skysight-inc/HackerNews huggingface dataset:
OP here!

I made a free ChatGPT bot for students with a bit of smart prompt engineering and data structuring(embeddings). There is a PRO version for longer responses etc. but you will not need it in 99% of the cases :)
especially two
> selling stocks puts downward pressure on price and also p/e ratio…selling bonds increase yields

These are financial effects. It takes extra steps to get to a real effect, unlike spending. (Financial effects are monetarily mediated, which means the Fed can do things.)

> lower growth for a good period of time

Agreed. That’s different from “a prolonged slump” [1][2].

[1] https://news.ycombinator.com/item?id=35512928

[2] https://www.investopedia.com/terms/s/slump.asp
Might be because it’s the “soldering in” that boosts its performance. So if you can plan ahead you come out ahead.
The author is in the UK. They noted that they were on a wait-list just to get tested and likely wouldn't be for a year at least so they decided to take it on themselves.
With LLMs, Researchers create Generative agents that interact with each other
Paper - https://arxiv.org/abs/2304.03442
That should be pretty easy to do in a browser extension. Keep track of the last time the comment section was opened, highlight comments newer than that.
Oh wow thank you for clarifying that. I was thinking it was odd that we're getting a single bank's update here.
My 2015 MacBook Pro is still working OK but I could be convinced to upgrade. But not with Apple’s pricing. I’m just using my Ryzen desktop instead.

I think MBPs great devices - for my employer to purchase, but as an individual they’re just too expensive now.
Thanks for the great article, you've inspired me to take another shot at making a habit of learning through spaced repetition!

I had a question: how much time do you typically spend on this activity in a day? Do you have tips for how to adjust based on the time you have available?
FTX's Alameda Lost Track of $50M at a Time: 'Such Is Life'
The central thesis of the Selfish Gene has nothing to do with "junk DNA", and when the book does talk about the subject it doesn't assume that it has no purpose.

(What it does say is "Biologists are racking their brains trying to think what useful task this apparently surplus DNA is doing" and "The simplest way to explain the surplus DNA is to suppose that it is a parasite, or at best a harmless but useless passenger".)
Do you have more to share? I use Alloy at work and research and would love to learn about how Apple uses FM.
Think about it for a second pal.

Men are famous for hitting on women. Men are even more famous for doing this behind screens, like thru DMs or Tinder.

Women WILL be pursued by every man that wants them. Then, the women already has loads of guys who aren't at the top echelon of attractiveness, so naturally when THEY initiate, it's to people who wouldn't initiate with them.

It's literally the same reason you could easily see dudes trying to swipe on women better than them: people want to date someone "out of their league"
I fully agree that's the case. I was more addressing the idea of the government providing the services directly and cutting the private providers out of the loop
Have you tried a mandibular adjustment device? You can get them pretty cheap online. They push your lower jaw forward. The only real downside is that they can screw with your teeth a little.
That wasn't it's main thesis at all. I don't remember his discussion on "junk DNA" specifically (perhaps I should reread as it has been many years), but the main thesis (to put it in my own words) is that a mental model of evolution as acting upon genes leads to more accurate predictions and better understanding than a mental model where evolution acts upon whole organisms. (There's also the discussion of memes and their roles in comparison/contrast to genes). When he talks about science and not rah-rah atheism I never found Dawkins to be fundamentalist in thinking, and I recall he would generally qualify when his thoughts were more speculative. (The author of TFA on the other hand, does give me that impression particularly with sentences like "Psychiatric drugs help some people in the short term, but over time, in the aggregate, they make people sicker")
I've had extremely poor results attempting to get current LLMs to generate proofs, for code or otherwise.
Actually it is quite small dataset by current standards (millions of images), so I guess it was using humans in the loop.
Is the name a reference to the democracy game from Scientific American back in the 80ies (or so)?

Also, is there a good equivalent for node-edge graphs?
Seems logical, but even today, how many families have $250-350,000 per kid to send to college? I'd argue, not many, even among relatively high earners. Yet college applications and enrollments seem to be at all-time highs.
Can't Datomic be used with any JVM language? Sure, it's a Clojure-first database (note that Mongo is a JS-first DB), but a major selling point of Clojure is you can use it with Java/Kotlin/etc.
Everybody is the main character
Is propane that bad? We have propane plumbed throughout houses everywhere here in the us, and while accidents happen they are extremely rare.

I would think that with a closed loop system the risk of a serious problem would be quite low.
YouTube Premium to Offer SharePlay and Enhanced 1080p Videos on iPhone
Yes, absolutely. It is worth practicing medicine when the treatment is inherently harmless and going through the medical system has been bottlenecked.

Nobody is killed (or really harmed) by trying a CPAP and the waiting list for sleep clinics can be months or years long, not to mention the expense.

It's one of the rare medical interventions that is relatively safe for an individual. Probably should be otc.
When following a recipe doesn't produce the intended result, who should take the blame?
In this article I share a long lost fable and two approaches to procedural work.
I had heard of ArmorPaint, but didn't realize they also had ArmorLab. I'll have to try it out. There's another really good alternative to Substance Designer called Material Maker (https://www.materialmaker.org/)
Something else important to note: this proof of commutativity of addition on natural numbers is definitely _not_ how you normally write these proofs in Lean.

Here is a closer approximation to how someone would actually write the proof in Lean:

lemma add_comm (a b : ℕ) : a + b = b + a :=
begin
induction a with a IH,
rw (add_zero b),
rw (zero_add b),
trivial,
rw (add_succ b a),
rw (succ_add a b),
rw IH,
trivial
end
Same as with Apple sales. It's a return to the mean. Pandemic caused a huge rush in sales in this sector. Now it's just slowing down to normal. Doesn't mean the market isn't growing, simply that it's growing slower.
Yet we have no problem hearing things going faster than sound
Domino’s now lets you order pizza via Apple CarPlay
Still using my 2013 MBPr, no reason to upgrade yet, runs the last non cloud versions of Adobe so i'm not spending $50/mo on software I already own. I bought a M1 mini for a desktop at home, no reason to upgrade that either, but switched to using Inkscape for design work on it as Adobe wants monthly fees now and I ain't doing that. Honestly looking for older Apple computers so I can still use non-cloud Adobe software.
Though to be fair that San Francisco fog is famous for a reason too. I'm sure that doesn't help.
You're right, it's way easier for the government to spend money it doesn't have. The end game on that path isn't pretty.

But that's not my question or point, and maybe I didn't write my other post very well.

The post I'm replying to suggests more taxes should have been used to suck up the excess liquidity. I'm suggesting that liquidity was caused by too many large spending packages and Fed rates that were too low in the first place... Hence, it might be inefficient.

Of course I'm biased, as my spending power has gone down tremendously in the past 1.5 years. I blame the large increases in money supply and low Fed rate for causing a wild near-free money environment.
The biggest EV battery recycling plant in the US is open for business
Learn how to prompt -> Write code -> deploy -> Test your plugin.
[ this comment was written in response to a user who appears to have deleted their comment before I could finish putting my response together. I'm not sure why they deleted it, it seemed reasonable in the face of the ongoing discussion in this thread. I'm going to leave my response here, partly so they can see it if so interested, and mostly just because I already spent the time to write it :) ]

I fail to see any distinction between your description of "mapping terms to latent spaces" and my assertion of GPT "working at a level of meaning and intent".

I fail to see any distinction between "It's using complex non-linear transformations to map observed text to an extremely high-dimensional latent space, and in addition learning to both encode text to this representation and decode it from this representation back to the source language" and my assertion that "the literal meanings are abstracted and re-encoded".

I feel like you're disagreeing with my stated positions because I am expressing them in a lay anthropomorphic language to express its functioning, but that we're otherwise agreeing?

I had initially been responding to the user dvt, who said

>LLMs work on tokens, which, for the most part, are words (longer words are generally split up into multiple tokens). Using concepts like "meaning" and "intent" muddies the waters unnecessarily.

this seemed like an incorrect characterization of the process as I understood it. he doesn't acknowledge the existence of what you refer to as latent spaces, and seems fixated on GPT as merely moving around tokens (though I may be reading his position incorrectly, of course). I was arguing a claim of GPT's ability to represent concept distinct from literal meanings of terms, and for "understanding" how to transform these abstract meanings into different contexts.

As far as I can tell, I don't really disagree with what you're saying at all.
If you would call out the inaccuracies and cite why you think they are, that would be far more useful and helpful to the discussion than just complaining and waving vaguely ... "over there" as where the errors lay.
How does Alloy compare to TLA+?
I'm assuming at this point you'd need a means of pruning expired information from your list, and then importing that shorter list into a new session.

I guess the question is, can we get ChatGPT to make that new list reliably?
This sort of testing is good and all, but I wish more attention was being paid to the more likely adverse impacts of gpt -- the socioeconomic ones.
OpenAI says they aren’t training on chat GPT conversations. Up to you to see if you believe them or not. They also said having a 30 days data retention policy, that is compatible with GDPR.

https://techcrunch.com/2023/03/01/addressing-criticism-opena...
Show HN: Attempt at an oscilloscope application for the flipper zero
> From the generation that brought you Ronald Reagan,

The age groups that Reagan won were the ones that are (predominantly composed of, because the categories don't perfectly match generation boubdaries) Silents and older. The Boomer age groups were tied (22-29 went 44 Carter, 44 Reagan, 11 Anderson) or for Carter (18-21 went 45 Carter, 44 Reagan, 11 Anderson.)

The generation(s) that brought you Reagan are, for the most part, dead.
I think too many do not understand one point of the Green New Deal, perhaps because that point is NOT advertised: convergence toward electricity it's not different than convergence toward IP, it means choosing a tech we need anyway while not the cheapest and use it for almost anything cutting much costs.

For instance a heat pump have much less raw materials and need far less high costs alloys than a gas heating system, essentially is cheaper to be produced, and if we can stay on electricity only we can spare the maintenance and expansion costs of gas/oil/* distribution networks.

Try to compare classical mechanical clocks vs modern electronic ones: the mechanical one it's far more costly per single unit, the electronic one cost next to nothing per single unit. For EVs it's not different: they have much less parts, less special alloys, less precision needed to produce them.

Heat pumps and EVs have both evolution margins, while classic ICEs and gas heating systems have already reached a sort of evolution plateau.

Those are the reasons of the Green New Deal: ecology is advertised as the only reason, in reality is a MARGINAL reason, the main reason is reduce much the demand of raw materials (once the transition will be done, of course) and lower much overall production costs. I imaging such reasons are not advertised because most of the benefit will go to those how steer the transition, not to those who pay it. But that's is and understand it and it's need means also steer the actual transition in a way more interesting to the people than a very small cohort of cleptocrats.
>My company is small enough to know everyone personally.

OK, so how do you identify, evaluate, and rank loyalty? If there's an objective mechanism for it, you shouldn't need to personally know everyone.

What I'm hearing is that you go by "feel" (aka the sum of all your biases) and make decisions based on that. How is this remotely objective, fair, or scalable?
The C++ code is a simple list type, and also a bunch of tests for that type to confirm that it works as intended. The crucial trick here is that because static asserts are used, the test values are computed during compilation, such computations are forbidden (by the standard) from having any leaks or Undefined Behaviour. Anything allocated must be freed by the time the tests complete, and no language Undefined Behaviour is permitted.

The latter is pretty normal for other languages but is a big deal in C++ where UB is a constant plague. However many languages have either forbid or have strict limits on compile time heap allocation - after all that heap isn't going to still exist at runtime. Requiring that you free everything allocated fixes that hole and means you get free leak detection.
Adoption of new methods takes a considerable time in medicine. Some methods may be considered unproven by the majority but are being adopted by pioneers. Now if you could distinguish pioneers from quacks easily…
TIL -- I thought serif was generally supposed to be easier to read.

How is this kind of thing studied, and what kind of outcomes suggest "easier to read"? Speed? Recall? Subjective?

What proportion of the population are we talking about, roughly? Is it even enough that one should consider providing both a serif and a sans version of their content?

Serious question.
In some way could call what is happening now "the great smartphone Plague". Hundred of people staring at a screen, all the Time, and for some, stoping to go out, and believing self-harming social-media driven ideology such as anti-health posture (anti-vax for instance).
Basically anything that is not C/C++ is a pain on non linux system...
Hijacking Arch Linux Packages by Repo Jacking GitHub Repositories
Kudos for just putting the product on the homepage, above the fold, and without asking me for random contact details before trying it out!

It's just ChatGPT with a preset prompt, but this is wrapped up nicely into a product.

Is there any other information sources this pulls from, or is this just ChatGPT's mostly-accurate confident responses?
I was listening to Jim Cramer discuss it this morning, and he said the banks are nervous about lending out money/investing, in what is usually considered safe. Things like US treasuries or real estate. They are fearing a liquidity crunch.

I'm looking for a more concrete source.

edit: Found a source: https://www.federalreserve.gov/releases/h8/current/
> Running inference does not change the trained weights.

That's true today.

I don't know how many days (or hours) away we are from GPT-4 running a LoRA-pass to update its weights after each round though?
I fixed a parasitic drain on my car in 408 days
Formal methods have their applications and specific use cases. It all depends on how much is at stake, economically.

I suggest checking into Alloy, which is far easier to work with. It feels like writing a SQL schema, but you get bounded model checking and much more.
You Can Now Order Domino's Pizza Using CarPlay
Now the misspelling has spread across this whole thread
>that totally destroys my stats

I don't understand what you mean. There are only 2 stats that are mostly significant. The first is, when first learning the card, if you hit again too many times the card becomes a leech - as in it leeches your time, at which point you should temporarily suspend that card and to the others first.

The other one is the recall rate: after you learn a card (on default settings, when you hit the 1 day mark for that card) how often you don't fail to recall the information. This rate is the single most important metric in your stats, and a value that is constantly below 90% means you should probably tweak your settings to show cards more often. This can be easily done by reducing the interval modifier. A value close to 100% might also be slightly problematic depending on what you want, because you might be wasting time with unnecessary reviews, which can be solved by slightly increasing the said interval modifier.

As for your main question, you can do it however you see fit. Some people might prefer to do everything in Anki, while others might prefer to read a textbook, watch lectures etc. first and then move on to Anki for that specific topic. Don't use Anki as a way to quiz yourself, it is not a testing tool. If you want to test yourself, use question banks. Use Anki as a tool that will help you memorize things. For this, you have to do your reviews on time, or the algorithm just won't work.
I remember someone mentioned on other thread that after distilled, llama will have no license issue.
can someone explain why is that the case?

Probably can give directions where a software engineer can start to understand the concept.
Prices are driven up by people’s inability to be financial savvy.

People keep overpaying for things like cars and houses. Any drop in prices by few % makes it look like a great deal, and people fomo into it; when in fact prices are still insanely high and completely disconnected from the real economy.

More and more people will be house poor. Many ex-FAANG bought into $8k mortgage depleting a good chunk of their saving for insane downpayment, thinking their income would go on for the next 30y.

I believe we will start see the effect of this in the coming years.

There is no way around it, people must stop buying and stop paying $5 for a coffe.
Previously unknown isotope of uranium discovered
Diagnosed at 24 with sleep apnea. I tried a bunch of things.

What worked for me was regular cardio exercise and daily doses of high absorption magnesium.

The magnesium is absolutely unproven pseudoscience nonsense that can't possibly work. But if I stop taking it my sleep suffers massively.
> the HTC hardware was slick, but WinMo was useless and incredibly dumb

You’re not kidding. I had a HTC HD2 and the hardware was very futuristic-feeling (one of the first phones with the original Qualcomm Snapdragon, and a “huge” 4.3” screen that my friends gently mocked for being ridiculously large), but the software experience was leagues behind iOS and Android, despite they themselves being in relative infancy. It would have been pretty nice if it got an update to Windows Phone 7, which was promised but never came.

HTC’s own customisations were the worst part. Their flashy animated home screen was very nice, but the iOS-style threaded SMS app couldn’t deal with threads longer than about 300 messages and would routinely lock up the phone for minutes at a time until you deleted your conversation history.

In the years after I got rid of it people continued to port newer versions of Android to it, but I just remember it being shit at texting and browsing the web—the only things I actually wanted it for.
I've seen this question asked repeatedly in many LLaMa threads, currently the best models that are truly open are the released models from the Flan family by Google, which includes Flan-T5[0] and Flan-UL2[1]. According to its paper, Flan-UL2 performs slightly better than Flan-T5-XXL.

These models perform slightly better than GPT-3 under some tasks[2], but they're still far from achieving the results from GPT-3.5 and GPT-4. This becomes evident when you try to use them in the real world; they're not "good enough" for general use cases, unlike ChatGPT models. However, if you can restrict your use case to one particular domain, you can achieve pretty good results by further fine-tuning these models.

[0]: https://huggingface.co/google/flan-t5-xxl

[1]: https://huggingface.co/google/flan-ul2

[2]: https://paperswithcode.com/sota/multi-task-language-understa...
I can sleep through incoming and outgoing artillery fire, .50 cal machine guns and humvees running over land mines (allegedly, they may have been messing with me), people snoring, all kinds of stuff. Someone talking and I’m wide awake.
I'm working on a few of these kinds of projects and progress is highly variable. Some days, I might only get a few lines of code done. Hardly enough to make a difference but then other nights, in maybe the same amount time, I'll build out some massive subsystem.

I think big progress will eat up an evening but I think the important point is that it's not a job -- so when it eats up an evening it should be fun and when you've not other important/interesting things to do. I almost never know when I'm going to make progress when I start.
No problem! It's an area I'm recently quite interested in but don't really have the background necessary to approach it.

I am also quite biased against any system that reduces the accountability of the care provider - and so much of modern application development is about being able to scale essentially everything _but_ accountability.

I like the idea of "ThoughtCoach" because you are framing it as empowering the user to improve their own abilities to manage their mental health. In this regard, it's kind of in the genre of mindfulness meditation (and the various apps/integrations that have shown up to help people with that). You could go with a gamified option like Noom does.

This requires you to scope out a progression for the user to go through - and to be informed (at least hopefully) by modern psychology and proven to work statistically before being implemented. This also requires you to significantly narrow the LLM's possible outputs/modes at each level - which alleviates many issues with overconfident outputs and unreliable patients (you can even force the user to choose from a list of words, rather than type anything at all).

I haven't checked this space out enough yet but it's rapidly evolving. A lot of chatGPT-based start-ups are in this learning-with-a-smart-tutor-available regime. I think it could be very powerful but a lot of clever engineering is still required. On the other hand, maybe the limits there prevent it from being nearly as useful as what you're imagining.

Food for thought.

edit: I guess my final thought is that, from personal experience, a good part of why therapy can be successful is that some amount of positive human interaction alone can be enough to improve one's general outlook. The context of "using an app" requires initiative and perseverance. The comfort from consistent human contact can inspire that but apps just feel like "thumbing through your phone". Reducing screentime in general is good for mental health. Thus, the app shouldn't be gamified really; because the only targets you can set in an app are LLM-based and will require the user to type or tap. Anything other than that is just what's already out there - Apple's Screen Time, step tracking, calorie counters, mindfulness guiding. Adding an LLM doesn't obviously help there.