barking_biscuit

It's one of the biggest games in the world, so I can see the appeal of targeting Minecraft players, especially since a lot of them are children and don't know what's going on. I checked my sons computer for this malware yesterday, and luckily he wasn't infected, but I ran OSForensics on his computer afterwards to see if he did get infected what kind of data an attacker might be able to get, and there was all sorts of PII from myself and my wife having used that computer before at one point or another. I'm sure with such a large install base there's plenty of opportunity to steal lots of valuable info.

This is my take too. If we knew then what we know now, we'd probably make different choices.

But then how would you loan out all your customers money to your shell companies?

I remember fondly participating in the hype around crypto in 2017 and going in on btc/eth and also building a mining rig etc. The discourse on HN back then is quite different from today. These days we've seen scam after scam, fraud after fraud, failure after failure. From a technology perspective it's neat, but the kinds of individuals it tends to attract make it seemingly not actually all that useful in wider society. These days I'm ultra skeptical of anything crypto.

I'm with you on this one. It was a solid argument in 2017, but even by 2018 the writing was on the wall for crypto. John Oliver recently did another segment on crypto and he absolutely nailed it in saying that the only real currency in crypto is confidence, and that tends to attract a certain kind of individual, namely scammers/fraudsters.

It feels like we're at the pareto frontier. Technological advancement used to feel like it truly was progress, but we're now at a point where advancement is simply advancement, and we're well aware that as the technology advances, there's an equal an opposite regression in society somewhere.

This feels like the correct take to me.

> What's "bad" enough to get a user banned from _all_ of Reddit?

explicit deepfakes

What's super confusing is people on r/LocalLLaMA often just refer too it as "ooba". The actual repo is https://github.com/oobabooga/text-generation-webui and you notice that oobabooga is actually the username, but a lot of non-technical people who don't use git are also playing around with stuff, and "text-generation-webui" is so generic as to be completely forgettable, and "oobabooga" is confusing and too long to say, so colloquially it's referred to as ooba.

That's humans for you.

>If we refused to advance out of fear, that fear will have done far more harm than access to AI will ever do.

Like anyone could ever know that.

Also people should know RT == Russian Propaganda

If you define it like that, it's just the internet.

We're all research professionals now.

An absolutely huge part of it for humans is that as the complexity of the thing being reasoned about grows, the accuracy of the mental models declines. That and we also train billions of individual models on a narrow slice of reality, and leverage a distributed consensus protocol through low-bandwidth "conversations" to update the weights. I think you could probably emulate this with conversational agents each with their own LoRA, that way they wind up with differing opinions.

This is crazy cool. This would be epic as an extension for text-generation-webui, so that we can run it with local LLMs!

At the risk of repeating classic HN Dropbox hubris... this just looks like what Automatic1111 + ControlNet is already doing.

>So it is with any technological innovation. Should computers not have been invented because they eliminated jobs? Should steel? What about agriculture? The future is sure to be different, but that doesn't mean we should fight to deny progress. That way lies the Luddite and Conservative. It's only possible to use new tools for good, not try to erase them to prevent evil.

It's not even necessarily evil, right? It's more likely just one big "whoops, majority of us didn't see that coming, and/or didn't agree with those who said it was". But that whoops lands you in a position that you may not be able to recover from.

Ben Geortzal makes your exact argument here: https://youtu.be/MVWzwIg4Adw?t=2795 and in the same interview he is talking about how his company already spent time and money on building decentralized infrastructure for it to run on "so that no one person can turn it off and stop the singularity" and gives his take that the takeoff is likely to be on the order of years and that it's going to be very rough.

So, he at least seems to acknowledge that it's very risky, and that we have no idea what we're actually walking into, but he also just doesn't seem to care if that happens to be a one-way door we walk through and find a big "oopsie" on the other side of.

This is the guy credited with popularizing the term AGI in the first place. I dunno man... am I wrong to be worried?

It's a fantastic interview. To clarify, his position boils down to something like "the risk is very real, the chance the risk materializes is quite significant, it's not a foregone conclusion that we are all definitely going to die from it, so there is some hope, but it's likely the default outcome and there aren't many people who take it seriously or who are working on it." I would say he's net bearish on it, which is why he spends time working on trying to mitigate the X-risk, or attempting to at least.

>Do you have a counterexample of someone who's gotten their predictions right? Because if not, that should only terrify you even more. If there's anyone out there who predicted how LLMs would work in a way Eliezer failed to, and if that person is predicting "AGI will be cool and will naturally prioritize our well-being", I would love to know.

A recent interview with Paul Christiano is about the closest I've come to this. He does note some semi-accurate predictions at the linked timestamp, but the forecast for how things are likely to go is not exactly rosy, though he's quite a bit more optimistic than Eliezer.

https://youtu.be/GyFkWb903aU?t=1357

Also this whole interview was pretty interesting. Near the end he details how few people world-wide actually work on X-risk from AGI. He also outlines how the academic ML community in general just continually keeps getting predictions really wrong, and many aren't taking X-risk seriously.

Overall his is the most balanced take I've seen. A lot better than Eliezer.

After watching virtually every long-form interview of AI experts I noticed they each have some glaring holes in their mental models of reality. If even the experts are suffering from severe limitations on their bounded-rationality, then lay people pretty much don't stand a chance at trying to reason about this. But let's all play with the shiny new tech, right?

>I used to be worried about AI alignment, until I realized something fundamental: We already have unaligned human-level artificial intelligences running around, we call them corporations

We also call them governments. They can get pretty powerful.

>"What will we do with all the people when we're optional?"

Judging by the COVID-19 pandemic response, having large aggregates of disempowered individuals from a highly irrational and political species that have become unhappy with the "new normal", it tends to garner some form of reaction. If they are reacting to things that observe and learn from those reactions, and then formulate new goals or sub-goals in response to what they learn, then what is it they might learn and how might they react?

The arguments go both ways. The only thing that's clear is that absolutely nobody on earth is going to be able to predict it with any degree of accuracy. You'd have to know too much.

Didn't know about this. Looks promising!

Can we call it LLMPeg?

Xenobots, even.

I didn't get the punchline of this, so I asked GPT-4 to explain the punchline. Actually quite amusing.

>"we can get results similar to OpenAI's API with our model that you can run on a Commodore 64!"

I have felt similar frustrations with statements that feel disingenuous too. Thanks for articulating this with such a beautifully hilarious metaphor.

No, the point is those people are also a black-box to you and they are a black-box that you trust because of YOUR training set and training process.

>If you want to trust a prediction, you need to understand how all the computations work.

I disagree with the premise here. You don't understand how all the computations work in the brains of people's predictions whom you trust. You simply have a mental calculation of their batting average through exposure to their track record and this batting average functions as a proxy for trust.

I find this is more or less the same way that I learn whether or not I can rely on GPT-4 for a particular use-case. If it's batting average is north of a certain % for a given use-case, then it doesn't need to be right 100% of the time for me to derive value from relying on it.

I think we are slowly crossing a threshold where we accept indeterminism and mistakes from machines in a way that we haven't in the past.

This is the main scenario I see that leads to "Oops, we didn't see that one coming, but in retrospect that was NOT a good idea".