aniijbod

The History of the word "Apricot"

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!

In the theory of the psychology of creativity, there are phenomena which constitute distortions of the motivational setting for creative problem-solving which are referred to as 'extrinsic rewards'. Management theory bumped into this kind of phenomenon with the advent of the introduction of the first appearance of 'gamification' as a motivational toolkit, where 'scores' and 'badges' were awarded to participants in online activities. The psychological community reacted to this by pointing out that earlier research had shown that whilst extrinsics can indeed (at least initially) boost participation by introducing notions of competitiveness, it turned out that they were ultimately poor substitutes for the far more sustainable and productive intrinsic motivational factors, like curiosity, if it could be stimulated effectively (something which itself inevitably required more creativity on the part of the designer of the motivational resources). It seems that the motivational analogue in inference engines is an extrinsic reward process.

"WHEREAS, the Large Language Model has merely mimicked a sophistication it cannot truly possess": says who(m)?

Personal brands developed by ChatGPT

I don't care about the math, the computation, the physics. This is just by far the most beautiful thing(s) I have ever seen.

Oh no! I thought that was Windows 11

Let the AI efficiency olympics begin!

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?

I'm the opposite. I live for calls. I don't like text messages. I'm not great at face-to-face. But over the phone, I'm at my best.

I think that the nature of the thing that was needing to be implanted would determine whether it was easier and safer to use a traditional incision. Hip replacements for instance use a titanium joint. However, seeing as the bone that it is replacing was not made of titanium, somehow nature has found a way to make bone strong enough to do the job. There is an important sense in which nature 'builds things using 3D printing' and does it without needing incisions, so even if we do manage to master doing 3D printing under the skin the way we do it now to an extent where we can replace things that currently need materials that are not suited to under skin 3D printing...

Even as just a meme, no-hole surgery and the technology that makes it possible may have sufficient potential to perform a valid service to medical research simply by sparking the imagination of students: reduced invasiveness is a time-honoured aim in surgical procedures, so taking it to the next (or ultimate) level does look like it's worth encouraging: a key question to some extent becomes one of language: do we still call it surgery when nothing constituting an incision is involved? Yes, we make a (very small) hole when we inject the 'ink', but injections are never referred to as being surgery. So if no-hole surgery is not a type of surgery, then what the heck kind of thing should we call it?

I've seen what appear to me to be far less deserving papers get the same kind of perhaps excessively exuberant hype, but in this case, it's not looking quite that far off the mark, IMO

Any ideas on what that would be like?

Yes, the original headline was actually pretty good

Ok, so can we and should we try to come up with a more suitable term?

Maybe the answer to how to implement controls is for the AI to spit out content in more 'modular' form?

So for instance an AI 'text to game' engine outputs the setting, gameplay, NPCs, etc, all in separate 'elements' that can then be 'Bret-Victor-ised' in terms of sliders, knobs and dials?

Ok, here is my post-hoc disclaimer: an LLM was indeed used as part of the process of putting this together, but I was heavily involved both before and after editing the text. I personally am not a bot. Would you like me to put some spelling mistakes in?

The point is this: renewables are getting cheaper faster. Batteries are getting even cheaper even faster. Batteries can support the grid. The demand for batteries to support the grid is going up exponentially whether the renewables market growth speeds up or slows down, because the grid is always short of storage, because energy generation investment always leads energy storage investment, irrespective of energy source. But because storage production can now grow even faster than generation production (this has never been the case before, it was always too expensive) storage can tap into pent-up demand that has been building up over decades. You are absolutely correct that batteries were not scalable before: they are only just crossing the scalability curve.

Thought and language are intertwined in ways we don’t fully grasp. The fact that certain cognitive tasks, like comprehension, can proceed without engaging traditional language-related brain regions doesn't mean thought doesn't use language—it just means we might not yet understand how it does. Thought could employ other forms of linguistic-like processes that Fedorenko's experiments, or even current brain-imaging techniques, fail to capture.

There could be functional redundancies or alternative systems at play that we haven't identified, systems that allow thought to access linguistic capabilities even when the specialized language areas are offline or unnecessary. The question of what "language in thought" looks like remains open, particularly in tasks requiring comprehension. This underscores the need for further exploration into how thought operates and what role, if any, latent or alternative linguistic functionalities play when conventional language regions aren't active.

In short, we may have a good understanding of language in isolation, but not necessarily in its broader role within the cognitive architecture that governs thought, comprehension, and meaning-making.

A way of thinking about what's inside any of the top LLMs right now: even if they never learn another single fact, even if they get ridiculously out of date as a result, even if they are even more riddled with errors and prone to biases than we know them to be, even if they are as prone to hallucinations as we know they they are and they never develop the capacity to cure themselves of this, they are more knowledgeable and capable of more reasoned response, despite their capacity for error, to more questions than any single human being that has ever lived.

"the captain would like to take this opportunity to remind passengers wishing to earn additional air miles that..."

You don't need to know about physics.

Some people who do know about physics don't need coders and some do.

You need to find people who do know about physics, but who still need coders.

Physics is just too big a subject to 'know about it' enough to 'get into physics as a coder'.

Yes, you will need to know about a specific 'problem domain' within physics

One that someone somewhere needs a coder for.

But start with people, not with physics

People need coders, physics doesn't

People have physics problems that they need coders to solve

Read up, find the people with the unsolved physics coding problems that you can work out how to help them solve

Then your problems will really begin

Then you'll find out if getting into physics as a coder was right for you

In Computers? The Mythical Man Month Fred Brooks In Mnaagement? Turn the Ship Around David Marquet In literature? Heart of Darkness Joseph Conrad In Philosophy? The Republic Plato In Religion? The Confessions St. Augustine In Mathematics? The Elements Euclid In History? Parallel lives Plutarch In Physics? Principia Isaac Newton

If it turns out that in order to make EVs cheaper to build than combustion cars right now you have to switch to castings because batteries are expensive, then when batteries become much cheaper, will we switch back to the current non-casting-based 'strut and fastener' model?

Also, because Tesla is so popular, is it possible that its attractions have far less to do with the environment and more to do with everything else about the car?

These concerns about the environmental impact of increased write-offs and increased insurance premiums are perfectly understandable, but I wonder if they will stop even a single sale?

Unless they do!

Les Patterson Culture Manual

Yeah, it turns out that it is totally misleading to dismiss something that is based upon text prediction as being only capable of things that require text prediction. In order to be able to predict the 'correct text', you, as a human, or as a 'device' are not just 'looking for instances where 'b follows a' in your training data. This would just amount to nothing more than running a query on a database, finding the data in there and then outputting it.

Sure, there is a bit of this going on with an LLM system.

But it turns out that both the finding and the outputting in a neural net are so different to what is happening in a database-driven solution, that although the information contained within the answer might not be something that would be impossible to derive from a 'conventional' database and therefore still make it unrealistic to claim that a conventional database has any 'understanding' of the query that it is attempting to execute, this turns out not to be the case with a neural net-based solution like ChatGPT.

In order to 'predict the next word', the neural net can't just look it up, because it is unlikely to be there. The neural net needs to have used its training process to have built up what we might call 'intuitions'. It isn't 'just' consulting its training data. It is mostly consulting its 'intuition-base'. To all intents and purposes, it is consulting its 'understanding' of the training data, rather than consulting the data itself. This intuition-base is so much more optimised than any conventional data base that lookup is near-instantaneous. That's why, when we 'try to figure something out' we can need to take a little time to 'think things through', but when we react to something, it's instant, nee jerk response. Using our own minds, when we are instantly reacting to something, are using the brain's neural net in the same way as ChatGPT, but if we are are figuring things out on a 'if this then do that' basis, our minds are working more like a computer running lines of code. Most of ChatGPT is based on NOT 'just' running lines of code, but there is a tad of code in there as well as a neural net. But to cut a long story short, yes, the intuition-base side gives ChatGPT its ability to analyse and understand and the word prediction aspect is jus ta deceptively misleading characterisation of what's really going on.

If what we need to determine is whether existing theory of mind tests can be fooled by responses which appear to demonstrate theory of mind but not do so, then we need to speculate exactly how such tests can be fooled and devise new tests. Asking 'how could this 'successful' response be produced without ToM is quite possibly not something that ToM studies have had to consider very much before. A human's experiential memory contributes to their ToM. Does something that has a different kind of memory form no ToM but instead use some kind of 'proxy' for a ToM which yields similar results to a ToM (except when a more genuinely exclusively ToM-dependant model successfully manages to 'triage-out' such a proxy? I don't know how or whether such a proxy could work, but I think that every sceptic of the extent to which the results of this set of AI ToM experiments proves anything might want to ask themselves what, if anything, would need to happen, in terms of experiment design, to address their doubts.

That darned movie again!

> Ironic that CBDC systems are being built on a technology exclusively aimed at eliminating the C in that acronym.

Thanks Pjkundert, you're correct I should have said 'first C".

What I meant was that it was ironic that CBDCs are being constructed using systems that use blockchain, i.e., centralised systems, designed to deliver centralised currencies, based upon technology exclusively designed to deliver decentralised currencies.

Ironic that CBDC systems are being built on a technology exclusively aimed at eliminating the C in that acronym.