jablongo

I've got to come to the OPs defense as well. This was a remarkable demonstration of Claude performing a task thats probably very out of distribution. This would not be interesting if it were a music generation model or program, it's interesting because this is not what Claude code was explicitly trained for. The fact that it generated waveforms from scratch and built up from there is really amazing. Your cynicism was applied before even reading the article.

There needs to be more documentation about what info was provided to the LLM and in which format before we decide that LLMs are necessarily bad at this. That said, you would expect the offering from a $500bn company to be more robust and better tested than this, assuming this is reported accurately.

I think you could have credibly said this for a while during 2024 and earlier, but there is a lot of research that indicates LLMs are more than stochastic parrots, as some researchers claimed earlier on. Souped up versions of LLMs have performed at the gold medal level in the IMO, which should give you pause in dismissing them. "It can't actually understand how many there currently are, the season, how much land, etc, and do the math itself to determine whether it's actually needed or not" --- modern agents actually can do this.

Interestingly in healthcare there is a correlation between companies that license/sell healthcare data to other ones (usually they try to do this in a revokable way with very stringent legal terms, but sometimes they just sell it if there is enough money involved) and their privacy stance... and it's not what you would think. Often it's these companies that are pushing for more stringent privacy laws and practices. For example, they could claim that they cannot share anonymized data with academic researchers, because of xyz virtuous privacy rules, when they are actually the ones making money off of selling patient data. It's an interesting phenomenon I have observed while working in the industry that seems to refute your claim that "there's no money in privacy". Another way to think about it is that they want to induce a lower overall supply for the commodity they are selling, and they do this by championing privacy rules.

Trump received 77.3M votes while Kamala received 75M. Since the total was 156.7M it was barely a plurality instead of a majority (just under 50%).

I don't think the US has "shitty class relations". Most of your complaints are true, but in the US social class is mutable and upgrades to social class are encouraged and celebrated (even though this is becoming much more difficult in practice). Contrast this with Europe and other parts of the world with entrenched aristocracies and castes that survive generations. There are major problems but social mobility is still relatively better in US; in Europe healthcare is way better and being on the bottom rung isn't as bad, but fewer people from the bottom make it to the top.

Would the Rawlsian say this is unacceptable?

It is what it is thinking consciously / its internal narrative. For example a supervillain's internal narrative with their plans would go into their COT notepad. If we want to really lean into the analogy between human psychology and LLMs. The "internal reasoning" that people keep referencing in this thread.. referring to the transformer weights and inscrutable inner working of a GPT.. isn't reasoning, but more like instinct, or the subconscious.

Upcoming: Selective pressure of AI coevolution leads to humans with a fear of unplugging things and the ability to sleep while sitting.

Not sure what we should we make of this. Besides the tragedy of losing a human being and a scientist, is this significant in another way?

I tried to make ChatGPT sing Mary had a little lamb recently and it's atonal but vaguely resembles the melody, which is interesting.

I had Claude make a web interface and it was very similar stylistically. Looks like Claude has some design preferences of its own!

I'm curious -- did you make the interface with Claude? I have a hunch you did, can you confirm/deny?

Why would it be more like OG YouTube, when the content they demoed very closely resembles YouTube shorts? The key difference is OG YouTube was long form.

To be clear I'm not disgusted by AI in general, I'm disgusted by short form video and AI/ML in service of dopamine reward loop hacking.

its well underway already

I think the last one takes the cake.

Sam Altman has made (for me) encouraging statements in the past about short-form video like TikTok being the best current example of misaligned AI. While this release references policies to combat "Doomscrolling and RL-sloptimization", it's curious that OpenAI would devote resources to building a social app based on AI generated short form video, which seems to be a core problem in our world. IMO you can't tweak the TikTok/YouTube shorts format and make it a societal good all of a sudden, especially with exclusively AI content. This is a disturbing development for Altman's leadership, and sort of explains what happened in 2023 when they tried to remove him... -> says one thing, does the opposite.

I lets you inspect what actually constitutes a given cluster, for example it seems like the outer clusters are variations of individual words and their direct translations, rather than synonyms (the ones I saw at least).

Usually PCA doesn't look quite like this so this is likely done using TSNE or UMAP, which are non parametric embeddings (they optimize a loss by modifying the embedded points directly). I can see labels if I mouseover the dots.

GPT-5 claims it is just GPT-4o. Is OpenAI sending overflow requests to an earlier model? How could this not be the first thing they checked when they updated GPT-5?

It's also worth considering that past some threshold, it may be very difficult for us as users to discern which model is better. I don't think thats what's going on here, but we should be ready for it. For example, if you are an ELO 1000 chess player would you yourself be able to tell if Magnus Carlson or another grandmaster were better by playing them individually? To the extent that our AGI/SI metrics are based on human judgement the cluster effect that they create may be an illusion.

Tao is now transitioning to psychohistory.

Id like to hear about the tools and use cases that lead people to hit these limits. How many sub-agents are they spawning? How are they monitoring them?

Establishing ground truth for this is not easy. Often the labeled calories on foods are quite inaccurate themselves, based on n=1 bomb calorimetry tests. There are also incentives that may lead to lower than actual reported calories on the label.

Do you use the LiDAR Scanner on the iPhone for your predictions?

The article claims that none of these apps use "depth analysis", but newer iPhones have this capability. I would guess at least some of these apps are using some kind of volumetric analysis for the food when available.

It seems like the ranking of likely success in the next 10 years is

1. Commonwealth (tokamak w/ high temp superconducting magnets)

2. Helion (field reversed configuration, magnetic-inertial, pulsed) ....

?. Wendelstein (stellarator)

Maybe stellarators will be the common design in 2060 once fabrication tech has improved, but for the near future I think its going to be one of the first two.