seadan83

The proof for TDD is usually looking at bug detection rates. Similar for code review. OTOH, the "design damage" of TDD is something overlooked by those metrics.

What it boils down to: - TDD in the hands of a junior is very good. Drastically reduces bugs, and teaches the junior how to write code that can be tested and is not just a big long single method of spaghetti with every data structure represented as another dimension on some array.

- TDD in the hands of a midlevel can be a mixed bag. They've learned how to do TDD well, but have not learned when and why TDD can go bad. This creates design damage, where everything is shoe-horned into TDD and the goal of 90% line coverage is a real consideration. This is maximum correctness but also potentially maximum design damage.

- TDD in the hands of a senior is a power tool. The "right" tests are written for the right reasons with the right level of coupling and the tests overall are useful. Every really complicated algorithm I've had to write, TDD was a life saver for getting it landed.

Feels a lot like asking someone if they prefer X or Y and they say "X" is the industry best practice. My response universally is now an eye brow raise "oh, is it? For which segments of the industry? Why? How do we know it's actually a best practice? Okay, given our context, why would it be a best practice for US". Juniors don't know the best practices, mid-levels apply them everywhere, seniors evaluate and consider when best practices are not best practices.

TDD slows development when tests are written in a blind way with an eye on code coverage and not correctness and design. TDD speeds up development in being a good way to catch errors and is one of the best ways to ensure correctness.

I agree the risk of bus factor zero is reduced when ramp up time is reduced (through the use of AI enabled tooling), but I disagree in that you still have bus factor zero nonetheless.

No, it's not a wish nor an expectation for a magical panacea, but logic.

The only code you do not have to maintain is code that is fully perfect (100% accurate, 100% of the time). Bus factor zero is a problem for code that needs to be maintained. If AI is short of the 100%, then it is generating code that needs to be maintained. Ergo, a bus factor zero will be a problem for AI generated code (until such time as that code is perfect).

Unless I made a terrible copy/paste error, I 100% quoted the guardian article that we are discussing. In other words, "did you read the article?"

To your other point: The goal post is the statement (I'm paraphrasing here): "It was not a majority of Gazans that voted for Hamas, but instead a plurality". My rebuttal is that for sure half of the country did not vote for Hamas because the last election is before the median age of the country (half the country was not even born yet).

Could you explain how I shifted goal posts?

I think you might be assuming that we "know" without elections that the majority of the current population is "radicalized". The evidence of pluralities and majorities is given through elections, we don't have evidence for the current population. Maybe that is what you perceive as shifting the goal posts?

If you're going off of something other than elections as evidence for support of hamas at a plurality level of current Gazans - please share the data you are using to be "terrifi[ed] of .. what would be elected" (quoting you @nobodyandpround with slight paraphrase to make the grammar work). The population is roughly 2M people, it's difficult to get to any answer other than "we don't know" without a full blown and free election.

> an argument for the thesis that LLMs are not intelligent, and that this is wrong,

Why is that wrong? I mean, I support that thesis.

> since being a next-token-predictor is compatible with being intelligent.

No. My argument is by definition that is wrong. It's wisdom vs intelligence. Street-smart vs book smart. I think we all agree there is a distinction between wisdom and intelligence. I would define wisdom as being able to recall pertinent facts and experiences. Intelligence is measured in novel situations, it's the ability to act as if one had wisdom.

A next token predictor by definition is recalling. The intelligence of a LLM is good enough to match questions to potentially pertinent definitions, but it ends there.

It feels like there is intelligence for sure. In part it is hard to comprehend what it would be like to know the entirety of every written word with perfect recall - hence essentially no situation is novel. LLMs fail on anything outside of their training data. The "outside of the training" data is the realm of intelligence.

I don't know why it's so important to argue that LLMs have this intelligence. It's just not there by definition of "next token predictor", which is at core a LLM.

For example, a human being probably could pass through a lot of life by responding with memorized answers to every question that has ever been asked in written history. They don't know a single word of what they are saying, their mind perfectly blank - but they're giving very passable and sophisticated answers.

> When mikert89 says "thinking machines have been invented",

Yeah, absolutely they have not. Unless we want to reducto absurd-um the definition of thinking.

> they must become "more than a statistical token predictor"

Yup. As I illustrated by breaking down the components of "smart" into the broad components of 'wisdom' and 'intelligence', through that lens we can see that next token predictor is great for the wisdom attribute, but it does nothing for intelligence.

>dgfitz argument is wrong and BoiledCabbage is right to point that out.

Why exactly? You're stating apriori that the argument is wrong without saying way.

> I'm more shocked that so many people seem unable to come to grips with the fact that something can be a next token predictor and demonstrate intelligence.

Except LLMs have not shown much intelligence. Wisdom yes, intelligence no. LLMs are language models, not 'world' models. It's the difference of being wise vs smart. LLMs are very wise as they have effectively memorized the answer to every question humanity has written. OTOH, they are pretty dumb. LLMs don't "understand" the output they produce.

> To them, if something is a token predictor clearly it can't be doing anything impressive

Shifting the goal posts. Nobody said that a next token predictor can't do impressive things, but at the same time there is a big gap between impressive things and other things like "replace very software developer in the world within the next 5 years."

I quoted the article. The median age in gaza is estimated to be 18. Half of the population was not even born the last time there was an election. Consider hamas lost 3 of 5, it was neither a plurality. It's not about how liberals or conservatives lie, what was written is a lie.

A plurality of gazans did not vote for Hamas because half of them were not even yet born. They had no vote.

I didn't write anything about targetting children.

But, while on the topic. Targetting vs accepting children as collateral damage are different. Both can be true.

The judiciary is also notably notoriously lenient in prosecuting crimes against Gazans.

Gaza is an occupied territory. It's not equal.

> Gaza citizens supported Hamas for 20+ years- cheering on 7th of October-and probably still are

This is a lie. The stats do not bare this out. Sure you can find examples, but a picture or three does not represent 2 million people. Even if it did, we're talking about badly maimed children that are clearly innocent. Last I checked humanity considers children as innocents.

You're repeating the same lies as laura loomer. Quoting the article: "Loomer wrote, before falsely stating that “95% of GAZANS voted for HAMAS.”

"In fact, Hamas got 44% of party list votes in the 2006 Palestinian legislative elections across Gaza and the West Bank, and lost three of the five districts in Gaza to the secular Fatah party. There has been no election since then."

It's an example of notable criticism. The campaign was on twitter, so the PG quote is context and as an example of what detractors are saying.

Every fact about Laura loomer could be wrong, doesn't change the cruelty of the policy change.

The VERY FIRST SENTENCE of your wikipedia link says: "Laura Elizabeth Loomer (born May 21, 1993) is an American FAR-RIGHT political activist, conspiracy theorist,[b] and internet personality." (caps added for emphasis)

> claims that true AGI wouldn't be any more powerful than humans very very much have a burden of proof. That's a shocking claim that I've honestly never heard before, and seems to fly in the face of intuition.

The claim in question is really that AGI can even exist. The idea that it can exist, based on intuition, is a pre-science epistemology. In other words, without evidence, you have an irrational belief - the realm of faith.

Further, I've come to fully appreciate that without actually knowing the reasons or evidence for why certain beliefs are held, often we realize that our beliefs are not based on anything and could be (and possibly often are) wrong.

If we standing on just intuition there would be no quantum physics, no heliocentric galaxy, etc.. Intuition based truth is a barrier, not a gateway.

Which is all to say, the best known epistemology is science (assuming we agree that the level of advancement since the 1600s is largely down to the scientific method). Hopefully we can agree that 'science' is not applicable to just a courtroom or a philosophy class, it's general knowledge, truth.

Your framing also speaks to this. As if it is a binary. If you tell me AGI will exist, and I say "prove it". I'm not claiming that AGI will not exist. The third option is I don't know. I can _not_ believe that AGI will _not_ exist. I can at the same time _not_ believe that AGI will _exist_. The third answer is "I don't know, I have no knowledge or evidence" So, no shocking claim is being made on my part here AFAIK.

The internet for sure is a lot less entertaining when we demand evidence before accepting truth. Though, IMO it's a lot more interesting when we do so.

Re-check the data presented. The outcome of whether kids go forward or not is independent of aptitude/skill/study habits.

You seem to imply the intent is to allow strong students to advance more quickly. Except the data does not show that correlation, it shows that skill and advancement are not correlated. It is a different intent.

France, UK, Norway, Spain, Canada.. here's your list: https://en.wikipedia.org/wiki/The_Economist_Democracy_Index

To your interesting aspect, you're missing the most important (IMHO): accuracy. All 3 are really quite important, missing any one of them and the other two are useless.

I'd also question how you know that ants have zero knowledge of what they do. At every turn, animals prove themselves to be smarter than we realize.

> And because of how it helps to distribute "the information" better.

This I find interesting because there is another side to the coin. Try for yourself, do a google image search for "baby owlfish".

Cute, aren't they? Well, turns out the results are not real. Being able to mass produce disinformation at scale changes the ballgame of information. There are now today a very large number of people that have a completely incorrect belief of what a baby owlfish looks like.

AI pumping bad info on the internet is something of the end of the information superhighway. It's no longer information when you can't tell what is true vs not.

Burden of proof is to show that AGI can do anything. Until then, the answer is "don't know."

FWIW, it's about 3 to 4 orders of magnitude difference between the human brain and the largest neural networks (as gauged by counting connections of synapses, the human brain is in the trillions while the largest neural networks are low billion)

So, what's the chance that all of the current technologies have a hard limit at less than one order of magnitude increase? What's the chance future technologies have a hard limit at two orders of magnitude increase?

Without knowing anything about those hard limits, it's like accelerating in a car from 0 to 60s in 5s. It does not imply that given 1000s you'll be going a million miles per hour. Faulty extrapolation.

It's currently just as irrational to believe that AGI will happen as it is to believe that AGI will never happen.

> It does not make sense to have admins and other parents with vested interests block kids from whatever classes they want to take!

Sure it does. There is a vested interest in some to ensure a desired peer group of the classes their kids take. More generally, to ensure 'space's at the top for those that get the teacher recommendations. Bluntly speaking, it's racist as shit. The data presented is a case study of systemic racism.

Who is to say any of this is a mistake and not exactly as intended?

Like, it was not a mistake during red lining laws that you had to go into a bank personally.

No, the issue is if you don't take algebra I by 8th grade then you won't take advanced math. Nobody is considering algebra I tk be advanced, the key is when you take algebra I in order to move on. Turns out, whether you take algebra I before high school has less to do with how good you are at math and more to do with (frankly) segregation. This is an article revealing in data how modern day segregation works.

I'm a product of NC schools. When going to grade school in the 90s I did not realize that those schools desegregated less than 10 years prior. The advanced classes were essentially all white. Those advanced classes in early grade school position you for the slow track, or the fast track.

I've found the best way to kill a conversation is to point out the appropriate place the conversation should have started.

The stats for collisions from rear are surprising, rarest way to get hit on a bike (and most of those are no lights at night).

It turns out, moving closer to the center of the lane reduces the chances of the most likely directions of impact - namely turning traffic. Either turning left as an oncoming vehicle, turning out from a side road or driveway, of someone that is overtaking you and then turns right.

I've found low speed crashes really want a helmet. Things like you roll sideways off the bike. You are not moving fast but are rotating quickly. (So back hits ground followed by back of head)

FWIW, I just noticed the common irrational rational fear of being run over from behind. It is a common mistake. Riding to the extreme right can make it worse, it is an invitation to pass when instead the cyclist is just afraid. Taking a little more room on a road (situationally) can make a person a lot safer.

The humiliation is the least of it IMO. When interviewing, let's say you've got to leads. You get hired and tell the test to pound sand. Companies (I've found) never like that. It's a burned bridge (despite the strong hire signal of getting hired).

Now, a month later - fired - it's worse than not having worked at all. Good luck reaching back out and starting over from scratch with your best options now off the table.

According to the data in the article, the white board does not even show ability to code.

Simpler, add random cat fact at the end. For reals can be extraneous company info. I'm of course referencing the recent finding that LLM accuracy nose dives when confronted with extraneous info.

> a lot of younger programmers treat these patterns like a religious dogma

First you learn what the pattern is. Then you learn when to use it. Then you learn when not to use it.

The gap between the first and third step can be many years.

I would say reliability is availability times accuracy.

(Your point remains largely the same, just more precise with the updated definition replacing 'reliable' with 'accurate'.)

I wouldn't take the claim to mean that humans universally have an attribute called "accuracy" that is uniformly set to the value 99.9%.

The claim is pretty clearly 'can' achieve (humans) vs 'do' achieve (LLM). Therefore one example of a human building a system at 99.9% reliability is sufficient to support the claim. That we can compute and prove reliability is really the point.

For example, the function "return 3" 100% reliably counts the Rs in strawberry. We can see the answer never changes, if it is correct once therefore, it will always be correct because the answer is always the same correct answer. A LLM can't do that, and infamously gave inaccurate results to that problem, not even reaching 80% accuracy.

For the sake of discussion, I'll define reliability to be the product of availability and accuracy and will assume accuracy (the right answer) and availability (able to get any answer) to be independent variables. In my example I held availability at a fixed 100% to illustrate why being able to achieve high accuracy is required for high reliability.

So, two points: humans can achieve 100% accuracy in the systems they build because we can prove correctness and do error checking. Because LLM cannot do 100%, frankly, there is going to be a problem that shows a distinction between max capabilities. While difficult, humans can build highly reliable complex systems. The computer is an example, that all the hardware interfaces together so well and works so often is remarkable.

Second, if every step along a pipeline is 99% reliable, then after 20 steps we are no longer talking about a system that usually works, but one that _rarely_ works. For a 20 step system to work above 50%, it really needs some steps that are effectively at 100%

I've heard management (and a skill I've learned to appreciate from leadership) is "creating alignment" amongst a group of people. Would you say that is different from setting direction?

Second question, if you don't set direction, what's the contrast/alternative?

> But is it better than no therapy? That's what matters.

Seemingly no, it is _worse_ than no therapy.

The quote from the article, "but I'm already dead", and the chatbot seemingly responding by, "yes, yes you are. Let's explore that more shall we." Sounds worse than nothing. Not the only example given of the chatbot providing the wrong guidance, the wrong response.