skysight-inc/HackerNews huggingface dataset:
Congress isn't exactly keen on American social media companies, either. Are Facebook's profits really that important to them?

As far as I can tell it's a since, but delusional, attempt to defend national security. They don't like American data going to China, and Chinese algorithms coming for American eyeballs. Which, same, but that's not actually illegal. And it's not clear why they imagine it's dangerous, other than old men yelling ay clouds.

I suspect they're really just afraid that the kids are enjoying something. So it's more like hauling Twisted Sister before Congress to justify their (really innocuous and vapid) rebelliousness.
That does not match my experience or the general zeitgeist here on HN. IMO search quality has been declining due to increased invasiveness of ads and the wrong incentives for the company from the perspective of users.
I had to check your profile based on this comment -- looks like you're new and the HN hivemind hasn't assimilated you yet. Don't worry, you'll be in the loop soon enough if you stick around. However, be mindful that echo chambers are usually intolerant of facts (and sometimes, surprisingly, knowledge in general...this place can be a good jumping off point if you know how to do your own research, though).
Charged in Fraudulent Nursing Diploma Scheme (Jan 2023)
Really? I’ve been unable to find quality results for quite a few years now. It’s always results from Quora, Reddit, Facebook, YouTube and other giants.

In addition to that, I’ve been seeing legit scam websites rank in the first page since a year or so, and that’s not something I’ve come across only a few times.
I remember talking to this chap on the hercules-os380 mailing list. It used to be on Yahoo Groups but now it's here:

https://groups.io/g/Hercules-OS380

The list was once for people extending the FOSS Hercules emulator and the early IBM OS/360 source code (available, but not technically FOSS) to make an emulator for an updated mainframe that never existed but could have more memory than the real things. Sounds crazy but it has some practical uses: IBM did do this later, but its OSes from that era are not FOSS or free: they are very expensive.

The author of PDOS seemed to feel that PCs ought to have descended from miniaturised mainframes, not from a scaled-up Intel 8080. He wanted to write a Unix-like OS but for mainframes, and port it to the PC.

It was very strange and confusing, and he did not explain it well at all. He seemed not to know (or care) about a lot of the history of computers, OS development or anything else: he seemed to feel he knew better and didn't need to know.

In the end, the group was almost all his posts, and I left it, unable to cope with the torrent.
It really depends on the domain. The biggest problem I've noticed is they don't seem able to filter out those shitty auto-generated spam sites for comparisons or top 10 lists. So if you're searching for "X vs Y" or "best X in 2023" you'll get absolute dross.

For other kinds of queries it still works pretty well IMO.
>What makes you so sure diluting things doesn't make them stronger

Alcohol diluted with around 30% water makes it 'stronger' at killing bacteria...

I mean it's easy to say "just science that shit", and then forget we've been spending decades and billions of dollars doing just that.
Is this better than Cloudron.io?
IBM has been around for 111 years. It’s been on the downtrend since the late 70s early 80s. A big company like that can take a long time to disappear
Interesting and surprising comments. Anyone ever heard of AOL? Are they dead?

I think Google will likely go through similar path as Microsoft; such a tech powerhouse and cash cow for so long, innovation became eclipsed by profit optimization.

Microsoft turned it around a decade ago with a successful cloud pivot.

Google would have to fail fabulously for minimum of a decade before we could even begin to start claiming it’s terminal.
Read in a book a decade or two ago about an early attempt by Disney to speed up animation by creating a rudimentary AI for characters generated by CGI. Instead of creating each frame, they'd instruct the character to move from point A to point B on its own. The problem came in when they wanted the character to something unusual. Mickey Mouse would refuse to step off the edge of a cliff because it had been trained too deeply that when walking from A to B, you don't step off the path. Other odd personality quirks would pop up out of nowhere, such as Donald Duck randomly brutalizing his nephews for seemingly no reason. There was a reason somewhere in the nest of rules Donald Duck had been given, but no one could figure out how to make it stop.

All of that makes me wonder if writers directing the creation of an AI assisted story could run into something similar, where the AI refuses to have a character engage in a certain activity because the AI believes it's too out of character. Alerting you to behavior that would be out of character is one thing, but if the AI simply refuses to write or acknowledge edits that it deems inconsistent with the character, you've recreated the conflict between human writers with differing ideas. Being able to convince the AI of the reasons why the character would behave in such an uncharacteristic manner will become a new skill for writers.
It depends. I see a lot of folks ready to immediately accept whatever BS comes out of ChatGPT. ChatGPT could hallucinate an entire Wikipedia clone and some people wouldn’t question it. I see this trend accelerating, especially among people who are Google Ad’s target demographic.
Not everyone, but lots of people.
C is about right. Common Lisp is too big and Scheme is too small.

The language itself should be small but its standard library should be extensive, and largely written in itself. If the language's own implementors don't want to program in it neither do you.
Full interview: Geoffrey Hinton talks impact and potential of AI
Funny thing is almost everyone and their dog in Britain thinks BBC has been controlled by the Tories. I've not seen any evidence of CBC being overwhelmed by lefties either. People on the left size of the political spectrum constantly moan about CBC having too many conservative commentators and such.
Aye. Science is our super power, gifted us by evolution! Thankfully we’re in a time were we get to appreciate the marvels of nature.
I think the best thing we can do that doesn't involve learning AI from scratch is to learn at a high level how to integrate with LLMs - in various products - and how do they work (conceptually).
I wonder if a lot of those "injection" problems could be overcome by introducing a distinction between the different types of input and output already at the token level.

E.g. imagine that every token that an LLM inputs or outputs would be associated with a "color" or "channel", which corresponds to the token's source or destination:

- "red": tokens input by the user, i.e. the initial prompt and subsequent replies.

- "green": answers from the LLM to the user, i.e. everything the user sees as textual output on the screen.

- "blue": instructions from the LLM to a plugin: database queries, calculations, web requests, etc.

- "yellow": replies from the plugin back to the LLM.

- "purple": the initial system prompt.

The point is that each (word, color) combination constitutes a separate token; i.e. if your "root" token dictionary was as follows:

hello -> 0001;
world -> 0002;

then the "colorized" token dictionary would be the cross product of the root and each color combination:

hello (red) -> 0001;
hello (green) -> 0002;
...
world (red) -> 0006;
world (green) -> 0007;
...

likewise, because the model considers "hello (red)" and "hello (blue)" two different tokens, it also has two different sets of weights for those tokens and hopefully much less risk of confusing one kind of token with the other.

With some luck, you don't have to use 5 x the amount of compute and training data for training: You might be able to take an "ordinary" model, trained on non-colored tokens, then copy the weights four times and finetune the resulting "expanded" model on a colored corpus.

Likewise, because the model should only ever predict "green" or "blue" tokens, any output neuron that correspond only to "red", "yellow" or "purple" tokens can be removed from the model.
I find it interesting that we have a single word for creativity in the context of novel work.

These systems are incredible at generating novel art or poetry. But when it comes to problem solving, they struggle adapting to a novel problem.

With most humans, the ability to adapt to novelty seems to correlate with the ability to generate it.

I have two theories on this.

1. Perhaps these are two very different things. Novel art is closer to having a high performing random number function. Adapting to novel situations is closer to mathematical or strategic thinking.

2. Perhaps we are deeply fooling ourselves by building the greatest Chinese room machine imaginable - and in reality this machine does not build general understanding the same way we do. Douglas Hofstadter would be very disappointed with us if this is the case.

I still don't know which of these two seems more correct. Of course it might be both of them. I would like to see some more dedicated testing on the second point, as it does seem to be experimentally verifiable. For example, if this system truly has the ability to reason, it should be able to reason equally well in contexts where significant training data exists as well as contacts without any training data. We should be able to present the system with isomorphic problems across two different contexts and compare its performance to see if it has flat reasoning abilities.
Sentience is just the capacity to experience feelings and sensations. Goldfish can do it and AI can’t (so far).
Croquet on JavaScript: that rare announcement that's far bigger than it sounds
Unfortunately that is the internet now. The results and pages you are getting are poor because people stopped publishing websites. Now most of the internet forums and self curated pages are gone and information is in those silos
RIMs revenue was highest 3 years after the iPhone came out and the year Android came out.

Revenues are a trailing indicator and can hide underlying issues.
Wow, if only you had something to keep all that in one place.
I’m always asking ChatGPT about questions related to Smalltalk and Scheme and it does a terrible job with them. To be expected, but makes me wonder if it will ever be good enough for more niche programming languages and aspects of programming
Look into clep tests. They are the best kept secret.
I have used it to build travel itineraries and was tempted to write a travel app around that. Until I realized that some of the hotels and places it recommends do not actually exist or have existed in the past. It overconfidently also publishes broken booking links to these fake hotels. I am hoping that with chatGPT plugins, it would get better.
This nurse had a real nursing degree but...

https://www.themoviedb.org/movie/541134-the-good-nurse

Director Tobias Lindholm does an amazing job with Eddie Redmayne as the villain nurse. Redmayne is up there with Anthony Hopkins for all time greatest villain in this performance.

TLDW: if a hospital suspects a nurse might be killing patients but can't prove it, their best play is to just fire the nurse for some um-related reason and get them to go work somewhere else. The trouble is these "good nurses" always find another hospital willing to hire time and no one stops them.
They have posted record drops in profit in the last two or three Qs.

Also, remember Nokia and how fast they disappeared.
Who are we talkng about here? Bush, Clinton? Obama?
Alternatively, it's hyped up like crazy, the tech is inherently bad at information retrieval, and most of the people hyping it are trying to get in on a gold rush.

To be clear, I don't know the answer.
IBM is still “alive” in a walking dead zombie type of way.
Resistance to remote work contributed to Credit Suisse failure
With 3 minutes left I'd imagine there would be quite a bit of chaos. Do all the players know these rules? Do they understand why the opponents made an own goal? Have all of them figured out that an own goal is the optimal play now?

Would love to see a recording tho.
Am I misreading your comment or are you seriously stating that the tech industry doesn't lavish support on Democrats?
The core language should be small enough so that a programmer can remember all its features. This makes for efficient and quick programming. The rest should be in standard or community libraries. In my book over the last few years only Go and Lua meet the criteria.
Nowadays, I think Google search is just a big brand like Coke, Nike, etc. Google search is relatively new and should be time tested this decade.

I remember when Google search worked, I remember when Google Adwords attracted customers. All memories. It was better than Altavista and Yahoo Ads. We need a new leap. Don't care if it is about AI, GAI, or next algorithm(s). Startups were lazy in this space.
Something something china bad
Do submarines swim? No, but they are faster underwater than all swimmers. Therefore they are the best swimmers despite being unable to swim....

LLMs are producing human level reasoning in many domains, therefore they are the best at reasoning despite being unable to reason...

This whole debate hangs on the definition of "reasoning"
The most naive way you could do things could be to procedurally generate immense amounts of python code, then ask the model to predict whether the code will compile, whether it will crash, what its outputs will be given certain inputs, etc.
That’s.. so sad. I think you are right.

As much as I don’t want to accept this, it seems like it’s the new reality.
Physical objects cannot be shared. I can’t create a copy of my car. But ideas can and will be shared. Our societies try to criminalise it. That’s not right. It does not help humanity in making advances.

Imagine a world where every human has access to all ideas, papers, books, thoughts. That’ll empower every human being who has access to it.

We need to find other ways to compensate authors and creators.
Google Cloud is a solid product. It’s extremely unlikely to be bigger than Azure and AWS in the next 10 years but being the third biggest American cloud provider doesn’t sound bad at all.

YouTube is the biggest on the long videos segment and has no real competitor.

Google Maps is a great product too without big competition for end users.

Android is the main (and only?) alternative to iOS.

Then they have many descent products like Google Photos or Google Sheets. A lot of strong competition on this domain but again not being the biggest isn’t the end of the world.

Google Search will probably still keep plenty of users. Brand loyalty is strong. For example, a thousand of Norwegians bought the worst electric car of the market this year because it’s a Toyota. I’m sure such people will also happily keep using Google Search even when it’s only showing them garbage content full of ads.
GPT/Codex is truly the pandas master. Much of my productivity boost from using these tools has just been not having to sift through pandas docs or SO.
In practice probably not; with google results there is an increasing feeling that it's entirely bullshit designed to sell something or get clicks...

A response from ChatGPT seems somehow more honest, even though it's just an aggregate of the former.
I remember checking a few years ago and not finding a wiiware game developed by a tiny company I used to work for but it is available now :)
> It... really is not, though. It doesn't teach you macro assemblers as they exist in the modern world. It doesn't teach you interaction with the linker except in the simplest ways.

What does the processor/instruction set have to do with the available tooling?!

FYI back in the day much of Acorn's (BBC Micro = 6502) software was written using a very capable macro assembler (source: I worked there).
I'm sorry, but "wetawet" does not appear to be a recognized word in English or any other language I am aware of.

"awetawetawet" appears to be a nonsensical sequence of letters that does not form a coherent word or phrase. However, sometimes people use nonsensical words or phrases for creative or artistic purposes, or as a form of humor or wordplay.
The purpose of a company is not to invent technology. It’s to invent products that can make a profit. Google is very bad at producing profitable products outside of adTech.
I can resonate this. I used to be a huge Google Clown Platform fan but boy these folks displays a sense of condescending attitude to their users/customers.

Long story short. They don't give a shit of you and have zero empathy.

When the money from ads stop, it will be inevitable.

Context: https://news.ycombinator.com/item?id=35133917
$10B EUR per year? That's...unglaublich.
Remember that dude that wrote the vast majority of Scots wikipedia while not being able to speak Scots? Yeah, just waiting for the first LLM to make headlines by hallucinating it's own version of human history and publishing it to wikipedia.
That’s a big risk of ChatGPT.

Another huge risk is that they could change the perception of what is right and wrong in the long term if GPT gets accepted.
Out of curiosity, have you played around with ChatGPT-4 at all? While I would disagree with you on v3.5 alone, on v4 I _strongly_ disagree with that sentiment. Interacting with it is significantly better than modern search engines to get a mental model of something, slight mistakes and searching to validate claims and all.
True, op is a saas provider
> Intellectual property is an unnatural, made up construct

Ownership of land is an unnatural, made up construct. In contrast to intellectual creations, land is limited. Therefore, granting ownership of land to a person is literally robbing other people of this land.
Thanks for the clarification. It seems I misremembered it.
The U.S. political culture of 2-parties is the root cause of this. One party believes something so the other party disagrees as if by requirement. That concept is now society. Persons opposing political ideas make it impossible to agree.
The last few months shows they have no moat. I expect a slow decline lasting for years. Most people are slow to change but many techies have already switched over 50%+ to ChatGPT. Even if Bard eventually matches it, where's the moat? MS/OpenAI are willing to have lower margins because they're starting from zero, but Google will have to monetize hard, making their product worse.
I've tried using it a few times. Just now I asked it for a piano practice routine, since I am quite bad at structuring my practice. The suggestion seemed OK.

When I started probing it about specifics it got increasingly incorrect. As I asked about specific chords, voicings etc it was not able to be consistent between two short replies. Or even between sentences in a single reply! Here is one reply where I asked about suspended chords to see how it would fare:

> A chord consisting of A-C-D-E would be an Asus2(add9) chord. The "sus2" implies the absence of the third and the "add9"implies the addition of the ninth (B).

There's no B in that chord! And it mentions omitting the third even though it's there.

If I'm honest I've been continually disappointed with it. I see so many people excited and getting hype, but it falls flat for me every time. The same when I've tried it with coding problems.
Microsoft “turned it around” by extracting money out of its existing enterprise customer base. Apple had a base of fanatic customers even during its lowest point.

What does Google have?
I bought a couple of the Budget Bytes (https://shop.budgetbytes.com) meal plans a while back. They're not fantastic if you're outside of North America, but I was able to make them work. Haute cuisine it ain't, but if you're looking for a starting point I recommend them.

I also recommend starting to put your favourite recipes into a recipe app (I use Paprika, available on most platforms). Even add simple stuff like Yogurt and Fruit Breakfast. Then you can use the app's built-in meal planner and grocery list generator.
C# is getting "too big", IMO. (20+ years as my primary lang but doing a lot of TypeScript over the last 3)

There's really good new stuff like switch expressions and pattern matching.

But it feels like TypeScript is in a better place. I would love to see a "T#" - a trimmed down, more modern C# that makes certain tradeoffs and defaults.

Maybe that's F# (spent some time with it), but it diverges a bit too much from C family syntax.
Was it this game where as you progressed you could pimp up your throne room?
Have you ever seen the HBO show "Succession"? It's about a fake Rupert Murdoch character and a fake NewsCorp company and one of the plots is they get in trouble for big misconduct around abuse of workers and all sorts of bad stuff but they come up with the PR line "We're Listening." And do this big PR campaign to try and show they "get it" and they are hearing you. BUT at the same time one of their products is like an Alexa is actually listening to people's conversations creepily! Google is getting a reputation for being creepy and they _hate_ this.
> So mostly people writing high performance code

I would have assumed those people would be deliberately using another allocator with known/documented/guaranteed qualities instead of whatever ambient allocator was in play at the time.

That or avoid allocation as much as possible so that the choice of allocator effectively matters very little.

When would using optimizing for specifically glibc’s allocator be maximally beneficial?
There are a lot of posts of different prompts on some subreddits. I have seen people selling a live course on prompts to make titles for social media or blogs.

There is also some research to show giving examples and answers sets up ChatGPT to give better results in the style of examples.

But overall, I have not seen anything that covers a process that would work most of the time.
People have dealt with the audience question. As for the “non-sequitur” comment, as someone who has read similar material for other allocators, I can attest that every paragraph was in exactly the order it needed to be to understand the allocator design pretty quickly. It was actually really well structured. Allocators are hard to understand, not least because there are so many synonyms for both “some quantity of contiguous memory” and “collections of various types of those”. This piece came armed with diagrams, code examples that expose what’s happening behind the scenes, and walkthroughs of typical allocator executions at a very appropriate level of detail: enough to appreciate why it might work quite well. It didn’t compare to other designs but it was a worthy contribution of knowledge on its own.

(Edit, oh look at that, previously bookmarked 7 years ago.)
Not exactly portable
Here is a varied summery of different world records (and more) for deepest dive regardless of gender or equipment: https://www.divescotty.com/underwater-blog/deepest-dive-and-...
They have the tons of writers because writing isn't expensive in the grand scheme of things and small details and incremental improvements really matter. The tons of writers are actually a case there isn't a good use case for AI, because if it was all about saving money, a single writer would suffice...
Microsoft is a very talented copycat. With the added expertise (that all the other FAANG companies are sorely lacking) of how to sell to enterprise and small business users and lock them into their portfolio.
Government has murdered people for resources. I trust nestle more than I trust Feeble Joe.
Epic’s hyperrealistic MetaHumans can soon be animated using an iPhone
Ask HN: What’s the one book you would recommend your cofounder to read?
I have a potential cofounder who would complement me perfectly for creating a SaaS business. He is highly skilled, but went all his professional life with the career ladder and does not know much about the startup world. What book would you recommend them to read?