skysight-inc/HackerNews huggingface dataset:
Out of curiosity, looking at the cheapest price for a H100 that I could find online.

Lambda Reserved Cloud [1] starts at $1.89 per H100 per hour.

It could be possible to get the cost down to a lower amount:

$1.89 * 96GPUs * 24hours * 14days = ~$61k

1 - https://lambdalabs.com/deep-learning/servers/hyperplane
> the copyright system creates a (relatively) shared understanding between creators and consumers that, by default, content cannot be redistributed, remixed, adapted or built upon without creators' consent. This shared understanding made it possible for a lot of content to be openly distributed on the Web.

That is not remotely a shared understanding, is wrong, and has nothing to do with making it possible for a lot of content to be openly distributed on the web. Content is distributed quite widely without concern for copyright.

> A number of AI systems combine (1) automated large-scale consumption of Web content, and (2) production at scale of content, in ways that do not recognize or otherwise compensate content it was trained from.

> While some of these tensions are not new (as discussed below), systems based on Machine Learning are poised to upend the existing balance. Unless a new sustainable equilibrium is found, this exposes the Web to the following undesirable outcomes:

> Significantly less open distributed content (which would likely have a disproportionate impact on the less wealthy part of the population)

That's even more ridiculous. The wealthy stand the most to gain from restricting the flow of information to channels which collect rent on behalf of their capital. It's the "less wealthy" who routinely find ways to distribute content outside of rent-seeking channels. It's the "less wealthy" who benefit the most from the commoditization of creative content via generative algorithms.

Quite frankly, I expected better from W3C.
It's sad now Newsweek has become news weak.
I just signed up for this genAI summit but the lack of social buzz and the profile of the organizers give me a strange feeling.

https://genaisummit.ai/#/

I'm afraid this is might be a fake conference created by AI. Am I crazy? I paid $500 for tickets. I almost signed up for the booth.

I'll have to start emailing speakers for confirmation because it's not passing the smell test.
That's probably true. Maybe there is a point to trade computational/energetic efficiency for attainability of a result. Let's see how this unfolds.
So you're thinking of expressions like "Winston said he had noticed a continued decrease in his suicidal ideation" (real example). I don't know if I'd agree that it's clear a rule-based system would be able to catch everything like this. Consider:

1a. (original) Winston said he had noticed a continued decrease in his suicidal ideation.

1b. (simplified) Winston noticed a decrease in his suicidal ideation.

2. Winston's suicidal ideation decreased.

3. There was a decrease in the suicidal ideation Winston felt.

4. Suicidal ideation decreased in the patient.

Many more syntactic repackagings of similar propositional content are possible, too. For perfect recall, rule-based systems need to grapple with this, and additionally, in a real setting you're probably getting predicted (rather than gold-standard) POS tags, relations, etc., adding additional noise.

My expectation (as someone who's mildly bearish on LLMs, btw) would be that if an LLM appears to be doing worse than a rule-based system then you probably haven't tried some low-hanging fruit yet such as adjusting prompting strategies, fine-tuning, using different pretraining data, etc.
“As low as 15%”

Great! That’s so much cheaper than the 0% you can get on other platforms.

This used to be acceptable when Apple was innovating and providing extra value, today it doesn’t fly.
I recall plenty of implementations turning into the same as a memory_order_acquire, which seems fine these days
I have the feeling that basically all current smart home products are either a disappointment in their limitations or useful but really time consuming.

The only smart appliances I got are Philips hue lights which are nice but well, after the initial discovery, I use them as classical light bulbs 99% of the time. I’ve found zero useful automation (not saying they don’t exists) and I can’t see why I would control lighting from my phone (at least not enough to justify spending hundreds into smart bulbs and smart switches).

Ultimately, I’m not against smart home but since each home is unique, by definition, those objects are only useful if the user is willing to invest enough time to tailor the configuration to be useful in his own unique house.

Oh I thought about ranting about my experience with Sonos speakers which are really nice speakers with great audio quality for the money and size and everything you’d want except the "smart" part you are forced to use with their terrible (and closed) software.
is the expectation that Zen 5 will be PCIe 6?
Automated lawn mowing is relatively mature at this point and works well, assuming you have a relatively flat lawn.

A one time purchase price of 20k would be acceptable. $20-30k per year is ridiculous. For that price you can hire a person to come and clean your toilet for 5 hours a day, every single day.
"I don't want a voice assistant, and never have."

"It's not the customer's job to know what they want" -- Steve Jobs
Funny, because I would pay twice the CC fee for credit card transactions to be as painless as crypto. I'd rather scan a barcode and wait two minutes, compared to typing my address, handing over my phone number, confirming my zip, waiting for my CC's TOTP to arrive. Only for it to still fail 5% of the time for who knows what reason.
Slope-intercept library design (2022)
In the lower left hand corner there is a "subscribe" button, and above that a "credits" counter.
So it sounds like you're saying that modern life is too complex to effectively navigate? There are many examples of rather simple people from humble beginnings navigating it successfully.

Your straightforward example consists of someone who consciously makes a short-term decision on the basis they won't be around to deal with the consequences. In your specific example, why should we externalize their risk? Isn't it theirs to take, and aren't the consequences theirs to own? If their assumption turns out to be wrong, don't they already have more than enough to be happy about?

You're basically suggesting we subsidize the short-term thinking of people who for whatever reason are not planning for their own future? What is the moral reason that entities them so such a subsidy?

I'm also speaking from lived experience. I was born into a single parent household of very poor recent immigrants. I'm also not a financial expert, but my thesis is you don't need to be to avoid falling into obvious debt traps.

> the left behind in the 2020

I am sorry about your brother. Do you think he was not personally, individually responsible for his decisions and actions? I've not met any employer who isn't clamouring for someone that will: 1) be sober 2) show up on time 3) work hard. Anyone who can do these three things can excel. There are countless instances of careers that span from entry level to executive. This is substantiated by research that shows "grit" as the key determining factor for economic success.

> I’ll kindly thank you to address the substantial points

Your thesis is that not all individuals have the same capacity to manage risk due to systemic inequalities or immediate crises. I agree with that. I simply disagree that this is a morally unacceptable status quo. I see society as a liberal ecosystem, where organisms are continually succeeding and failing. The authority required to mount a collective response to these inequalities is too susceptible to corruption, and represents injustice in its departure from liberalism. Not to mention that well-meaning interventions by federated authority have an abysmal track record.
Pretty sure you can get a domestic service to pop by at much lower than that. Biologics are still king.
> Or maybe I need to dive deeper into HomeAssistant...

This is the answer.

HomeAssistant is fantastic and has unified everything of mine into a single platform. Control mostly happens through Google and Apple/Homekit devices (other than hardware switches), and everything works pretty seamlessly.
Running Fava on NixOS
It would seem ideal to have the line-up area where cars are turned in, inspected and cleaned set up with a bunch of retractable charger leads in the ceiling, ala shop air. As soon as you pull up, the attendant pulls down a lead and plugs the car in. Bam.
It seems like the same economics of tweaking the size of the fee for returning a rental Tesla uncharged, which is a flat $35 fee ($25 for Hertz Gold Club members) [0] vs the much higher rental cost ~$60-200/day [1], then most customers will skip recharging and pay the fee; just like returning an ICE car without refuelling (or comparable to returning it 1-2hrs later than the agreed time). Then it's Hertz's business model's challenge to figure out how to incentivize/penalize their customers. (If you return it at 79% do you still pay the same fee as if 10%? This is harsher than the unfuelled ICE penalty).

If Hertz has a "morning/evening rush hour gap" between when uncharged EVs are returned vs when they're charged and cleaned and available again, then (just like surge pricing, or same-day standby offers that airlines make when oversold) maybe send individual customers $$ incentives the evening before to charge it or return it earlier.

And as for improving first-time customer experience of renting EVs, Hertz has an incentive to do better with steering them towards reserving a hotel/motel with L1/L2 chargers (give them a coupon for the price premium), or at least nearby ones. At least on their last night before returning. Or help them plan out which nights it'll need recharge, based on their itinerary, then factor that advice into suggested hotel booking.

And another idea: the Hertz app could set reminders the day before for "If you want to return your car at 8am charged, and you estimate the return trip will take 45min and 8% of battery, then you need to charge overnight, or else start charging by (say) 5am, to 88%".

I don't see any of this as a limitation of EVs, just figuring out how to incentivize behavior modification in rental customers, improve the app, teach customers how to plan for it, give coupons, do hotel partnerships etc. If the Hertz app won't, then a calendaring or driving-directions app could.

[0]: https://www.hertz.com/us/en/vehicles/tesla/faq/your-first-dr...

[1]: https://www.way.com/blog/how-much-to-rent-a-tesla/
I have absolutely checked those numbers, and I have written PCIe hardware cores and drivers before, as well as microbenchmarking CPUs pretty extensively.

I think you're mixing up a few things: CAS latency and total access latency of DRAM are not the same, and SSDs and generic PCIe devices are not the same. Most of SSD latency is in the SSD's firmware and accesses to the backing flash memory, not in the PCIe protocol itself - hence why the Intel Optane SSDs were super fast. Many NICs will advertise sub-microsecond round-trip time for example, and those are PCIe devices.

Most of DRAM access latency (and a decent chunk of access latency to low-latency PCIe devices) comes from the CPU's cache coherency network, queueing in the DRAM controllers, and opening of new rows. If you're thinking only of CAS latency, you are actually missing the vast majority of the latency involved in DRAM operations - it's the best-case scenario - you will only get the CAS latency if you are hitting an open row on an idle bus with a bank that is ready to accept an access.
Here is a recent HN discussion of an article that talks about this. https://news.ycombinator.com/item?id=39748537

Anecdotally, I literally "added knowledge" to a model via fine-tuning earlier today.

Fine tuning can do extremely well given a specific question and answer, the tuned model "knows" how to answer that question much more accurately.

I gave it a specific question, and a good answer as a fine tuning input. (Literally 2 data points as the input, 2 questions/answer sets.)

I asked it that question, and the tuned model blows the base model away, for answering that specific question.
It is a feature:

https://en.cppreference.com/w/cpp/utility/launder
The Lathe of Heaven is favorite science fiction book ever
There are a bunch of things in a house that are time consuming that would benefit from the help of robots. In fact it’s all the things that rich people can afford to hire someone to do:

- cooking

- cleaning

- taking care of kids

You can be sure that a ton of people are working on those.
IMO this debate about what "open" means itself obfuscates the issue significantly.

This is because if you just say "Well technically LLama 2 doesn't fit the traditional definition of open source!", it implies that there is some sort of significant caveot or difference that makes it significantly more restrictive than other open source projects.

This, of course, isn't true. Almost everyone can use LLama 2 for almost whatever they want. Yes, there are some restrictions, but the restrictions are so small that making a big deal over them incorrectly implies that there is some huge restriction, when there isn't.
I was in exactly your position a couple of months ago and have just got my first apps running this week!

Im a web developer so had a bit of experience with containers, cli and linux but only basic web related stuff.

Ill detail my journey and then let others tell you how wrong I am.

I bought a thinkcenter m715q for $200ish which was suggested as a good budget starting machine. There's lots of info about this on https://reddit.com/r/homelab , https://reddit.com/r/selfhosted and https://www.servethehome.com

I installed ubuntu and had a play around but then decided proxmox seemed like the way to go for what I wanted to so. So I watched a range of youtubers
https://www.youtube.com/@christianlempa
https://www.youtube.com/@TechnoTim
https://www.youtube.com/@CraftComputing

who all have different series on this and related topics.

Basically you burn the proxmox iso onto USB, plug it in, install it on the computer and its ready to go (obviously watch a few videos!). You need to access Proxmox from another computer on the same network through the IP address you get at the end of install. So if your router/gateway is say 198.168.0.1 you might set Proxmox as 198.168.0.99. Im still figuring the best practices on this out as obviously security is a major factor...

Actually you can use a single computer but need to do something like this
https://pve.proxmox.com/wiki/Developer_Workstations_with_Pro...

Which worked for me but its actually more convenient to use another comp as you want to be using your normal environment to use the services.

Once its up you browse to it, sign in and its ready to go. I got started by setting up plex by using this site:
https://tteck.github.io/Proxmox/
which gives you a single command to run an install script of whatever you want to install. It will install it as a LXC Container which is like Docker but less overhead.

Or you can create VMs and run docker in them. This is next weeks job for me.

Each container gets created as a new service with its own IP address on the network. To expose them externally creates security risks if you don't know what you are doing. So I chose to use Cloudflare Tunnels which was super easy but I use CF daily. Now i have a working Plex server at plex.<mydomain>.com and a Mattermost server at chat.<mydomain>.com !

Its super fun and you just nuke stuff if it doesnt work. Proxmox UI is easy to understand. My biggest issue was understanding how to connect external drives and share them with the containers permanently. So understanding mounting drives, permissions in linux in general and then in Proxmox
https://pve.proxmox.com/wiki/Linux_Container#_bind_mount_poi...

I have a massive amount to learn before I feel comfortable and secure. But totally worth the time spent so far and not as hard as expected once I decided to go down the Proxmox direction.
I do not know. But they do according the source I linked.
I understand the methods to address the fine-tuning and RAG issues but lack the time and possibly the technical skills to implement the solution. Fine-tuning can potentially dumb down a perfect model, and RAG has context limitations and may not cover all content. My thinking, we should vectorize the text and embed these vectors into all layers of the model at inference time. This approach would bypass the context size limitations and resource wastage associated with fine-tuning, as vectorization is fast. I believe this vectorization and embedding strategy is the solution.
edit: Okay, nvm, thank you for giving me permission to form opinions -- I regret attempting to dive down into "why people come to the idea [of shadiness]". Your position is understandable, best of luck.

Peace :)

---

original post: That's how posting on a forum works --- most people read, very few engage.

I've been reluctant to engage because I found some answers like "you can go look at the pricing in the HTML of the SPA" particularly uninviting.

Especially after I invested some time... trying to comprehend how much I should care about what you're building.

Thank you for all the other points -- and let me put aside any "something feels off" references/notes/comments.

(In my (very limited) life experience, when you ask for feedback... actually addressing it goes very well (in life, and also on HN). Additionally, introducing yourself as an actual person with a backstory seems to work.

In case you have never ran across it, may I recommend https://news.ycombinator.com/yli.html ?

My main question (and point of curiosity) remains:

You seem to love building BrowserBox. Why? How did you come across this?

(This is supposed to be an anthropocentric question, thereby best answered by anthropocentric terms -- not technological terms.)

GIVE US THE/A NARRATIVE.
It was tried and failed--admittedly a long time ago. However, today, I want to have a pretty good idea of the battery health of the battery in my car and avoid it randomly changing when I "fill up." Also most recharge locations are 24-hour with no one on staff so you'd drastically cut when and how an automated replacement could happen.
Always Cancel American Airlines Trips at the Last Minute – View from the Wing
A thousand times this. Hertz dumped a Polestar on me on a 6 week trip in Britain and it was absolutely ridiculous. No cash option anywhere. Most charging stations didn't even accept a credit card, and those that did required installing a badly written app that only works 20% of the time. Most apps/chargers only link your bank account, and I'm a fucking tourist, I don't have a bank account. And to top it all off, absolutely no charger anywhere gives out receipts, so I couldn't present the receipts/invoices for tax purposes.
I would pay like $5000 for a laundry folding robot. I just want a big washing-machine sized box where I dump my laundry at the top and slowly everything gets folded. That's 1 hour / week freed up.
There's a really nice series of episodes on the Extremities podcast about Pitcairn.
It's fascinating to me how much people discount their privacy.
So? That's focusing on what they know and not having time to notice the extra.
Different from making incorrect statements
> They were wrong.

As their goal was a language that would be very popular, and given that languages that heavily rely on GC have many times more users than languages that don't, it doesn't seem that they were wrong, at least not about the centrality of GC (although, "value types" and arrays-of-structs are coming to Java).

> SGCL never pause threads, so it can collect garbage more often and more efficiently.

I can't examine the algorithm right now and I couldn't find a paper describing it (so I can't tell you if it's one of the algorithms we've tried), but if you believe you have a more efficient GC than those in the JDK, feel free to plug it in and test. If you're right, you'll have many millions of users and the overall impact of that algorithm on the software industry would be much greater than it would as a C++ GC.
So... I have a gardener. He works two days a week doing all kinds of stuff.

The mowing itself (and trimming) takes 5% of his time, or even less.

Funny how people enjoy automating the part that you easily could do yourself without a massive time impact.
that failure is much more a leadership issue than a talent issue. Google was founded by PhD students and it shows. (I am one.) It's like a giant lab where things get prototyped and innovations are pushed, but where product ends up sidelined by bloated admin (how many levels are there and why does it feel like an MMORPG i.e World of Warcraft) and lack of clear capitalist vision (I'm actually anti-capitalist but even I can admit to this LOL). Honestly, it sounds exactly like a university. I used to think Google was slated to be the king of AI back when I starting out because they had ALL the talent (even OpenAI is its offshoot if you consider early employees and Ilya himself). I feel like it was so lateral that it was a loose federation of small tribes of smart people that live under the same banner, but not a tight organization where each team had its purpose within a giant mechanism. But as the saying goes too many cooks spoil the broth.

Apple is WAY different internally. For all its dreariness and corpo atmosphere (not allowed to talk to each other, teams siloed and laser focused on shipping a specific product) they have much clearer vision of what will sell and what not, usual company missteps (AR glasses) notwithstanding.
Maybe before you get too boggled, consider that the original article is about a scientific instrument designed to be attached to a telescope. The aperture and focal length given in the other source are properties of the telescope, not the instrument.

It's not uncommon to discuss CCD cameras for large telescopes without making any mention of the focal length or aperture of the telescope. See, for example: https://www.eso.org/public/teles-instr/lasilla/ntt/susi2/

Here's a page for another imaging device which lists the aperture and f-number of the telescope—and then gives a separate f-number for the instrument, without stating the instrument's aperture:
https://www.eso.org/sci/facilities/lasilla/instruments/wfi/o...

So I don't think the LSST media department dropped the ball on this one. The numbers (focal length and aperture), which you understandably think of as being essential info for any camera, just aren't as relevant here, partly because comparison with other options isn't in the forefront of the scientists minds (the camera is totally bespoke and there are many ways in which it is tailored to the telescope, which constrain its design, including in those two respects).

Focal length and aperture of the LSST camera aren't mentioned here, either https://www.lsst.org/about/camera