skysight-inc/HackerNews huggingface dataset:
For NFTs that are copies of other NFTs we go with the general idea that the oldest (first) similar result is likely the original. This is an area where the blockchain as a fundamental time stamped ledger is very useful.

In cases where an NFT is stolen from existing web content (happens A LOT) our version of the API (with auth) integrates search results from the Tineye API. These searches are relatively expensive so with the initial release we put them behind an API key. That may change.

In terms of copyright violations... We've talked to a lot of lawyers in the space and it breaks down into two broad categories:

1) Straight up infringement. This is anything with a (roughly) 94% or greater pixel match. In terms of copyright this is an open and shut case for infringement.

2) Some kind of derivative work... Whether a well intentioned remix of another work or a deliberate attempt to avoid detection or cause confusion we haven't yet received hard legal guidance on where this line falls algorithmically.

3) A new work that's visually similar. Again, not sure what the computer vision approach is here.

In any case it comes down to "What can you do about it?". First steps are making sure people don't buy it and creators are aware of it. Next steps (working on this!) are getting this content off NFT marketplaces. That can come either through cooperation with them or automatically serving DNCA take downs to content hosts (problematic with IPFS, etc).
I've only done them at one place over 1 year but they're easily among the worst things to come out of the Silicon Valley cargo-cult school of management.

The root problem is that what works for the front-page of the internet who have a firehose of money and millions of users probably doesn't work for a pre-PMF start-up or B2B product. Primarily there's insufficient 'pressure' in any metrics to derive any meaningful signal from any changes a small group of developers can make. Any metric you can derive is way too noisy and spread over sales, marketing and development.

Sure, Gmail can change the location of the Compose button and measure the change in emails started with high reliability, but when your feature has at most 5 users and takes 2 months to deliver the impact is far less clear.

I felt in the company using OKRs we had one C-level person who was incredibly enthusiastic about them but with only 10 developers we'd have been far better served by a unifying vision and shared product understanding.
GraalJS has ~99% support of the JS language features, as for GraalPython it's unclear to me what's missing but it should get feature parity in the next few years. It already support modern python versions so that's a good sign.
I read it

I don't hold to the extremes OSI does as to whether something fits their esoteric view of "open source", however
Well if you try out the GraphQL API its API gateway is Elixir! The fields themselves provide data from a multitude of services downstream, but the gateway unifies it and sits in front.

I hope you like product :)
http://altavista.digital.com

I honestly switched to google from alltheweb and altavista initially because of the easier name and muscle memory taking hold. To this day I believe Altavista was better when google first took off.
Unfortunately the fuzzy search thing is in a kind of feedback loop in terms of user expectation. Because of Google users are used to typing the wrong thing and getting the right answer. If I search for "how old is Roger Redford" Google tells me that Robert Redford was born in 1936 (it doesn't even display the "Did you mean...?" correction). And to be fair, in 99% of cases the person probably did mean Robert Redford.

But anyway, this is the behaviour I think people are being trained to expect from searches. I sometimes have to show new users our business systems (which manage residential property data) and it's seen as a drag that you have to have some level of precision when searching for anything.

It's like a spellchecker. As they've got better over time you can be less and less accurate with words you're not quite sure on and they still find the word you meant.
Taking Sim City 2000 into pieces
Kanmail – organise your inbox with kanban
It's kind of telling that "after 2015" (so 7 years) is considered a whole new generation of people in tech.
there is no need to "invest" in ethereum in order to use it. if you wish to send 1000 USDC to a friend in another country, you can buy that amount, send it to them, and then exit the ecosystem entirely.

if you want to buy an artist's work to support them, you can purchase some ETH, purchase the NFT, or just send them the ETH if you'd rather, and then hold no more ETH than you need to pay gas fees.

the idea that crypto requires constant investment is something that is pushed by laser eye btc bros but is not how these networks will be used in future.
And yet there are strong physiogenic correlations among the stereotypes of race. Whether they make enough difference to care about socially or politically is more of an aesthetic decision. ("I like your kind/I scorn your kind".) Mating/breeding ability is sort of a continental drift. Horses and donkeys can breed, as can lions and tigers. They are more strongly distinguished than Australian aboriginals and Swedes. Who knows how many generations it would take before we'd start to separate procreationally, if the "races" didn't like to share their genes around the edges of their territories. We forget we've had different species of human in the past.

The bugbear is probably that if brain structure or function is in any way also correlated with the other traits (not caused, just correlated), or things like adrenaline production that might influence temper, then the whole superiority/inferiority thing all of a sudden has the possibility of legs. We've learned that redheads have different pain sensitivities, for example.
> There's a pretty well-developed waste-stream sorting technical capability now, though the best time to disaggregate is prior to disposal (e.g., different recycling bins), or barring that, on collection (where much does happen).

True, and sorting capability is getting better every day. I was looking into building my own sorting robots a few years ago and found that they're already pretty much off-the-shelf now, eh?

I do like the idea of people paying me to give me raw materials.

> In practice, the economics of recycled material resale are poor (IMO a market dysfunction), and the effort is often not cost-effective. That's highly unfortunate.

I agree. Maybe carbon costs will make recycled materials more acceptable.

> Tip scavenging is also a well-established informal labour niche in low-wage societies. Again, with high negative externalities and societal costs. Again, unfortunate.

I've been there. I was homeless for a few years. It's insane what people throw away. And then they lock the dumpsters so you can't salvage it. Madness.

But I think you're talking more about the folks who basically live in the waste streams, like the families living in the Mexico City dump, or parts of rural China until they stopped importing waste?
Hey @lettergram, it's 80.9% off peak! BUY BUY BUY!
I agree when compared to BT mics. They suck, in general. But compared to a decent (~50€) wired headset, they lose, hands down. You can also find really decent mics in second-hand stores. I got a 900€ mic for 20€ and just had to replace a few components.

Also, there’s nothing more annoying than hearing birds chirping when you’re trying to have a meeting with the volume turned all the way up to hear you talking. Buy a freakin headset.
Expecting nobody to ever name their project "textual" ever again is somewhat far-fetched. It's a common word.
I'm developing an alternative using SQLite, focused on JavaScript developers productivity.

https://javascriptdb.com
A lot of popular web frameworks have their take on how to arrive at the same goal which is to be able to create responsive feeling sites without writing a lot of JS and creating API backends.

Rails has Hotwire Turbo (which is technically back-end agnostic), Laravel has LiveWire, there's also HTMX which is a bit lower level and back-end agnostic. There's also Django Unicorn and Rails Stimulus Reflex.

All of these solutions let you return HTML back from your server and partially update areas of a page while writing no-to-little JS. They're all implemented differently but for a huge classification of web apps the implementation doesn't matter.

After jumping between Phoenix and Rails for quite some time (years), personally I find Hotwire Turbo's implementation and overall using it extremely intuitive, it "just works". It's been legit one of the best development experiences I've encountered. The best part about it is that it works with any back-end too, so you're not even limited to Rails. DHH and the Rails team never cease to amaze me in what they release to the world.
How does NixOS have so many packages?
have you actually benchmarked that? I think (someone please correct me if I'm way off here) the AMX instructions can hit ~2.8tflops (fp16) per co-processor and there are 2 on the 7-core M1. That's 5.6tflops vs the 4.6tflops the GPU can hit.
I'm interviewing right now, and thus far still plenty of interviews. It probably matters what kind of thing you're looking for: I mostly prefer small outfits but stay away from SF-style "venture-backed" setups in the first place. Turns out that outside of the "bubble" the economy is just churning along as usual. The position I'm most excited about now is just a small self-funded company making something useful and is making a profit (shock and horror).

That said, I did have a job offer that was rescinded at the last moment (which is why I'm out of a job, since I quit my previous position – probably not the smartest move but I really hated it there, so...) but that could just be coincidence as well.
> I've seen more than once recently an engineer saying that software solutions outside of the Serverless ecosystem (FaaS, DB, etc) is "the new legacy".

There's, as I see it, three different kinds of legacy: (1) code that has an inordinately costs to maintain and especially update to changing requirements because it lacks tests, documentation of existing business intent and/or design, or otherwise has lost institutional knowledge needed for nontrivial work, relying on the foggy memories of a high priesthood increasingly, over time, working through ritual without understanding, (2) software with deep and fundamental dependencies on platforms or external components that are no longer supported or no longer available, and (3) software which doesn't meet the current arbitrary tech platform decisions of the organization using it, but which has no fundamental problem preventing maintenance or use.

In lots of places, software that isn't adapted to a particular serverless architecture that the org has adopted is now the third type of legacy.

> And that cloud providers have solved all the pains that Erlang was supposed to address.

They haven't, though for some use cases, the parts of the stack Erlang would be most useful for implementing are the parts you are likely to just get from a cloud vendor (that's not true of all use cases, though.)

> Elixir sounds very compelling to me, but I worry that I might be going in a direction that's not where the industry is going.

Elixir is probably not the best bet if your concern is to direct the most focussed possible effort learning the things that are most likely to dominate the largest share ofnthr general software dev marketplace in the near future.
Speed is even more important there, anything over 25 mph should not be allowed in areas where people live. Of course that is not the case even in cities with a clear political will towards walkability the I Need To Drive Fast mentality often wins or at least is thw default
If Python doesn't depend on the C stack anymore (for most of its work), that's basically what you'll have for free.

Python's own stackframes are heap-allocated and chained (so each function has its own stack, in essence), so its use of a single unified allocation space for stack is already an implementation detail of the interpreter.
The developer could grey out the option, and (upon triggering) advise the user to install Amazon app store (or F-Droid) and reinstall the app from there for full functionality.

I'm sure that Google would (not) love that, but linking to a curated page of apps with enhanced functionality on alternate stores would be useful in the many ongoing antitrust actions against the Play store.
Hah, no not satire. Believe me - I felt like a 6yr old writing that sentence but with all of the shady and criminal activity in the space I wanted to be as straightforward and emphatic as possible that we aren't doing all of this as some sort of ruse to steal content.
I laughed and cried at that last sentence. 10/10
GitHub used to have something like grey on dark blue in its dark theme. And it is nearly unreadable.

Fortunately, they changed it to some sane color.

https://userstyles.org/style_screenshots/199552_after.png?r=...

I used to make user style just to make it readable. The top right is the original color of GitHub dark theme, and left bottom is the one I modified.

Someone set the color must forget how srgb works. #808080 is not half of the light level. It's about 1/3.
$10/m for a household, if this is as good as people are saying, would be a no-brainer subscription for me.

Not paying $10/m per person in my household, though. That'd be way too high.

[EDIT] Though I guess with no retained search history, we could just share one account anyway, so it doesn't matter. I was thinking about keeping those separate. Unless there are per-user settings that we might not all want to share.
I’ve learned that B2B SaaS are actually a way to scale your company, there aren’t enough really good people to go around, so think of it as outsourcing good skills
>/as Qonto is a 'neobank', we wanted to charge our customers directly in their wallet, through a ledger connected to our internal billing system. The team started from a duo of full-time engineers building a billing system (which is already a considerable investment), to currently a dedicated cross-functional team called 'pricing'.

Stored procedures (ca. Oracle v6) suddenly sound a walk in the park.
COBOL Devs probably earn more than React Devs.
A classic, from http://www.canonical.org/~kragen/tao-of-programming.html

> There was once a programmer who was attached to the court of the warlord of Wu. The warlord asked the programmer: ``Which is easier to design: an accounting package or an operating system?''

> ``An operating system,'' replied the programmer.

> The warlord uttered an exclamation of disbelief. ``Surely an accounting package is trivial next to the complexity of an operating system,'' he said.

> ``Not so,'' said the programmer, ``when designing an accounting package, the programmer operates as a mediator between people having different ideas: how it must operate, how its reports must appear, and how it must conform to the tax laws. By contrast, an operating system is not limited by outside appearances. When designing an operating system, the programmer seeks the simplest harmony between machine and ideas. This is why an operating system is easier to design.''

> The warlord of Wu nodded and smiled. ``That is all good and well, but which is easier to debug?''

> The programmer made no reply.
Oi, thank you for mentioning tini. I'm working on an init named tini, but it appears krallin got there first. Will have to think of a new name for mine.
It really depends on what one considers bad and good. People against immigration and helping the poor or workers in general are going to be seen as having bad intentions by many, people for bodily autonomy are going to be seen as having bad intentions by American Christians, Catholics and others, then we have a growing population who just support outright wars of invasion, genocide and ethnic cleansing, so...
The reddit hack for reviews succeeds at being a good source for "reviews", _because_ that's not what it's for. As soon as you create a search engine, someone will figure out how manipulate the results. Even reddit search results can be pretty spammy as I think some people have figured this out.
It's not unique, but it can be implemented in a way that is stable. E.g. SVD does this (but is quite overkill for the requirements).

It's highly relevant from an algebraic perspective, hence it's curious that it's not covered (at all) in the numeric literature.
Sure but users can decline them and never reboot
Nice, hope you'll like it!
Right! Thank you for the clarification.
There’s no way an enterprise can follow the consumer cadence for patches and updates. There are dozens if not hundreds of custom apps that could break
Godel’s incompleteness theorems are about formal systems.

A formal system can be thought of as an algorithm that takes a purported formal proof of some arithmetical statement (e.g. there is no largest twin prime) and returns true/false depending on whether the proof is correct. Call the algorithm a “proof checker” and say it “accepts” a statement if it returns true for some purported proof of the statement.

Godel’s first incompleteness theorem says that at least one of the following is true:

(1) There is some statement such that the checker accepts both the statement and the statement’s negation (e.g. the checker accepts both “2 + 2 = 4” and “2 + 2 ≠ 4”). This is called inconsistency.

(2) There is some true statement which the checker will not accept. This is called incompleteness.

Since Godel’s first incompleteness theorem is not a formal system, it does not apply to itself.
We have that. They’re called automatic stabilizers. There are a ton of them. For example, when people make more money, they pay a higher tax rate.
* What does USB-C do to the thickness of a phone that wouldn't be a problem in a tablet?

* How does the phone react to the differences USB-C offers - does faster charging heat the phone inexcusably?

* What happens to the phone if the USB-C male end breaks, arguably one of my favorite parts of Lightning. I can replace a cable much easier than I can replace a port on a phone.

* How will consumers react to changing the standard? A lot of people had a lot of 30-pin accessories.

To name a few.
The Fed Has a Recursion Problem
> The effective federal interest rate is 0.33% today. It was 2.4% before COVID...

I believe it is actually over double that and sits around 0.84

https://www.newyorkfed.org/markets/reference-rates/effr
> I can't see the future but I don't think it's going to be a bloodbath like the .com crash

I think you're right, but I also think that we'll see a more general downturn than the .com crash was. Most people outside of tech didn't feel the .com crash. I suspect we're in for a recession that's closer to the '08 crash which means it's going to take a while to come back.
Kalman filter solves the problem of getting accuracy from noisy or infrequent speed data. However with only acceleration data you still can have integration errors build up over time. IN other words, Kalman filter can't solve that the driving steadily at 50 and 55mph are effectively indistinguishable from acceleration data.

OTOH I'm skeptical that this method really solves it either
The spec does say that. You can put them in the interface, but you can't use the interface. Try it:

https://go.dev/play/p/9ptEd8zasML
Ship your machine as CI, problem solved /s
I understand they do something, but it’s probably 1/1000th the time spent as a developer.

I don’t have a specific number, but I’d prefer to just be charged for developers and have non-dev be free since their marginal cost is so low.

Same for “system accounts” and whatnot.

The key metric should be how many developers are using so there’s not much profit in adding more users other than it makes the devs happy.

If it has to be a non-zero amount then maybe $1/year or something. I have 25,000 people in my org so that’s still a lot of money even though there’s maybe only 100-200 actual devs.
I basically agree with you, except for your last sentence:

> The anarchy stuff is just marketing nonsense.

With this sentence you're implying that Wikipedians want the public to believe that Wikipedia is anarchic, but this is incorrect, see: https://en.wikipedia.org/wiki/Wikipedia:What_Wikipedia_is_no...

The link is a Wikipedia policy, so pretty much as official as it gets. The sad truth is that Wikipedia policies, guidelines, etc are mostly irrelevant to the functioning of Wikipedia.

The real de facto reality of how Wikipedia operates is that it's a complicated system with most decisions being made being local to only a single or a few articles. Furthermore, nothing is set in stone at Wikipedia, be it content or policy, they all change with the whims of the editors currently active at the relevant place and time. Which is also why policy is mostly powerless.
Or if you're going to learn something new. I do side projects when I want to learn websockets or something like that. Even when the project doesn't go anywhere, I got something out of it.
I've been using Brave Search for months now, much better than DDG. I had a Kagi invite sitting in my inbox, just signed up and set as default search.

Will give it a spin, but so far I like what I see.

EDIT: I immediately boosted all `github.com` and `reddit.com` results. That's a killer feature!

EDIT 2: better than Brave Search on mobile: there's a search button to enter a new search, and the textbox doesn't move around like Brave or Google do causing you to click on the first suggestion. I bloody hate that. Well done Kagi.
Language models as a solution to what problems?

Yes, you can easily use AutoModel.from_pretrained('bert-base-uncased') to convert some text into a vector of floats. What then?

What are the properties of downstream (aka actually useful) datasets that might make few-shot transfer difficult or easy? How much data do your users need to provide to get a useful classifier/tagger/etc. for their problem domain?

Why do seemingly-minor perturbations like typos or concating a few numbers result in major differences in representations, and how do you detect/test/mitigate this to ensure model behavior doesn't result weird downstream system behavior?

How do you train a dialog system to map 'I'm good, thanks' to 'no'? How do you train a sentiment classifier learn from contextual/pragmatic cues rather than purely lexical ones (example: 'I hate to say it but this product solves all my problems.' - positive or negative sentiment?)

How bad is the user experience of your Arabic-speaking customers compared to that of your English-speaking customers, and what can you do to measure this and fix it?

My linguistics background really helps me think through a lot of these 'applied' NLP problems. Knowing how to make matmuls fast on GPUs and knowing exactly how multihead self-attention works is definitely useful too, but that's only one piece of building systems with NLP components.
web3 is a scam and no one cares about it.

there now anybody else with this opinion won't need to comment it here
Sure, but from an algebraic (categorical) perspective, taking kernels, co-kernels and images are the most fundamental operations you can think of.

The question is: How do you compute them in an effective (avoiding full SVD) and stable way?
Hyper (YC S21) is hiring a senior back end engineer to build mobile avatar tools
It still doesn’t wrap in Safari mobile’s reader mode