sharmajai

The answer my friend, is blowing in the wind (https://www.youtube.com/watch?v=MMFj8uDubsE&list=RDMMFj8uDub...).

I'll let the data do the talking:

Cursed companies:

- https://permtrack.app/employers/microsoft-corporation

- https://permtrack.app/employers/tata-consultancy-services-li...

Blessed companies:

- https://permtrack.app/employers/oracle-america-inc

- https://permtrack.app/employers/tesla-inc

I see, maybe your use case is indeed pathological for Qwen 3.8 27b. Another thing to try if you are using llama.cpp is "reasoning budget". That makes the thinking stop after the budget has been reached and inserts a custom message you can choose, so something like "you have thought for too long, now continue with the execution ..."

For what it's worth, if you haven't already, you can also let it run overnight (if you have compaction enabled) to see if it ever gets out of that hole. The reason `xhigh` is the default is because 3.8 is trying to optimize for long horizon tasks where monitoring its every single thinking misstep might not be a good use of our time.

Without knowing anything about your benchmark, it might be your harness at fault here. I say this because with longer thinking you run the risk of filling up your context faster and you need a good context compaction strategy in your harness to mitigate that.

I have heard good things about Pi which supports auto-compaction, but I can't personally vouch for it since I use my own.

This confirms a theory I have to explain the minimal loss in quality when using lower quants (I use IQ3_XXS with an 8-bit KV cache) and the XHIGH (default) thinking level.

It's well-known that while quantization affects the sampling probability distribution (given the same context, which next token is the most probable), Qwen 3.8 27b seems to offset that by just thinking more and as a result eventually finishing the task (benchmark or otherwise).

So as long as the thinking (albeit longer) is sound, this leads to the same success rate (as shown in the article) but potentially at the cost of more tokens and hence more time.

I think it'll be further useful to chart each quantization's used tokens as well, in addition to the success rate.

Thanks for doing and sharing the research!

Really feels like AGIPO is here.

Thanks for the movie suggestion, looks very interesting, will check it out. Also, the Pixar movie Soul has a similar message.

You'd be a great CEO, preaching people to tie their worth to their output in life.

I am getting 14 t/s on my 16 GB card at full context with the UD-Q3_K_XL quant. Model link: https://huggingface.co/unsloth/Qwen3.8-27B-GGUF.

Who said investing is _only_ for "capital and capital appreciation"? It can also be for social good.

They have a very opaque and subjective permanent residency program. So while they get all the benefits out of you as an immigrant, they may provide none in return.

Product companies with deprioritized R&D wings are the first ones to die.

I get the urge to be cynical all the time, but this isn't that time. "Once you grow", they have already grown and competing with the SoTA models and still giving it all back to the community.

I just wish this smear campaign against them stops sometime soon.

I am 100% sure that company is the F in FAANG.

Dude, that's cheating!

But but look at all the Turing Award and Putnam Prize winners he was worked with.

Maybe not everything should be about business.

What're the issues with PayPal that you're aware of?

That's being tried [1]. Although, it's not going well [2].

[1] https://www.visalaw.com/onboarding-mass-litigation-clients/

[2] https://twitter.com/LilySAxelrod/status/1437846756394520582

While I agree that Peter's suggestion is the safe thing to do, based on the following tweet from the official account, if you were in the country legally on 06/24, the proclamation doesn't seem to apply.

https://mobile.twitter.com/TravelGov/status/1285331446232743...

Of course it does, because it can be combined with other characters. This is the semantic meaning: https://en.wikipedia.org/wiki/Acute_accent

I don't see which of those 4 definitions supports the grapheme cluster interpretation.

<nitpick>All Unicode characters map, one-to-one, to their code points. A code point being a numeric identifier. It's a grapheme that combines multiple characters to form a unit of writing.</nitpick>

That's an amazing price given it's retailing for more than twice that. One option to expand storage is have an always-inserted, low-profile USB 3 flash drive like SanDisk Ultra Fit, providing read speeds upto 150 MB/s.

It's a pun on "14!".

Note the sub-optimality of generatePermutations.

For the second but last level (which will be entered n! times) it is doing n iterations which gives us a (not so tight) lower bound of n * n! instead of the optimal n!.

The issue is the use of an array for visited instead of, say, a linked list where each level gets a list of only unvisited nodes.

You provided no evidence for the hype claim but even then you are contradicting yourself:

Statement A: Tesla is just hyping autonomous driving since no technology can deliver fully autonomous driving right now.

Statement ~A: Low-cost LIDAR is available to any high-volume customer, of which Tesla is one, given Model 3 demand. And LIDAR can deliver fully autonomous driving.

The point simply being, I have a hard time believing that even with good-looking, cheap LIDAR being a possibility, as you claim, Tesla chose to go with an inferior sensor suite, for no apparent reason.

> Once the cost goes down...

> ...expect to see better design.

> ...costs too much until one of the three companies claiming to be building low-cost automotive LIDARs Real Soon Now manages to deliver.

All I see is future promises. Tesla wants to do this now, that too at mass market costs, independent of whether those promises materialize or not.

It also depends on how much you trust their R&D team. If they thought this was a week sensor suite and something else was just around the corner, they won't risk fitting their cars with inferior technology which would be obsolete in a couple of years, making all the collected data worthless. Yes I am aware they did this to existing cars lacking the full autonomy hardware, but I find that OK, since, for them, they never promised full autonomy to begin with.

Downvoting.