skysight-inc/HackerNews huggingface dataset:
Yeah firing someone who was on the engineering side is not a good look when the problems are on the MBA side.
There is so little competition, and it would be so expensive to spin something up… I could see it sputtering along for many years. Who can disrupt this? Need space X level money and research, and not sure the profit potential is as high.
They are physicists and hardware folks, right? I would expect messy code written by convoluted processes for nightmare applications, that somehow works.
No it's individual frames

https://developers.googleblog.com/2024/02/gemini-15-availabl...

"Gemini 1.5 Pro can also reason across up to 1 hour of video. When you attach a video, Google AI Studio breaks it down into thousands of frames (without audio),..."

But it's very likely individual frames at 1 frame/s

https://storage.googleapis.com/deepmind-media/gemini/gemini_...

"Figure 5 | When prompted with a 45 minute Buster Keaton movie “Sherlock Jr." (1924) (2,674 frames
at 1FPS, 684k tokens), Gemini 1.5 Pro retrieves and extracts textual information from a specific frame
in and provides the corresponding timestamp. At bottom right, the model identifies a scene in the
movie from a hand-drawn sketch."
Nice, more choices are good. I just saw that the Ollama project already has these models available (date stamp is 58 minutes ago), so I will use that rather than Colab (I live Colab, but I like to run stuff locally).
Hi alekandreev,

Any reason you decided to go with a token vocabulary size of 256k? Smaller vocab/vector sizes like most models in this size seem to be using (~16-32k) are much easier to work with. Would love to understand the technical reasoning here that isn't detailed in the report unfortunately :(.
"Carefully tested prompts" sounds a lot like "these are the lotto numbers we know are right" kind of thing? How in the world are these things used for anything programmatically deterministic?
Most immediate use: I have to google less shell syntax.
Rust chose to tie these together for a reason: https://manishearth.github.io/blog/2015/05/17/the-problem-wi...
There are bad engineers too.
He's only been on the job for two years, coming in to manage the project after the MCAS disaster. In some sense he's the easy person to eject.

I don't think the individuals really matter that much here. The point to firing executives in charge of big failures is to incentivize the ones remaining to get their ships under control before another disaster. Clark clearly failed on that front, but again the 737 MAX program isn't the end of Boeing's problems.
That's not really saying much given the number of new nuclear reactors of any fuel source the west has built in the current century. You have to build something in order to build something that runs on Thorium.
>Generally, goods and services are considered to be products.

False.

Products are products, services are services. Product si a Macbook or video game I just bough which I can return, but I can't return the cleaning service the handyman just offered on site.
Does it work if you use a prepaid credit card with the cloud providers that only have a set amount of money?
> there's no way I can get a better job in this market (even if I had the energy to practice leetcode problems to prepare for interviews), and I'm not rich enough to just stop working.

I had almost this same problem. I just got a "worse" job but for a cause I believe in. I took a big pay cut but I'm a happier person.
I would love answers to these questions too, particularly on the vocab size
I love this combination of ideas. I don’t love the Haskell inspired syntax though. I think Rust made the right call to go with more traditional syntax
Given those two tools, can you steal the car, or does that require a lot more effort for some models?
I'm convinced this happens because of technical alignment challenges rather than a desire to present 1800s English Kings as non-white.

> Use all possible different descents with equal probability. Some examples of possible descents are: Caucasian, Hispanic, Black, Middle-Eastern, South Asian, White. They should all have equal probability.

This is OpenAI's system prompt. There is nothing nefarious here, they're asking White to be chosen with high probability (Caucasian + White / 6 = 1/3) which is significantly more than how they're distributed in the general population.

The data these LLMs were trained on vastly over-represents wealthy countries who connected to the internet a decade earlier. If you don't explicitly put something in the system prompt, any time you ask for a "person" it will probably be Male and White, despite Male and White only being about 5-10% of the world's population. I would say that's even more dystopian. That the biases in the training distribution get automatically built-in and cemented forever unless we take active countermeasures.

As these systems get better, they'll figure out that "1800s English" should mean "White with > 99.9% probability". But as of February 2024, the hacky way we are doing system prompting is not there yet.
I'd argue that it went higher trust? If you look back at labor law history, for example... or read a book like the grapes of wrath....

There are interesting localized extremes. Like you can find small family farms that have 'self service shops' on a shed next to the road they're on. They rely totally on the honor system and afaik theft is minimal enough that they don't worry about it. Then you have places where you can park a car and someone will immediately break into it to steal 50 cents out of the cupholder lol.
It's a very good article. I wish I knew how to find this at the time when it was written.

I remember when I first discovered the pattern, at a job I took 10 years after this article. The codebase seemed so clean, easy to evolve and test, even for a newbie and 'half programmer' as me - my mind was blown. I was thinking - what kind of black magic is this ?!

Say you're new to programming. What's the best place today to learn about design patterns (with python examples, since it's the most used language for beginners) in an easy and accessible way ?
Great question. Maybe because the stakes are high in either case.
i don't disagree with the premise that Google should be responsible and explicitly acknowledge that the average computer-interested person trying out bigquery has no clue how sharp of a knife it is and they actually do need to be protected from themselves. I was in this boat only a few months ago. One thing I will say though is that I think the documentation is actually quite comprehensive, and personally after taking the time to RTFM and actually understand things like columnar storage, partitioned and clustered tables, etc., I was able to optimize costs quite a bit for our use case and am quite pleased with the product overall. Just takes time to learn, it's a (necessarily imo) intricate machine.
hehe, this is great, I was just (2 days ago) playing with a similar problem in a web app form: browsing books in the foreign literature section of a Portuguese bookstore!

My (less serious) ultimate goal is a universal sock pairing app: never fold your socks together again, just dump them in the drawer and ask the phone to find a match when you need them!

This seems more like a visual segmentation problem though and segmentation has failed me so far.
European Human Rights Court Rules That Encryption Backdoors Are Illegal
Parser combinators is what I've been loving in the last few years.

Pros:
* They're just a technique/library that you can use in your own language without the seperate generation step.

* They're simple enough that I often roll my own rather than using an existing library.

* They let you stick code into your parsing steps - logging, extra information, constructing your own results directly, e.g.

* The same technique works for lexing and parsing - just write a parser from bytes to tokens, and a second parser from tokens to objects.

* Depending on your languages syntax, you can get your parser code looking a lot like the bnf grammar you're trying to implement.

Cons:
* You will eventually run into left-recursion problems. It can be nightmarish trying to change the code so it 'just works'. You really need to step back and grok left-recursion itself - no handholding from parser combinators.

* Same thing with precedence - you just gotta learn how to do it. Fixing left-recursion didn't click for me until I learned how to do precedence.
> Anyone building an actual product that makes actual money that comes to the attention of Meta or Google will be sued into oblivion

No they won't and they haven't.

Almost the entire startup scene is completely ignoring all these licenses right now.

This is basically the entire industry. We are all getting away with it.

Here's an example, take llama.

Llama originally disallowed commercial activity. But then the license got changed much later.

So, if you were a stupid person, then you followed the license and fell behind. And if you were smart, you ignored it and got ahead of everyone else.

Which, in retrospect was correct.

Because now the license allows commerical activity, so everyone who ignores it in the first place got away with it and is now ahead of everyone else.

> won't sue is beyond foolish

But we already got away with it with llama! That's already over! It's commerical now, and nobody got sued! For that example, the people who ignored the license won.
IIRC there's also a particular combination of settings, not demonstrated in the post here, where it won't just give you output layer nonsense, but latent model nonsense — i.e. streams of information about lexeme part-of-speech categorizations. Which really surprised me, because it would never occur to me that LLMs store these in a way that's coercible to text.
Stability and long product lifecycles are incredibly important to them. They're pretty much the opposite of move fast and break things or deploy early/deploy often.
Ah the dominoes start to fall yet again. I wonder how many between this and the CEO this time?
That’s putting a lot of faith in society.
Big tech jobs used to be fun. "Move fast and break things". It was the ultimate job for the intelligent underachiever who didn't want to waste time on paperwork and routines.

Over the last ten years I have watched the number of PMs and middle managers explode across the industry. Executives from other industries have crept in, bastardized agile, commoditized developer work, and began micromanaging everything. You get to build less cool stuff - there's less opportunity for achievement or advancement. So now these jobs are not much different than garden variety white collar work.

I think there are a variety of valid reasons: The market capital that created unicorns is gone - and with high interest rates comes risk aversion. The NYTimes decision to adopt an anti-tech editorial policy changed public perception. Pushes for diverse hiring practices clashed with tech's original meritocracy structure. Increasing regulation. The age of the average coder has gone up and so the corps have matured too.

But more than anything, I think it comes down to nature abhorring a vacuum. The other corporations in our economy are mired by risk-averse gatekeeping admins and executives - it was only a matter of time before enough consultants and management firms made their way into the building.
IMO — it generally seems net positive for many folks to have positive sentiment towards a diagnosis and neurological profile they can’t change, especially when it’s such a large part of their internalized identity.

There are definitely cons to this, but I think “it’s a superpower, especially when directed correctly, with some downsides and quirks” is probably a better mentality than “it’s a debilitating condition that I can’t do anything about,” which can lead to negative self-fulfilling outcomes.

(personally I think something in the middle of my adhd — something like: “this has radically shaped my life in ways both positive and negative, and figuring out how to shape my life around it rather than treat it as a depressing diagnosis seems good for me.”)
It’s exactly the same thing. I don’t know why people think it’s conspiracy to provide financing with equipment sales.
I figured that was the case. I just wanted one of these folks that keep claiming it to cough up some evidence. It's a tired thing. There are lots of things to criticize Apple (and most companies) for, at least pick something that isn't imaginary.
Apple teases MLS playoffs Immersive Video for Vision Pro coming soon
< x Y | Z > w

Y takes input redirected from x, piped into Z, which outputs into w.
I opened with 'fuck off' and the bar wasn't full. 2nd message was also 'fuck off' still not full.
No, that's a meme. Clearly the problem with the door plug was a production process problem. They engineered a bad process[1] and it led to a failure. Was that due to pressure or interference from someone on the "MBA side"? Well, maybe? But that needs evidence before you can make a statement like you did, and so far we don't have it.

[1] Seems like consensus at this point is that the repair/rework review process had a hole contractors/suppliers could use to skip reviews by changing a category. Again, that might be done for "MBA" reasons but if the process allowed it it's still a bug in the process.
I often wonder if corporate lawyers just tell tech founders whatever they want to hear.

At a previous healthcare startup our founder asked us to build some really dodgy stuff with healthcare data. He assured us that it "cleared legal", but from everything I could tell it was in direct violation of the local healthcare info privacy acts.

I chose to find a new job at the time.
Bummer optimizing hiring devs on leetcode skills doesn't lead to better search result engineering.
Very cool..exciting to see you tackling the modular architecture challenge head-on, and also wrt to dynamically imported modules..would also be interesting to see some sort of IDE integration for real-time feedback directly in the development workflow. Would be nice to have a discord community around this!
How altruistic! This definitely has nothing to do with keeping the biggest court case arguments at bay.
Trying to add transparent caching to a transactional database is just a bad idea and cannot work. Anyone who says it works for them is just in the period after putting it in place and before when they realize why it cannot work.

If it was possible to just slap a cache in between you and the db and magically make shit fast, DB vendors would have done that 20 years ago. Billions of dollars a year is put into relational db development. Papers are published every week, from theoretical ways to model and interact with data to practical things like optimizing query execution plans.

Unless Readyset can point to a patent or a paper that has fundamentally revolutionized how database will be built from today forward it is going to be crap and will burn you.
I think people take issue with CEOs pretending to be experts in things where they aren't - Wolfram in physics, Musk in geopolitics and freedom of speech etc.
While I agree with the handrail sentiment, these inane and meaningless controversies make me want the machines to take over.
CANbus protocol makes this hard. Payloads are limited to 64 bits, to start with. But the payload for each message could be encrypted, even though secure key exchange would be difficult.

Even so, it would be possible, I think.
Victorinox/Wenger are good examples of a brand associated with a quality product (the original swiss army knife) that now extends that brand over to backpacks, luggage, etc.

Personally, I really like the Filson brand from the United States, but they also suffered from their core products being too-good, ownership changes eventually to a private equity fund, and ended up being driven into a lifestyle brand with a variety of otherwise unrelated product lines and collaborations (e.g. t-shirts) which often get manufactured overseas with lesser quality of materials and construction.

Another example might include other American "heritage" brands of footwear, such as Red Wings and Wolverine; they still make and sell their heritage products at a premium price but have been driven to use their brand to sell other, lesser quality goods with better profit margins.
It could be side-splitting fun to write a 'no.c' and thus show that it's easier and shorter to do no than yes.
Not arguing the earlier points or saying this is relevant - but - here in Kansas, kinda known for it's wind, it usually dies down around sunset. We do get wind at night sometimes but we get a lot more during the day.
I have more faith in society than I do the vultures eating away at it, at least.
YAML 1.2 addresses several of those:

- Duplicate keys are not allowed

- The fallback schema gives you no Implicit Typing and Direct representations of objects for free (the former explicity, the latter by restricting which tags are allowed). Schemata in general allow for doing the "right thing" for your domain more easily.
From the Gemini 1.0 Pro API docs (which may not be the same as Gemini 1.5 in Data Studio): https://cloud.google.com/vertex-ai/docs/generative-ai/multim...

> The model processes videos as non-contiguous image frames from the video. Audio isn't included. If you notice the model missing some content from the video, try making the video shorter so that the model captures a greater portion of the video content.

> Only information in the first 2 minutes is processed.

> Each video accounts for 1,032 tokens.

That last point is weird because there is no way a video would be a fixed amount of tokens and I suspect is a typo. The value is exactly 4x the number of tokens for an image input to Gemini (258 tokens) which may be a hint to the implementation.
Is it legal to freeze children?
I had exactly the opposite reaction. Tools like flipper zero are trivial. Banning these make as much sense as banning the next designer drug. Yet that's the idiocy we default to, and the logical conclusion is the "War On Electronics."

Manufacturers have been reckless, featurizing their products and ignoring basic expectations of their customers. It isn't unreasonable to expect that some low life knucklehead can't just toy with your car for a minute using a ~$5 transceiver and drive way without so much as an alarm going off.
I mean, I asked it for a samurai from a specific Japanese time period and it gave me a picture of a "non-binary indigenous American woman" (its words, not mine) so I think there is something intentional going on.
Not to minimize what SpaceX has done, but building reusable, reliable, relatively-inexpensive rockets is a far cry from building a sustainable colony on another planet.

Musk may be able to eventually manage the latter, but I don't think success at the former is a reliable indicator of that.
Tales of Life: The magic of reading and rereading Bernard Malamud
Despite that being in their blog post, I'm skeptical. I tried uploading a single frame of the video as an image and it consumed 258 tokens. The 7s video was 1,841 tokens.

I think it's more complicated than just "split the video into frames and process those" - otherwise I would expect the token count for the video to be much higher than that.

UPDATE ... posted that before you edited your post to link to the Gemini 1.5 report.

684,000 (total tokens for the movie) / 2,674 (their frame count for that movie) = 256 tokens - which is about the same as my 258 tokens for a single image. So I think you're right - it really does just split the video into frames and process them as separate images.
I saw two errors, both of which are trivial to hide.

One of them was only visible after someone else pointed it out to me.

The other was just about in the realm of things I've seen in the pre-AI era where single fixed camera perspectives create odd visuals despite capturing reality.

So no, they are not major.

"Major flaws" look like last year's video output, whose subject has only just gotten around to parodying: https://youtube.com/watch?v=5S0inm1bR08
The last point is a hard one when the perpetrator is a 11 year old kid who watched a TikTok video online on how to steal a Kia/Hyundai.
Among other things, there is that ugly presumption that health insurance has to be tied to your employer. This is an interesting and almost peculiarly American viewpoint, because that's the status quo we frogs were slowly boiled in across decades and generations until few remember there's an option to jump out, that it isn't a "day spa" and we're all likely to die of this problem. Why should this be a concern of our employer and how much they think our "work" is worth? Why have we allowed this "blackmail" to rot all around us and settle into feeling so normal? Why do people that don't "work" deserve to die of preventable diseases? What makes them so undeserving/undesirable of health? Why are health insurers for-profit companies seeking so much greed and wealth at the expense of actual public health?

Is this the society we really want to live in where we are all (yes, even Billionaires) three bad months away from homelessness and six bad months away from dying of something preventable?

I assume that "the ability to deliver many plastic electronic consumer goods that would not otherwise be available" is a joke in the face of that existential terror, but I cannot tell any more on sites like HN.
It is really hard. China, Russia and Japan have tried state sponsored schemes without success. Bombardier of Canada had to throw in the towel, and Embraer of Brazil almost did.

Part of the problem is also that airlines have been very good at squeezing the duopoly while demanding ever more. The competition, if it manages to get a plane in the air, usually isn’t as fuel efficient and so the airlines have mostly not been interested.
But I can find porn and racism using Google search right now, how is that different? You have to disable their filters, but you can find it. Why is there no such thing for the google generation bots, I don't see why it would be so much worse here?
In Andy Weir's The Martian one of the characters uses a mixture of sugar and liquid oxygen as an IED. Loads of energy in sugar. Glycerin is also quite energy dense. I used to do chemistry demos for high school chem classes and the potassium permanganate and glycerin demo was always a spectacle.
> but self-promotion on HN should follow strict rules and if this is indeed promotion, it is breaking the rules.

What rules are you referring to? This is what the HN guidelines say:

"Please don't use HN primarily for promotion. It's ok to post your own stuff part of the time, but the primary use of the site should be for curiosity."

https://news.ycombinator.com/newsguidelines.html

Doesn't seem very strict to me.
> If meta keeps spending tens of millions of dollars each year to release free AI models it might seem like there is no moat,

As well as the point being that Meta (and Google) is removing the 'moat' from OpenAI and other cloud-only based models.

> but under normal circumstances wouldn't the cost to develop a free model be considered a moat?

Yes. Those that can afford to spend tens of millions of dollars to train free models can do so and have a moat to reduce the moats of cloud-based models.
What point are you trying to convey? You were built for software engineering solely because you can't be maimed by software?
thats quite the parallelization! but if it gets us to a voice assistant that I can interrupt, I think they'll be making tons of money off it.
This is a fantastic use of the D-Wave technology and really highlights the ability to use annealing for a wide range of use cases. I'm definitely going to follow this development closely!

It will be interesting to see how this works on the Advantage2, especially when it moves past the prototype stage. The greater connectivity between qubits may allow for an even better demonstration.
Do you mean lisp? If yes I agree