C# has a dictator with a budget: Microsoft integrated async into C# in a formal way, with 5.0, including standard libs, debugging, docs, samples, clear guidance going forward, etc. What holes there were were dealt with in an orderly and timely manner.
JavaScript actually had a pretty messy start with async, with divergent conventions and techniques. Ultimately this got smoothed out with language additions, but it wasn't all that wonderful in the early days. Also, JavaScript started from a simpler place (single-threaded event loop) that never had "fork" and threads and all that comes with those, so there was less legacy to accommodate and fewer problems to overcome.
Python had a vast base of existing non-async software chock full of blocking code, plus an incomplete and haphazard concurrency evolution. There are several legacy concurrency solutions in Python, most still in use today. Python async is still competing and conflicting with it all. Not unlike the Python 2->3 transition.
>Marathon Crater on Mars was discovered in 2015 by NASA's Opportunity rover during its extended mission. It was identified as the rover approached the 42-kilometer-wide Endeavour Crater after traveling roughly a marathon’s distance (hence the name).
>>is it a crater?
>>>Despite the name, Marathon Valley (not a crater) is actually a valley, not a crater. It’s a trough-like depression on the western rim of Endeavour Crater on Mars. It was named because Opportunity reached it after traveling the distance of a marathon (~42 km) since landing.
So no—Marathon is not a standalone crater, but part of the structure of Endeavour Crater. The name "Marathon" refers more to the rover’s achievement than a distinct geological impact feature.
That reaction is very different from the Marathon crater one though it uses the same pattern. I think OP's reasoning that there is a naive commitment bias doesn't hold. But to see almost all LLMs to fall into the ambiguity trap, is important for any real world use.
The other aspect is it can’t reliably tell whether it „knows” something or not. It’s conditioned to imitate the corpus, but the corpus in a way is its „universe” and it can’t see the boundaries. Everything must map to something _in_ the corpus.
This isn’t true — LLMs can generalize and synthesize information not in the corpus. You can ask one to create a new written language and get a grammar and vocabulary that is nowhere in the corpus.
How come there is not the equivalent of a stable diffusion "sampler * selection for LLMs? The restart sampler for stable diffusion is so good compared to most of the original samplers. I often try to get an answer from the LM studio people but I think I really should ask the llama.cpp people.
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