skysight-inc/HackerNews huggingface dataset:
Clojure is really good at self-selecting for people that really care about innovation in programming languages. The other jobs in a tech company care about innovation in their domain. They rarely align.

So for every weird, cool innovation you see, the productivity is immediately lost because people equally care about how you deal with state on app startup, or routing, or database interaction. And since none of those other things move the needle much in how you compete in your business domain, competitors who are not concerned wind up eclipsing you. While you're arguing integrant vs. mount, people are just running dotnet new and bikeshedding over things closer to the business domain.

PMs/EMs/QAs/etc. may not have technical knowledge, but they smell something off about programmers arguing about what library to use for routing. Why didn't people complain about this at their past jobs? Surely if it was important, it would have come up. They just perceive you as having hired a bunch of senior people who are incredibly slow relative to their past companies. It really breeds resentment.

I have seen clojure-first companies creatively hive off parts of their engineering org to have a separate org that is allowed to use a different stack. They're not super transparent about it to avoid a big exodus of people, but I've personally seen it happen more than once.
"the world could well live without the Higgs boson" (c) Sabine Hossenfelder

https://www.science20.com/tommaso_dorigo/what_it_means_to_be...
Indeed. Abu Ghraib is actually kind of unique in US history, it is an exception of the norm where the people responsible are actually charged, found guilty, and not pardoned after the fact. Compare this to e.g. Guantanamo—which is still, over two decades later, holding people captive which have never been charged of any crime—has not held anyone responsible for systematic torturing of prisoners. Obama even went so far to explicitly immunize James Elmer Mitchell and Bruce Jessen who designed the torture program, as on of the first thing he did in office.

Even the Nosiour square massacre in 2007, which was a particularly atrocious, and not conducted by a military personnel, took a whole year to file charges (despite overwhelming evidence) found five Blackwater soldiers guilty, but had the charges dropped on technicality in 2009 (despite taking a whole year in preparing the charges). Now later rulings found this was an error, and four of them were finally charged with the massacre 2014 (seven years after the massacre). Charges were as such:

- Dustin Heard - 12½ years in prison

- Evan Liberty - 14 years in prison

- Nicholas Slatten - Life without the possibility of parole

- Paul Slough - 15 years in prison

Additionally Jeremy Ridgeway got 1 year and 1 day in prison in a special deal by pleading guilty and testifying against the other.

Predictably all four (not Ridgeway) were then pardoned by Trump in 2020.

This is a clear case of the US justice system not actually wanting to press these charges, and only did so reluctantly after an immense pressure from the electorate.

If you also compare the Nisour Square Massacre to the helicopter murders of journalists Namir Noor-Eldeen and Saeed Chmagh (as leaked by Chelsea Manning). The only people that answered for those murders were Chelsea Manning and Julian Assange, and that was only for revealing the truth about those murders.
If they had a permit to be there and there was no conflict needing to be shut down the whole ordeal described sounds like pretty awful police misconduct.

I don't know if there's any recourse in Brazil, but in America, at least it sounds like you'd have a case.

The problem here isn't the pepper spray. The problem with the people were physically attacked while being within the law.
Sounds like you’re ignoring more important issues like the train derailment to focus on sports.
Immediate resignation reason and turns out the ones who got recently laid off are the real winners as they walk away with a severance package at least.
I will mention again for the fun of it, that private healthcare for profit works very fine in other places, like Switzerland for which I can vouch. There might be a lesson somewhere, maybe?
> GPT is basically the language portion of your brain. The language portion of your brain does not do logic. It does not do analyses.

I like this analogy as a simple explanation. To dig in though, do we have any reason to think we can’t teach a LLM better logic? It seems it should be trivial to generate formulaic structured examples that show various logical / arithmetic rules.

Am I thinking about it right to envision that a deep NN has free parameters to create sub-modules like a “logic region of the brain” if needed to make more accurate inference?
I am an AI researcher, and I wholeheartedly agree with Tom here. I love AI, I love designing and training models and seeing all the amazing things they can do. But I would be lying if I said I wasn't scared. Like Tom, I have no idea where on the sigmoid curve we are, but I personally believe we're very near the beginning. I thought that becoming a practitioner in this field would make me less susceptible to making big, sweeping claims about it, but I've found the opposite to be true—the more I learn, the more I am convinced that AI will change everything in a manner at least as radical as the internet, if not more. In my opinion, society is completely unprepared for this change and for the new ethical dilemmas, challenges, tools, discoveries, and advancements it will enable.

ChatGPT is a proof-of-concept. There are agents far, far more capable than it on their way, and it is impossible to know for sure how they will impact the world at large. We are observing science fiction become science fact and it is really unnerving at times.

Tom is a smart and thoughtful guy, and I think he's right on the money with this video.
Efficient joins in NoSQL are done by persisting the relation in a brand new entity. Thus they only make sense when the query is really and constantly needed, not when one is writing up SQL, researching, creating a custom report, etc.

NoSQL DBs take large volumes of data, little CPU, and almost no RAM

SQL DBs take lower volumes of data, loads of CPU and RAM

Storage is cheap, CPU is expensive, hence NoSQL is cheap. Even when your project is not in the 100 of milions records this can be significant because you then are able to offer a cheaper product than the competition's
I don't think anyone really ever thought they were. I've posted a similar sentiment a bunch of times, but both of the following can easily be true:

1. There are companies that are run inefficiently, especially ones that grew spectacularly quickly during the pandemic due largely to FOMO concerns from execs.

2. Large companies have a huge number of responsibilities and needs for staff that are rarely grasped by the "It's just a website! I could build this in a weekend!" crowd.
It seems like DoorDash, Uber etc. really are great jobs for people who have trouble getting more traditional jobs: people without prior skills or connections who just want an easy job, "want to be their own boss", don't want rigid structure, etc. As they were originally and still are marketed.

They just need to be treated and payed better. The people using these services by design have money to spend, "outrageous" delivery tips and fees can be justified if the fees are actually going to the workers.
GPT3 will recite Harry Potter if you ask it
The explanation I keep seeing is

"the United States Federal Reserve raised the Federal Funds Rate from 0.25% to 4.75% in the past 6-18 months, therefore, these companies are reacting to that and having to cut back on costs"

where it falls apart in my mind is (and I might be missing something)

why is that having such a massive impact so quickly on these companies to the point where, the cost to service NEW debt (not existing) rises?

i thought a lot of these companies had so much cash due to high tech margins that, they didn't really finance growth through cheap debt?
This looks cool. If I think one step ahead, this reduces enough incidental complexity its the kind of thing that, when combined with AI, could produce the holy grail of an AI writing most of the code for a full CRUD app.
How it should work is the model should be pre-trained to interact with the bing backend and make targeted search queries as it sees fit.

I wouldn’t put it past Microsoft to do something stupid like ground gpt3.5 with the top three bing results of the input query. That would explain the poor results perfectly.
A way to mass manufacture eco-friendly fast-decomposing plastics of all types.
Would our landfills essentially become trivial to manage at that point?
> It consists of a set of highly optimized data objects that can be used to build complex systems like hierarchical file systems, relational database tables, logging frameworks, configuration managers, or content indexers.

That sounds like a "general-purpose database", unless there's something that disqualifies Didget from being that. If it's a database, you're probably competing with something closer to the free and open-source SQLite than you are the free and open-source Postgres. This can be done (see rqlite), but in any case it seems like being free and open-source would be necessary (although not sufficient) for people to consider it.

> I tried all the usual tricks to speed it up.

I don't know what "usual tricks" means (maybe you have a link?), but I think it would add some credence to performance claims to specify what you're doing.
> I’ve only ever understood dogfooding to mean that you use your own product to find the bugs, improve the workflow, and encourage feature suggestions.

I've only ever understood dogfooding to mean this as well, but I like GP's point. If you're forcing yourself to use the product to find bugs instead of using the product because it's a great product, then you have problems.
It seems to me it is really good at writing. I would think it could replace the profession of techincal writing for the most part, it could help you write emails, (bring back clippy MS you cowards), it could be used as a frontend to an FAQ/self service help type system.
Thanks for the measured reply.

I hope what you're saying actually results in a transition with minimal violence. I would also like minimum interference from foreign powers, the US included.
Create marvelous content 10x faster with AI (writero.art)
Writero is an artificial intelligence trained assistant to write and create amazing, original and creative content and images 10X faster.(writero.art)
I did not. I teach at a community college. Having a Ph.D. probably would have hurt me had I gone into private industry as a programmer. So I have been told.
Imagine you are autocorrect, trying to find the most "correct sounding" answer to a the question "Who won the super bowl?"

What sounds more "correct" (i.e. what matches your training data better):

A: "Sorry, I can't answer that because that event has not happened yet."

B: "Team X won with Y points on the Nth of February 2023"

Probably B.

Which is one major problem with these models. They're great at repeating common patterns and updating those patterns with correct info. But not so great if you ask a question that has a common response pattern, but the true answer to your question does not follow that pattern.
Ay but come on, likening it to stock keeping is a bit disingenious. A company's perfectly entitled to keep track of their stock, and they don't need anything from me to do it.

The credit card companies are more like it but I opt out of that game too, by not using them. Their practices are well known to me.
That's insane! I think a good future indicator before joining any company is their hypergrowth ... avoid at all cost. Smoke and mirrors. When you hear CEOs blathering on doubling, tripling etc .. headcount ... run ...
> Affordable housing would cease to exist.

Because the guy you bought it from would have torn down the valuable house and then the kit would be left empty forever?

That makes no sense. The unit would exist either way.
Sorry, but I'm only willing to continue this conversation with a true Scotsmen.
That's very interesting. I've been using whisper via pip also but I'm surprised you haven't sought to optimize whisper at all?

I've been looking at using compilation in torch but not successful yet as otherwise it can take awhile to run.
https://pytorch.org/tutorials/intermediate/torch_compile_tut...
I doubt there is a single team in the world right now that would be capable of recreating ChatGPT from scratch using their own model.

Why not? Lack of knowhow or lack or resources? If say Baidu decided to spend a billion dollars on this problem, don't you think they have the skills and resources to quickly catch up.
Show HN: Generate User Interface Components with GPT-3
I’m building an experimental tool that can generate a UI component from a high-level text description, i.e. “Design a card for viewing goals in a goal tracking application”.

Basically, stable diffusion but for user interface components instead of images.

This tool is at best a proof of concept. It currently only generates a single type of component (small cards that have basic info about an object), but the goal is to be able to design entire applications (either in one fell swoop or by piecing together components that the tool generates).

The components it generates can be exported as react code. You can also have it modify an existing design. The tool isn't useful yet but it's somewhat fun to play around with.

Having it generate a component rather than an entire screen made the problem easier but I'm not sure if there are any users that this would appeal to. I could see it appealing to developers who lack design and CSS skills and want to quickly build a decent looking frontend for their app.

Looking forward to hearing what you guys think of this project and the generative AI for UI space in general. If you're interested in collaborating on a startup or open-source project in this space, email designhat dot ai at gmail dot com
This is the worldview of all apl developers.
Surprised anyone is getting excited about these mistakes at all. Expecting them to be fully accurate is simply not realistic

The fact that they’re producing anything coherent at all is a feat
Journalist != newspaper.
Maps directions, travel planning, etc will finally account for "happiness" and not just fastest/cheapest/shortest/etc path. You'll give it feedback about why you preferred a given route and then it'll learn. Food, wine etc recommendations will similarly improve, as they match words found in descriptions and reviews, with your feedback.
We just rolled out Lago billing in Rivet yesterday. Lago is very well designed and the team is incredibly helpful!
It's often the case that this happens, because building/fire codes always balance cost as a part of the decision whether or not to require something... sometimes cheap things don't help much but we do them anyway because they're cheap. Sometimes expensive things would help a lot but we don't do them because it's prohibitively expensive.
Seems like if you can just will an international governing body into existence, there isn't even any need for subsidiary cloak-and-dagger.
These models are very impressive, but the issue (imo) is that lay people without an ML background see how plausibly-human the output is and infer that there must be some plausibly-human intelligence behind it that has some plausibly-human learning mechanism -- if your new hire at work made the kinds of mistakes that ChatGPT does, you'd expect them to be up to speed in a couple of weeks. The issue is that ChatGPT really isn't human-like, and removing inaccurate output isn't just a question of correcting it a few times -- it's learning process is truly different and it doesn't understand things how we do.
If it flops on certain information and the UI is. It properly adjusted to limit certain things is does poorly, it will back fire on MS
Totally agree. Thats an issue thats also been occurring in the UK. Remember WannaCry in 2017? Probably caused by Torries defunding it.

Lots of downsides to socialized healthcare with incompetent govs.
But all those profitable activities aren't being proposed or offered by the issuer, and require additional affirmative actions and effort by the holder, taking on additional risk and interactions with third party entities. Just because tools can be used for profitable ends doesn't make tools themselves security offerings.
UK names new internet regulator
Companies generally only make detailed plans a year ahead based on data from the prior year or two. Which works out most of the time and the times it doesn't you can't really do anything about like financial crisis and covid boost then normalization.

If you were buying in the stock market early and didn't sell (or held on to vested stock), you probably felt the same and wouldn't have predicted such a precipitous crash. It looks obvious now but if you said mid-2022 that 2023 growth is gonna be lower than even pre-covid you get funny looks. Then the unplanned growth strains support, customers are complaining, your competitors are doing well too and are going to keep R&D expense ratios, so you do the same to stop your product falling behind. Investors are high on the bubble, you can spend money with much less scrutiny
What the hype machine still doesn't understand is that it's a language model, not a knowledge model.

It is optimized to generate information that looks as much like language as possible, not knowledge. It may sometimes regurgitate knowledge if it is simple or well trodden enough knowledge, or if language trivially models that knowledge.

But if that knowledge gets more complex and experiential, it will just generate words without attachment to meaning or truth, because fundamentally it only knows how to generate language, and it doesn't know how to say "I don't know that" or "I don't understand that".
Worse probably means something like "accidents per mile".

Edit: was curious, so I did the math. The standard unit seems to be 'crashes per 100 million miles' so according to the Tesla safety report (only source on Autopilot safety I could find easily) that works out to [0]: one accident for every 4.41 million miles driven = 22.7 accidents per 100 million miles.

Without autopilot, the AAA foundation (again, easily available source, feel free to find a better one, this is from 2014) [1] says that our best drivers are in the 60-69 age range, and have 241 accidents per 100 million miles. Our worst drivers are our younger teens (duh) with 1432 crashes per 100 million miles.

So unless you can find better data that contradicts this, Autopilot seems like a net benefit.

[0] https://insideevs.com/news/537818/tesla-autopilot-safety-rep...

[1] https://aaafoundation.org/rates-motor-vehicle-crashes-injuri...
> “you may also choose to disable the sharing of Device Analytics altogether”

I think Apple's concept of "sharing" means with other companies.
Well that’s a thing to say. Not what I actually said but absolutely a valid position. Everything has pros and cons and it’s absolutely valid to ask if the cons outweigh the pros. To deny that is just silly.
I only trust search engines to list vaguely relevant links. Then peruse those. Form your own opinion.

> collect different "schools of thought" and the reasoning behind them

The thing is, if an AI can accurately present the reasoning behind them, then it could also accurately present facts in the first place (and not present fabulations). But we don’t seem to be very close to that capability. Which means you couldn’t trust the presented reasoning either, or that the listed schools of thought actually exist and aren’t missing a relevant one.
This is the correct take, but it is funny, because everyone is always lamenting the "quarterly focus" of the stock market but the reality is bloated companies are given huge runways in public markets.
I agree completely with the first part of your post. However, I think even performing these language games should definitely be considered AI. In fact, understanding natural language queries was considered for decades a much more difficult problem than mathematical reasoning. Issues aside, it's clear to me we are closer to solving it than we ever have been.
Genuine question: Are you characterizing Tom Scott as a gatekeeper here, or am I misinterpreting your comment? I am not sure what your intention is here and would appreciate clarification.
It becomes difficult to defend police forces when entire police forces are okay with this type of behavior.

It means the officers are not thinking for themselves, and that this type of thing is (can be) policy in some locations, which is not okay by me. I don't want to pay guys to do this.
I love this idea. I wondered why this wasn't leveraged by cryptocurrency miners. You could supplement and subsidize heat all winter for any apartment building or office.
That's a lot if you only open a few links a month.

It also doesn't at all help people like me who don't use any major news sites at all, but are only redirected to specific articles there through links on platforms like this one.

These services depend on using their aggregator, not any you want.
Solid API as well.
That title is straight out of a cyberpunk novel.
It's here FYI https://gitlab.com/magnolia1234/bypass-paywalls-clean-filter...
I even remember the 1998 'crash'. I am convinced we are heading there again, but in much slower motion. It may never hit rock bottom, but we are definitely not in a bullish market at this point.
+1 appreciate the effort, but just get to the point thanks...
I think this government does not have problem with criticism, but opposition is doing very bad job of criticism itself. It fails to present proper solution/ better approach on things that matters to national security, policy and way forward for country and people dont appreciate such cynical thinking anymore. strawman arguments on high moral ground will not work after a while.

As for BBC "The Modi Question", comes from wrong place itself. India has left that issue long ago, but internal and external forces who doesn't much on Modi in politics plays same card again and again.

Few videos I found to their narrative -
https://www.youtube.com/watch?v=bkVQ4RNxBB4

Truth about Godhra 2002 riot
https://www.youtube.com/watch?v=Dcn4Yv-dR-Q
https://www.youtube.com/watch?v=eUI1Cc0gkcU

PS: Author AKASH BANERJEE is well know youtuber who extreme leftist. India's are not interested in people who cant represent them anymore. We lack centrist government / opposition.
(Lago co-founder here) Thanks for your message Louis, we always welcome genuine and actionable feedback and appreciate the time you invested into writing an example!
> Russia are approaching the end of their existence as a nation

Everything seems to be pointing to that, I really hope you are right.

> regarding the use of nuclear weapons

If they do that they are done. Also I'm not sure if they still have any working nukes. The maintenance is too expensive and I've seen how the things really are in russian science and aerospace industry. I would say that I would be surprised if the situation with nuclear crap is better.
That's a good argument for why they should be allowed to put those things on the website or install those types of technologies. But it's not a good argument for why I shouldn't be allowed to do whatever I want with my computer.
I don't like the telemetry. I don't think they should add it, I will be disabling it, and recommending the rest of my team disable it.

However

> Introducing telemetry is not (contrary to the claims of Google) naturally part of open source development.

Google is not wrong here. Many large "open source" projects include either forced-choice or opt-out telemetry. This includes "consumer" software like Ubuntu and Firefox, development tools like Arduino, and "backend" software like OPA. It's reasonable not to like it, but it's not reasonable to single out Google here. It is a long-term cost of turning so much development over to corporations and foundations.