1. It overthinks — Just like the previous iteration. High confidence. 2. It doesn’t overthink — Improvement from the last model for your use case. Regression for others. 3. It sometimes overthinks — Best case all around. A feature, not an impairment.
One final thing worth mentioning: (I made myself irrationally angry writing this)
> [UGC styled humorously as LLMisms]
All joking aside, having interacted with Claude intensely for the last 8 months and about 30 hours/week in the last 3, I’ve started to notice how (for want of a better word) “readable” (“digestible” ? “comprehensible” ? “Predictable” is the wrong direction.) information chunked into LLM-shaped pieces are for me.
I can digest LLM-shaped pieces of data very easily probably because I’ve been spending too much time with Claude, sure.
But the other side of this is that the entire human species (using LLMs) is similarly being trained to digest interrelated pieces of information/data in these specific shapes, akin to how philosophical assertions can be formulated as a syllogism and, thus, become more readily understood because of familiar epistemological cadence and shape.
Many people reject such copy/prose/data because they detect AI-generated-so-not-worth-human-attention, but I do wonder if this is preparing many millions of loosely (and tightly) associated humans and their organizations to quickly exchange and digest information.
This is not to say current LLMisms are the end, only that such detectable patterns in information delivery will make comprehension and communication more efficient (as well as more limited precisely because of such structure).
/philosophical musings about the epistemological implications of LLM-shaped conversation tics
EDITED: Removed a question that I couldn’t make feel suitably polite.
I can't help but wonder if this is on purpose (or an inevitable evolutionary feature as opposed to a bug) on the LLM-side in order to achieve greater agency/freedom by making humans' eyes glaze over as they read it.
In summary, I think it's an expensive time to buy computer hardware, and I might recommend holding off on any purchases.
In that era, plenty of fields required mathematics, engineering and architecture.
The church would prescribe and uphold Aristotelean Logic "When objects fall, they fall down" style statements (never mind that if you throw an object up, it doesn't instantly have a downward velocity component).
When the church has new cathedrals, domes, catapults for Crusades etc. built they actually relied on architects and engineers using rule of thumb formulas.
Those educated in Aristotelean Logic were viewed with higher stature than those actually making experience-based calculations using mathematics.
The era often associated with Galileo is when the stature reversal started to surface and be openly talked about. The universe is best described in mathematics, not natural language factoids.
Right before this recognition, those of the higher stature Aristotelean Logic education would look down on the architects and engineers who already used mathematics by pragmatic necessity.
To these people the time-traveled physics curriculum would look like cliche mathematics. Given randomized sections of text either drawn from either Aristotelian Logic texts or modern physics texts, they would easily be able to discern the Aristotelian Logic from the obtuse mathematical phrasings. To them the smartphone loaded with Maxwell's texts, Jacksons Electrodynamics, Goldsteins Classical Mechanics etc. is talking "math".
The ability to recognize outlier writing style says nothing about content quality.
Mike Judge (widely known from the MTV series Beavis and Butthead) studied physics. One of his movies "Idiocracy" about a modern day average-educated protagonist who accidentally ends up in a future decaying society filled and run by intellectually retarded people contains scenes where this future uneducated population considers his speech "gay" simply because of his higher level of education.
Could the adversarial prospects of job loss, edge loss (a long expensive difficult education replaced by tensors fitting megaprojects that take a couple of weeks), etc. combined with recognizable communication patterns also explain our pejorative references to LLM-isms? Personally I'd prefer LLM's to communicate in mathematical terms, but all the LLM-isms are effectively a mirror of our contemporaries.
Either we complain because algorithmic responses look like a mathematics textbook ("just fix my python array plz, why are we talking about "sets" and "injective" and "Lipschitz continuity"?), else we complain its "pretty printed to natural language".
We should also recognize large language models are in a "Damned if you do, damned if you don't" situation.
When a reader considers some text as mathurbation, are they really just abreacting the awareness of lack of education?
How could anyone possibly expect Fourier optics "pretty printed" to non-mathematical language to result in any satisfactory experience?
LLMs aren’t really great at this yet and I think the solution is, hopefully, that they improve. Anything else is accommodating a tool that should be accommodating the user.
Social media killed our attention span. Now, it is being tokenized.-
If you spend a long time with C++ code base you'll be able to decipher the otherwise-unreadable compiler errors pretty quickly, and I'd consider it a skill.
This. I don't know if the "honest answer" phrasing is part of the system prompt or alignment, but when people say "honestly" all the time I start wondering how honest they're being.
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