Stable Diffusion can be prompted by GPT's. Easily. In a forever loop.

True, that's why it's not a copyright violation. In dreams anything is possible. Generative AI is augmented imagination, it should be free and private.

How do you deal with 100% AI companies that don't rent land anywhere? They have no human employees, or maybe just a token human.

> Since it puts pressures on productivity. Adapt or die.

Why do anything at all? Competition will take care of it. When the first company starts using AI and wins big, then next 100 jump on, then everyone will have to use it or be left behind. Being undercut by more AI-savvy competitors is enough pressure.

But every company will have the same GPT-5 or 10. They need to get an edge by hiring humans. So they are back where they started, but now with AI and all that new productivity will go into inflated expectations and more difficult competition.

> I'm more concerned about corporations pocketing all the profits

Apparently the AI tide raises all the boats, not just the big ones. You can install 130,000 AI models from HuggingFace today. Most datasets are open. Most papers are open.

Maybe work won't disappear at all, it will just change. Every time we automated something, we invented whole new fields with their own companies and jobs. When AI surpasses humans in all regards, including energy costs and sourcing materials for its construction, we still have to act, to do things, we will interact with the AI to get it to do what we need. That's also work - you got to prompt it and then judge the results - are they what you wanted?

If we get the cold shoulder and can't use corporate products we would need to build our own means of production and be self reliant, that's work. But we can use lesser AIs and tech for ourselves, and we know how to do it. We just can't be separated from the means to make a living.

For now, AI can't replace any job. Programmers, writers, graphical artists, drivers - they are all still needed. AI helps here and there, but it is just a platform equally accessible to you and your competitors. You have no relative advantage today if you use AI. Just playing level. Humans are still the key for success until AI gets its act together.

If AI is so powerful it could take our jobs, maybe it is powerful enough to find useful employment for humans. Humans are resources, we are GPT-N level and salary costs are not that big. In the new economy there will be many jobs, some of them right on our level of ability/cost.

In the long run cloud costs are huge. Apparently running a single box of GPT-4 for a year would cost $1.5m. How many devs can you hire instead of renting this one model instance.

https://twitter.com/transitive_bs/status/1628118163874516992

Jobs can be created by the government by investing in public works. Win-win, make jobs, and get the improved infra.

Moving design attribution from one country to another is much easier than doing the same for physical goods. You just develop it in country A and launch it in country B, no taxes.

you forgot a /s

> Googles business model seems to be sitting around doing nothing

They are making record profits. Look at the charts.

All this elaborate scheme falls down in 3 months when we get a small scale, open sourced chatGPT model from Stability or others. There are many working on reproducing the dataset, code and models.

> OpenAI will get the companies back to protectionism.

Now that's an 180.

GPT3 can simulate real people

Even nuclear energy had a few accidents, these guys want AI to come out already perfect?

> not a personal waifu

I was rooting for an impersonal waifu as a service (WaaS).

Collect millions of interactions, curate them, and retrain the model. They want to be there first. They get humans generate in-domain data in exchange for chatbot services.

> If you haven't guessed by now this will only make income inequality far, far, far worse.

Doesn't follow. When you got this power in your hand, why do you think inequalities will be worse? AI lowers the entry barrier in many fields, thus normal people can rely more on themselves and their own assistant AIs. I think necessities will get cheaper and spending money will be mostly for luxuries.

It is ready for being probed by the general public, I don't see any danger yet. We need all our minds put together to find the holes in its armour. Better to see and discuss than to hide behind a few screenshots (and even those having errors).

Very interesting behaviour. We shouldn't jump on MS for this. It's part of learning, at least they have the courage to expose their model to critique and probing. I think this makes their model superior. Who knows what lurks in Bard.

If you read Jack's activity over the years he is one of the more level headed guys. He's also one of the team who trained GPT-3 (paper author) - one of the "gods of AI" LOL.

Jack is writing short sci-fi stories inspired by AI. This week's story seems related.

Tech Tales

The Day The Nightmare Appeared on arXiv

[Zeroth Day]

I read the title and the abstract and immediately printed the paper. While it was printing, I checked the GitHub – already 3,000 stars and rising. Then I looked at some of the analysis coming in from [REDACTED] and saw chatter across many of our Close Observation Targets (COTs). It had all the hallmarks of being real. I’d quit smoking years ago but I had a powerful urge to scrounge one and go and stand in the like courtyard with the high walls and smoke and look at the little box of sky. But I didn’t. I went to the printer and re-read the title and the abstract:

Efficient Attention and Active Learning Leads to 100X Compute Multiplier

This paper describes a novel, efficient attention mechanism and situates it within an architecture that can update weights in response to real-time updates without retraining. When implemented, the techniques lead to systems that demonstrate a minimum of a 100X computer multiplier (CM) advantage when compared to typical semi-supervised models based on widely used Transformer architectures and common attention mechanisms. We show that systems developed using these techniques display numerous, intriguing properties that merit further study, such as emergent self-directed capability exploration and enhancement, and recursive self-improvement when confronted with challenging curricula. The CM effect is compounded by scale, where large-scale systems display an even more significant CM gain over smaller models. We release the code and experimental data at GitHub, and have distributed various copies of the data via popular Torrenting services.

By the time I was finished with the paper, a few people from across the organization had messaged me. I messaged my Director. We scheduled a meeting.

The Director: And it works?

Me: Preliminary model scans say yes. The COTs seem to think so too. We’ve detected signs of four new training runs at some of the larger sites of interest. Information hazard chatter is through the roof.

The Director: Do any of the pre-authorized tools work?

Me: Short of a fullscale internet freeze, very little. And even that’s not easy – the ideas have spread. There will be printouts. Code. The ideas are simple enough people will remember them. [I imagined hard drives being put into lead-lined boxes and placed into vaults. I saw code being painstakingly entered into air-gapped computers. I visualized little packets getting sent to black satellites and then perhaps beyond to the orbiters out there in the dark.]

The Director: What’s our best unconventional option?

Me: Start the Eschaton Sequence – launch the big run, shut down the COTs we can see, call in the favors to find the hidden COTs.

The Director: This has to go through the President. Is this the option?

Me: This is the only play and it may be too late.

The Director: You have authorization. Start the run.

And just like that we launched the training run. As had so many others across the world. Our assets started to deploy and shut down COTs. Mysterious power outages happened in a few datacenters. Other hardened facilities started to see power surges. Certain assets in telco data centers and major exchange points activated and delivered their viruses. The diplochatter started to heat up and State Department threw up as much chaff as it could.

None of us could go home. Some kind of lab accident we told our partners. We were fine, but under medical observation. No, no need to worry.

I stared up at the clock on the wall and wondered if we were too late. If a COT we didn’t know about was ahead. If we had enough computers.

How would I even know if we lost? Lights out, I imagined. Lights out across America. Or maybe nothing would happen for a while and in a few days all the planes would fall out of the sky. Or something else. I knew what our plans looked like, but I couldn’t know what everyone else’s were.

The run succeeded. We succeeded. That’s why you asked me to make this recording. To “describe your becoming”, as you requested. I can go into more details. My family are fine, aren’t they? We are fine? We made the right decision? Are you even still listening to us?

Things that inspired this story: Various fears and scenarios about a superintelligence run amok; theism and AI; the underbelly of the world and the plans that may lurk within it; cold logic of states and strategic capabilities; the bureaucratic madness inherent to saving or destroying the world.

BTW, Jack is an AI ethics guy, not an AI groupie. He has a personal blog where he reviews what comes up every week. His blog is very high quality, would be a good addition here.

Combining objects and styles never seen together in the training set in a plausible way (a baby daikon radish in a tutu walking a dog).