skysight-inc/HackerNews huggingface dataset:
Near-infrared penetrates very well. The same intensity is much safer, up till you get to the levels of radiation that are dangerous regardless of how they're distributed in your tissues.

That's one of the things that makes it suitable for thermal nano cancer therapies. You

(1) Create a nanoparticle with a gold core of the right size that it excites when exposed to near-infrared radiation (the far end of "near" is ideal),

(2) Coat it with something that's hopefully less toxic than the cancer because the gold nanoparticles are pretty reactive (silica was popular last I checked, though I'm not convinced that's actually safe, and there hasn't been much testing on it),

(3) Coat that in something that binds to the right antigens,

(4) Inject that into the patient so that you'll eventually have a tumor rich in these nanoparticles while the rest of the body has a very low concentration,

(5) Shine an intense near-infrared beam at the nanoparticles. It safely penetrates body and causes minimal heating, instead depositing all its energy at the tumor, selectively cooking just the bits of tissue you don't want anymore.

It's yet another way to make mice immortal, but human testing is a long ways off. The hard parts are (2) and (3), along with the (4a) I didn't mention where most of these things don't want to stay "nano" in most chemical environments, and the solution they're suspended in is usually also not ideally suited to being injected into living mammals who would like to retain that "living" property.
I like reading Marginal Revolution because it doesn't have this rule whilst also being a rather intellectually curious place.

(not suggesting HN ever takes this route)
Appreciate the reply!

We have 2 binary datasets in there [1], but of course, those results are not separately presented - you see the averages. The choice of datasets here is based on what other papers report, to have comparable results. In our experience with real data, AL doesn't fare any better on average - our pipelines use different representations (not just BERT based, includes some legacy ones like n-grams+tf-idf) and classifiers.

We do see some strong peformance with RoBERTa (Fig 6) and the margin strategy, which is an uncertainty based strategy like least confidence (Fig 7) - these probably correspond to your observations (to an extent).

It is a little hard to comment on differences without looking closely (I'd be happy to go through any document/tech. report you might be able to share) but in our experience, we have seen inconsistencies arise from:

* Not performing model selection at each iteration.

* Not calibrating the selected model at each iteration.

In these cases, a non-random query strategy sometimes just makes up for the lack of proper model selection, making it seem like the query strategy is stronger than it really is.
Another point of difference is the seed data size - that can have a significant effect on "priming" the query strategy.

On a related note, specifically wrt uncertainty-based strategies, sampling bias is a known problem [2].

[1] On the Fragility of Active Learning, https://arxiv.org/abs/2403.15744

[2] Section 1.2 in Two faces of active learning, https://cseweb.ucsd.edu/~dasgupta/papers/twoface.pdf
I wish things were so simple!

Reducing latency doesn't automatically translate to winning the market or even increased revenue. There are tons of other variables such as functionality, marketing, back-office sales deals and partnerships. Lots of times, users can't even tell which service is objectively better (even though you and I have the know how and tools to measure and better know reality).

Unfortunately the technical angle is only one piece of the puzzle.
If you can read the small type on Hacker News, you're OK.
Too bad they did not put any comparison tables into the blog post.
I recently changed jobs, I also had a co-worker with similar length of experience start looking for a job before I did. He said he has put in over 200 resumes, and has only gotten a couple of callbacks, and no interviews. I asked to look at his resume, and even though I knew what his skill set was, you couldn't tell from the resume. It had a lot of experience, but in unassociated things. It had some UI/UX experience, some moderate programming experience, and some digital photography experience. I asked him what he was applying for, and he said "I don't know, anything to pay the bills".

On the other hand, I'm strictly a programmer. I wouldn't say I'm an expert at any one thing, but I have enough experience over the years to be able to pick something up and contribute in a short amount of time. Embedded systems, desktop, backend, front end and everything in between. I made it clear that I was a "Full stack software developer with 25+ years of experience in multiple programming environments." I enabled the "Looking for Work" option on LinkedIn. I had around 10 recruiters call or message me on there, and within 2 weeks I had 3 interviews. I went to 2 interviews, the second place offered me a position, and I took it, and had to call the 3rd one back and cancel. It's not a FAANG company (which frankly I'm sick and tired of hearing about on here and Reddit), but it's a big public company with 7 offices and over 600 employees. I got a 25% raise, better benefits, and better flexibility so I have more time to do the things outside of work that I want to do.

And no, I don't have a public GitHub repo.
Pinning is always done for heap-allocated GC memory, yes. Otherwise fixed statement does nothing for pointers/byrefs that originate from stack and it should be also a no-op for e.g. NativeMemory.Alloc-returned pointers.

On the other hand, GCHandles[0] are rare and only ever needed when you have complex object lifetime where, for example, the object reference needs to be passed back from unmanaged and object needs to survive in the meantime. The unmanaged code cannot interact with an object itself because it is not representable and would have arbitrary layout.

Today, there is support for multiple calling conventions and ways to interact with FFI. [UnmanagedCallersOnly] exports with NativeAOT-compiled libraries are C exports in the same way they are for the dynamic (or static) libraries compiled with GCC. Various flavours of function pointers have existed for a long time, yes. The most recent one allows to cast pointers directly to the desired unmanaged function signature within unsafe code, or create one given mentioned UnmanagedCallersOnly annotation on a C# method.

[0] https://learn.microsoft.com/en-us/dotnet/api/system.runtime.... note specific use case, it's not the bread and butter regular marshaling and pinning are
More that the manual needs to be in all those languages, and you might needs to communicate in them for warranty, etc.
Better than open-plan offices.
And even then it's only a disguise. The two degrees-of-freedom which a complex numbers has, are still there (and QM needs it for interference, etc.). There is not way getting around the number of degrees-of-freedom of a system or a theory. It's as "real" as it gets.
Brazil is under a judiciary kind of government regime, having that Alexandre Moreas as their supreme leader.

They're hostile to high tech companies and entrepreneurs, but ok with the organized crime.
> So in short, they're just making every single project out there that relies on ESLint go and either add a flag or rename one file

Not every project. Many people switched to the .js format a long time ago since it’s more powerful. I understand the inconvenience though, especially since I don’t remember them deprecating the rc format when they introduced the js one.
Or maybe it’s just more pleasant to write than C?
The grinding apparatus often contaminates the product. Lead gears were used to increase reliability by the British and these spice fields still use machinery they left behind because it saves transport costs to compact on site.
A couple of other things the people commenting about people having a lot of money might be overlooking:

1. My guess is that a lot of the people are treating this as a vacation and the money for it comes from foregoing some other vacation trip that they would have taken this year.

2. It doesn't have to be expensive to see an eclipse. My trip to see the 2017 US eclipse had these costs:

• $50 for a place to stay for the day of the eclipse and the day before.

It was at a farm where the farmer had converted one big field into an overnight parking area for people who were going to sleep in their cars, an adjacent big field into a place for people who wanted to park and set up tents to sleep in, and another adjacent field into a place for food and souvenir vendors and entertainers. They had set up a ton of portable toilets in all three of those areas, and had shuttle buses running a loop through all three areas.

The $50 was for a spot in the "sleep in your car" field.

• Whatever it cost to operate my car for the ~600 mile round trip.

• Maybe $10 for a small PC case fan, which I connected to a small solar panel I already had. I could then put the solar panel on the car roof, open a car window just enough to wedge the fan in, and have a nice breeze in the car. (The 2017 eclipse was in August and temperatures were expected to be in the mid-80℉ to 90℉ range where I saw it).

• A car windshield shade. Maybe $20?
Marcus has a good point when he says that the scaling will only benefit in a logarithmic way, not in a linear way. I watched the Sora video as well and in the Q&A session, they admit that they will need a lot of data. Marcus' contention is that there isn't enough data on the internet and synthetic data will just result in errors.

Where Marcus gets it wrong is that he defines "right" as producing an algorithm that an AI will follow to get a deterministic result. So, every time Sora 2 (Gary's Version) produces a video of a glass shattering, it is the same shatter pattern being produced; and it must be a precise duplicate of a glass shattering in nature. That's Marcus' win situation, which Sora will unlikely ever reach.

Maybe transformer-based AI will never be capable of perfectly simulating reality in order to unlock its secrets. It seems to me that, according to the transformer-denialists, in order to create an AI that understands reality, we must fully understand reality first and then program the AI with that understanding.

In my mind, I imagine neural networks as drift-car drivers (I think of them as Ken_Block, Paul Walker would also be acceptable). Sure, your average drift-car driver has no idea how to solve a three-body equation algorithmically, but a great drift car driver can maneuver four spinning tires in a state of critical oversteer around a race track curve without the use of a calculator and get it right most every time.

And yes, race-car drivers have short lifespans, it's true. That's what terrifies Marcus so much about neural networks as well, and why he is so adamant that we listen to him when he says that there are dangerous curves ahead.

I personally would rather live in a world where there are Ken Blocks and Paul Walkers, and that's how I live my life (not in auto-racing, though) but I understand why that frightens people.
I whipped up some card rendering CSS for this, pretty fun!

https://colab.research.google.com/drive/1VERzr75vpCgmXE6lgQC...?
usp=sharing
Could you expand on why you think living healthily doesn't increase your lifespan?

Untreated STDs can cause infertility, sexual dysfunction, cancer, brain damage, and death. No method of preventing them is 100% effective besides abstinence or having sex with a small amount of partners that you trust not to lie about being clean.

Drugs carry the risk of overdosing, and for those that even just use semi regularly they still reduce lifespan.

Eating excess calories makes you fat which hugely increases your risk of having a heart attack among other health issues. Even if you control your calories, eating processed food makes you more likely to die early or develop a debilitating disease.

This is all very common sense about how to live longer, if you think you've cracked the code and any of the above is wrong please explain.
Forget the layout and such, at the very least academia needs to completely get rid of PDF as a format.

Completely unreadable on different format screens and makes accessibility impossible and therefore narrowing the field of possible readers even lower.

We've had HTML since what, the beginning of the WWW? How are we still using PDFs in 2024? Completely absurd.
> Any missile you use is way too expensive relative to the price of the drone

Western missiles have been designed for generations assuming they're aimed at something expensive you want to break, or to break something next to something sensitive you'd rather not. We have the technology to create swarms of well-enough aimed small rockets. There simply wasn't a niche until now.
I don't see why it's inconsistent for me to feel similarly about a small part of something as I do about the whole, or why it might not be rhetorically useful to help explain something by drawing a comparison between them
Yes I have done this upon occasion. You just know your going to get downvoted, so you really turn the rationale up to 10 but you know it's still not enough.
Both of the examples are archetypical extremes.

But FWIW the character created for example #2 is not mainlining mountain dew and fentanyl.
> After a few years, the weakest professional players were better than the strongest players before AI. The strongest players pushed beyond what had been thought possible.

Human Instrumentality Project
I didn't use any eclipse glasses and I'm afraid the thick 100% clouds may have damaged my eyes. :)
Get in line behind the other religious groups aiming for a piece of power.

I wonder how Scientologists view Christian nationalism and vice versa?
> So, how do we stop people lionising "strong men"?

We have the solutions and have, perhaps not incidentally, discarded them in last 10-20 years:

Postmodernism - yes, I know the reaction to that outrageous idea - is at its heart a distrust of power as corrupting and its application as necessarily evil. Power is the Ring; Gandalf's mission was to stop the Enemy without raw power, but by defeating despair and arousing people's goodness, honor, and courage (e.g., the clearest example being Theoden).

Democracy: No kings, no aristrocrats, no masters; all created equal; liberty and justice for all; every one's opinion as good as another's; everyone is equally trusted to live their own life, make their own choices, choose their own words and religion; everyone gets an equal vote and is a valid juror. To assert greater power was a sin; megalomania was transparently ridiculous. Remember the humility of Washington, Lincoln, etc.

Eary American Protestantism (I'm open to better terms, and I can't define this one well): Humility, simplicity, service to others as the ultimate measure; charity; personal wealth almost an embarassment of greed; the Golden Rule; etc. I remember a New Yorker article about such a culture even on Wall Street in (iirc) the 1980s; high walls around homes in the suburbs were frowned upon as arrogant and not engaged in the community; the head of one bank wore a cheap watch and soon everyone else did too.

We have all that, we know all that. Those who want to seize power try - for obvious reasons - to say they are impossible or to ostracize them. The failure is that leaders who know better - who should remember Washington, Lincoln, Eisenhower, so many more - haven't bothered to pick up the banner from where it was dropped. I think that's all we need.
The team behind this project (read: we) developed an expansive SDK for multi-user collaborative apps, including realtime docs. We use it to power many of the features of https://backbone.dev/

The multi-user scenario is significantly harder to get right without running into nasty vulnerabilities. We plan to write more about how we built it and what to look out for.
I’m curious about this phenomenon for grapes as well – how many incredible varietals live in the spaces in between, undiscovered by humans?
He's been trying to recreate this for years, I can understand why he's so excited to do it and that it works so perfectly.
See, C does it very well.
Great stuff. Karpathy has a gift for teaching.
Probably because Google are designing the entire hardware (its not a Dell rack server) and data center together, they are also responsible for the entire workload if something goes wrong and likely also have data center redundancy for an entire power loss for the entire workload there.

In third party data centers you're co-located with other customers that have mostly comodity server hardware which won't have those options, they generally (at least in my experience) all provide UPS power as part of the facilitiy so you have it already and something like a fire if it did happen, would impact lots of other customers who likely don't have redunancy between data centers or fire compartments.

Additionally depending on your exact setup (it's possible you may have dark fibre directly out of the facilitiy, but often not) you're likely to be uplinked through powered equipment at the same facility, that wouldn't have the extra UPS power either.

Plus as others mentioned, the loss of cooling is the biggest problem. In fairness maybe that would buy you a few minutes for the kindof automatic switchover they talked about. But that's quite a bit of co-ordination to have your own power, to not rely on anyone else being powered and then to be able to co-ordinate your shutdown before the room gets too hot - and not be at risk of overheating the room for others.

Plus there are safety issues like emergency power out for fire fighters etc which again, I'm sure Google could deal with at a facility-wide level, but if you're a small fish in a much bigger data center its harder to co-ordinate that kindof thing.

So while I'm sure it's all possible, there are obvious headwinds in many directions.
The simplest way of building an MLP on top of the embeddings is simply to concatenate the embeddings and put some dense layers on top.

However, if you use a "two towers" approach and have several additional MLP layers on top of each embedding separately, and then a dense MLP on the concatenations of each tower, the individual tower MLP layers are an embedding transformation, and will improve retrieval.

Like this:

Final MLP
/ \
QP MLP DP MLP
| |
QE DE

Now, you can apply the document preprocessor ("DP MLP") to your document embeddings ("DE") before storing them in the vector database, and apply the query preprocessor ("QP MLP") to your query embeddings ("QE") before querying your vector database.

This should improve the precision and recall of your vector retrieval step beyond using e.g. raw LLM embeddings. Even better is for the final layer to just be cosine similarity, maximum inner product, or L2 distance, rather than having an MLP so you can just use a raw threshold (it's at least worth trying).
Same for me, and AirTags don’t push a subscription service down my throat with spammy notifications.
> I'm glad we don't rely on a single man's fears, whatever are his genius and rationalizations.

You have no idea how hollow this rhetoric is, especially when it comes to the numerous events that took place during the nuclear arms race. Just in the time period alone.
The sensors should be sensitive[1] well into the near-IR, and there are people in the astrophotography community which can service digital cameras to remove the IR-cut filter, these[2] for example.

Another alternative I was thinking about is just to use one of those monochrome astrophotography cameras, something along the lines of this[3]. The monochrome version doesn't have the IR-cut filter and sensitivity is pretty ok down into near-IR.

edit: The IMX492 sensor in that one has a 40% response at 850nm, and 850nm IR diodes are plentiful and shouldn't emit[4] much at all below the 700nm of the IR-cut filter the color camera should have.

Not sure how mixing sensor sizes and such would affect things, or if it's better/easier to just run two of the same camera.

[1]: https://s1-dl.theimagingsource.com/api/2.5/packages/publicat...

[2]: https://www.lifepixel.com/

[3]: https://www.zwoastro.com/product/asi294mm-mc/

[4]: https://lumileds.com/wp-content/uploads/files/DS191-luxeon-i...
The Story That's Sold
> zero transparency

> could be a state actor trying to lay the foundation for future backdoors

idk if presence of “names” are a good signal to indicate otherwise either

https://www.wired.com/story/jia-tan-xz-backdoor/
> I think when we start using it as a temporary measure it will become very clear what the downsides are

It seems more likely we won't know the downsides until the damage is done, which is what happened with using fossil fuels in the first place.
If I may explain: the dystopian part to me is the lack of transparency around training code, training data sources, tuning, meta prompting, and so forth. In Google’s case, they’re a large corporation that controls how much of society accesses information. If they’re secretly curating what that information is, rather than presenting it as neutrally as they can, it does feel dystopian to me. I’d like transparency as a consumer of information, so I know to the extent possible, what the sources of information were or how I am being manipulated by choices the humans building these systems made.

I appreciate the issue you’re drawing attention to in the example you shared about images of an angry person. I think I agree that focused tuning for situations like that might be noble and I would be okay with a model correcting for that specific example you shared. But I also struggle with how to clearly draw that line where such tuning may go too far, which is why I favor less manual biasing. But I disagree that such tuning should be required, if you meant required by the law. Like with speech or art in general, I think anyone should be able to produce software systems that generate controversial or offensive speech or art. Individual consumers can choose what they want to interact with, and reject LLMs that don’t meet their personal standards.
All the bodily processes the baby doesn't use in the womb such as its digestive tract, pulmonary and immune function, must be triggered to begin once the baby has left the womb. Those babies who do not receive adequate stimulus after birth essentially are born into a slow-waking state. This is autism. ALL the symptoms of autism are rooted and linked to the processes that must be triggered/innervated after birth, but fail to, or at least do not receive adequate neural innervation. Infants and young children have to develop the ability to respond reflexively to the external environment, as well as their own internal environment, for survival.
Last time I made a pinhole camera cardboard box, which--while dramatically less cool to wear over my head--at least involved safety measures I was confident in.
Imagine X and Y axes, perpendicular as usual. If you become 3 units more X, that doesn't change how Y you are. Contrariwise, if we nudge our axes out of orthogonality, now moving along the X axes changes where I am on the Y. Obviously the use here is metaphorical, but that's the sense meant.

Edited to add: consider "independence" and orthogonality in vector spaces, if you want to get mathematically precise about it.
Near infrared isn't naturally emitted by room temperature objects. You're thinking of far infrared.
Somewhere an AI is pumping it's fists in excitement
> Counterpoint: Magsafe. They had USB-C and went back to something proprietary.

They added MagSafe and still kept USB C charging.

> So you're saying that's what they wanted to do all along, it just took them almost ten years, and it just happened to neatly coincide with the EU regulation as well?

They had already starting to move iPads to USB C
Fair. But looking at that story (very interesting btw, thanks), they did recreate it. So incentive does mean a lot when $$ is also available, which I'd suspect it is in movies.
They're on Hugging Face. Interestingly enough they don't compare it against Mistral 7B.

https://huggingface.co/allenai/OLMo-7B