skysight-inc/HackerNews huggingface dataset:
That's correct, but it doesn't mean artificial neural networks cannot achieve intelligence, or even superintelligence. The fact that the human brain doesn't work like that doesn't automatically imply that (structurally) simpler models are fundamentally less capable.
My car used to get vapor lock in high school. The fuel line was run too close to the hot exhaust pipe. At red lights when there was no air moving, the exhaust pipe heat would be so hot it would cause the gas to vaporize. That vapor’s higher pressure caused no more fuel to flow, and the car to stall. vapor lock
The Raygun Conspiracy (1990) [video]
Maybe they have a low crime rate for reasons that have nothing to do with prosecution.
It hallucinates a bit, yes. But in general it gives me suitable colours for when I need them. I've yet to try this with GPT-4 or some of the other models suggested in the comments here.
Big companies pay millions to GCP, surely that is seen as its own revenue source? I don't see anything that would make want to use their search either after using their cloud stuff.
sounds like you're looking for rapidbay

https://github.com/hauxir/rapidbay
Which benchmarks are you going off ?
Which benchmarks are you going off ?

Also, just take it easy :)
I'm sorry as a large language model I cannot turn on "kinky sex bang list 47".
FYI, according The Information they're in discussions to be acquired by Snowflake.

https://www.theinformation.com/articles/snowflake-in-talks-t...
It would work no different from the current apps on the backend; (chat)gpt will fill a typed object, for instance a Transaction, software will validate this object as it does now (you can fill an object in an illegal way now and send it to the api; no difference), show it in the chat window as a strict UI to ask you if you are sure and then execute. The gpt part is only for you, not for the backend.

So people can try to make it do whatever; the banking backend logic won’t execute it, so it doesn’t matter. The user will just be wasting their own time.

Until of course neo-neo-web3-gpt-banks pop up that are ‘built up from the ground with ai’. But those will fail regulatory before they launch anyway.
Yeah it’s really concerning just how fast its coding ability has fallen off.
Thanks - The flow is pretty simple:

1. Every hour a Node Red flow runs
2. It generates a prompt using a Home Assistant Jinja template
3. The prompt is sent to Open AI
4. The response gets parsed from JSON and sent to Home Assistant's "input_number" entities
5. Lights in Home assistant pick up the state change and set the new colours

If you're keen, I can share the Node Red flow diagram (or JSON).
> Like, anyone who has spent 5 minutes on this forum already knows this

You would think, and yet...
People also mis-use LLMs.

ChatGPT is forced to given an answer. It's like a human on "truth serum". The drugs don't stop you lying, they just lower inhibitions so you blab more without realising it.

The more obscure the topic, the more likely the hallucination. If you ask it about common card games, it gives very good answers.

If you asked a random human about 3 cards from a random board game at gunpoint and said: "Talk, now, or you get shot", they'll just start spouting gibberish too.

PS: I asked GPT 4 about that game, and it prefixed every answer with some variant of "I'm not sure about this answer", or it completely refused to answer, stating that it did not know about any specific cards.
> Language is roughly what separates humans from other apes

Maybe not.

A recent study pushes back the "dawn of speech" to 20 Ma which is far, far beyond the horizon where we consider humans to separate from apes. https://www.science.org/doi/10.1126/sciadv.aaw3916 Even if you consider Sahelanthropus tchadensis to belong to humans that was only 7 Ma and that is still under debate.

I personally find "the fundamental human trait is control of fire to be used for cooking" theory very convincing. We do not yet know how far this goes back but no one pushed that back beyond 2 Ma.
What examples of committed crime do you see mentioned?
I never said that either GPTs or calculators are useless.
Tbh, changing PyPi urls to git urls at GitHub would almost be a win-win. At least GitHub has namespaces and many other indicators of trust, such as issue tracker, stars, git log and so on. You would loose semver however.

Usually checking the official GitHub projects readme for exact name of pip install command is what I normally do anyway. I would never ever use PyPi as a discovery mechanism, it has too many typosquatters and other lookalikes.
For me it's a little more subtle. When I sit down to write, say, an email, I usually have a specific point that I want to make but I usually haven't yet figured out exactly how I want to get there. I'm not even sure it is even possible to conceive of writing without doing it word by word. Perhaps the difference though is that we have the ability to go forward and backwards in the sense that we can usually think faster than we can type or write which allows our thoughts to advance beyond the tokens we have produced. This allows for a kind of real time editing process that incorporates both past and possible future information. But I imagine there us probably a way to enhance LLMs to branch and edit before producing the next word materially (if they aren't already doing that).

To go even more meta, there is an analogy I'm trying to make right now in which I am visualizing a road and thinking about how describing the road relates to the process of writing. In my mind's eye, I can see the full length of the road and all of its contours but I can't actually describe the individual stretches of the road coherently without enumerating them. Something similar happens with writing. I can visualize what I want to say far beyond the next word, but it's true that the actual process of writing goes word to word, much like how the process of token selection is described for an LLM. The question is whether the LLM has an analogous conception of where it is going. Going back to the process above, sometimes I know where I am going and haven't yet figured out how to articulate it yet. It is through the process of writing that I am able to articulate that thought. But the thought preceded my articulation of it. I don't know to what extent LLMs have coherent thoughts that they are articulating or if that even makes sense for the type of intelligence they project. My suspicion is that they don't have additional sensory inputs beyond language that give thoughts the immaterial shape that then is expressed in language. Without that, I am skeptical that they will truly get beyond regurgitating and/or remixing what has already been fed to them textually. That doesn't diminish how amazing they are, but I am somewhat more in the Brooks/Knuth camp that they are impressive and surprising, but there is something that ultimately leaves me a bit cold about them.
The times I've experienced "prime membership" [0], Amazon generally offers "no rush shipping credits" of $1 towards "digital content" [1]. Obviously their cost basis for that is much lower than the face value. But assuming 50% discounting, 100% labor cost overhead, and using the 60 packages/hour figure in a sibling comment, only 20% of customers would have to choose the option for a worker to get a 15 minute break every 2 hours.

The popularity would also be a great indicator of how many customers resent their practices, before they simply disappear.

[0] free trials of course, because why would I pay to subject myself to a sunk cost fallacy?

[1] aka stuff that you're better off torrenting
> Since 2002, 779 Muslim men and boys have been held at Guantánamo, nearly all of them without charge or trial. Today, 39 men remain indefinitely detained there, and 27 of them have never even been charged with any crime. Fourteen of those 27 have been cleared for transfer or release, some for years.

https://www.aclu.org/news/human-rights/20-years-later-guanta...
Does Maven have these problems? I haven't seen it if so.
Not sure if this includes fuzzy search, but having it will make this much more usable.
There is something different about the way the Feyman lectures is written.

It's been years since I have read it, but I remember it explaining how one could derive the change in atmospheric pressure with altitude by just knowing a few properties of the gas.

I don't remember the derivation, and I am not sure I could reproduce it. But it changed how I thought about a lot of physical phenomena.
There's also this article on HN a short while ago: https://news.ycombinator.com/item?id=28314072
AI is not going to build and repair roads, or houses, or pretty much anything else physical any time soon, nor is it going to replace nurses, cooks, shop assistants, or any number of other occupations that require human interaction. Even the vast majority of assembly lines, warehouses, etc. still rely on human labour because turns out building and maintaining robots is expensive and difficult, and even the best robots are bad at manipulating the real world with the kind of flexibility a human can (AI, or lack thereof, is not the main bottleneck here).

What you're talking about is the stuff of distant future speculative fiction that may or may not happen some day, but if it does it sure won't be heralded in by ChatGPT.
Even better and even worse
> One way to resolve this surprise is to find some reason to believe these strange abilities are fundamentally not an understanding of the world. Thus stochastic parrots, this article, Yan LeCun and Chomsky, etc.

I mean, it is kind of obvious that predicting text based on a large corpus of text written by people with a model of the world will, if it works at all, look like having a model of the world.

The question is whether that involves having a model of the world, and secondarily, if there is a difference, what is the practical impact of the difference?

Or maybe that’s not really the question, because the whole “model of the world” thing is metaphysical omphaloskepsis that is inherently unanswerable because we can’t actually unambiguously reduce it to something with testable empirical predictions, reflecting a rationalization for elements of our culture and particularly our own view of our own special place in the universe, and the different answers to it likewise have no real meaning but simply reflect people’s bias for whether or not they want to share that special place, either in general or with the particular computing systems under discussion in particular.
> writing code in national languages is mostly a shit idea

Huh? Plenty of people out there who don't speak english, should they just be excluded?
> How would you quantify how much “what and why” has been defined?

Has been defined or needs to be? I'll assume the latter for sake of discussion.

When skeletal feature specifications can be coded against requirements such that stakeholders and engineers can have a meaningful discussion of the functional expectations (as captured by the specs), along with the engineers having enough understanding to perform impact analysis on the existing system (if any). This is usually an iterative process engaged before any significant implementation is undertaken.

Essentially, the upstream-processes I reference regard establishing a shared understanding. As such, most delivery metrics are not relevant at this point. However, an important benefit is that unneeded effort is often identified and not engaged.

> Some kind of diff between the planned architecture or requirements on day 0 and the final codebase?

In general, system architecture and code bases exist in the "how", not in the "what and why." At a macro (business) level, sometimes architecture decisions such as whether or not to use a cloud provider or data centers do influence the "what."

It's kind of like branching in a programming language. Typically, the earlier an execution flow is determined, the less are needed later. So, too, the sooner stakeholders clearly define "what and why", the less effort is needed to identify "how."
According to the office for national statistics in China, for jan/feb of 2023 http://www.ce.cn/xwzx/gnsz/gdxw/202303/27/t20230327_38464161..., car manufacturing profits is down 41%. non-metal products manufacturing profits is down 39%. chemicals manufacturing profits is down 56%. electronics manufacturing profits is down 71%!! In fact, all businesses have dropped 22% in profit. Not to mention the 1M+ SMB that failed in the last 2 years.

1 in 5 Young Chinese Is Jobless, and Millions More Are About to Graduate
https://www.nytimes.com/2023/05/19/business/china-youth-unem...

China’s shipping containers pile up at overcrowded port as overseas orders dwindle https://www.scmp.com/economy/china-economy/article/3210870/c...

China to raise retirement age to deal with aging population https://www.reuters.com/world/china/china-raise-retirement-a...

Guizhou Province may become the first provincial government to go bankrupt in China. https://twitter.com/tankman2002/status/1646905359184044032?l...
The months long lead time is not purely a scheduling/capacity issue though. Producing the masks for these modern processes is very complex and slow. Adding more fabs won't help because because its a latency issue, not a throughput issue.
Sundar Pichai continues to enshittify Google.
agree that using the API is likely the nicer route. you can also apply for a quota increase, I recently applied for youtube API quota increase to 100,000 units and it was approved for my app (https://cmdcolin.github.io/ytshuffle/) I was concerned they wouldn't like that the app downloads so much data but it was approved without much question, they just wanted terms of service prominently displayed to end users
I'm not a Kagi user (yet) but I think you're missing the point.

In order to display just one ad, the engine has to start tracking you. The converse, just display a random ad, is not valuable to advertizers and they won't pay for it.

Equally, the kagi user base is so small that even if I -wanted- to put an ad on Kagi, I'd get very few impressions per month.

Lastly given that the user base is self-selecting as a group paying money not to see ads, my ads will likely get no clicks.

Thus, imo, you can be subscription supported, or ad supported but not both.
You beat me to it. This is the exact vision I had. A workflow automation with embed first in mind.

Well done and best of luck
baiting nintendo lawyers right on the splash page. bold.
What I found disheartening was many of those scientists, especially those on the "nothing to worry about" camp, seemed not to entertain the thought that they could be wrong, considering the scale of the matter, i.e. human extinction. If there's a chance AI poses an existential threat to us, even if it is 0.00000001% (I made that up), should they be at least a bit more humble? This is uncharted domain and I find it incredible that many talk like they already have all the answers.
> thinking about the concept in non verbal ... abstract terms

The abstract terms we think about are concepts, and we think about multiple concepts, at various levels of abstraction, and their relationships to each other, before getting a sense of what we want to say or write.

Only then do we begin speaking or writing, grouping concepts into paragraphs, breaking them down into sentences and words.

And there's evidence that LLMs do something similar, creating embeddings for both big ideas and small details, modeling how the small details combine into larger concepts, discovering the relationships between concepts, and only then generating a probabilistic sequence of tokens to express those deeper concepts.
Another reason to sanction India is the rampant fraud that emanates from that country in the form of phoney IRS/FBI/Medicare scams and so forth.
KeyDB – A Multithreaded Fork of Redis
This kind of demonstrates that at the fundamental level, physics has been stagnating for quite a while, no?

Imagine, during the time the Feynman Lectures were created, trying to study using 60-year-old material. Utterly unthinkable. You wouldn't even know about neutrons. In fact, you would barely be able to understand what an atom is. You would be completely ignorant of quantum mechanics. Relativity would be cutting edge, with many important models not yet known.

But today, despite immense research effort over decades, using some of the most expensive equipment ever built, there isn't much fundamentally new to add to the Lectures, except a few more particles and a couple new quantum phenomena.
> You can't possibly know that, given that we don't actually understand how LLMs work on a high level.

It's a fair assumption to make however - basically 80/20 rule.

AI research isn't a new thing and I bet you could go back 40/50 years where they thought they were about to have a massive breakthrough to human level intelligence.

> GPT-4 is three months old and you're confident that its working principle cannot be extended further? Where do you get that confidence from?

I'm guessing from actually using it.

GPT4 is super impressive and helpful in a practical way, but having used it myself for a while now I get this feeling also. It feels a bit like "it's been fed everything we have, with all the techniques we have, now what?"
Okay, cool, but the collector is used at runtime with TinyScheme. _cons calls get_cell calls get_cell_x calls _get_cell calls gc for example; what makes you think otherwise?
It looks like you're running searches using LIKE: https://github.com/NotJoeMartinez/yt-fts/blob/050981c0519a96...

SQLite has a really power full-text search mechanism built in - FTS5. It can handle things like stemming and stop words and relevance ranking.

My sqlite-utils Python library includes helper methods for setting that up: https://sqlite-utils.datasette.io/en/stable/python-api.html#...
I am in no shape, way, or form affiliated with OpenAI or any other AI company.

What I and many others have noticed about the "Are LLMs really smart?" debate is that everyone on the "Nay" side is using 3.5 and everyone on the "Yay" side is using 4.0.

The naming and the versioning implies that GPT 4 is somehow slightly better than 3.5, like not even a "full +1" better, just "+0.5" better. (This goes to show how trivial it is to trick "mere" humans and their primitive meat brains.)

Similarly, all pre-4 LLMs including not just the older ChatGPT variants, but Bard, Vicuna, etc... are all very clearly and obviously sub-par, making glaring mistakes regularly. Hence, people generalise and assume GPT 4 must be more of the same.

For the last few weeks, across many forums, every time someone has said "AIs can't do X" I have put X into ChatGPT 4 and it could do it, with only a very few exceptions.

The unfortunate thing is that there is no free trial for GPT 4, and the version on Bing doesn't seem to be quite the same. (It's probably too restricted by a very long system prompt.)

So no, people won't form their own opinions, at least not yet, because they can't do so without paying for access.
The thing that struck me the most was how hemmed in OpenAI is to return copy generated by humans when it’s a topic OpenAI would rather not engage with you in (eg “I’m an AI and thus have no emotions” isn’t coming from the LLM)
You can ask the original ELIZA anything and get an answer but that doesn't make it "intelligent" according to any generally accepted definition of AGI.

Regardless of how you define it exactly, AGI means essentially the ability to converse relatively intelligently on any topic. That means an app that tends to spout gibberish when asked a question most humans should be able to answer is, well, not an AGI.
Seems right up his alley, too - star of the show was killed off in the first 10 minutes of the pilot.
After using several bank clients in different countries I can confidently say that some banks just have bad UI, and other banks are just good enough.
I don't think human language is simpler than good simple interface, though it can shine as a guide or navigator.
Finally level 8 cleared!

It's interesting and inspiring, I don't even know I can use so much tricks to pass through the defense.

Thanks Gandalf.
To do a great deal of harm, GPT-X just has to have enough of a world model to be useful for automating tasks like deception and impersonation at a scale humanity has never before experienced.
Sure. Maybe better if I qualified it with "as they exist as we know them today"
I think you are looking at much higher rates. The question is not what it cost to them, but what they will make from that much time. They may pay the worker 20 dollars an hour, but that worker may be earning them 100 or 200 or even 1000 an hour, and that is Amazon's loss if they get an hour's break.

I am not an amazon employee, and this is standard in every industry ... the employee salary is just a small part of what it costs an employer. The corporate office, the worker's office (or warehouse), the management overhead etc., all add up to what it costs the company per hour of employee work and that is the bare minimum we should plan to donate (per above formula), and then what I mentioned is the profit side of things which would be even higher.
I don’t care if they want to improve their PR retroactively if the result is rapid deployment of renewable. “Who was right all along” doesn’t matter as what actually gets done.
The Symbolics graphics software was bought by Nichimen. Nichimen ported it to SGI/IRIX and Windows NT, using Franz Inc.'s Allegro Common Lisp. It was commercially available as N-World.

https://en.wikipedia.org/wiki/N-World
Good to hear! I didn't mean to imply anything; just wanted to make sure that wasn't overlooked having been on the other end of it. Good luck to both of you
Q: Am I able to run my TLC/QLC ssd in SLC mode? As that sounds sometimes useful
Do you have a source link for this?
Does RL give computers an “imagination”?
Recently on Hacker News, there was a discussion on Nikola Tesla his method of coming up with inventions by visualizing machines and their individual moving parts. [1]

Do you think this is comparable to how AI "simulates" possibilities through iteration? Also could we learn from people like Tesla in improving RL?

[1] https://news.ycombinator.com/item?id=35992553
> IMHO in order for AI to be truly useful, we need to be able to trust it

Disagree, but perhaps we have different ideas of "useful". I think automated systems including AI can be very useful but that executive decisions yielded by nondeterministic processes (such as AI) must be signed off by a human and that usage should be mindful of inherent limitations. This includes cross-checking factual claims with sources and verifying produced code works - just as you would (I hope) with a forum comment or Stackoverflow answer before publishing it as fact or pushing it to production.

So I'd rather say: In order for AI to be truly useful, we need to be able to work with it with never trusting it. Let go of unsupervised execution.
To be clear, there aren't limits. You pay 1.5c per search. You can choose a level to get some bulk-search rates.

Which thus leads to a value proposition for you. Would you pay 1.5c to have this search Ad free?

Personally I think the pricing model is presented incorrectly - it would be better to charge per search, with say a $5 minimum and a $25 maximum.
Kodi addons
Randy Pausch Last Lecture: Really Achieving Your Childhood Dreams
If they went with "let's make the default lookup work well with versions in other registries", I'd love that solution.
The primary question is, what phase are we in now? Are we just at the beginning or somehow already in the asymptotic phase?