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Excited to see this here! Only yesterday I used it to create an interactive native-like notification my coding agents use to ping me when they push a PR. I had tried a few different libraries over the past month but only hs had the ability to render custom panes over maximized windows.

Will be using it for more automation tools moving forward.


The problem is that dealing with regulators takes years and millions of dollars, reducing competition and societal benefit. He's quoting $200m in additional health costs borne mostly by Medicare/Medicaid. Regulations aren't a useful part of the system if they're gunked up.


The thing is, we really don't need people competing at selling carbon credits because it's an industry that literally only exists due to badly written regulations so it's hard to come up with a ton of sympathy.


Saying it exists only due to badly written regulations is rather bold assertion. It exists, because companies damage what isn't theirs. It is a regulation to protect property rights.

Companies are polluting shared resources. Classic tradegy of commons.

Credits is one of things we have come up that does work.

Sure, we could just ban it outright and say goodbye to industrial civilization. Most people don't agree with that.


Doesn't that go away as a cost if the government stops paying for healthcare? I heard they were doing this in the US?


The government pays for healthcare for about 43% of Americans. The rest mostly get it from work.


I don't believe we have any indication that the big offerings (claude.ai, Gemini, operator, tasks, canvas, chatgpt) use multiple models in one call (other than for different modalities like having Gemini create an image). It seems to actually be very difficult technically and I'm curious as to why.

I wonder how much of an impact our being still so early in the productization phase of this all is. Like it takes a ton of work and training and coordination to get multiple models synced up into an offering and I think the companies are still optimizing for getting new ideas out there rather truly optimizing them.


...or its all a farce, for now.


Ooh, what are these ASICs you're talking about? My understanding was that we'll see AMD/Nvidia gpus continue to be pushed and very competitive as well as have new system architectures like cerebras or grok. I haven't heard about new compute platforms framed as ASICs.


Cerebras has ridiculously large LLM ASICs that can hit crazy speeds. You can try it with llama 8B and 70B:

https://inference.cerebras.ai/

It's pretty fast, but my understanding is that it is still too expensive even accounting for the speed-up.


Is Cerebras an integrated circuit or more an integrated wafer? :-)

And yeah their cost is ridiculous, on the order for high 6 to low 7 figures per wafer. The rack alone looks several times more expensive than the 8x NVIDIA pods [1]

[1] https://web.archive.org/web/20230812020202/https://www.youtu...


https://www.etched.com/announcing-etched

I think there's another one but I can't remember the name of it.

Also a bit further out is https://spectrum.ieee.org/superconducting-computer

"Instead of the transistor, the basic element in superconducting logic is the Josephson-junction."


Yeah I found that interesting. Flubbed embargo times makes sense, but could it also be that they're letting the news organizations have first dibs to build a little goodwill with the industry?


I'm not finding any direct sources from OpenAI, but here's this snippet from a Reuters article [1]

> Priced at 15 cents per million input tokens and 60 cents per million output tokens, the GPT-4o mini is more than 60% cheaper than GPT-3.5 Turbo, OpenAI said. It currently outperforms the GPT-4 model on chat preferences and scored 82% on Massive Multitask Language Understanding (MMLU), OpenAI said.

...

> The GPT-4o mini model's score compared with 77.9% for Google's Gemini Flash and 73.8% for Anthropic's Claude Haiku, according to OpenAI.

For some more context: We don't know the size of 4o-mini but Mistral's just released NeMo 12B scores 68% on the MMLU. [2]

[1]: https://www.reuters.com/technology/artificial-intelligence/o...

[2]: https://mistral.ai/news/mistral-nemo/


Also for some reference:

Gemma 2 27B scored: 75.2 in MMLU

LLama 3 70B scored: 79.5 in MMLU

Haiku scored: 75.2 in MMLU

GPT 3.5 scored: 70.0 in MMLU

Based on pricing I see in openrouter.ai across different providers this seems like the cheapest model for this kind of performance.

ref: [0] https://www-cdn.anthropic.com/de8ba9b01c9ab7cbabf5c33b80b7bb...

[1] https://blog.google/technology/developers/google-gemma-2/


Just tried Toucan and it can't be disabled on localhost, a major pain for using it during work as an engineer. For those that haven't used toucan, it's an extension that translates words/phrases inline on a page with various levels of replacement frequency and complexity based on your proficiency with the language.


This [1] help article says that it's free. Not sure how much we should trust that though. Did you find a better source?

[1] https://support.babbel.com/hc/en-gb/articles/13752043233170-...


A YouTuber named DirtyTesla has done a series of drives over the years throughout his hometown where he's tracked the intervention and disengagement rates per mile. He often shows those numbers at the end of his videos.


Is it the same route every time?

If not, they might take harder and harder routes as FSD gets better. Making it look like there is less progress than there really is.


You just know that Tesla would tune the software for this specific route, if the value of the comparison number became meaningful.

Just like you cannot trust benchmarks, Goodhart's law will kick in https://en.wikipedia.org/wiki/Goodhart%27s_law

> Any observed statistical regularity will tend to collapse once pressure is placed upon it for control purposes


Their model architecture don't allow for individual route tuning.


I think that is not true. They can just take data from the route, annotate it and put it into their training set. That is how you would do route tuning.


Sort of off-topic but I believe Openpilot allows this. You can record every route you take, copy it off to your PC and run it in a simulator. You can then tweak the model for this particular issue.


They claim.


There is no publicly known archive of Tesla software images, at all. Which, with the benefit of hindsight, do sound wrong.



In this case, I think of this as more of a search endpoint than a list. What would you think about using a parameter to specify the relation? i.e.

GET /comments?blogId=<id>


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