Isamu

Wait, is the tree in a VM?

To me the dream of AI is: an agent can do the drudge work of tracking every statement down to the supporting reference, documentation and ultimately the work involved in verifying.

It is NOT being used for this, instead we want faster “answers” that avoid due diligence. Same as always but lazier.

You are comparing the sins of corporations that have been around for over 100 years and world wars to one that has been around a couple decades? Give Meta some time, they seem to have aspirations.

I started using the original TECO based Emacs on TOPS-20 at CMU in maybe 1980, so much better than the line editor of the time.

And I used Emacs (on Linux) this morning.

Let me know if you remember the DEC20 and the dreaded “not running” message that happened to everyone in the room when it went down.

Also interested if you remember Gosling Emacs, the first rewrite for Unix. James Gosling of Java fame.

> Workers are under the perennial illusion that they'll ever benefit from productivity gains, but that hasn't been the case since the 1970s.

Agreed, except that workers have never benefited from productivity gains, those always accrue to the employer.

The wage growth before the 1970s was mostly from the postwar boom, before jobs started to be moved out of the country. After that there was downward pressure on wages.

When I was young I did summer work for a woman who described how difficult it was getting to find a new washer with a wringer, which if you are not familiar is a pair of rubber rollers above the washtub to really squeeze out the water. This was a wealthy woman who just couldn’t change her workflow.

I think you are interpreting “mashup” to mean something like a collage where there’s snippets of a literal piece of this next to a literal piece of that.

But the language model captures not just literal patterns but also patterns of patterns and higher order structures. This is what is mashed up. The model itself doesn’t capture anything beyond what it was trained on but that’s quite enough, it is always a bigger training set than most humans have read on in a lifetime.

This brute force approach is very effective.

Their “takes” are pulled from a mashup of the training data set. It’s a superposition of various human opinions.

The covid experience for corporate is that they can save money by downsizing the office, reducing leases and maintenance costs. In my experience this was followed by increased in-office requirements, such that you are then competing for space.

There is always an internal tension between what works and what they can cut. They will tend to err on the side of cutting too much, in order to meet cost reduction goals, and then correct in order to meet production goals. In control theory we recognize this as not optimal.

I think it depends on the motivation of the funding partners. I think funding is mostly about building researcher and student talent and knowledge moving forward.

To transfer that to AI in private hands seems a bit crazy, but what do I know? I think funding bodies will stay the course in the short term before bending to some behind closed doors persuasion to feed the AI machine.

>divert resources away from math and become a math research entity unto themselves

If only pure math were a source of riches, that might work out well for them.

I have a book on mathematical cranks where that seems to be the common delusion, that if only you solve some open problems then fame and fortune must surely follow.

I agree it’s very mixed, it strongly depends on what you are developing, how big and established your codebase is, how opinionated you are about simple vs overdone, how many subtle and nonlocal interactions your codebase has, etc. Plus the more experienced you are the more you are likely to reject the AI solution as not well considered, whereas to someone new may think it looks plausible and confident.

Yeah what’s disingenuous about the “spies from China” is that if they are already identified as spies they would be under targeted surveillance already.

I think we should start to shift away from pure concern that a text is written by AI and toward strictly rewarding better writing. I realize that only some of this involves literal pattern matching against annoying AI ticks that grate like fingernails on a chalkboard.

But moving forward the goal should remain that writing should be comprehensible and not overly reliant on templates and other annoyances.

[edit] some good disagreements here which I appreciate. Thanks! I am continuing to think about this.

Okay whose design

I look to AI as an unprecedented tool to clear out the slop and find the well supported work. But no, the slop pipeline pays its way and finding a way around it is not very important it seems.

I love that the comments on TFA include Unicode cuneiform, not images

Conflating two things. Actually lobbying is the act of trying to persuade by meeting with a representative. Campaign contributions are also a way of persuading but are separate.

I say this because you could make monetary contributions illegal and lobbying would still be legal and ethical. We talk about campaign contributions as a separate issue and they have been treated in the courts separately.

I agree that putting strict limits on campaign finance is an important battle that is still ahead of us.

Campaign finance is [currently] corrupt. But it doesn’t have to be that way.

Anything before latex would be a based on an animal intestine eg rather the same as a sausage casing, except maybe tanned to make it durable. Not inexpensive, not very disposable. Not in widespread use.

You can be a democratically elected dictator. A dictator is defined by the powers they possess, not by the process by which they obtained power.

There is an ongoing argument in the US that a person was elected, therefore everything they do after that has the blessing of the electorate. Funny thing though, the people don’t really have a crystal ball to see into the future how their elected official will decide betray the country in the name of a “mandate”.

>and, most significantly, there has been a wave of AI-produced solutions provided with no explanation.

Counter productive and dumb, although not dumb from the viewpoint of an AI company trying to win hearts and minds hoping that translates into revenue.

Lots of mathematical problems require WORK, and now we have a homunculus to do the work. Indeed most AI companies are oriented toward brute forcing every way forward in order to claim the prize of being profitable.

This could genuinely serve the purpose of mathematical understanding for humanity, but in the short run it is a series of stunts. In the long run I am optimistic that we will benefit.

Sure, my point is not that you can’t wire up introspection, just that it’s not currently an extensive part of image generation. I expect that to change over time as better quality is demanded.

“Don’t tread on me, tread on THEM”

The part of the AI generating the mashup doesn’t really understand what the signature means, or how it may be interpreted, it’s just a visual part of a New Yorker cartoon. Elsewhere in ChatGPT there is plenty of information about signatures and what they mean, and what plagiarism is.

It’s not organized like a human brain, it shouldn’t be surprising that unusual results occur. They are approximating human intelligence from a different angle. It’s interesting to see the improvements in areas like this that require introspection that isn’t fully wired up yet.

[edit] I should add that a human making a New Yorker cartoon is extremely iterative and introspective. Current generative AI is meant to push it out, and you can do the iteration and introspection yourself.

Yeah discussions of consciousness fail to define it in detail because that’s boring, you want to jump ahead to whatever conclusions you have already reached.

It’s an image of ink-on-paper cursive handwriting, with what looks like markings added during the original decryption to keep track of where they were in the process.

So image to text, then a brute force attack on a Napoleonic era cypher.

This is one of the reasons why AI companies are looking for explicit regulations, it can help to reduce the risk of possible liability and maybe make the legal way forward more tractable. With a regulatory framework in place much of the burden of identifying risks falls on the regulatory authority.

Then the AI companies have more confidence that they can move forward in a certain way, and issue investor guidance that is maybe closer to reality.

The lore of the church is fascinating, the story is that the line of Solomon came to Ethiopia by way of the Queen of Sheba, and the ark of the covenant made its way there. And that figures into Rastafarian beliefs.

I agree, there’s the collective intelligence that created all the content used to train the model. The model is a superposition of all that material with RL tuning. Analogously to reading a book, the intelligence you perceive is from the book’s creator.

You could look at it as a kind of evolutionary pressure, where the AI driven companies that have no tether to reality are eventually extinct. Companies that are able to get a handle on the direction they are being dragged may have a fighting chance of survival.