HarHarVeryFunny

The ancient Roman republic (i.e. pre-Caesar) did just fine run by the senate without any emperor (they were vehemently opposed to the idea of putting so much power in the hands of one individual).

One of the ways they made this work was by assigning temporary powers to elected/appointed individuals appropriate and sufficient to get their job done, whether that was provincial governor, tribunus plebis, consul or whatever. A notable title was that of "dictator" (where the modern word derives from) which gave sweeping temporary powers to a general sufficient to execute a war.

Julius Caesar famously abused this system, effectively becoming the first emperor (despite no such position existing) by assuming the title of "dictator perpetuo" (perpetual dictator), although that did not end well for him. His successor, Augustus (whose adopted name later became the name of the office of emperor) initiated a more acceptable version of this by simultaneously holding multiple "elected" positions thereby having the power of them all.

Honestly seems fair game to me - he did qualify to get on the ballot by going through the primary system and ranking #3 (with 2.5% of the vote). Top 4 get on the ballot.

I've got to wonder about correlation vs causation.

Normally, as well as food sources, your body naturally produces Vitamin D as a reaction to sunlight (being outdoors), and not having sufficient time outdoors, especially in a pleasant/nature environment, may be contributing to depression.

I'm not sure how you are imagining an LLM "self evaluating". They are feed-forward auto-regressive predictors. The only source for the next word they spit out is what came before and the patterns that contains.

If you ask an LLM to "win like Magnus" it can't because, as above, it is a feed-forward auto-regressive predictor. Do you realize how much different this is to how something like Stockfish (that can play at, and far beyond, Magnus' level) works?

A big LLM is still an LLM - the architecture and operation doesn't change. It just has more capacity to learn, both to learn deep predictive patterns and to memorize factual knowledge.

Does it not occur to you that your beliefs of what LLMs are capable of (generating amazing prose) is totally at odds with what we see them doing? Where is all the amazing prose?

The Roman's hadn't invented soap, so oil worked as a cleaning agent since it mixed with oily secretions, then being scraped off with a special purpose "strigil" scraping instrument - usually done at the public baths.

Yeah - code rewrites are generally a thing to be avoided since the requirements of older production code is typically not fully documented, even if it originally had been. Production code accumulates bug fixes, performance tweaks, special cases, additional requirements, etc, with documentation and test suites not always being updated in sync.

Your rewritten codebase will presumably look much cleaner and more maintainable that what it's aiming to replace, but it's easy to miss the purpose/necessity of all of the old "cruft" which need not be just poor coding but rather later enhancements not anticipated by the original design whose implementation was therefore crufty.

Does anyone here work at Cisco, and have any insight as to why a rewrite is considered necessary and might be expected to succeed?

I'm not sure what culture(s) you're referring to as "in antiquity", but in the Roman world at least olive oil was mostly for consumption - a way to add some flavor, moisture and calories to bread that was the core staple keeping the population alive. Olive oil was such a necessary part of the diet that emperor Septimius Severus instituted the "Oleum Publicum" making olive oil part of the Annona - free distribution of food primarily within the city of Rome.

Yes, with the "scenario expectations" just being the necessary setup to deliberately create false expectations and make the punchline that much more unexpected/funny.

I think both music and humor are both exploiting the same evolutionary essentials of human nature - to find comfort/safety in predictability, and excitement/danger in unpredictability. Laughter would seem to be a social thing - perhaps it helps develop a theory of mind in signalling that you get the joke - that the punchline is indeed unexpected to you as well ? And/or perhaps it helps draw others attention to an unexpected situation with learning potential.

The goal (literal, not figurative) of an LLM is to reduce training/inference errors - to predict the training material.

The "quality/goodness" (likability) of output is only selected for to extent that it also reflects RLHF preferences originating from low paid contractors who are scoring based on "looks good to me", not based on Pulitzer prize prose potential.

To explore a false hypothetical, suppose an LLM was only trained on the output of a single popular author, then you'd certainly expect it to reproduce that author's style, but it would not be "upredictably interesting" but rather predictably quirky, reproducing the same "surprises" over and over so that they no longer are surprising and therefore interesting.

To continue the hypothetical, if you trained an LLM exclusively on the output of multiple good authors, then rather than get the best of each you'd get a statistical blend (this is how training works) that emphasized what they had in common rather than the individual quirks that made them interesting.

There is a fairly common misperception that "AI" (LLMs) is always trying to do it's best, where "best" has been anthropomorphized to have the human sense rather than the LLM sense of "the most statistically accurate continuation prediction" it can make. For example, if you give an LLM the moves of a partial chess game and ask it to predict next moves for one of the players, it will NOT play to win, but will rather play to predict how the game would have continued, which means continuing at the level (ELO rating) and style of the player who had made those moves.

Of course you can ask an LLM to play to win, just as you can ask it to write in a style that is, say, "unpredictable and interesting", but it can't escape itself - you will necessarily get predictable unpredictability.

> All human communication is based on internally simulating the presumed mind that was/will-be at the other end

Which requires a bunch of things an LLM lacks, such as theory of mind, knowing who it is talking to, and willingness/ability to engage in short turn conversation to assess and steer the conversation according to the feedback it is getting from the person it is talking to.

A model trained to minimize statistical prediction errors is going to sound ... predictable (aka boring). A (good) human author tries to keep their writing interesting, while an LLM strives for predictable instead.

It's not just predicting content but also the form/shape of the response, highly shaped by RLHF preferences, which seems to encourage longer form responses which need padding with filler to generate the "preferred" amount of verbiage.

It seems most of these models have been trained to interpret questions as wanting a long-form authoritative/comprehensive-sounding response (even when midwit filler is all it has to offer), rather than initiating a short-turn conversation which would better allow you to steer the conversation. Apparently Muse is much better in this regard, but so far I've resisted signing up for any Meta/FaceBook service, and not inclined to break this winning streak!

Interesting idea .. "Google Prime" including access to all their best stuff.

What's the betting we see another "dramatic" Anthropic release either shortly before the IPO, or at same time they release their Q3 results which were conveniently omitted from their S-1 filing.

Yeah - follow the money.

Hard to trust that a for-profit benchmarking company isn't biased due to profit-maxxing.