skysight-inc/HackerNews huggingface dataset:
Well, I suppose the more striking statement is that you can find two trees and two bushes such that there is a tree/bush pair that is closer related than the tree/tree pair.

Ginkgo biloba (Ginkgo/Maidenhair Tree) https://www.vdberk.com/trees/ginkgo-biloba-mascia/

Pinus strobus (White Pine) https://www.wildflower.org/plants/result.php?id_plant=PIST

Ephedra sinica (Chinese Ephedra/Ma Huang) https://www.inaturalist.org/taxa/135489-Ephedra-sinica

Juniperus horizontalis (Creeping Juniper) https://www.gardenia.net/plant/juniperus-horizontalis-blue-c...

I think visually the first two look alike and the last two look alike. I would phenotypically bucket them together. But the reality of genetic relation is different.
I'm sure this is valuable for you, but here is my point of view.

I've worked professionally in many languages like Perl, Python, Kotlin, C# and dabbled in Common Lisp, Prolog, Clojure, and other exotics one. Whenever I forgot the exact syntax (like the loop DSL in CL), I know that there is a specific page in the docs that details all of these information. So just a quick keyword in a search engine and I will find it.

So when I come back in a language I haven't used in a while, I've got a few browser tabs opened. But that only lasts for a few days until I get back in the grove.

So for your specific example, my primary choice would have been the IDE autocompletion, then the MDN documentation for the array type. Barring that, I would have some books on the language opened (if it were some language that I'm learning).
This is a optimization to prevent redundant calculations. If it was not performed the result would be the same, just served slightly slower.

The whitepaper you linked is a great one, I was all over it a few years back when we built our first models. It should be recommended reading for anyone interested in CS.
Yes, they should be able to deliver such email. Forwarding messages is absolutely vital for a lot of use-cases, starting from trivial one-to-one forwards but also mailing lists. DKIM signatures can also expire and length extension attacks are not possible unless both the signer and assessor are badly configured. In any case a theoretical replay is significantly less dangerous than unauthorised mail being sent because of SPF's inherit looseness.

In the end once the letter has left your server, it is _not_ up to you to decide what they do with it. We already have ARC to basically bypass SPF when DKIM is missing. Letters _will_ be forwarded.

SPF is obsolete and weak in other ways as well. A mere IP address is not the proper way to authenticate or authorize anything.
This is how it goes. Once one "undesirable" group has no civil rights at all, no one does. All that has to happen is for you to be accused of being an undersirable.
Yeah I mean, if you can reason about, say, how an automobile engine works, then you can reason about how a modern computer works too, right? If you can discuss the tradeoffs in various engine design parameters then surely you understand amdahl's law, caching strategies of a modern CPU, execution pipelining, etc... We just need to give those auto guys an LLM and then they can do systems software engineering, right?

Did you catch the sarcasm there?

Are you a manager by any chance? The non-coding parts of my job largely require domain experience. How does an LLM provide you with that?
Not to mention that most hashmap implementations for managed languages incur ~2 cache misses per lookup. I've had an awful lot of optimisation wins over the years just by ripping hash maps out of software that either didn't actually need arbitrary key->value lookups, or had datasets large enough that a sufficiently wide tree-like structure handily beat the hashmap
Current events are motivating people and their stores and governments to not choose U.S. products. The motivation is strong and widespread. I would have to think that sensible marketing folks in the U.S. have to be wargaming the effects upon their bottom line when their product lines are under such suppressing forces:

https://www.cbc.ca/news/politics/f35-blair-trump-1.7484477
Look to other cultures and markets for this. India and Japan in particular have a massive variety of general and specialized containers in assorted materials, for whatever your needs might be.

Europe/Russia and Nordic countries have more similar bakeware to the US, but since that's not how I normally cook, I'm not as familiar.

I also have friends who are ceramicists, so if you have access to any, you could ask them what they'd charge for some custom glazed earthenware.
Not Myarmar, but in Cambodia scams are soon or already larger business than official GDP

https://thediplomat.com/2024/09/laos-and-cambodia-dont-inclu...
> via a good explanataion.

That is the point I was making.

Note the quotes on “sell” and “persuade”. That’s a hint. Meaning a lot of words meant to sell or persuade are actually harming those purposes.

Three word highly opinionated statements, like my paragraphs began with, are best viewed as strong (re-)prioritization. Not a prohibition on nuance once the point is understood.

So, I appreciate and agree with your nuances.
Very well put. I also read books to learn concepts. I usually only turn to documentation to remember the nitty gritty details that are easy to forget. Consider loading the first 100 rows of a large CSV. About as basic as code can get. Yet as I move between languages and libraries, it's hard to remember all the different syntaxes, so I find myself looking up official documentation.

read.csv("large.csv", nrows = 100)

read_csv("large.csv", n_max = 100)

pd.read_csv("large.csv", nrows=100)

pl.read_csv("large.csv", n_rows=100)

CSV.read("large.csv", DataFrame; limit=100)
This advice strikes me as very sensible if I want to maximize my audience of readers who lack the attention span to take in any information of real depth.
The machine optimizes for clicks. Do not question the machine. /s
> can ask for obscure things with subtle nuance where I misspell words and mess up my question and it figures it out. It talks to me like a person. It generates really cool images. It helps me write code. And just tons of other stuff that astounds me.

It is an impressive technology but is it US$244.22bn [1] impressive (I know this stat is supposed to account for computer vision as well but seeing as to how LLMs are now a big chunk of that I think it's a safe assumption)? It's projected to grow to over US$1tr by 2031. That's higher than the market size of commercial aviation at its peak [2]. I'm sorry if I agree that a cool chatbot is not approximately as important as flying.

[1] https://www.statista.com/outlook/tmo/artificial-intelligence...

[2] https://www.statista.com/markets/419/topic/490/aviation/#sta...
TSMC was heavily sponsored by the Taiwanese government with the goal of making Taiwan so valuable that other countries would feel required to defend them against China.

It is against their interests to outsource too much or outsource cutting-edge nodes. This is exactly what we see.

The recent Arizona fab is N4 which is just N5 with some refinements. N5 was sampling iPhone chips in 2019 and N4P has been available since 2020-2021. That's a half-decade ago.

N3 started up in 2022, but won't be in the US until 2028 some 6 years later. By 2028, TSMC plans their Taiwanese factories to have produced 2nm, 1.6nm, 1.4nm, and 1nm.

If the US wants cutting edge chip manufacturing, it 100% is NOT coming from TSMC.
Hey I recently made an android app that uses QUERY_ALL_PACKAGES to list all the known trackers on your phone. It's just a small app with a few installs, but I wasn't sure how/if I could replicate that for iOS.

I had thought of Zeptos model but it wasn't as interesting since it just handles the 150 most known apps.

I already have the data for all the trackers on appgoblin.info, I just want to make it so a user can quickly generate a list of their 100 installed apps IDs.

Any thoughts. Great post.
Right, that was my thinking. Though frequently incorrect, it is intuitive that similar things are more closely related than dissimilar thing.
"Would you like some breakfast" isn't quite so overly wordy that I'd say it sounds unnatural, but it absolutely is not the bare minimum for idiomatic English.

"Do you want breakfast?" is perfectly grammatical, and "Want breakfast?" would be a totally normal phrasing, even if some might argue that eliding the subject isn't technically correct.
It's not inevitable by any means. There's definitely a way to build buildings so that at any point they are as resistant to earthquakes as they will be at the end.

Actually I think it would take special effort to make it so it's vulnerable during construction but safe at the end.

For example, do you think the foundation of the building is somehow weaker during construction but gets stronger at the end? How could that possibly work?
I think you're being downvoted because this comes off a bit... I dunno... petty I guess?

Maybe reply to the original post and let your product stand on it's own merits.
I pasted the study into ChatGPT and asked it if the study is saying we need to take on a ketogenic diet to get the benefit or just take a supplement, and it suggested that just taking a supplement (exogenous ketones) in particular D beta-hydroxybutyrate ( D-βHB ) is enough. And that the benefit occurs during the years of 40-60 but that past 60 the window to benefit may have passed.
So you are working on a way to generate toolpath gcode from python? I need that.

I have a python workflow for my laser cutter, I can make a drawing with drawsvg and then cut it with lightburn.

I have used build123d to make 3d models in python but not yet found a way to generate toolpaths for my milling machine.
That is the kind of thing a good union is supposed to fight against. People go on strike when offshoring happens.
In the 1980s, many Keralites were courageous enough to leave the land for better prospects abroad, many in the Middle East and the UK. I remember going to my friends place and find their houses were modern and it was the first time I saw a glass door. Not to mention some of my Keralite friends are the most sincere and hard working and they have risen to very high ranks regardless of their grad scores and academics.
I think it’s both.

“After seeing a brief demo of a grotesque zombie-esquire creature, Miyazaki pauses and says that it reminds him of a friend of his with a disability so severe he can’t even high five. “Thinking of him, I can’t watch this stuff and find [it] interesting. Whoever creates this stuff has no idea what pain is whatsoever. I am utterly disgusted. If you really want to make creepy stuff, you can go ahead and do it. I would never wish to incorporate this technology into my work at all. I strongly feel that this is an insult to life itself.”

Near the end of the clip, after hearing that the animators’ goal is to create a machine that “draws pictures like humans do,” Miyazaki’s comments are even more grim. “I feel like we are nearing to the end of the times. We humans are losing faith in ourselves…””

Admittedly there’s an editorial cut in the end of the clip to make it seem more like Miyazaki is directly responding to the animator in criticizing the “machine” process, but I do think it’s apparent from the video that he also has an aversion to how it’s made.
> The 22 cases include Chicago resident Julio Noriega, 54, a U.S. citizen who, according to court documents, was arrested, handcuffed and spent most of the night at an ICE processing center in suburban Broadview. He was never questioned about his citizenship and was only released after agents looked at his ID.

It’s only going to get worse and more normalized. This isn’t a mistake either, there’s a reason why this administration is trying to end birthright citizenship [0]

[0] - https://apnews.com/article/trump-birthright-citizenship-nati...
Scaling Your K8s PyTorch CPU-Only Pods to Run CUDA with WoolyAI
Currently, to run CUDA-GPU-accelerated workloads inside K8s pods, your K8s nodes must have an NVIDIA GPU exposed and the appropriate GPU libraries installed. In this guide, I will describe how you can run GPU-accelerated pods in K8s using non-GPU nodes seamlessly.

Step 1: Create Containers in Your K8s Pods
Use the WoolyAI client Docker image: https://hub.docker.com/r/woolyai/client.

Step 2: Start Multiple Containers
The WoolyAI client containers come prepackaged with PyTorch 2.6 and Wooly runtime libraries. You don’t need to install the NVIDIA Container Runtime. Follow here for detailed instructions.

Step 3: Log in to the WoolyAI Acceleration Service (GPU Virtual Cloud)
Sign up for the beta and get your login token. Your token includes Wooly credits, allowing you to execute jobs with GPU acceleration at no cost. Log into WoolyAI service with your token.

Step 4: Run PyTorch Projects Inside the Container
Run our example PyTorch projects or your own inside the container. Even though the K8s node where the pod is running has no GPU, PyTorch environments inside the WoolyAI client containers can execute with CUDA acceleration.

You can check the GPU device available inside the container. It will show the following.

GPU 0: WoolyAI
WoolyAI is our WoolyAI Acceleration Service (Virtual GPU Cloud).

How It Works
The WoolyAI client library, running in a non-GPU (CPU) container environment, transfers kernels (converted to the Wooly Instruction Set) over the network to the WoolyAI Acceleration Service. The Wooly server runtime stack, running on a GPU host cluster, executes these kernels.

Your workloads requiring CUDA acceleration can run in CPU-only environments while the WoolyAI Acceleration Service dynamically scales up or down the GPU processing and memory resources for your CUDA-accelerated components.

Short Demo – https://youtu.be/wJ2QjUFaVFA

https://www.woolyai.com
And yet... On almost every new ATX motherboard, there are PS2 inputs. And barely any options at all even available for purchase for individuals with, say, more than one RJ45 port, regardless of price. I don't get just how stagnant that industry is.
Feels like AI could fix this, learning with a llm companion that never is exhausted and always encourages you to follow your intuition and curiosity is already better than 99% of teachers on a public school (sadly)
not blaming the teachers, but the system, one teacher 30 students will never work well
Not surprising. A 7.7 is absolutely massive. (In terms of energy, 10^23.35 erg. Or 5 megatons of TNT, if my math works)
Fascist and commuist regimes often purge the highly educated first.
That straight line in the map doesn't look like the maps for any earthquakes I've felt. It looks like it was on the Sagaing Fault which is a different type of fault from the ones I've experienced.

https://en.wikipedia.org/wiki/Sagaing_Fault
I did art. I did postgrad. I did work(n). I did dishes. I did Paris. I did the walls, but hired someone who did the roof.

Not idiomatic for all nouns, esp those for which there's a more applicable verb.
Also in the vein of crumbling Fourth Amendment rights:

[1] https://news.ycombinator.com/item?id=43428798 : Officials Believe Order Lets Immigration Agents Enter Homes Without Warrants
The US has found ways to get China to adhere to IP laws, but they're never going to agree to restrictions the US doesn't impose on itself. Presuming that there is no way China will respect IP laws is BS.
sure. isn't that effectively what Sabine is doing though? She just doesn't have as compelling a use in the cases where LLMs are strong.
Off the top of my head:

* I did a puzzle.

* I did a bad thing.

* I did a backflip.

Or, since this is just normal English, it's exactly the kind of thing that ChatGPT is good at, so here's a dozen more examples if you want: https://chatgpt.com/share/67e6d457-5ff4-8002-a5c7-15040f3d22... .
I'm still doing it when I am typing at a physical keyboard. Hard habit to break. I learned it so long ago too.

You can tell when I've edited something on both a phone and a physical keyboard, based on the inconsistent use of spaces.
Not that I've noticed, but I've made a concerted effort from the beginning to mentally work through any AI-generated code I use. Yes, it does require a lot of discipline.

I believe it's equally important to ask it to explain why it generated the code when the output is unexpected. More often that not, it's acting more like "fancy autocomplete", though.
Why go with Ibis over Narwhals? Just curious.

I really tried to work Ibis into my projects when I thought the native Ibis functions could be used until I went back to another tool like DuckDb or Polars, but I was finding Ibis couldn’t do some things. At that point it was either flip over to polars to do x, or just use polars.
To :+1: this, even if it's a book - there is a central thesis - a headline and a sentence that tells you whether you want to read more. "Your pet could save your life" - The six surprising reasons that people with pets live longer than others.

Then each chapter has the same: "Getting in touch" - why stroking your cat soothes your body. Etc

You may even have sections within the chapters and each can follow the same format.

Thousands of years ago it was enough just to write down stuff you've learned, call it "Meditations" and hope people would still be reading it in the distant future.

Now if it's just "stuff I've learned about coding" or "things that make me happy" you're going to need an extremely strong hook to tie that together and build an audience.

So start with a single thesis and decompose from there. Inverted pyramids all the way down :)
Parylene C, a chlorocarbon: [1]

> Derivatives of parylene can be obtained by replacing hydrogen atoms on the phenyl ring or the aliphatic bridge by other functional groups. The most common of these variants is parylene C, which has one hydrogen atom in the aryl ring replaced by chlorine. [2]

[1] https://www.science.org/doi/10.1126/science.ado1782

[2] https://en.wikipedia.org/wiki/Parylene#Permeability
This guy agrees with you:

https://www.youtube.com/watch?v=mgS1Lwr8gq8
Doesn't a Kerala temple contain in excess of $22 billion worth of gold?
is it a paradox? how unlikely is it that there's a plastic substance out there that can be quickly dissolved to bio-degradable substances but only using a relatively cheap and non-toxic solvent not present in most use cases for plastic? that's not a paradox, it's an engineering problem.
Thank you for the great discussion. You've put your finger on the right thing I think. We can now dispense with the old VC-type thinking (i.e., that it's because the hypothesis space is not complex enough that we get generalization). Instead now the real question is this: is it the loss landscape itself, or the particular way in which the landscape is searched that leads to good generalization in deep learning.

One can think of perhaps an "exhaustive" search with say God's computer of the loss landscape and pick an arbitrary point among all the points that minimize (or are close to the minimum). Or with our computers we can merely sample. But in both cases, it's hard to see how one would avoid picking "memorization" solutions in the loss landscape. Recall that in an over-parameterized setting, there will be many solutions that have the same low training loss but very different test losses. The reference in my original post [1] shows a nice example with a toy overparameterized linear model (Section 3) where multiple linear models fit the training data but they have very different generalizations. (It also shows why GD ends up picking the better-generalizing solution.)

Now people have argued that the curvature around the solution is a distinguishing factor between well-generalizing solutions and not. Though already now we are moving into the territory of how to sample the space i.e. the specifics of the searching algorithm (a direction you may not like), but even if we press ahead, it's not a satisfactory explanation since in a linear model with L2 loss, the curvature is the same everywhere as Zhang et al. pointed out. So the curvature theories fail for the simplest case already unless one believes that somehow linear models are fundamentally different from deeper and non-linear models.

[1] points out other troubling facts about the curvature explanation (Section 12), but one I like more than the others is the following: As per curvature theories the reason for good generalization at the start of the training process is fundamentally different from the reason from good generalization at the end of the training process. (As always, generalization is just the difference between test and training, and so good generalization is when that difference is small; not necessarily that the test loss is small.) At the start of the GD training process curvature theories would not be applicable (we just picked a random point after all) and so they would hold that we get good (in fact, perfect) generalization because we didn't look at the training data. However, at the end of training, they say we have good generalization because we found a shallow minima. This lack of continuity is disconcerting. In contrast, stability based arguments provide a continuous explanation: the longer you run SGD the less stable it is (so don't run it too long and you'll be fine since you'll achieve an acceptable tradeoff between lowering the loss and overfitting).

[1]: https://arxiv.org/abs/2203.10036
The Eternal Tao Might Be an Asshole
What the author calls "automatic code migrations" is known as "refactoring" and many of the safe refactorings are automated.
Another technique is to introduce a method signature while keeping the old one, and rewriting the body of the old method to fix up the types and call the new method.
As far back as 1994 with the publication of Design Patterns: Elements of Reusable Software the Facade pattern provided a way to allow maintaining a consistent interface across varying implementations.
Good point. On a video recording system we had problems with dropped frames from the USB camera. When an external USB keyboard was connected the problems became rarer. Obviously the keyboard kept some component to enter deeper energy states, and when everything staid up all the time frames were no longer lost as commonly.

Surprising to me as a layperson in this field is that camera with 30 fps would allow entering a deeper state than a keyboards with a data rate orders of magnitude smaller.
Looks like this is one sided political propaganda article. Googling shows real picture.

Unemployment is at 40%.
https://en.wikipedia.org/wiki/Unemployment_in_Kerala

Kerala is in the grip of a surging drug crisis
https://economictimes.indiatimes.com/news/india/kerala-is-in...

Kerala rooting on central govt to solve state's Rs 26,000 crore monthly expenditure crisis
https://keralakaumudi.com/en/news/news.php?id=1498119&u=kera...
> Interestingly, at least in my browser and grabbing the direct link to the comment with curl, show the bytes as 0x20 for both. Perhaps the comment submission handler, or even the browser, collated your more specific U+2009 (thin) and U+200A (hair) spaces into the regular U+0020 space?

Probably! I think HN strips out emoji; maybe it just takes the safest approach and strips out all non-white-listed Unicode.
That Hit Song You Love Was a Total Fluke
At least the slims have Ethernet too, maybe you could download code to memory
Especially with the deeply dysfunctional dynamic between DOGE and the subject matter experts.
Looks super interesting. I hadn't heard of Graphiti before, but the idea of giving Cursor some kind of persistent, structured memory across sessions definitely sounds useful.
Socializing the risk in this way is a regressive tax, there are clearly other alternative organizational structures.