I don’t know, but your question reminds me of this paper which seems to address it on a lower level: https://arxiv.org/abs/2204.06974

“Planting Undetectable Backdoors in Machine Learning Models”

“ … On the surface, such a backdoored classifier behaves normally, but in reality, the learner maintains a mechanism for changing the classification of any input, with only a slight perturbation. Importantly, without the appropriate "backdoor key", the mechanism is hidden and cannot be detected by any computationally-bounded observer. We demonstrate two frameworks for planting undetectable backdoors, with incomparable guarantees. …”

The maze has no valid solution! How allegorically relevant.

this is where i’d like to chill when they wake me up from the simulation.

>Are they buying them to try and slow down open source models

The opposite, I think.

Why do you think that local models are a direct threat to Nvidia?

Why would Nvidia let a few of their large customers have more leverage by not diversifying to consumers? Openai decided to eat into Nvidia's manufacturing supply by buying DRAM; that's concretely threatening behavior from one of Nvidia's larger customers.

If Groq sells technology that allows for local models to be used better, why would that /not/ be a profit source for Nvidia to incorporate? Nvidia owes a lot of their success on the consumer market. This is a pattern in the history of computer tech development. Intel forgot this. AMD knows this. See where everyone is now.

Besides, there are going to be more Groqs in the future. Is it worth spending ~20B for each of them to continue to choke-hold the consumer market? Nvidia can afford to look further.

It'd be a lot harder to assume good faith if Openai ended up buying Groq. Maybe Nvidia knows this.

> Besides, there are going to be more Groqs in the future.

And likely some of them are going to be in countries that won't let them sell out to Nvidia.

This conviction doesn't seem to acknowledge the problem at scale. Decades of great UI development will still leave out edge cases that users will need to use the tool for. This happens fundamentally because the people who need to use the tools are not the people who make them, they rarely even talk to each other (instead they are "studied" via analytics).

When /humans/ bring up the idea of integrating LLMs into UIs, I think most of the time the sentiment comes from legitimate frustration about how the UI is currently designed. To be clear, this is a very different thing than a company shimming copilot into the UI, because the way these companies use LLMs is by delegating tasks away from users rather than improving their existing interfaces to complete these tasks themselves. There are /decades/ of HCI research on adaptive interfaces that address this, in the advent of expert systems and long before LLMs -- it's more relevant than ever, yet in most implemenations it's all going out the window!

My experience with accounting ^H^H^H^H^H^H^H^H^H^H bookkeeping / LLMs in general resonates with this. In gnu cash I wanted to bulk re-organize some transactions, but I couldn't find a way to do it quickly through the UI. All the books are kept in a SQL db, I didn't want to study the schema. I decided to experiment by getting the LLM to emit a python script that would make the appropriate manipulations to the DB. This seemed to take the best from all worlds -- the script was relatively straightforward to verify, and even though I used a closed source model, it had no access to the DB that contained the transactions.

Sure, other tools may have solved this problem directly. But again, the point isn't to expect someone to make a great tool for you, but to have a tool help you make it better for you. Given the verifiability, maybe this /is/ in fact one of the best places for this.

That’s the nano-bots

Yesterday I spent two hours looking for something that I thought I needed. Ten minutes in I thought of an alternative solution that wouldn’t require the item I was looking for. I wanted to do more interesting things, but I still /had/ to find it. I’d accidentally end up doing it again when I try to stop. A friend who was observing this tricked me into eating something, and then I was able to stop.

If I forget a word mid conversation, I spend a lot of time trying to remember it. I can google or ask the chat bot, but emotionally I want to get there it on my own.

I think that I’m addicted to the feeling I get when I find these things or solve a very difficult problem. After reading an earlier article about “aha” moments, I wonder if it’s the same circuit. Maybe there is also a natural predisposition for hunting in my brain, which is why food seems to help me get past these … moments.

> I miss that kind of media discovery, our modern always-online world tends to smother serendipity.

I miss it too. I used to read computer game magazines as a kid. I recently re-evoked that feeling by subscribing to a linux magazine. Maybe there are still game magazines out there but i’m too lazy to look.

Yeah. It’s very common to notice anomalies inside of a dream. But the anomalies weave into the dream and feel normal. You don’t have much agency to enter a lucid state from a pre-lucid dream.

So the idea is to develop habits called “reality checks” when you are awake. You look for the broken clock kind of anomalies that the grandparent comment mentioned. You have to be open to the possibility of dreaming, which is hard to do.

Consider this difficulty. Are you dreaming?

…

…

How much time did it take to think “no”? Or did you even take this question seriously? Maybe because you are reading a hn comment about lucid dreams, that question is interpreted as an example instead of a genuine question worth investigating, right? That’s the difficulty. Try it again.

The key is that the habit you’re developing isn’t just the check itself — it’s the thinking that you have during the check, which should lead you to investigate.

You do these checks frequently enough you end up doing it in a dream. Boom.

There’s also an aspect of identifying recurring patterns during prelucidity. That’s why it helps to keep a dream journal for your non-lucid dreams.

There are other methods too.

I don’t see color change but I “hear” them when I scan my eyes over the pictures, and when I listen more closely I can spot more subtle details (including the 5-leaf clovers).