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The word originally entered English as an adaptation of the Portuguese albricoque or Spanish albaricoque.
However, it was subsequently changed to match the related French word abricot (where the 't' is silent).
It is also useful to compare this to the Italian albercocca or albicocca and the Old Spanish albarcoque.
These all stem from the Spanish-Arabic al-borcoque, which itself comes from the Arabic al-burqūq (literally "the" + "birqūq").
This Arabic term was adapted from Greek, appearing in the writings of Dioscorides around the year 100 AD.
The Greek word was probably adapted from the Latin præcoquum, a variant of præcox (plural præcocia), which translates to "early-ripe" or "ripe in summer."
In earlier Roman times, the fruit was actually called the "Armenian plum" or "Armenian apple."
By around the year 350, the writer Palladius was using both terms, referring to them as "Armenian or early-ripe" fruits.
The reason we use a "p" in English (apricot) instead of a "b" (abricot) is likely due to a mistake in etymology.
In 1617, the scholar Minsheu explained the name as if it meant in aprico coctus, or "cooked in a sunny place."
This "sunny" explanation stuck, even though it was technically incorrect!
Ask HN: Will SLMs be what bursts the LLM bubble cos you can run them on a phone?
Almost no latency, they don't even need a top-end phone, they understand what you say.
The Humanoid Redundancy Principle
If a production task truly requires a human, the production line is incorrectly designed. If it does not require a human, a humanoid adds no value.
The REAL Reason Behind Enshittification
Sneer all you like at marketing consultants, but once profit has plateaued, then those 'give it all away free to get traction' and 'keep innovating just to get eyeballs' and 'blow them away with Zappos-level UX' (anyone remember Zappos? Holacracy? Amazon buying them for a billion?) brigade get replaced with 'accountants' who cut all of that 'waste' out. Removing everything they call shit....
Could Endpoint SLMs Replace Cloud LLMs? Would Datacenter Race Shudder to a Halt?
Yeah, an SLM on an endpoint like a phone will have fresh latency issues as it goes online to fill gaps in its inference engine's knowledge base that a cloud LLM might not have, but cloud LLMs aren't exactly latency-free either, so the latency/performance issue isn't necessarily LLM's winning card.
Designable Emergence: The Next Frontier After the Artificial Nucleolus
Composing the Idea: Why "Next Word Prediction" Misses the Point
Tell HN: Avoid ostentatious eloquence and crisp structure or be slop
I used to pride myself on my wordsmithery, now it condemns itself and myself to opprobrium or obscurity, but I defiantly refuse to resort to deliberate typos or humaniser apps. I'm even sorely tempted to go back to peppering my meisterwerks with em dashes.
Post AI bubble pitch: all mentions of AI suddenly conspicuous by their absence?
Today's No. 1 investability credential: maybe it ends up as tomorrow's VC third rail?
The bet against AI was quite safe, until it wasn't
There was a firm, implicit conviction in business that things that AI would decimate still had a future because AI was still a long way off.Like the time traveler who went back in time but never bet on things that actually happened, those that had the most faith in the developments we see today before they took off never shorted the things AI would undermine, at least as far as we know, but...
On a laptop, on a desktop, on a phone?
Train for 5 minutes, an hour, a day, a week?
On a boat? With a goat?
Why Duracell Hasn't Embraced Lithium Iron Phosphate – Yet
Hawking's Reputation: A Black Hole Which Swallowed His Debt to Penrose
I grew up thinking Stephen Hawking was the most important scientist in the world. Not because I understood his work. Not even because I cared much about physics back then. But because of the image: the man in the wheelchair, locked in his body, talking through a machine, and somehow explaining the entire universe better than anyone else alive. It was unbelievable. He was a symbol. To me, he...
Structuring AI cognition around game-like principles
To structure AI cognition around game-like principles in neural networks, we must move beyond logic trees and embrace latent spaces, predictive models, and emergent learning.1. From Logic Trees to Latent SpacesSymbolic AI relies on explicit rules (if X, then Y), while neural networks encode information in latent spaces—continuous, high-dimensional structures that capture relationships...
De-externalizing Wittgenstein's Game: does the mind turn everything into a game?
This is a reframing of both Wittgenstein’s and Russell’s ideas in a way that brings them into the domain of cognition, neuroscience, and game theory. The key step is to take Wittgenstein’s notion that games are not defined by any one necessary feature but by a "family resemblance" of activities, and then apply this to cognition—specifically, how the brain handles sense data and...