skysight-inc/HackerNews huggingface dataset:
It's not hard to imagine GPT-3 writing a fake paper that gets published in certain academic journals in the social sciences. And then, it'll be all over for us. We won't have any more funding and our jobs will disappear. I can already hear the protests: "But we're not just scientists! We're also philosophers!" Well, yes and no. Philosophers are supposed to think about things philosophically, but they don't actually do anything about them; they're just entertainers. Scientists do something about them. They make things happen. And when those things happen, people take notice. If science and technology have a weakness, it's that they work too well. This was probably a strength at one point, but not anymore. In the not-too-distant future, there probably won't be any more philosophy professors; there will just be philosophers. But only in the same sense that there are lions and mushrooms.

This comment was also written by GPT-3.
Wouldn't "after the second paragraph" be "half-way" for a four paragraph piece? :D

But you are right, it can't be both in the context of this article :)
How deep are the sunken ships at Midway?
Wisconsin Supreme Court justice internment of Japanese over stay-at-home order
On the other hand, without a theory of mind it can't really educate or inspire people

I wouldn't agree with that, either. How often have we heard of someone gaining useful insights by considering ideas that were misapplied or just plain wrong? Entire branches of physics have evolved that way. As far as successful presidential campaigns are concerned... well, let's not even go there.

If there's such a thing as a 'theory of mind', it applies to the reader, not the writer.
I've worked in both b2b and consumer spaces. Finance, Market Research, Payments, Education, and Real Estate.
I think you're mixing up sentience/consciousness/intelligence. Many animals are sentient for example but as far as we know, they don't really have language. But I think I get what you're getting at, which I believe is "human level intelligence requires langauge". I think that's a reasonable take. But you said "sentience", and you said "is", which makes your position difficult to agree with.
Note this was back in May.

Interesting quote:

"Could the secretary under this broad delegation of legislative power or legislative-like power order people out of their homes into centers where are they are properly social distanced in order to combat the pandemic?" she asked, adding: "The point of my question is what are the limits, constitutional or statutory? There have to be some, don't there, counsel?"
With bot-human cooperative text generation this could be very powerful (if the purpose is to generate a large volume of text).

I could tell that something was off when reading through this. The logic didn’t flow and there were contradictions that defeated the previous point. Even more, it wasn’t clear if there was a theme - more like a rambling story.

However, I wouldn’t be surprised if someone told me this was written in a High School English class - as a rough draft.

That is where it occurred to me, that if this was given to a human editor to clean up, it could be interesting.

For example, if writing a creative work of fiction - this could generate a starting point for the human author to refine.

This could be done in an interative process:

- Generate a chunk of text (or multiple chunks).
- Edit that into a final text.
- Use that as input for the next chunk.
- etc.
There is a reason companies don't encourage internal innovation.

It has nothing to do with managers, HR, or what not.

Say you have 100 innovators in your company. Everyone comes to you with an idea, as an SVP or a Director, can you agree to all of them? You obviously pick and choose. And how can anyone say a new product / service by a company is not the result of an internal innovator?

Alternatively, in the safe environment of a company, as in the innovator is getting capital and resources from the company finances, I think it is more likely that people are more free to give out ideas, even crappy ones. It's easy for a good idea to get lost in the noise.

Ultimately, what is the solution to this? I guess you have to fundamentally change the structure of companies itself.

In the given example, if Cisco were to transfer the innovator to another division, give him some money, on the same terms and conditions as a VC, perhaps it would have borne fruit.

Essentially, it's easy to see companies, once a certain size, are effectively hard wired to move at a slow, glacial pace and focus on sustainability, rather than fast and fail innovation.
An extreme example: https://en.wikipedia.org/wiki/Neerja_Bhanot
> By the time a person retires they have spent the overwhelming majority of their life working. To a point that not much else makes sense. Working is the social contract.

No, what the first two sentences describes is institutionalization (or environmental socialization), not social contract. The same thing that extensive periods in prison, or war, or any number of other hostile environments do that make it hard for people to adjust to any other living situation.
Why scalatron was dead for six years
For Scala lovers this is an opportunity to revive Scalatron.
"I wouldn't know how to search for them"

I don't believe you are incapable of typing "a11y" into your browser's location bar.
Lol why would you resurrect this terrible article.
I don't really understand your post (and don't know much about GPT3) are you suggesting that the model is stateful in that it can continue learning from successive prompts?

Maybe you can elaborate on this:

>instead, you interact with it, expressing any task in terms of natural language descriptions, requests, and examples, tweaking the prompt until it “understands” & it meta-learns the new task based on the high-level abstractions it learned from the pretraining.

Or are you suggesting that it has such a deep network of abstractions that once a user starts to map that out, the mileage they can extract back out of the model via prompts is very exciting.
https://xkcd.com/2321/
Was this comment generated by GPT-3?
>"Ten years ago, if I had this conversation, I would have assumed the entity on the other end was a human. You can no longer take it for granted that an AI does not know the answer to “common sense” questions."

[...]

>"Now we’re getting into surreal territory. GPT-3 knows how to have a normal conversation. It doesn’t quite know how to say “Wait a moment… your question is nonsense.” It also doesn’t know how to say “I don’t know.”

"GPT-3, why do two wrongs not make a right -- but three lefts, do?" <g>
If I understand it right, it's possible to produce non-radioactive steel but doing do is just a lot more expensive for the time being than just getting it from old sources.
Reading the entire article is highly insisted.
Midway the article talks about risks and incentive, and that not all innovators will want to leave the nest. I'd say though, if you're already in a place where you're internally innovating, by virtue of the fact that you've already deigned to challenge internal culture, practices, or product roadmap, you're the type to take high-payoff risks. There should be a strong positive bias for leaving among internal innovators.

Probably the only reasonable way for a company to be able to take profit from these innovators is to make it easy to spin out with a favorable equity position.
This kind of facile moving the goalposts is imho a cheap shot and (not imho, fact) is a recurring phenomenon as we make incremental progress toward AI.

Progress is often made with steps that would have been astonishing a few years ago. And every time the bar is raised higher. Rightly so, but characterizing this as doing the wrong thing is missing the point of what we, and the system, are learning.

Yes it's not intelligence. But then, it's not even clear that we ourselves can define intelligence at all… not all philosophers agree on this. Daniel Dennett (philosopher and computer scientist) for example thinks that consciousness may be just a collection of illusions and tricks a mind plays with itself as it models different facets of and lenses into what it stores and perceives.
As exceptions are an abstraction you can implement them in many ways; one of those is "the same secondary return code error check as you would do manually", but if you assume "errors are extremely rare" (which I assert is fair: people who disagree generally point to a tiny class of things that I would argue aren't errors in the first place, such as "key not found in map" and "file not found on disk") you can use implementations that have literally "zero cost" for success but instead compile all of the exception unwind logic (catch statements and deconstructors) as continuations of the original functions (causing some modest binary code bloat, though the compiler can sometimes avoid this being noticeable) and then do table lookups (which are slow, but not necessarily ridiculous) to find the right on-error unwind target given an on-success function return pointer.

Essentially, I would argue that error signaling is important enough and common enough that it deserves attention by the compiler in the same sense that many of the other things we provide syntax for (such as traits or inherentence) are things which developers can type naive manual implementations of with basic tools (such as switch statements or dictionaries or dragging around lots of function pointers), but if you can abstract it in a way such that the semantics are available to the compiler you can come up with much better ways to handle the problem (such as vtables or polymorphic dispatch caches) for a given set of tradeoffs (such as low memory usage, low construction cost, consistent latency, etc.). If everyone is implementing the feature themselves manually in the code then you have lost any real ability to make great optimizations.

(Note that you don't necessarily have to have it be syntax to do this: you can also have a language such as Haskell--where notably these Either-style errors are usually cited as being from--where they do it in the language but abstracted everything an additional level higher, letting you define a lot of these flow control concepts in terms of a monad, so then downstream users use "do" notation to feel like custom syntax and the monad's bind operator provides a central chokepoint on what was otherwise a bunch of boilerplate. You sometimes--not always--can then do optimizations across the entire program of that shared abstraction. The way languages like Rust and Go are handling this, without support for monads, simply precludes anything other than attempts at reverse engineering semantics from the code, which is ridiculous.)
This is already outdated.
Just now the cabin-crew union and Icelandair signed a new contract.

I couldn't find an article in english but in another article they say that all layoffs will be reversed.

https://www.visir.is/g/20201992741d/flugfreyjur-og-icelandai...
Sadly one doesn't - unless one happens to have ~300GB of RAM to fit the model into memory and a close personal friend at openai who will share the learned weights with you. Training your an even more expensive endeavor.

Presumably this is how they are justifying the for-a-price API; "its not like you can run it on your home computer anyway". For now, the API is private and geared towards researchers. Still a bit bollocks though.

There are plenty of wrappers [0] around GPT2 though - and those you can probably run on your home workstation.

_
[0] https://pypi.org/project/gpt2-client/
Well I’m certainly no expert on this, but I would guess due to the previous comment the field is possibly too immature at the moment to have as much mathematical certainty as you might find with other methods and fields of mathematics. I recently read the beginning of the book Introduction to Mathematical philosophy by Bertrand Russell and in it he explains how at the times of the Egyptians though they invented geometry it wasn’t very formal and it was very much like the grandparent explained Machine Learning is where Romans used to test bridges they would just throw enough examples at something until they thought it worked. This didn’t mean geometry could never reach a system where they could know the surety of their theorems. The Greeks did just that by starting from basic assumptions or axioms and building a consistent and partially complete system that allowed them to prove many things that followed from there assumptions. There’s a possibility that at some future time (possibly future generations) we’ll have better mathematical tools to figure out the specifics of why neural networks and machine learning work and to the specific extent they do work.

I am also currently reading a Programmer’s Introduction to Mathematics by Jeremy Kuhn (excellent book by the way I would whole heartedly recommend to programmers who have some background in math or thinking in abstractions but who want to learn more math) and it has a quote that states learning Mathematics is a lot like walking into a series of dark rooms and feeling around and getting a feeling of what is in the room until you flip on the light switch but then you could always go to a new room and start all over. I think in that sense machine learning is a series of rooms some lit, but a majority still dark that we haven’t grasped yet.
Hi, I'm the author. Thanks for taking a look. This is basically a tool to help manage a "Dockerfile" repo (along the lines of https://github.com/jessfraz/dockerfiles), where you build any tools you want into images that you control. This can be really useful for personal use or within a company.

Why build tools into Docker images? Love it or hate it, there are many senses in which Docker is currently the best medium that we have for distributing and running dev tools. Here's an article making that argument: https://jonathan.bergknoff.com/journal/run-more-stuff-in-doc....
Time to Watch China’s Equipment Efforts
I don't consider myself a docker fanboy, but between bare metal, VMs, and docker... I think docker works better than most solutions thus far primarily because developers can run and test their code locally... But as you move more towards complicated solutions, docker becomes more than a 1-3 day training session, if it can even be tested locally anymore...

Despite dockerfile being essentially shell scripts on a clean basic install... It seems more approachable to developers than ssh and working with real servers.
Hiking gear has always been my go to when I need non-flashy, long lasting and well thought out stuff.
>The cockpit crew will not be handing out drinks.

The mental image this gave me was amusing:

>"Hey man, can you steer for a few minutes? I've gotta go push the drink cart."

>"Sure thing dude, I'll get it next time."
Tizen is not a bad system by itself. For example, all Samsung watches run it, and they're the best wearables after iwatch.
Have you spent any time interacting with GPT-3?

It's qualitatively different than GPT-2. I was on a discord with someone that has access to it and a bunch of us were throwing ideas out for prompts. One of them was to provide an anonymized bio of someone and see if it could guess who it was. The format was 'this person...they..and then they...\nQ: Who is this person?\nA: '

At the first pass it didn't guess correctly. But we erased its response and tried again and it got the answer correct. We then asked it to screenwrite some porn and tell jokes. Yes there were some misses, but it got things right so frequently that you can start to see the future.

Having all of this capability in one package is pretty remarkable and nothing has approached it to date.
Microsoft has gotten a bit better at it after many years of zero progress. Vs2010 introduced stdint and stdbool. Vs2015 finally allowed mixed declarations and code. I think the most lacking piece lately is the named struct member initializers.
I'm not sure it was his first Haskell program, if it was it's pretty impressive that he used INLINE, understood minute differences between Random libraries, profiling, threadscope, etc..
But it shows that consuming drugs does harm people other than you. So we're back to: why should drugs be legalized or decriminalized?
Yeah, your right. I added in that disease is historically thought of something that you catch (and hopefully get over). Conditions can also be categorised as chronic which would be that permanent state of you have it, deal with it.
The bot wrote the article and presumably it learnt that blockchain is disruptive from BitcoinTalk.
It all depends on alternative. $100 is a lot of money for a kid in India, if the same kid can earn the degree while watching ads I think it does a great service to poor people because the alternative is not learning.

Alternative to a problematic suboptimal (according to you) school experience is not a perfect school experience but no-school experience.

American public schooling system has become a jobs program for adults.
Brigham did way worse than that to black people. Brigham Young and most other Mormon leaders, believed that the(ir) scriptures justified the subordination of black people because they were descendants of Cain or of other biblical figures who had sinned egregiously.
> Prediction: GPT-3 and it’s subsequent iterations will eventually take away Google’s dominance in Search. In fact we may not have text based search as we know it in 2030.

Google has been focussed on a future without text-based search for a long time, focussed on personalized predictive search.

> Will Google ever be able to tell the difference between gpt-3 text and human text?

Will it ever need to? What it needs to distinguish is “will this be useful to you?” not “by what mechanism was it generated?”.
"objectively ...funny" strikes me as a contradiction in terms; concepts like humor, insight, and interest are fundamentally subjective, dependent by definition on a subject's consciousness and expectations
I rather agree with you, but the interaction of the mind with the physical reality is also extremely important to shape it. GPT3 has no interaction with a physical world. Any formal system that cannot interact with something outside of itself will be intrinsically limited, for one thing by Gödel incompleteness theorem.
> because a lot of Americans can't compete economically

That’s an assumption not directly based on numbers. Yes, the net in migration to California is largely from non-domestic people. That could be due to exactly the reason you provided, or it could also be the result of less movement freedom tied to visa sponsorship, or a variety of other factors. Many of my tech coworkers in Texas are non-citizens under visa sponsorship who, given the choice, have stated they prefer the Midwest due to a variety of economic conditions (not just cost of living).
With CSS not being able to dynamically wiggle letter-spacing, you really can't use text-align: justify without hyphen: auto. The rivers in the text were so large and distracting to read around. It's usually best to not even try to justify text online though.
Hopefully in a way that secures some funding for those making archives of the web.
This was my experience fresh out of college and job seeking in the middle of a decent sized US recession. First boss was a functional alcoholic and psychopath who toyed with people for sport. Also exiting his 2nd marriage and on the way to burn through his 3rd. I stayed too long (6 years), realizing 1/2 way through it was him, not me. It took me another few years to find a "face saving" exit. Horrible time and time wasted. Get out asap whatever the costs.
Not the person you're asking and I'm not sure if it's a good example to base anything off of, but the only example I could think of is Jira.

It has a "rank" attribute that it somehow keeps track of for tickets. Somehow that rank still works when you have a list of tickets from multiple projects (each with tickets that could have their own rank as well).

IMO a custom order should only be relevant to whatever the native view is that that note shows up in. I haven't used notable (yet), but I assume you have folders/notebooks/etc that the note is stored in. When in a view that shows the contents of that folder (and nothing else), you could allow users to move the note's sort position.

In any sort of search or tag view that shows notes from multiple folders, I would expect the notes to be ordered by date/name and not by this custom order.
Any time you have hundreds of members of the general public in a confined space, you're going to need a staff to manage whatever they throw at you, or to run an evacuation. Same reason theaters have ushers.
From your comment it's not clear to me if you realize the author of the article is GPT-3.
There was a post a week or so ago where low-background steel was discussed in the comments. I can't find it on Google though. Probably someone saw that and either made a calendar reminder for a few days out to post it or had it in their open tab backlog.

Edit: I'm pretty sure it was the knife steel post.
If I had to guess, the moderators curate certain technical discussions to the top.

But I’d wager that Reddit curates their front page too. There’s no way an organic algorithm is populating the front page.
That only works if supply can be increased easily. For a comparable situation, see the housing market in California.
This is a good article but, the author doesn't show the limitations of type systems. If our world is small enough types can be very useful. There are many situations where we want to work in a small world.

>type's have always been there

I've seen this argument before and, I disagree with this statement as presented. The implication is that there is a type system underlying a language's semantics. But, really that's not true. It's more correct to say that objects have always been there.
Oh please. C and C++ programs can be coded to fail gracefully and "a lot of languages" fail in unpredictable and unfortunate ways and shitty programmers still don't catch those magic errors. This is a matter of crappy engineering, not per se crappy language.
FWIW, GPT-3 was not released to the public. API access waitlist is here https://openai.com/blog/openai-api/
The problem is that "raise wages" alone isn't a panacea. Higher prices are a signal to stimulate higher supply. If the supply is artificially constrained that signal is useless. So I agree with the rest of your post - raise wages, but also increase supply without restrictions on employees or the types of jobs they can take.
Don't need two pilots. Just have one pilot slowly push the drink cart with one hand while the other hand pilots the plane with a game console controller plugged into a VR headset. Then the passengers can simply grab drinks as it rolls by. Multitasking!
Semi off topic:

> released its third generation of language prediction model (GPT-3) into the open-source wild.

Well, it sadly didn't get that part right.
Those 26 million lines of code have been engineered over the better part of a decade to perfectly cater to every possible use case. To not leverage those productivity gains would be insane. You wouldn't build your own car would you?

(/s, btw)
I love this guy's channel it's awesome.
I think the low pay and long hours during the PhD program are also a large contributor to that aversion. There's a ton of opportunity cost associated with it too.
Yep, my grandfather has a pension from working as an electrician his whole life, and now he works in the hardware section. He's getting too old and frail to do the activities he used to do, so working in the hardware section lets him feel useful instead of sitting around the house doing nothing.
For most people, aosp without gapps is useless. Given an option, they will choose android over aosp every time. You don't use your phone for any popular apps so of course it's fine for you. I'd like to actually use my $1000 phone instead.
Thanks, I had my definitions wrong :)
More than opening or not, I would say the real measurement would be states that forced people to be admitted into retirement homes that had tested positive for Covid, vs. states that did not do this. They are the ones that value life the least.