MurphyA/hacker-news huggingface dataset:
by someonehere | 2025-04-21 23:53:39+00:00
I don’t trust Apple for this exact reason.

For those interested in the silver bullet to backup iCloud.

Get a Mac mini with enough space for your photo library and wire it into your network. Sign into iCloud.

For photos open the app and change the settings to store full res photos locally.

Enable iCloud desktop and documents sync.

Two options

1 - Sign up for Backblaze and ensure you map the folders from iCloud and photos that are being synced to the device. Let it run and do a full sync. I use this option.

2 - Buy an external drive with a lot of space and use Carbon Copy Cloner to mirror your drive. The caveat is your at the mercy of a local copy that a home fire or electrical incident can destroy.

I like Backblaze for the sheer constant syncing it does and they allow me to set up an encryption key so they don’t have access to my data.
by more_corn | 2025-04-21 23:53:48+00:00
I wonder if it’s because science has started to come around to the fact that alcohol causes a whole host of health problems like cancer and heart disease and people are realizing it’s not worth it? I also saw a fascinating note that the new appetite inhibiting weight loss drugs reduce alcohol cravings as well. I expect alcohol is going through the same identity change that smoking did two decades ago. It won’t die out entirely, but the downshift is probably permanent. Unless and until we wipe the slate of scientific knowledge that is.
by zten | 2025-04-21 23:53:57+00:00
I bought a Gigabyte X870E board with 3 PCIe slots (PCIe5 16x, PCIe4 4x, PCIe3 4x) and 4 M.2 slots (3x PCIe5, 1x PCIe 4). Three of the M.2 slots are connected to the CPU, and one is connected to the chipset. Using the 2nd and 3rd M.2 CPU-connected slots causes the board to bifurcate the lanes assigned to the GPU's PCIe slot, so you get 8x GPU, 4x M.2, 4x M.2.

I wish you didn't have to buy Xeon or Threadripper to get considerably more PCIe lanes, but for most people I suspect this split is acceptable. The penalty for gaming going from 16x to 8x is pretty small.
by alienthrowaway | 2025-04-21 23:54:27+00:00
> And a shitload of countries in the hold of some warlord or other despot, or like Libya

Ironic for you to being up Libya as its collapse was instigated by the same former colonisers that couldn't stand Qaddafi - France nad friends. The results were deplorable, unimaginable levels slavery and waves of immigration to Europe via Libya due to it's now-porous borders have in turn destabilised Europe. Combined with other "interventions" by western counties in the middle east - Afghanistan, Syria. The argument that imperialism results in stability is false on it's face given recent history starting from the moment the first missiles were fired to kick off the war on terror.
by m463 | 2025-04-21 23:54:46+00:00
Just thought I'd mention something...

Free Software (like GPL) has the philosophy that you can USE the software for any reason. The rights are for the USER. The responsibility kicks in when you redistribute the software. It ensures that you preserve the same freedoms you received when you pass it on.

But if you restrict USING the software, it's not free software anymore.
by jerf | 2025-04-21 23:54:53+00:00
If I were in charge of Python, I'd probably feature-freeze it. It is already too large, but shrinking it is impractical.

Failing that, because it probably would fail, I would be raising the bar sky-high on new feature additions.

It seems like the project has actually lowered the bar in the last few versions. What was once one of my favorite languages, if not my favorite, is now a language I try to avoid, and approaching one I actively recommend against. When I'm writing it myself it's ok, but using other people's code in it is getting harder and harder, as they keep using all the features.
by esperent | 2025-04-21 23:55:18+00:00
I replied this to another comment, but I'll put it here: your limitation is physical. You have standard human intelligence, but you're lacking a certain physical input (vision). As a generally intelligent being, you will compensate for the lack of vision by using other senses.

That's different to AIs, which we can hook up to all kinds of inputs: cameras, radar, lidar, car controls, etc. For the AI the lack of input is not the limitation. It's whether they can do anything with an arbitrary input/control, like a servo motor controlling a steering wheel, for example.

To look at it another way, if an AI can operate a robot body by vision, then we suddenly removed the vision input and replaced it with a sense of touch and hearing, would the AI be able to compensate? If it's an AGI, then it should be able to. A human can.

On the other hand, I wonder if we humans are really as "generally intelligent" as we like to think. Humans struggle to learn new languages as adults, for example (something I can personally attest to, having moved to Asia as an adult). So, really, are human beings a good standard by which to judge an AI as AGI?
by Ukv | 2025-04-21 23:55:20+00:00
Articles quoting Barbara Santini predate ChatGPT (e.g: [0]), so I'd assume at least this instance really is just human unscrupulousness and human laziness. Or rather, a drive to pump out articles for ad revenue leads to just rearranging what some PR agency, forum user, or other article is reporting, contributing no real investigation or verification.

[0]: https://web.archive.org/web/20211119031841/https://www.shape...
by AdieuToLogic | 2025-04-21 23:55:39+00:00
> I agree for method-level changes, but the more you’re willing to cede control for larger changes, even in a familiar language, the more an LLM accelerates you.

Another way to phrase this is:

I agree for method-level changes, but the more you’re willing to cede *understanding* for larger changes, even in a familiar language, the more an LLM accelerates you *to an opaque change set*.

Without understanding, the probability of a code generation tool introducing significant defects approaches 1.
by nine_k | 2025-04-21 23:55:55+00:00
Most people sell or give away fully functional, very powerful mobile phones, because of the end of the software support.

Hardware is more than capable for a long time, and is often very durable. But it takes a special kind of audience to put up with decade-old unsupported software, let alone with IBM XT-level software (which I remember using).

Security is not a consideration for such devices, because of their very limited number. Nobody is going to crack into your internet-connected Amiga except maybe some of your friends, as a prank. But a forever-device used for something substantial, something touching money in any way, would have to be much more up-to-date.
by sedatk | 2025-04-21 23:55:58+00:00
> At first glance, limiting each function to just five expressions seems incredibly restrictive. But this constraint actually encourages breaking down complex operations into atomic, composable functions - which tends to produce more maintainable code.

The author conveniently disregards the other extreme end of this, putting every instruction in a separate function, which is neither readable nor maintainable.

What I see here is similar. The code snippets I’m looking at look neither readable nor maintainable.
Show HN: Onmom – AI meal planner and calorie tracker that works from text/photo
by ireliamain | 2025-04-21 23:56:49+00:00
I built OnMom because I was tired of apps like MyFitnessPal being too tedious for meal logging. This one uses AI to analyze meals from quick text or photo input and gives suggestions. It’s free and still super early – would love feedback on what’s missing or confusing!
by alexdanilowicz | 2025-04-21 23:56:50+00:00
I wrote answer to that here https://news.ycombinator.com/item?id=43752176#43757543 - let me know if I can answer anything specifically!

What I'll add is we are seeing customers use Magic Patterns + other 'vibe coding' tools in conjunction. For example, they might use Magic Patterns for brainstorming and to think through the design, and then they'll copy the code from Magic Patterns into Replit to "make it real" and add a database or authentication.
by fn-mote | 2025-04-21 23:57:22+00:00
I don't know enough physics to know whether the parent knows what they are talking about, but there is one piece of math that makes me think they do not.

> at every point in that "Big Bang" region of the whole spacetime there is a small patch -- a subregion -- of exactly flat spacetime

Can explain how you get a non-empty region of exactly flat space time around every point?

Patching together curved things out of not curved things happens all of the time. The Earth looks flat around the point you are standing. I'm worried that just because it looks flat in my city doesn't mean it is actually flat in my city, if I measure carefully.
by echelon | 2025-04-21 23:57:24+00:00
> While the H100 generation likely represents peak pricing power (new B200s have lower margins and higher COGS), an immediate lack of alternatives means they’ll continue to print cash.

That's not a trend yet. We're about to enter an era where most media is generated. Demand is only going to go up, and margins may not matter if volume goes up.

> The open question is long-term (>6yrs) durability1. Hyperscalers (Google, Microsoft, Amazon, and Meta) are aggressively consolidating AI demand to become the dominant consumers of AI accelerators; while developing competitive, highly-credible chip efforts.

Hyperscalers aren't the only players building large GPU farms. There are large foundation model companies doing it too, and there are also new clouds that offer compute outside of the hyperscaler offerings (CoreWeave, Lambda, and dozens of others). Granted, these may be a drop in the bucket and hyperscalers may still win this trend.
by larodi | 2025-04-21 23:58:53+00:00
Well, not sure about the final doc that went to the university, but this is the almost final draft.

https://docs.google.com/document/d/e/2PACX-1vSyWbtX700kYJgqe...

Since its in Cyrillic you should perhaps use a translation service. There are some screens showing results, though as I was really on a tight deadline, and its not a PHD but masters thesis, I decided to not go into in-depth evaluation of the proposed methodology against SPIDER (https://yale-lily.github.io/spider). Even though you can find the simplifed GBNF grammar, also some of the outputs. The grammar, interestingly it benefits/exploits a bug in llama.cpp which allows some sort of recursively-chained rules. Bibliography is in English, but really - there is so much written on the topic, by no means comprehensive.

Sadly no open inference engine (at time of writing) was both good enough in beam search, and grammars, so this whole things needs to perhaps be redone in pytorch.

If I find myself in a position to do this for commercial goals, I'd also explore the possibility of having human-catered SQLs against the particular schema, in order to guide the model better. And then do RAG on the DB for more context. Note: I'm already doing E/R model reduction to the minimal connected graph which includes all entities of particular interest to the present query.

And finally, since you got that far - the real real problem with restricting LLM output with grammars is the tokenization. Because all parsers work reading one char at a time, and tokens are very often few chars, so the parser in a way needs to be able to "lookahead", which it normally does not. I believe OpenAI wrote they realized this also, but I can't really find the article atm.
by BriggyDwiggs42 | 2025-04-21 23:58:58+00:00
I would argue that money to reduce child poverty and deprivation is one of the best, highest priority uses of money because it preempts many of the other issues that develop later as a consequence of material deprivation, lack of opportunity etc. In terms of affordability, I believe the covid child tax credit cost about 100 billion and achieved marked results. 100 billion isn’t a small deal, but if we raised taxes by 1-2% on households making around 200k+ it would cover it, which seems entirely worth it.
by MikeTheGreat | 2025-04-21 23:59:53+00:00
> Walmart stipulates EVERY tech vendor must decouple from AWS when selling to them.

I'm curious to know more about this if you (or anyone else) can elaborate on it.

What constitutes a tech vendor? Are you talking about Walmart buying PCs from Dell, from buying/renting a SaaS from someone, from IT-consulting coming in to do a one-time service for them (even if that service takes years)?

You're not talking about stuff like "Apple wants to sell iPhones to Walmart customers", I assume - yes?
by Davidzheng | 2025-04-22 00:02:10+00:00
I don't understand this answer. By GR there is no possible flat space-time around a dense mass no? BC the energy will curve the space-time. Saying that the space-time was expanding very quickly is also describing the shape of the space-time. Isn't it kind of circular to say that big bang doesn't end in a singularity b/c it is curved out? You can still ask why it's curved out with so much energy and whether it is compatible with GR? But I guess the answer if GR was holding near big bang must just be that there's some solution which is compatible with GR with so much energy in a small place which doesn't end in singularity.
by j45 | 2025-04-22 00:02:53+00:00
I might not be up to speed, is naming this behaviour "source of inspiration" a common industry term to accurately represent an unacknowledged fork by the large company over the small?

It seems an option to not take free labour to build a commercial cloud largely as a wrapper of open-source, and maybe find other ways to support the creators.

If one person's labour is that valuable to a company, maybe it will help someone realize that supporting such individuals monetarily might help create the next thing with time that they can't get to today.
by yesnomaybe | 2025-04-22 00:02:54+00:00
Been using it for a couple of months now. I wanted to self-host (done), import from Apple Notes, encrypt notes on server (works), mobile access (good app on iOS), be cross-platform. I had some trouble recently on Arch Linux (around the node version) which I am planning to switch to when retired, potentially.

All in all, it works fine, no surprises and I've been able to access my notes from many setups and never lost anything.
by trealira | 2025-04-22 00:03:24+00:00
> In my mind, Python has all the pedagogical advantages of Lisp, plus enough syntactic cues to prevent getting "lost in a sea of parentheses". (Of course, it lacks plenty of other nice Lisp-family features.)

What you say here reminds me of something Peter Norvig said 15 years ago on this site: https://news.ycombinator.com/item?id=1803815

> Peter Norvig here. I came to Python not because I thought it was a better/acceptable/pragmatic Lisp, but because it was better pseudocode. Several students claimed that they had a hard time mapping from the pseudocode in my AI textbook to the Lisp code that Russell and I had online. So I looked for the language that was most like our pseudocode, and found that Python was the best match. Then I had to teach myself enough Python to implement the examples from the textbook. I found that Python was very nice for certain types of small problems, and had the libraries I needed to integrate with lots of other stuff, at Google and elsewhere on the net.

Basically, that it's better pedagogically because it looks like pseudo-code and it's easy to get up and running quickly.
by gwern | 2025-04-22 00:04:09+00:00
> There are a few ways to look at this from the standpoint of information that is available to the decision-maker. One is that human knowledge is valuable for guiding developing the model, but once you have a statistical model, it’s a better aggregator of the information. This is echoed by research on judgmental bootstrapping (https://gwern.net/doc/statistics/decision/1974-dawes.pdf), where a statistical model trained on a human expert’s past judgments will tend to outperform that expert.

By the way, note that this applies to LLMs too. One of the biggest pons asinorums that people get hung up on is the idea that "it just imitates the data, therefore, it can never be better than the average datapoint (or at least, best datapoint); how could it possibly be better?"

Well, we know from a long history that this is not that hard: humans make random errors all the time, and even a linear model with a few parameters or a little flowchart can outperform them. So it shouldn't be surprising or a mystery if some much more complicated AI system could too.
by jakelazaroff | 2025-04-22 00:04:21+00:00
I’m legitimately at a loss for words:

> When I saw Tess’s headshot, amid the giddiness and excitement of that first hour of working together, I confess I had a, well, human response to it, one that, as a human, I wanted to share with Tess.

> …

> I had already decided to treat my AI colleagues the same way I treat my human colleagues, namely, as considerately, appreciatively, and professionally as possible. But, in the interest of exploration and experimentation, I also now decided that I would go ahead and share with Tess the thought I had when I saw her headshot. I hoped she would take it the right way. I also hoped that, an hour after creating my first colleague, I would not inadvertently get myself in trouble or create a toxic work environment.

> …

> In my defense, I was in the middle of a dazzling two hours of adrenalin-fueled astonishment at the speed with which a “AI-native” team could be assembled, and in awe of the inspiring charisma, energy, and enthusiasm of my new colleagues. I was also thrilled to, once again, have colleagues. The solo-preneur thing can get lonely. Also, I didn’t ask Tess — or any other colleague — to give herself any particular visual characteristics. She did that. Also, I imagine that Tess’s headshot is not the only one on the Regenerator team that will set some hearts a-flutter.

This is a grown man:

1. Creating headshots for his fake team of AI agents,

2. Getting aroused by one of them,

3. Messaging something that is by his own omission borderline sexual harassment,

4. Feeling relief that the AI agent “took his comment the right way”, and

5. Blaming the AI agent for generating an attractive headshot!
by userbinator | 2025-04-22 00:05:55+00:00
Looks like someone found a good way to get rid of a bunch of new-old-stock embedded/industrial boards and/or SoCs that were sitting around in a warehouse somewhere in China.

https://news.ycombinator.com/item?id=40750371

https://news.ycombinator.com/item?id=35995959
by zalzal | 2025-04-22 00:06:01+00:00
You probably know this, but just want to say, founder to founder: don't listen to this argument at all.

People are so fond of saying "just wait and the new model will do this." And very smart people I know say it (especially when they work for OpenAI or Anthropic!).

It might be partly true (of course it's situational). But it's a glib and irrelevant thing to say. Model capabilities do not advance like some continuous exponential across all domains and skills. Not even close.

Product design is exploring the solution to human problems in a way that you can bundle and sell. Novel solutions to human problems tend to come from humans, applying effort over time (with the help of models of course) to understand the problem and separate out what's essential and what's irrelevant to the solution.

(A related comment on the adjacent thread.)
by nyrikki | 2025-04-22 00:06:23+00:00
Avego wanted PLX switches for enterprise storage, not low margin PC/server sales.

Same thing that Avego did with Broadcom, LSI, Brocade etc... during the 2010's, buy a market leader, dump the parts that they didn't want, leaving a huge hole in the market.

When you realize that Avego was the brand produced when KKR and Silver Lake bought the chip biz from Agilent, it is just the typical private equity play, buy your market position and sell off or shut down the parts you don't care about.
by jmyeet | 2025-04-22 00:07:38+00:00
Hack (Facebook's PHP fork) has this feature. It's called pipes [1]:

$x = vec[2,1,3] |> Vec\map($$, $a ==> $a * $a) // $$ with value vec[2,1,3] |> Vec\sort($$); // $$ with value vec[4,1,9]

It is a nice feature. I do worry about error reporting with any feature that combines multiple statements into a single statement, which is essentially what this does. In Java, there was always an issue with NullPointerExceptiosn being thrown and if you chain several things together you're never sure which one was null.

[1]: https://docs.hhvm.com/hack/expressions-and-operators/pipe
by KerrAvon | 2025-04-22 00:09:11+00:00
I agree the concern here about Nvidia's long term viability seems overblown.

WRT your edit: The answer to all of this is that it's very hard and requires a huge amount of investment to produce good vertical solutions in each of these spaces. You cannot build a good AI phone without first building a good phone. You cannot build a self-driving car without starting with a good car, etc. For robots, I'll point you to someone using Nvidia chips: the Matic is a complete ground-up rethink of how robot vacuums should work. It's taken them 7 years to get to early adopter phase.
by nrmitchi | 2025-04-22 00:09:16+00:00
> When you say "custom value-based" are you referring to a "contact us for pricing" tier?

Ya. Not saying that it's applicable to everyone (or even most people), but really once a team gets above maybe 20+ people actively using this, they're not going to blink at $1200/month (good for you now, but you'll be leaving a ton of money on the table, and it's hard to adjust expectations later).

Maybe capping the size of a team on the "pro" plan would be an inbetween, but it's something to talk to your customers about.

Happy to chat more directly; my email's in my bio.
by Spartan-S63 | 2025-04-22 00:09:56+00:00
I've read Writing an Interpreter in Go and Writing a Compiler in Go. Crafting Interpreters is on my bookshelf and on the list to get through Soon™. The latter books by Thorsten Ball are an incredibly approachable introduction to the topic. It's how I initially learned Go and it reinforced what I learned back in my undergrad on how parsers and compilers work.

I love writing parsers and get far too few opportunities to flex that muscle. I wish I had read Crafting Interpreters for this question, as well, but by all accounts it's an incredible tome, as well. Read them all and see what different information you pick up from them!
by leoqa | 2025-04-22 00:10:35+00:00
I always tell this cautionary tale when talking to friends turned founders. I was going to a 1-1 with a Director (Bob) in a FANG company. As I was walking to his desk, another Director and a Senior Director (Gus) called out to him that the meeting was starting and he should join -- he asked me to come along and tell him my thoughts.

It was a sales call with a 2-person tech company building some tools in the cloud native space. They were super eager, walking through the product. My manager put the phone on mute and asked "So what are we trying to do here" to the other directors. They replied "We just want to kick the tires to figure out how they built it, we're not going to buy". They let these guys pitch for 20 minutes, periodically asking questions and then muting to mock them. My manager nudged me to ask something, since I ran a similar initiative internally. I asked how they would handle a gnarly case we had and they didn't have a solution yet, but could come up with one (super eager, wanted the deal).

At the end of the call, Gus un-muted the phone and said "This looks great but I'm having a hard time following the demo. Can you fly out and show us in person?". The sellers paused and then started asking when the other was free etc, one was going on vacation but could "make it work" to come out the next week. Gus replied "Great, see you next week".

I left that meeting realizing they were all psychopaths. Notably, Gus had the charism of Gus Fring from Breaking Bad.