skysight-inc/HackerNews huggingface dataset:
> supply and demand works on the final price, not on "price before tax"

That's correct.

> So the tax level is irrelevant to the value of the market price, if you believe in supply & demand as the price setting mechanism.

Taxes raise the price, which reduces demand. If the prices don't rise, then the margins decrease, which reduces the incentive for the business owners to continue.

> doesn't make you a low margin business

It makes you a lower margin business. It reduces the margins on all the businesses, and the marginal (!) ones are no longer viable, and a new set of businesses become at the edge.
I really dislike this as OpenAI has spent the past months signing sweetheart deals with any publisher willing to sell their content for training data.

It ties everything to their platform and returns a regurgitation of prioritized content without indicating any sort of sponsorship.

SEO will be replaced by cold hard cash, favors, and backroom deals
Perhaps no-one could answer my question in [0] because many (including me) knew OpenAI would release their own search engine; eventually in [0].

"Who can tell me how and why is Perplexity.ai is worth $1BN? How much revenue are they making vs the amount of money they are burning? What is the justification of this valuation?" [0]

At this point with this unsurprising announcement, Perplexity is worth <$50M.

[0] https://news.ycombinator.com/item?id=40313461
In an ESOP, employees typically own 100% of the stock.
It will be censored as is usual to be useless like GPT now :/
Moving the goal post of dumb search.
That comment was sarcastically saying the opposite of what you took it to mean—at least I believe so, based on the account's history.

Of course, it was still a bad HN comment and rightly flagged by users—but if it's evidence of anything, it's evidence that other HN commenters agree with you.

Please see https://news.ycombinator.com/item?id=41071782 and https://news.ycombinator.com/item?id=41071644 also. I've replied in each place you posted this because people often jump to wrong conclusions about the community and it's important not to do that.
Funny thing is, it wasn't even effective. Most of the decline was before the introduction of the one-child policy, and other countries, like South Korea, Taiwan, Singapore, and Hong Kong (which is a country for these purposes; it has a different government, it's a country) managed to make it fall lower, without such legal barriers. It was a failure on multiple levels.

See https://ourworldindata.org/fertility-rate.
IMO, Perplexity does absolutely shine in a kind of search for what other engines don't compete at all. But it's way worse than normal engines for most of the things I search.

Anyway, comparing it by speed isn't useful at all.
That's downright ironic.
Public transportation varies widely in the US. A few places have great subways and commuter rail, but most don't. A few places have reliable bus service that has enough capacity utilization to actually save pollution and money, but in a lot of cases bus service is supported only as a means of getting low wage workers to their jobs. In many many places on-demand rides are the only plausible thing that would reduce private car trips.
The author calls this out specifically:

> and this makes the whole analysis problematic, as we still don't know if this is actually a good difficulty indicator for how a human perceives the difficulty
That presumes you can only have 1 partition at a time. That is not the case. You can optimize for good behavior when you end up with 2 disconnected graphs. It’s absolutely the case that a graph with N nodes can end up with N separate groups. Conceptually, imagine a single switch that connects all of them together and that switch dies.

You can engineer cloud services to be resilient. AWS has done a great job of that in my personal experience. But worst cases can still happen.

If you have an algorithm that runs in n*log(n) most of the time but 2^n sometimes, it can still be super useful. You have to prepare for the bad case though. If you say it’s been running great so far and we don’t worry about it, fine, but that doesn’t mean it can’t still blow up when it’s most inconvenient. It only means it hasn’t yet.
Gradient descent is a search. Where does it say the search space has to be small?
Search engines for me is keyword based. I want to type "pizza <town> near <street>" or "<function> <library> <language>" and get sensible result. Anytime a search engines tries to interpret my query with something far semantically and ignoring my own keywords, it's a worse experience.
TypeScript was really really easy to get started with back in the day. It allows for incremental correctness, has good docs, and good tooling. On top of that a lot of beginner React tutorials started out with TypeScript, which onboarded a lot of new engineers to the TS ecosystem, and got them used to the niceties of TS (e.g. import syntax).
Shameless Google search clone
^ this. I had a similar feeling when I saw the landing page as I have been waiting for Sora to be available after it's "announced".
Hijacking copy paste in apps is pointless now that phone ocr on screenshots works so well to seemlessly reenable text selection and copy.
Lol more like, Perplexity has a terminal diagnosis.

Doing RAG using like.. prompt hacking and text embeddings + vector store when you have no access to the underlying model, nor ability to fine tune the generation for RAG, will fail. It will fail in an epic fashion compared to doing RAG the right way.

What do I mean by RAG the right way? The RAG term has been overloaded.

There's RAG that's just kind of bolted onto the LLM after it's been fine tuned for instruction following, and then there's RAG where the document/fact retrieval is a part of the LLM itself that is differentiated and optimized.

Almost everyone is doing the first "hacky" kind of RAG, but Meta published in 2020, the "correct" way to do RAG, where you include a neural retriever in the feedback loop.

Almost no one is doing this because it's more expensive (requires fine tuning the model), but will produce much better results than doing "bolted-on" RAG.

https://ai.meta.com/blog/retrieval-augmented-generation-stre...

Perplexity does not have access to any GPT model weights. It's unlikely they'll be able to compete on quality.

It's game over.
The Lego Boost set is quite a nice set. It comes with three servo's and a color/distance sensor. The scratch like programming tools are nice and accessible and not that limited. However you can also flash micropython on the controller with PyBricks. Then you can pair it with other Lego hubs and a remote over bluetooth.

This setup gives you pretty much all the possibilities of Mindstorms at a small fraction of the investment
Interesting. I was not aware of that level of spend from CA. There are a number of resources that get into, this one [1] from 'calmatters.org' agrees with you by saying essentially housing is too expensive (and goes a bit further to say that the housing that was built was also expensive itself). That resource gives 3 main resources, bad tracking of money spent & (2) and (3) are again really saying it's just too expensive to live in CA.

The 10B number is even low! It appears that CA spent 20B over the last 5 years [2], $42,000 per homeless person. [1]

The part I find really interesting, is the per-capita spend amount. California has a population of 39M, and spent 20B per five years, that is a $1000 per capita (per year) amount. In contrast, that number in Seattle is a meager $148, and across the lake from Seattle, in Bellevue that drops to $21 [3]

I'm really shocked at the per-capita spend difference. My impression was that in Seattle the policies don't work because there is no money behind it and an inadequate and broken shelter system. The data from CA - shows that money alone is not enough.

My takeaway, actual housing first, a well functioning shelter system do still seem to me to be biggest key to the problem. Clearly though, throwing money at the issue is not sufficient.

[1] https://calmatters.org/commentary/2023/07/something-clearly-...

[2] https://www.latimes.com/california/story/2024-04-09/state-au...

[3] https://www.seattletimes.com/seattle-news/homeless/does-seat...
This discussion is about the proposal to, by law, force all businesses to be workers cooperatives. That's not the liberal capitalism found in Nordic countries, it's communism.
Yeah it would suck if they decided to add search features into ChatGPT without a way to turn it off. There are lots of use cases for a language model on its own without all the extra noise. I really hope they keep them separate.
Yes, technology wise, I think it could have been done; once I left Sun/Oracle I stopped paying attention, so I can't speak to what else was done later.
35/50 moves
I wouldn't have noticed the slug if you hadn't mentioned it. Made my day, very appropriate ))
Regarding point B, how often do they prioritize worker welfare to the point that they do the equivalent of cutting through the branch they sat on?
How does that make any sense?

If increasing the price hasn't decreased the abuse, why would increasing it more decrease the abuse?
Open ai always surprises. They are yet to completely release some of the features announced an year ago, but still announced a production ready model last week.

Maybe this is the difference between anthropic and open ai.. Anthropic has sharp focus on improving their core product and open ai is spread out.
I'm not that trusting. I just think that if it came out that Alexa devices were recording outside of their wake word then it would do tremendous damage to the brand and they'd not want to risk it. I feel like the incentives are aligned in this case.

I don't consider data collection and targeting from data collected during the wake word to be spying.
The problem with the Google one is accuracy. It told people to eat rocks. OpenAI just needs to beat that.
>Tractors are slower than cars, why would you use them?
Interesting. So it seems that Gaia-X is a process that defines how to talk about discussing things that could be done without defining what those things could actually be or do. It is a meta-meta level. Hmmm... Let's discuss how to discuss things...
People get convinced in the heat of the moment that they want something, when if they had time to reflect/research/etc. they might very well conclude that their money is better spent elsewhere. Marketing in a capitalist system is highly motivated to make you think you want or need something more than you actually do.

One tactic that some people find helpful when they want to buy a discretionary item is to wait a few days/weeks, and make sure that it's not just a whim that they'd regret.
https://github.com/ItzCrazyKns/Perplexica
https://github.com/miurla/morphic

LLM frontends for search engines have been commoditized for a while now, this doesn't seem to add anything new (at least technologically)
They are not research focused anymore they are a product company now.
In an ESOP, stocks are not normally fungible and cannot be traded easily. Usually they are bought back post employment. In my case I was able to either get cash or have it put into a 401k.
The private company case is worse because now it's completely illiquid. This all strikes me as a rich person's idea of what poor people want. Someone making $15/hour wants the $15 not $10 + equity in a private company worth $5 which they cannot sell but gives them 1/1000 voting rights and maybe sometimes a 7 cent a quarter dividend subject to board approval and market whims.

Most workers are not sophisticated investors and I'd rather they put excess savings into broadly diversified index funds instead of low quality equity in whatever small business they happen to be working at.
Is a map without transit even a map? I still use Google Maps as my default for transit, but Citymapper is considerably more reliable and I've been trying to remember to use it more.
I recommend checking out SpinalHDL generally - I do a ton of this very same kind of work with these same chips (7 series, US+) and would never look back to Verilog!

AXI (and all memory-mapped bus protocol schemes) becomes very very pleasant. SV interfaces get you 5% of the way there, though!

Also - I was under the impression that S1000-2M is a higher-end material, not cost-optimized? (But not Rogers, of course.)
Again, a partition that leaves you with no quorum anywhere is like the cloud being down.
TutorialKit – Create interactive coding tutorials
Getting more richer context of the current web events and doing that in a faster way. The current website scrapping feature is too slow.
I've been using Perplexity for the past 3 months on a regular basis and it has replaced DDG for most use cases. It's really nice to have answers directly.

Product comparison/updates/features:

> What's the difference in speedo latex cap vs elastomeric?

> What's new in iOS 18 Beta 4?

Documentation (esp for non-mainstream tools):

> How do i find the sioyek db files? How do I move it to my local iCloud folder instead?

I'd assume SearchGPT's results might be better given the partnerships with publishers and creators vs Perplexity searching the internet. More importantly, Perplexity already did the work of finding Product-Market Fit for OpenAI.
What do you think of Nix/NixOS?
Google is so done

The already trash product could mabye compete with Perplexity, but it can't compete with the hype and user base openAI can conjure up
My condolences to OpenAI-dependent developers who just discovered their product was a feature.
How far back do you want to go? Even pre-privatization, there wasn't a "uniform strategy" - you had NSE, Inter-city, Provincial doing things up north, Scotrail in Scotland, not to mention the variety of PTEs who had their own schemes.
If anyone imagines that "Traditional, Christian" Europe was a nice place...
None of the above are brute force search.
Have we figured out a way to monetize AI-powered search yet? Presumably a product like this (or Perplexity) will ultimately be free, in which case they'll be forced to offer ads (bringing us back to Google's status quo) or perhaps worse, we'll have "product placement" in our AI-written results.
If it doesn't send you to the sites, what's the difference from just using ChatGPT?

My impression from the demo is it has a perplexity-like result, with the answer and references to where each part comes from.
>SEO will be replaced by cold hard cash, favors, and backroom deals

Maybe it's my pessimistic nature, but it's garbage either way to me - backroom deals in your scenario, or the SEO-gameified garbage we currently have.
I clearly would not. "Slow down your site" because information is super useful when you can't search it properly.
I truly miss working in software in the early 2000's. We were all using XP but it was all customized up the wazoo. Almost all of us had custom themes and icons and what not.

I ran a Mac at home, and had that customized as well, I forget the name of the app that would install custom themes/docks, but CandyBar would install custom icon sets.

Now days most people don't even bother to change their wallpaper. Live a little!
By its nature hard math problems do not have fast algorithmic solutions--you can only solve them by search or clever search. Mathematicians have heuristics on helping us decide intuitively what's going to work what can make progress. But in the end--there is only search
So glad to see that the CAP "theorem" is being recognized as a harmful selfish meme like Fielding's REST paper with a deadly seductive power against the overly pedantic.
That's a good point. I expect it is ultimately unenforceable though. I'm describing training a model for myself, not for sale or public consumption.
> need to hold companies accountable by very transparently disclosing those energy costs.

And if they do, then what? If it is "too high" do we delay research because we need to keep the world how it is for you? What about all the other problems others face that could be solved by doubling down on compute for AI research?
GG Google and I couldn't be more pleased.

It may not be this specific iteration that kills it, but a search product with AI (and without trash) is what will dethrone it.

I'm already using ChatGPT for ~30% of the queries I used to use Google for. I prefer hallucinations to ads, to be honest.

They were right to call Code Red when GPT came out, but their response to it has been extremely poor, even when they had all their cards in their hands. The quality of their products has been increasingly worse with time, everyone (but their own VPs) has been telling them that, it's hardly a secret.

They literally just have to go through the first two or three comments on this site (or Reddit or w/e) and fix the extremely obvious pain points people have with their products:

* Bring back verbatim search, make search *actually* work.

* If I search for "italian restaurants", I want a list of italian restaurants not a blog post with someone's opinion on why italian restaurants should hire more immigrants because of blah blah blah ... I want to *eat* something!

* The whole "vikings were black" episode ... wtf.

They kind of deserve it at this point.
DeCAF: "the OG foundation model in vision" (ICML 2024)
> Open ai always surprises.

Not this time. With this one, we were given notice about this as a rumor 3 months ago. [0]

[0] https://news.ycombinator.com/item?id=40313359
FIRST (https://www.firstinspires.org/) is a more structured program intended to be organized through schools or similar communities (homeschooling groups, 4H, etc.). I have more experience with the bigger robots intended for high schoolers, but they have programs all the way down to kindergarten.

Doing something similar at home is very possible, and if you are nearby an existing team or program they are usually more than happy to have a conversation with parents about how to get their kids started even if it doesn't mean joining the team.
The peer responses pretty much cover most reasons.
No, but it's very probable li2uR3ce bought things that were portrayed as being much better than they actually were. These days "profitable" for the seller rarely equates with "good value" for the buyer.
No. I would say it is more impressive than 50/50 there. (Source: I used to do math comps back in the day sorry it's not a great source)
Reporting on Tech with Kelsey Piper
Things I Learned from a Job Hunt for a Senior Engineering Role (2018)
I had the same question about touchstone from the same episode. I am becoming a Burke-ite after digging up the mention of 'The Trigger Effect' episode of the 70's 'Connections' from an HN Crowdstrike thread and am now binge-watching the entire first series. Amazing stuff.

I'd recently read 'The Ascent of Money', Ferguson, and was thinking there's more to be understood than what I found there. I've got 'Debt: The First 5000 Years', Graeber, in my queue, but am looking for other resources. Any ideas?
You're confusing domains of law.

* Contract law does not require arm's length. A contract for $1 is okay.

* Tax law may require arms length.

* I've never heard of arm's length in employment law, but there are laws which lead to what you describe (e.g. mandatory overtime pay, minimum wage, etc.). In some jurisdictions, there are limitations on how much an employer can change the terms of employment. If you hire me for $100k, and after I quit my old job a week into the new one, you give a pay cut to $80k and otherwise change the terms of the deal, that might not be okay.
Obvious errors make for good comedy and create obvious moments for reflection on what is actually being done. Subtle errors lead to fractured realities.
OpenAI, up to this point, has shown a willingness to outcompete some of the very companies that rely on their API to function, most famously with the release of GPTs, which had a quite severe impact on many "AI startups" [0]. In that way, they remind me of Apple with Sherlock way back in the early 2000s.

Despite this, I was doubtful that they'd go so far as to release a full-on search product due to their relationship with MSFT and reliance on Azure credits. I am happy to admit that I have long stopped any attempt to properly understand how OpenAI's corporate governance and company structure work, so I have a hard time following where this falls under and who would decide on this release, as well as how they interact with the part of OpenAI cooperating with MSFT and the Bing team, but I still have a hard time seeing how releasing a clear Bing competitor wouldn't cause some trouble for their entire suite of products and maybe even hinder future expansion by limiting the resources they can rely upon.

I am also interested in how this will impact search in https://chatgpt.com/, which, like everything in that product, has been inconsistent to a maddening extent. Started out barely usable, failing consistently, then got reliable whilst retaining the ability to search through multiple sites and handle more than one request in a row, then lost most of those capabilities and now barely works anymore, only looking at an incredibly limited, often barely fitting selection of results, whilst also needing to be manually invoked by asking for a search, rather than before when that was done automatically whenever it seemed sensible.

Like so many changes, e.g. the subjective reduction in GPT-4's abilities over time whilst retaining the model's name (not to mention the regressions they publicized in the name of efficiency, like the "turbo" variants), this is certainly done to reduce costs to the point of finally becoming financially viable at the $20,- price they charge for ChatGPT+. I might be in the minority, but I will continue to scream from the rooftops that I am more than willing to pay far more for a consistent, guaranteed, high-end LLM with web access (which sadly excludes Anthropic's efforts).

[0] I still dislike using that term for companies solely relying on third-party API's, a frontend and database solution, especially since I also detest calling LLM's "AI", but it's what this crop of companies have been termed and how they collected bucket loads of VC.
Also the financial institutions are making enough profit that they can afford to lose a little bit in the process of reconciliation. Consider how the 3.5% fees credit cards charge mean they can afford to eat a bit of fraud and actually can tolerate more fraud than a system which had lower fees could.
Dupe (+ more discussion at): https://news.ycombinator.com/item?id=41071639
A modern virtualization architecture can be found in the OSS pKVM L0 nested hypervisor for Android Virtualization Framework, which has some architectural overlap with HP/Bromium AX L0 + [Hyper-V | KVM | Xen] L1 + uXen L2 micro-VMs with copy-on-write memory.

A Bromium demo circa 2014 was a web browser where every tab was an isolated VM, and every HTTP request was an isolated VM. Hundreds of VMs could be launched in a couple of hundred milliseconds. Firecracker has some overlap.

> Lastly, this approach is almost certainly more expensive. Our instances sit idle for the most part and we pay EC2 a pretty penny for the privilege.

With many near-idle server VMs running identical code for each customer, there may be an opportunity to use copy-on-memory-write VMs with fast restore of unique memory state, using the techniques employed in live migration.

Xen/uXen/AX: https://www.platformsecuritysummit.com/2018/speaker/pratt/

pKVM: https://www.youtube.com/watch?v=9npebeVFbFw
Modern robotics with deep learning/imitation learning is surprisingly accessible. The low-cost robot arm I used in this project is very easy to 3D print and assemble: https://github.com/trzy/robot-arm

An iPhone app is used to teleoperate the arm and gather examples of an action. You then train the model and deploy it and the arm performs the actions based on current camera input and joint angle state.
Atlas: Manage your database schema as code