater concepts), but rather operate as complex probability machines?

What does it mean to "operate as a probability machine"? And what does it mean to understand anything?

One recent example of understanding is that llms/transformers learn to parse context free grammars via dynamic programming (https://arxiv.org/abs/2305.02386). Basically they've understood what's going on well enough to mold their neurons I to the optimal algorthm for parsing this kind of text.

I think they understand lots of things like this. Of course there's other things they don't understand or just pretend to understand.

Re: Many in the AI field think the bigger-is-better approach is running out of road

#185

Post by thomasahle »

tempodox wrote: post #159
michaelteter wrote: post #63

Isn't the fundamental problem that LLM's don't actually understand anything (as greater concepts), but rather operate as complex probability machines? My 2 month active experience with ChatGPT-4 gave me the following takeaways: - when it's right, it's amazing; and when you, the operator, can recognize the niche use case where it performs really well, it can be a game-changer (although you could have programmed a tool…

Only you, a human developer can be truly creative. An LLM can only ever reproduce what it has seen before.

> An LLM can only ever reproduce what it has seen before.

Anyone who's played around with these models know that at least some generalization is taking place.

Re: Many in the AI field think the bigger-is-better approach is running out of road

#186

Post by goldenshale »

p-e-w wrote: post #167
goldenshale wrote: post #158

Earlier quoted context omitted.

What nonsense. I've spent over a decade 100% focused on AI, and the broad consensus among everyone I've worked with is not to be that concerned at all. The only consensus is that a small group of self proclaimed experts who make a lot of noise is that they get lots of press coverage if they scream and shout making predictions based on zero scientific evidence. We can understand the physics of greenhouse gases and tak…

> Show me any evidence for AI risk today beyond people's theories and beliefs? Deduction. Empirical evidence isn't the only source of insight. You don't have to conduct experiments in order to reasonably conclude that an entity that 1. outperforms humans at mental tasks 2. shares no evolutionary commonality with humans 3. does not necessarily have any goals that align with those of humans is a potential threat to hum…

1) Computers, smart phones, and pocket calculators also outperform humans at mental tasks. So do birds, dolphins, and dogs for that matter, at tasks for which they are specialized.

2) so? What are you imagining this implies? An infinity of possibilities does not a reason make, unless you are talking about arbitrary religious beliefs.

3) Right, no goals, no will, no purpose. Just some matrix multiplies doing interesting things.

Deduction requires a premise which then leads to another premise or a conclusion due to accepted facts or reasons. I'm genuinely curious why you think any of these properties automatically implies danger?

The future is uncertain. The stock market, the economy, your health, your friendships and romances, are all unpredictable and uncertain. Uncertainty is not a reason to freak out, although it might encourage us to find ways to become adaptable, anti-fragile, and wise. I think AI will help us improve in these dimensions because it is already proving that it can with real evidence, not beliefs.

Re: Many in the AI field think the bigger-is-better approach is running out of road

#187

Post by [deleted] »

chaosjevil wrote: post #172
bemmu wrote: post #111

Earlier quoted context omitted.

I’m not convinced the language part of my brain isn’t just a complex probability machine, just with different trade-offs.

Nah. Human utterances convey purpose on a discursive level; including your comment or mine. We say stuff because we want to do something, like showing [dis]agreement or inform another speaker or change the actions of the other speaker. This is not just probabilistic - it's a way to handle the world. In the meantime those large language models simply predict the next word based on the preceding words.

[deleted]

Re: Many in the AI field think the bigger-is-better approach is running out of road

#188

Post by letitgo12345 »

croes wrote: post #83
letitgo12345 wrote: post #67

Earlier quoted context omitted.

The next iteration will be trained on your own data where "when it's a little wrong, you (the expert) can fix the issue and move on without friction" so that case will become "when it's right" and some amount of "when it's any amount of wrong" cases will become "when it's a little wrong". A few more cycles of this and we could be looking at GPT-10 which is a complete replacement for most tasks.

Better result from less data? I doubt that.

? adding on ChatGPT data into existing data is not lessening the amount of data...

Re: Many in the AI field think the bigger-is-better approach is running out of road

#189

Post by goldenshale »

siilikuin wrote: post #183
goldenshale wrote: post #157

Earlier quoted context omitted.

A realist is someone who accepts reality as it is, not as they might be able to anxiously envision that it could be. Life is too short and attention too precious to fill the meme space with every dreamer's deepest concerns. None of these dramatic X-risk claims is based on anything but beliefs and conjecture. "Thinking dozens of times faster?" What do you even mean? These are models executing matrix multiplies billion…

Let's try to rewrite this in a somewhat more dispassionate style: A pragmatic perspective requires one to accept the present reality as it is, rather than hypothesize an exaggerated potential of what could be. Not all concerns surrounding existential risks in technology are necessarily grounded in empirical evidence. When it comes to artificial intelligence, for instance, current models operate at a speed vastly supe…

Hahaha, thanks ChatGPT! This is better said than my snarky, frustrated at the FUD version, and I can learn from the approach.

Re: Many in the AI field think the bigger-is-better approach is running out of road

#190

Post by civilized »

p-e-w wrote: post #153
goldenshale wrote: post #120

As if anyone is good at predicting the future. Please can we stop acting like expertise equates to fortune telling capabilities?! Nobody has any clue what a 1000x sized GPT model could do, and anybody who makes strong claims is a charlatan. In this age of paranoid AI risk cultists we need to cultivate humility and calm, a willingness to follow data rather than beliefs and predictions.

> paranoid AI risk cultists There is broad consensus among experts that a hypothetical strong AI would be a threat, and potentially an existential threat, to humanity. While not everyone agrees on details like timeline and alignment issues, the idea that AI is dangerous is not a cult, it's the mainstream view. Climate scientists cannot "predict the future" with certainty either. That doesn't mean their warnings are h…

"Expertise" in a speculative concept like AI risk is not remotely comparable to expertise in a scientific field like climate change.

There are two definitions of expertise:

1. Knowing more than most people about a topic. This is the type of expertise that wins the Quiz Bowl.

2. Actual mastery of a field, such that predictions and analyses generated by a person possessing such mastery are reliable. This is the type of expertise that fixes your home or car.

The first definition is easily verifiable, and due to the availability heuristic, it is often presented as a legitimate proxy for the second. But it isn't really, not in general.

If I know more about horoscopes than most people, I am a horoscope expert. But it doesn't mean I can be relied on to predict any of the things horoscopes supposedly predict. It's the same with AI risk. Expertise in AI risk is not a basis for credibility because AI risk is not a real scientific field.

Climate change is a real field of science. AI risk is Nostradamic prognostication by people who know more than you.

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