light_hue_1

We had something similar with my father in law who just passed from pancreatic cancer.

The doctors each saw one small part of the case, he was being passed between multiple doctors and NPs. There was no coherence. At one point he ended up on so many medications that made no sense he passed out. Only at the hospital when a doctor looked at everything together did they realize what a mess had been created and got him back on his feet.

I ended up giving all of his records to an agent and making it the coordinator. It found a bunch of problems. He was being given the wrong pain medication on the wrong schedule, the moment that was fixed he felt a lot better (unfortunately he lost so much weight on the wrong schedule it's what got him in the end). They also use voice transcription software, which led to a key error about what genetic markers he had. Fixing this changed his treatment plan!

In general, I wish we had been much more aggressive with this. Last time we had a major medical issue an NP almost killed my wife. At the time there was no AI, so we just had to recognize things were in decline and start being aggressive about getting in with the right doctors (the moment we found the right one she was diagnosed, had surgery and was cured in weeks).

He started doing better when the AI became the central coordinator and doctors/tests/etc. became their inputs. It was an excellent advocate. And while we have science backgrounds, we aren't doctors. But it could present evidence for actions in ways that the doctors appreciated (his oncologist was impressed and called the AI a member of the team).

Unfortunately his physical reserves were very drained at that point. He probably would have had another 6-12 months with his family if it wasn't for the disorganized mess of a care system that we have.

These are not explanations. They're visualizations. There's a huge gap between the two.

Explanations give you a mental model: when I move this parameter this the effect it has. This just shows you the obvious, make a thing bigger, it gets bigger on screen. That's not an explanation.

Models are quite horrible at explaining things. They produce local narrow views that don't take into account the mental model of the listener nor do they attempt to produce the kind of long-term knowledge gain that a teacher does. I taught for over a decade.

This is why models are extremely good for people who already know what they're doing. That narrow why is all you need, like, tell me the 3 sentences that describe the mechanism behind this paper, and I'll get the rest. But building the scaffolding onto which to hang a lot of knowledge?

Give it a try. Try to have a model teach you something new. Not like "how do I tie a knot" but like a new area of math where you're going to dedicate 3 months of your free time to learning it. The results are pretty horrible.

It's chartjunk filler.

And you see this in the other examples too. The teach the CLT piece was funny. It's and error-ridden mess that isn't even an explanation at all!

The best part is, someone looked at that and thought yes, that's right. Shows you clearly why programmers will be needed in the future. The LLM might be able to run circles around that person in math, but that person also has no idea when they're being bullshitted.

I wish this just implement tikz without latex. I've yet to see a better drawing library that is both simple and has the depth to build the most complicated things.

There will be many scientists, myself included, that would band together to break the cartel if it forms. It's just a matter of money. It is absurd.

Any logic shows that this is really about their valuations and being tired of innovating instead of having any safety concerns. What would happen if the US did this? Chinese and EU labs would eventually win. And then either the US becomes a backwater or they have to eventually spend the money to keep up anyway. But in the meantime they will have bought themselves a few years at insane valuations.

Also, look at the stark choice they want to offer "we'll kill everyone or you give us the power to do whatever we want with the most important tech around". That's it. If we aren't in an oligarchy now, we will be if this goes through. They're going to end up stealing trillions of dollars from the rest of society.

If you think that OpenAI won't look at your data to gain a massive advantage, you're naive.

The real story here: the priority dispute and its implications on AI.

When your hosting provider has unlimited resources to throw at any problem, all they need to know are the good problems, and they can learn that from your logs, how can you trust them?

They could easily have looked at the logs. We don't know. We'll never know!

You can't trust places like OpenAI or Anthropic with your IP if you're a business. They can easily review all of your logs for interesting discoveries. For example, if your drug discovery pipeline fails to find something that they think might work with 1000x the compute, they can do it. And now suddently they have a new business and you don't.

"Flooding" implies some nefarious purpose. There's no evidence of that in this paper. Maybe these agents are finally giving people who could never find the time, resources, knowledge, etc. to engage with the system.

"Public services are increasingly becoming more accessible with LLMs" How about that as the title?

They also have zero evidence that this is because of LLMs. They just got some data related to volume, did a really crappy analysis that wouldn't even stand up as an intro to stats course project, and declared their biased opinion as likely true.

There is a certain amount of slack that we have. Things that are obvious consequences of what we've already discovered but that we haven't taken advantage of yet. AI is reaping that slack. It isn't adding brand new ideas at the moment. We will run out of this slack pretty quickly.

> Again, by using differentials instead of derivatives, we have transformed a number of processes that students find unintuitive into a single process where the intuition is supplied by the student’s knowledge of algebra.

Ah yes. Algebra. The subject all students love dearly. If only we could get students to love and appreciate calculus as much they love algebra!

I have a hard time even imagining an article that is more disconnected from the reality of teaching calculus to tiny humans.

This animation is worse than useless. I've taught a lot of students. This is not learning, it's stamp collecting.

You're just memorizing a nonsensical recipe. What are the constraints? Why do we do X rather than Y? How does a particular thing scale? etc.

All you're doing is fooling yourself into thinking that you've acquired some knowledge. When in reality you haven't even learned the basic mental model to reason about this stuff.

You've learned something when you have a mental model that makes correct predictions. Until then you've memorized it at best, and as with most memorized things it will decay exponentially and will be gone from your memory soon enough.

As someone who has worked in two industries that are at the maximal end of data sensitivity and privacy this comes across as a tinfoil hat issue not a real business requirement. In such cases we've always found ways to trade dollars for the privacy we need without having to run our own inference at excruciating slow speeds.