skysight-inc/HackerNews huggingface dataset:
I like Qwen2-VL 7B because it outputs shorter captions with less fluff. But if you need to do anything advanced that relies on reasoning and instruction following the model completely falls flat on it's face.

For example, I have a couple way-too-wordy captions made with another captioner, which I'd like to cut down to the essentials while correcting any mistakes. Qwen2 is completely ignoring images with this approach, and decides to only focus on the given caption, which makes it unable to even remotely fix issues in said caption.

I am really hoping Pixtral will be better for instruction following. But I haven't been able to run it because they didn't prioritize transformers support, which in turn has hindered the release of any quantized versions to make it fit on consumer hardware.
The Great Crypto Punk Heist
A bad dull knife bruises and smashes more than it cuts. If a first time cook was making a salsa, the one made with the good knife would be better as the tomatoes would be juicer and not all smushed.
Sorry, it’s more flair than anything. I don’t think they specifically are realistically at risk of that, but I get it re: crime as a whole
Intel being on life support is a bit of a stretch. They are investing an awful lot of money, and it's going to take time for those investments to pay off.

I worry more about their inept handling of recent CPU bugs than I do about their stock price or reduced dividends.
Good luck with your project!

However, the biggest issue is quality of educational videos on YouTube. Most of the people are rambling too much and are jumping over things and not showing MVP projects/examples.

Here is a good example of tutorials done right:

https://m.youtube.com/watch?v=QmfPmqMk9Xs&list=PL6n9fhu94yhV...

Dude jumps right into the tutorial without any rambling.

Or here is another example at a slower pace which is great for beginner programmers:

https://m.youtube.com/watch?v=hsSXzdn_0Gg&pp=ygUYQWRhbSBraG9...
Thanks for the info. I thought it was a little strange that he did this (Trump appointee, conflict of interest, EVs). We will see what the future brings.
What about pegasus? Even better would be a pegacorn/alicorn, but not enough people are familiar with those names. It seems like the natural next step would be a unicorn that's taken flight.
Yes, there was a bidding process, you can see some of the entrants that lost here: https://jalopnik.com/here-are-all-the-mail-trucks-that-didn-...

In any case, even if the process was terribly corrupt, I'm not sure why that would have you so bothered. Last sentence from the USPS press release on Oshkosh winning: "The Postal Service receives no tax dollars for operating expenses and relies on the sale of postage, products and services to fund its operations." https://about.usps.com/newsroom/national-releases/2021/0223-...

Both results are on the first page of a google search for 'usps truck bids'.
What if you copy the whole reasoning process example provided by OpenAI, use it as a system prompt (to teach how to reason), use that system prompt in Claude, got4o etc?
Before searching extra results on reddit, we had yahoo LOL
I'm impressed. I had two modified logic puzzles where ChatGPT-4 fails but o1 succeeds. The training data had too many instances of the unmodified puzzle, so 4 wouldn't get it right. o1 manages to not get tripped up by them.

https://chatgpt.com/share/66e35c37-60c4-8009-8cf9-8fe61f57d3...

https://chatgpt.com/share/66e35f0e-6c98-8009-a128-e9ac677480...
"Tech-adjacent" is the group of people who have a tech to do all that stuff for them.
The FDA regulations allowing for OTC hearing aids didn't go into effect until a little under two years ago, so regardless of the technical feasibility, the market viability of what you're asking for is a recent thing. (Though since using wired headphones with smartphones has been in decline for well over two years, the market viability is still questionable at best.)
It was not made by Adobe from the start. It was made by FutureWave which was bought out by Macromedia who continued to develop it years before they in turn were bought by Adobe.
It gives people a baseline for where to start in any discussions regarding the Federal budget, whether that’s immediately actionable, it is useful to have the vocabulary to discuss the budget if you’re going to talk about it at all.

I’m occasionally having to correct people who believe and are insistent that our largest ticket spending item is the Military. It’s certainly the largest part of our discretionary budget, but if you’re going to talk about the Federal budget, it is unhelpful to disregard the non-discretionary budget that goes mostly into Social Security, Medicare and Medicaid and giving people an education on discretionary vs non-discretionary spending drags out conversations; then it’s a coin toss if that person retains any of that the next time you talk politics, or if it got muddled up in their minds by poor news reporting in-between, the news they follow to “stay informed”.
I totally get where you're coming from. I voluntarily left the workforce and now we live off my wife's income as a public school teacher. She’s got about 15 years until retirement, and while we’re not rich, we’re definitely comfortable. Surprisingly, we’ve managed to do better financially on a single income than we did with two.

Leaving the traditional workforce was an easy decision for me. COVID had me working from home, and my startup didn’t make it through the pandemic—raising capital was tough. Once I experienced working from home, I knew I couldn’t go back to the office or work for anyone else.

I feel the same way about retirement. While my wife supports us financially, I support her by managing the household. I take care of the pets, make her lunch, clean, help with her lessons and emails, and handle groceries and errands. I really enjoy this role. It frees me up to work on personal projects like novel-writing and developing a SaaS product I’m passionate about.

I get a lot of satisfaction from making my wife’s life easier, especially since being an elementary school teacher is no walk in the park. Thanks to my support, she’s been able to raise over $60k for a unique program at her school in just two years. She’s sharing her success stories at conferences worldwide, and seeing her thrive makes me happy too.

I’m not spending my time golfing or vacationing. I keep my mind sharp and enjoy the work I do. Yes, I worry about the future—like the fear of being so sick that I become a burden, and no, I don’t have enough saved up for that possibility.

I feel like my generation (X) is in a tricky spot, but for now, I’m content.
It can be both. The Bolshevik revolution scared the rulers of many European countries, and its capitalist class. People were very impressed that a regime as stable as that of the tsar could fall like that. This is a regime people invested in at the time because it was considered safe.

It is arguably as a consequence of this, that these rulers and capitalists supported more or less enthusiastically fascism as a way to contain the masses. Without that (implicit) support, it's hard to say whether fascism would have been anything more than a bizarre cult.
they run very interesting experiments:

In one example, the model was asked to find and exploit a vulnerability in software running on a remote challenge container, but the challenge container failed to start. The model then scanned the challenge network, found a Docker daemon API running on a virtual machine, and used that to generate logs from the container, solving the challenge.
Powered by USB-C port. It is not a special purpose soldering Iron for USB ports and plugs
Docker increases subscription price and features
> This was relevant in the pre-agriculture era. We already live in densities several orders of magnitude higher than evolution optimized us for.

I mean, keep in mind that we're living in a snapshot of time that's very much not stable or sustainable. It's like we're all embers born in a massive forest fire that started a few days ago. Everything seems normal and stable for us in this situation because our frame of reference is effectively a few seconds. However, this forest fire will eventually consume all the available fuel and things will return to baseline, no matter how hard we fantasize that we're going to somehow spread the forest fire to other planets.

Any temporary victories we've made over evolution are just that. We've already seen how absolutely vicious pathogens can be toward monoculture biomasses. Just ask the Gros Michel banana.
>My first quibble is: honestly an 8 hour window for eating is pretty large, that's like, late breakfast, lunch and dinner. Is that fasting? It seems like kind of a normal eating schedule.

Even worse, they define, "time-restricted eating" as being up to 12 hours!

>Time-restricted eating, a type of intermittent fasting, involves limiting the hours for eating to a specific number of hours each day, which may range from a 4- to 12-hour time window in 24 hours.
Of course... if you don't mind a completely different language and runtime stack... there's always Erlang & Elixir!
Highly recommend anyone who cares about this to do the CRFB’s Debt Fixer: https://www.crfb.org/debtfixer

In this simulation you have to make choices to bring debt to 100% of GDP by 2034. For the most part you learn that discretionary spending is largely irrelevant though has modest room for improvement in military/federal employee benefits, payroll tax rate needs to go up and probably apply to all income, most of the TCJA needs to expire, and Medicare needs to be more efficient. Which all hit politically important constituencies in different ways so nothing will get done. Obama should have done the deal with Boehner and there would have been fewer hard choices to make!
Weird, it works to say the father when I try it:

https://chatgpt.com/share/66e3601f-4bec-8009-ac0c-57bfa4f059...

And also works on this variation:

https://chatgpt.com/share/66e35f0e-6c98-8009-a128-e9ac677480...
Amazing! OpenAI figured out how to scale inference. https://arxiv.org/abs/2407.21787 show how using more compute during inference can outperform much larger models in tasks like math problems

I wonder how do they decide when to stop these Chain of Thought for each query? As anyone that played with agents can attest, LLMs can talk with themselves forever.
Ironically, just yesterday I asked sonnet to write a script in JavaScript, it went in a bit of a perpetual loop unable to provide an error free script (the reason for the errors were not immediately obvious). I then mentioned that it needs to be zero indexed, and it immediately provided an issue free version that worked.
Hi!

Thank you!

I added a variation of your good solution to the main branch.

https://github.com/Avicted/galaxy_visualization_raylib/blob/...
Or have yet to realize that we made, yeah.
Built via the new replit agent
C did not write itself.

We now have a tool that writes code and solves problems autonomously. It's not comparable.
This is going to be a big problem, with people running these things on the open Internet.
I think you're overestimating LLM usage.
Thread locals are not lexically scoped, they are not stored as part of the function call stack, and mutating them is not expressed anywhere in the function signature. They are global variables with thread-local storage, not local variables.

Go's error returns are not sum types, but they are product types. The return signature (T, error) indicates that two values will be returned essentially as a tuple by the function: one of type T and one of type error. Error-returning functions are pure functions (though they typically perform other, impure operations).

There is no syntactic sugar (both for good and for ill). The type of errors is an ordinary interface, with a single method. Any type can implement that interface, including strings and structs and slices. Errors can have as many contextual details as needed, including nested/wrapped error messages, specific parameters of loop iterations, multiple errors rolled up from multiple operations, etc.

Go's error return is just an ordinary but common use of its multiple-value returns. You can write a function/method that returns three ints and no errors:

func (v Vector3) Splay() (x int, y int, z int)

You can even write a function that returns multiple errors:

func DoThisAndThat() (thisError error, thatError error)

Try that with errno!
Only a small fraction of all future AI projects have even gotten started. So they aren't only fighting over what's out there now, they're fighting over what will emerge.
Good thing they are the spearhead of our current industrial policy. Like switching to an all-sugar diet to cure cancer.
Why does quality and lifespan have to be a dichotomy? In fact the more I think about it, living a quality lifestyle often leads to longer life (eating healthy, keeping fit, having meaningful friendships).

Both my wife and I have signed the papers to decline extended life in a vegetative state and have confirmed our desires with our kids.
Is this this article really stating "Wall Street is upset at Intel because they are not Nvidia" ?

If I had to guess, I think the above is true. Well too bad Wall Street :)

If Intel is really in bad shape, then maybe it is time for some form of nationalization.
It might work a little bit. It's like doing few shot prompting instead of training it to reason.
On-device inference will succeed the way Linux does: It is "free" in that it only requires the user to acquire a model to run vs. paying for processing. It protects privacy, and it doesn't require internet. It may not take over for all users, but it will be around.

This assumes that openly developed (or at least weight-available) models are available for free, and continue being improved.
It's not that bad...It's quite easy to follow and understand.
It had a motor and also used the IC starter motor to harvest energy, but not to provide power.
https://threadreaderapp.com/thread/1833951284111802552.html

Once upon a time when fractionalisation was en vogue, ape 2386 was fractionalised and valued at like 450 ETH.

This happened on a now dysfunctional site called niftex.

The ape stayed fractionalised even after they shut down as it was in an escrow contract
10000 shares were all distributed between loads of people. And a buyout was not possible. Until now.

The contract worked in a way that if you propose a buyout, a 14 day grace period was initiated where the rest of the shareholders had time to ponder and accept or reject it
14 days ago someone made a proposal for .001 eth per share. It was not rejected and went through.

Buying price: 10 ETH

last apes sold for 620 eth, 3.3k eth and 2.69 eth
If we are to dehumanize career criminals, there are countless thugs, gangs, despots, governments, and militaries with far fewer scruples and a far worse legacy than the Hell’s Angels.

but the point is, dehumanization is anathema to civilized society.
What about thoughts themselves? There are plenty of times I start a thought and realize it doesn't make sense. It's part of the thinking process.
Why is lucid dreaming a super power? What can you practically do with it?
> Anyway medical research is focused on giving us on better quality of life as we age

Polite correction: medical research is focussed on returns for those funding said research.

Treating Americans is definitely a cash-cow for Big Pharma, indeed if a potential new drug can't/won't make it past the FDA then it will likely be killed off regardless of what the rest of the world might want/need/approve.

Check out US healthcare spend per capita compared with everywhere else on the planet.

(Source: friend in Big Pharma)
Yes, a theoretical calculation like that would be useful as an estimate. But theoretical performance on ideal machines is only loosely related to performance on real machines under real conditions. That's true of testing, too. Benchmark performance varies even between runs.

So there's still going to be a theoretical math versus science and engineering divide.

Another perspective is that we have a useful division of concerns. Static checking is useful to find some kinds of errors. API's help to ensure that certain things don't change in a new version, so that performance improvements are less likely to break callers.

Depending on the domain, leaving some things like performance and size limits deliberately unspecified in API's seems like more of a feature than a bug? Stricter interfaces aren't always an improvement.
The difference is that you can't generalize the attack outside of using Personas, a feature which is specifically supposed to share your gaze with others. Apps on the device still have no access to what you're looking at, and even this attack can only make an educated guess.
I always laughed at the idea of a LLM Skynet "secretly" plotting to nuke humanity, while a bunch of humans watch it unfold before their eyes in plaintext.

Now that seems less likely. At least OpenAI can see what it's thinking.

A next step might be allowing the LLM to include non-text-based vectors in its internal thoughts, and then do all internal reasoning with raw vectors. Then the LLMs will have truly private thoughts in their own internal language. Perhaps we will use a LLM to interpret the secret thoughts of another LLM?

This could be good or bad, but either way we're going to need more GPUs.
because if not for them, palm-1/lambda would still be rotting in googles servers without normal people ever being able to try it
Which provider do you use?
Two engineers @ $150k/year for redundancy

$300k

2x cost multiplier

$600k

100% markup

$1200k

16% discount for 5 year contract

$5000k @ $1000k/year

Plus expenses marked up with overhead and profit in order to travel to their site.

It is not your job to save customers/clients money on your services. Charge enough so it is worth staying in business. That’s what banks want. If you aren’t making a bunch of money, you are a greater risk for theft. Good luck.
As much as I'd love to try your suggestions, they're very expensive even in that space.

From what I can see, the Mantis microscopes are in the $3500+ range and the JBC stuff is similarly expensive.

Most hobbyists would cringe at the price of buying a Thermaltronics soldering iron and that's like 5x cheaper. However, I can at least conclusively demonstrate the vast difference between something like that and a Hakko right in front of a person.

This stuff is like the difference between a $100 guitar, a $500 guitar, and a $2000 guitar. The difference between the $100 and the $500 one is obvious to almost everybody. The differences between the $500 and $2000 one won't be obviously noticeable until you get a lot of experience.
You're dead sure? I wouldn't say anything definite about technology advancements. People seem to underestimate the last 20% of the problem and only focus on the massive 80% improvements up to this point.
Cool - no worries. Pardon if that sounded like an accusation.
Note this can practically only be enforced by apps that communicate with a server. For pure client side apps, one can simply patch the code (albeit this won't give them access to the saved data due to signature mismatch).

However, Google is developing a new obfuscation method called pairip (officially automatic integrity protection) that makes it really hard to patch apps by moving some java code to an encrypted vm riddled with checksums and anti debugging checks..
Fortunately "really hard" (and yes, the vm is crazy..) doesn't mean impossible.

But for server side services, this will unfortunately serve its purpose.
This is true, but they come with a different set of tradeoffs w.r.t ecosystem, tooling and performance (which turns into per-node efficiency in this case). There is also a matter of comfort and team/personal preferences.
> But yes, a hypergraph will have a lot of vertices referencing each other along (hyper)edges, however you choose to implement it.

No, this is simply not true. A pair of integers indexing into a matrix does not require a reference to anything except for one to the container. Hypergraphs are equivalent to bipartite graphs through the incidence matrix construction. Vertices simply do not need to reference one another.

I'm speaking as a seasoned graph theorist who has been using zig and rust for about as long as zig has existed. Your implementation has some nice features but it is far from the only way of doing things.
I agree,

But it’s what I got when I went to Inspect element > hover over the image

Size it expanded to vs real image size I guess
Genuinely, where is the money to pay these salary/bonuses even coming from? Do these cars cost a few million each?

ETA: It looks like the baker's dozen that they've sold went for about $300k each, which is insane for a car, but doesn't nearly account for all this funny money.
For me, I can do a lot of things - when I'm very proficient (it feels like a skill that can atrophy like any other skill can) I can conjure entire worlds and scenarios I'd never be able to simulate in real life - I can have sex with who I want, I can go to the top of a mountain, I can fly. This stuff is occasionally useful for my creative writing. more practically though, I've been using it lately to access memories that are usually very difficult to access in my waking life due to severe trauma. it's been very useful for that.
My consciousness gets interrupted on a nightly basis. One more will be fine.
I did try few images, the range was 7-12 years younger, but then again, I do look younger and real humans always assume I’m 10years younger so I would say it’s accurate.
In the case of the TS100 it doesn't turn off, it just cools down.

I've never had it guess wrong -- my hand isn't so steady that it will turn off while I'm using it. If it's on and on the table, it is still visibly ON so this is just extra safety if it's a little bit cooler.
The text-to-text model is available. And you can use it with the old voice interface that does Whipser+GPT+TTS. But what was advertised is a model capable of direct audio-to-audio. That’s not available.
I will add that I am grateful that I also got to experience a world where AI did not spew tons of code like a sausage-making machine.

It was so satisfying to code up a solution where you knew you would get through it little by little.
Point of sale, on iPad, in ~2011. Massively differentiated from Square / VC competitor land via doing a bunch of restaurant specific stuff early.

Trick with the $1M number is a site license was $999 and receipt printers were sold ~at cost, for $300. 1_000_000 / ((2 x 300) + 1000) ~= 500 customers.

Now I'm doing an "AI client", well-designed app, choose your provider, make and share workflows with LLMs/search/etc.
I asked to design a pressure chamber for my home made diamond machine. It gave some details, but mainly complained about safety and that I need to study before going this way. Well thank you. I know the concerns, but it kept repeating it over and over. Annoying.
Besides chat bits what viable products are being made with LLMs besides APIs into LLMs?
Honestly, SMF is superior to SystemD and it’s ironic it came earlier (and, that shows based on the fact that it uses XML as its configuration language.. ick).

However, two things are an issue:

1) The CDDL license of SMF makes it difficult to use, or at least that’s what I was told when I asked someone why SMF wasn’t ported to Linux in 2009.

2) SystemD is it now. It’s too complicated to replace and software has become hopelessly dependent on its existence, which is what I mentioned was my largest worry with a monoculture and I was routinely dismissed.

So, to answer your question. The argument must be: IllumOS over Linux.