skysight-inc/HackerNews huggingface dataset:
People already wear earbuds all day. Go to any college campus and tons of those kids never take them out, even when taking with each other. Lots of people at work keep them in most of the day. I am pretty sure I wear my AirPods Pro more than I wear my glasses.

Voice recognition is already really good but people barely use what their devices can already do. For these short interactions you are talking about, our phones can already do this and people rarely use it. Our home assistants can already do much of what you are talking about and uptake has been abysmal because people don't like it.

The smart phone and smartwatch paired with earbuds already does what you are wanting. Hell the HomePod/alexa/google home already do much of what you are taking about and people don’t use it.
If you care about inference time, then you'll do two things.

1. Train a student model from your fine-tuned model. (Known as "knowledge distillation").

2. Quantize the student model so that it uses integers.

You might also prune the model to get rid of some close-to-zero weights.

This will get you a smaller model that can probably run OK on a CPU, but will also be much more efficient on GPU.

Next: architect your code so that the inference step sits behind a queue. You do not generally want to have the user interface waiting on a inference event because you can't guarantee latency or resource availability, and your model's inference processing will be the biggest slowest thing in your stack, so you can't afford to overprovision.

So have a queue of "things to infer", and having your inference process run in the background chomping through the backlog, storing the results in your database. When it infers something, somehow notify your front-end clients that it's ready in the database for them to retrieve. In this model, you can potentially run your model somewhere cheaper than AWS (e.g. a cheaper provider, a machine under your desk).

Or, for the genius move: compile the model to ONNX and run it in a background thread in the users' browser, and then you don't have to worry about provisioning; users will wonder why their computer runs so slowly though.
On the note of contributing to open source: please contribute to a project you personally use and care about.
> The neighborhood is what it is.

I did go out of my way to describe it as “roughest” and not “worst”. Least compatible with the image of perfection projected by the typical tower-dwelling corpo? :)

In fact I have a lot of fond memories from the mid-2010s of stopping by the weed lounge on Jessie for a Volcano bag and a few floors of Isaac Rebirth on my PSVita any time my afternoon train was significantly delayed. Alas that just closed too for the same reason: https://sfstandard.com/2024/02/02/san-francisco-cannabis-dis...
It's over 20 years too late to be making moves like this.

The PRC joined the WTO in 2001. That was the ballgame.
It might not be technically correct that they learned the full set of Chinese grammar in a week, but I can imagine one week is sufficient for a beginner to get the basics and start reading/speaking/writing the language and absorb the other nuances or nitty-gritty details through everyday usage.

I mean, I'm pretty much a Chinese/Cantonese native user, so I can't be sure about that since I never "learned" the language in a classroom setting, but my impression is that this short period of learning grammar for Chinese language leaners is quite typical.
> There's little faith that public projects have the expertise to actually get it done and make it work.

This ends up being self-fulfilling. People don't trust the government, so they suffocate the project in fixed payscales and low-bid rules and endless reviews, and so the government can't get anything done, and so people don't trust the government...

> At the end of the day you need some people who actually know how to do the job rather than just argue over plans and subcontract twelve levels deep.

Right - so you need to be able to hire those people and pay them something close to what they're worth, or build up that expertise over the long term by having a steady pipeline of projects and training people as you go. But voters don't trust these governments enough to empower them to do that.
My understanding is this was a foreclosure auction and that the lender bought it (but I'm not actually sure if it was the lender, because articles are saying it was the 'special servicer).

At California foreclosure auctions, my understanding is the lender will usually bid up to the loan balance or their estimate of what they can sell it for with some marketting and time. That it sold for $6M to the lender tells you that nobody was prepared to make an offer on it given the time constraints, not that the fair market value is $6M. The lender will operate it and prepare it for sale and buyers will be able to take their time to do due dilligence etc, and most likely it will sell for somewhat more than $6M.

The purpose of a foreclosure auction include clearly establishing a change of ownership. If the lender pursued judicial foreclosure and a deficiency judgement, the fair market value will be litigated some time after the sale, and the borrower may need to make up the difference between the loan balance and fair market value.
That it's an emotional reaction to someone using easily available material to train a program rather than themselves.

I always saw it as a technological consequence of allowing people to view their work; training a model is no different to an individual looking at it.
Are you saying you can't listen to music in a Tesla without a subscription?
Ah, by risky I meant software developed without paying customers up front.

I am curious if there is a open source type model for getting a higher return for doing riskier work, as economics would suggest is fair and also helpful.

That is obviously a typical closed source situation, but people find creative solutions.

Not talking about selling services, but somehow compensating for writing the code after the fact, risk adjusted, while keeping the code itself free. Might need a temporarily hybrid license to accomplish this. I.e. the code is obligated to become free, after some fixed license fees have covered the work cost and risk.
That is basically what I hear in my head everytime I see that flag
Convenience and familiarity.

I'm ashamed to admit, but I too expect to see screenshots and features listed inline on the landing page; it's been a common practice in the last 10 years or so.

> Personally I don’t see the difference between scrolling down or pressing buttons

Scrolling is untargeted, you just move the wheel or drag your fingers back and forth. Pressing buttons requires you to identify such elements, target and then click them. Both sound trivial, but they're different classes of trivial.
It's not so much that it's cynical, it's also that it steers the thread towards an unpleasant and already well-tread line of political bickering where both sides are talking past each other.
Does anyone have an archived link?
it is prob meant to be used through OpenVINO which is open-source, so I don't expect an obscure blob.
A lot of the answers to your question focus solely on the infra piece of the deployment process, which is just one, albeit, important piece of the puzzle.

Each model is built using some predefined model architecture and the majority of the LLMs of today are the implementation of Transformer architecture, based on the "Attention is All You Need" paper from 2017. That said, when you fine-tune a model, you usually start from a checkpoint and then using techniques like LORA or QLORA you compute new weights. You do this in your training/fine-tuning script using PyTorch, or some other framework.

Once the training is done you get the final weights -- a binary blob of floats. Now you need to use those weights back into the inference architecture of the model. You do that by using the framework which is used for training (PyTorch) to construct the inferencing pipeline. You can build your own framework/inferencing engine too if you want and try to beat PyTorch :) The pipeline will consist of things like:

- loading the model weights

- doing pre-processing on your input

- building the inference graph

- running your input (embeddings/vectors) through the graph

- generating predictions/results

Now, the execution of this pipeline can be done on GPU(s) so all the computations (matrix multiplications) are super fast and the results are generated quickly, or it can still run on good old CPUs, but much slower. Tricks like quantization of model weights can be used here to reduce the model size and speed up the execution by trading-off precision/recall.

Services like ollama, or vllm abstract away all the above steps and that's why they are very popular -- they might even allow you to bring your own (fine-tuned) model.

On top of the pure model execution, you can create a web service that will serve your model via a HTTP or gRPC endpoint. It could accept user query/input and return a JSON with the results. Then it can be incorporated in any application, or become part of another service, etc.

So, the answer is much more than "get the GPU and run with it" and I think it's important to be aware of all the steps required if you want to really understand what goes into deploying custom ML models and putting them to a good use.
Its always the management consultants and finance guys that ruin things ...
I built mine using a Hydreon Rain Gauge sensor (RG11 in my case) and combined it with an off the shelf wind sensor from AliExpress, presumably sold by Adafruit's supplier, which closes a reed switch every rotation. Everything is powered through PoE, controlled by wESP32. I spent a couple hundred bucks at most including all the mounting hardware.

It all controls an aluminum "awning" in my house that's supposed to open above certain wind speed, close when it rains.
Take a look at these projects: https://aosabook.org/en/

Should give you a good overview of interesting projects to potentially work on.
Powerful in terms of productivity. The occasional N+1 query problem here and there isn't a big issue for many projects and means you can launch 10x faster than someone using some other technologies. If you're successful, you can easily write raw SQL and optimize as needed.
Free trade != free domestic market and capitalism.

Furthermore even free trade (which the US doesn‘t exactly practice) does not mean allowing foreign adversaries (which China arguably is) to undermine the political system which is democratic (which they may not do yet but there is no need to enable them to being able to choose to do it later).
Thanks for sharing your thoughts! I agree, knowing when to start enforcing payment policies is key to keeping cash flowing. How do you decide the right time to take action? Do you use any tools to help track overdue invoices and handle them efficiently?

I've looked into over 300 AR platforms on tracxn.com, especially the top 20. It seems like while they handle some parts of the accounts receivable process, like collecting payments and preventing delinquencies, they don't fully cover everything—especially when it comes to needing legal action or debt collection. It feels like there’s still a gap there.

Also, I'm curious what everyone else thinks about using tech for this. Do you guys build your own tools, or do you use third-party services to manage your accounts receivable?
it's a series:

- part 2: https://www.mostlypython.com/django-from-first-principles-pa...

- part 3: https://www.mostlypython.com/django-from-first-principles-pa...

also here's the repo: https://github.com/ehmatthes/django-first-principles/
There's lots of other posts: [0] (60 points, 44 comments), [1](42 points, 27 comments)

[0]: https://news.ycombinator.com/item?id=40139681
[1]: https://news.ycombinator.com/item?id=40139794
It seems to be mostly polished.

I don't like how it's generally advised to use an SSD, I think Pi software should be SD optimized.

A lot of third party stuff uses some cloud API that breaks constantly, not much anyone but the manufacturer can do about that.

I think their internal APIs are a bit excessive. They have different entity types for everything as opposed to basic data types with compostable metadata.

That also lends itself well to constant tweaks and breaking changes...

I don't see why a garage door needs to be any different from a light switch. One might need an extra flag to require confirmation prompts, the icons are different, but... It's just a thing that can be in two different states.

It seems like a huge amount of the code just deals with different data types.

But then, I've never made a serious attempt to use HA, I just use YoLink's native platform plus my own system for CCTV.
Yes, at some point. It's the IDE I use myself so I definitely want one, but it's also one of the hardest ones to write a plugin for, so I haven't gotten to it yet.
Ah, sorry. It wasn't clear that SQLA meant SQLAlchemy in your first comment.
Tap water at a restaurant might be free.

I’ve seen bottled water for €1 for 0.5L while 0.75 of wine is €0.95 at the same store.

Cans of Coke Zero are typically about €1 too at retail prices.
They are surging from Windows_CE_ to FreeBSD, the headline unfortunately omits the “CE”.
Perhaps like they did for their silicon on desktop, they are going for performance parity with a fraction of the power requirements? Power supply driving all those GPUs is currently most AI companies biggest costs IIRC
> …the biggest thing was we didn’t have good tests or good types, so I had to do a lot of work to do e2e testing of stuff whenever I wanted to ship stuff

Shouldn't solve that one by itself after a couple iterations? If one's really testing what they wrote + surroundings because there were no tests, there will be tests over all of the codebase very fast.
Brand Recognition API utilizes advanced AI-driven image processing to meticulously analyze images for brand presence. It adeptly identifies various brand marks and logos, and efficiently provides a detailed JSON output of the elements detected in each image. Distinguishing itself from other logo detection technologies, our API requires no additional setup to accommodate new logos, offering seamless integration right from the start. It supports an extensive catalog of brands and trademarks out-of-the-box and includes sophisticated algorithms capable of autonomously recognizing and integrating unknown logos, ensuring comprehensive coverage and adaptability in dynamic market conditions.
Hemmelig: Paste a password, confidential message, or private data
just move on! see if you can start something new and ask those people to join you.
Your writing makes it seem like you are a vulnerable and confused person. I'm not the one to be afraid of. The people you are spending time with online are a potential danger to you.
Happens on mine too.

I discovered not later than yesterday that if I plug a Nintendo Switch to one of the USB ports (to recharge it), the interface disappears.

And this is still one of the least garbage infotainment I had to endure to this day.
At the one man band level, it works fine if it is a hobby. The problem is figuring out how to make a living supporting a small project.
Boring mathematicians of the school of actual concrete formalisations level the criticism that his Principle of Computational Equivalence is never given a formal definitive statement and is more of an aspirational feel good kind of fuzzy wuzzy thingy.

eg: Lawrence Gray in his 12 page review: https://www.ams.org/notices/200302/fea-gray.pdf

Cosma Shalizi's infamous Rare Blend of Monster Raving Egomania and Utter Batshit Insanity review: http://bactra.org/reviews/wolfram/
In practise the flight is much slower due to security etc, and having to get to and from the airport.

For example, I wouldn't consider taking a flight from Copenhagen to Århus (40 minutes vs 2¼ hrs) as the saving is wasted on waiting, and flying is much less comfortable.

(That's an extreme example for the distance, as it crosses a sea.)

It's certainly a competitor, but definitely not the preferred option.
I don't own my own car here, but whenever I ride taxis or rent cars in Japan I noticed that they almost all appear to have aftermarket infotainment units. This makes sense now!
You just choose a superlong playlist before starting the car and then play it randomly. You don't have to interact with the phone.

Last time I had a car I had an old mp3 portable mp3 player constantly hooked up to the car with 4GB of music inside. I would just hit play and drive and would only adjust volume from the steering wheel if I needed to. If I had a car again I would probably do the same, that is the lowest distracting way to have music in your car.
Openrouter
Trump admin tried to ban it in 2020 via Executive Order
> it is twice as fast as quicksort for large sets of string

Define large.
Interesting as I find the complete opposite for myself; I love the easy access to all options at the top instead of doom scrolling for possible information usually hidden between horrible animations that slide in and out, breaking natural scrolling etc.
Don't forget where your paying customers came from.

They didn't find your closed source plugins, they were funnelled in from the open source project. The split license plugin model works because both sides of it are useful to different groups of people.

You get to upsell your free users additional features or support.

But more than any of that, all users complain, even paying ones. Especially paying ones. Don't kid yourself into thinking going fully closed will stop that, the difference is you'll just be dealing with fewer people. That's not as good as it sounds.
MSYS2
Ask HN: Why do so many developers hate DORA metrics?
DORA haters and lovers are spread on about 50-50 basis.

Haters say they are gameable & simplify a highly complex process as software delivery into 4 numbers whereas DORA lovers feel the visibility they add based on hard data is a game changer.

Have you implemented DORA in your org? What kind of an experience has it been for you?
There are lots of third-party providers that will host your fine-tuned model for you, and just charge per token like OpenAI. Here are some of the providers I've personally used and would vouch for in production, along with their costs per 1M input tokens for Llama 3 8B, as a point of comparison:

- Replicate: $0.05 input, $0.25 output

- Octo: $0.15

- Anyscale: $0.15

- Together: $0.20

- Fireworks: $0.20

If you're looking for an end-to-end flow that will help you gather the training data, validate it, run the fine tune and then define evaluations, you could also check out my company, OpenPipe (https://openpipe.ai/). In addition to hosting your model, we help you organize your training data, relabel if necessary, define evaluations on the finished fine-tune, and monitor its performance in production. Our inference prices are higher than the above providers, but once you're happy with your model you can always export your weights and host them on one of the above!
But as you've implicitly noted, you cannot see something without looking. That would be physically impossible.

You can also use "look" to emphasize that focus does not exist; one of the sentences I've collected for interesting use is "He stared at the page, not seeing it."

In that case, there is no possibility of a page being overlooked or otherwise missed. What the sentence is telling us is that although "he" is directing his eyes at the page, his mind is on something else, so "seeing" never occurs.

The difference between "see" and "look" has nothing to do with focus. It is what I noted in the discussion of Mandarin - success. Seeing is the goal of looking.

Note that this phenomenon where native speakers have no trouble obeying a distinction that their language requires, but come out with total nonsense when asked why they choose one form or another, is completely characteristic of grammatical rules, and not characteristic of vocabulary selection.
Ugh, CarPlay 1 is exactly the division of responsibilities I want. I don’t want Apple anywhere near the actual driving functions and instruments. It takes a long time for my car to connect to CarPlay and it’d be super distracting to have the instruments suddenly change to Apple’s as I’m driving.
Make stuff. Make a requirement for yourself that you will enter unknown territory.

Revisit your old code often, and improve it.
It is amazing to see that the recommendation "put them on Apple, enable parent control, it just works" is countered with an argument from an Android user who does not understand the point: using Apple vs. Android / Windows is about how the product make you feel.

Hypothesis: Android UX is more inconsistent compared to IOS and some inexperienced users get anxiety because of that.

Hypothesis: on Android and Windows it is much simply to get maleware etc. then on Apple, because Apple can be closed down completly (and this is great!)

Hypothesis: on Android and Windows you can damage the account/system very easily with a non-admin User, on Apple this is much less likely

Hypothesis: on Android and Windows the amount of admin work needed to keep the device alive is much higher then on Apple
A foreclosure auction is an ownership transfer that triggers a reappraisal. So this building will likely see a big jump (unless it had an uncapled appraisal recently). Most likely the appraised value will be more than the foreclosure sale price, as a foreclosure sale doesn't meet the free market value conditions. The sale was forced, and buyers don't have time to complete due dilligence between the announcement and the sale.
Progress Quest: The original idle game
For some reason, I didn't have a Reply link available at your comment for hours.
> When being condescended to it's your choice to either be incensed or reflect

Or just chuckle at and ignore the misinformed idiot doing the condescension
and move on with your life if appropriate.
I notice that Google Maps does very poorly on my iPhone 13 Pro with the multi-level roads, like riding around in the tunnels under Tokyo or on the roads with highways above the local roads, whereas builtin navigation units usually have no problems with this. I also find their directions to be much harder to follow than the built-in navigation units when riding around the major roads where turning right requires you to exit to the left for instance. Also, Google Maps fails to provide the variety of route options with fine-grained toll-booth costs, that all navigation units I've used in the last 5 years have gotten spot-on.
As a CTO, I have to admit the fresh perspective of HTMX is quite refreshing and inspiring. It might be a step in the right direction, as they have identified a niche market where simple applications don’t have a lightweight library that comes without the decorators and extensive ecosystems which can overcomplicate the process. However, it is still at its nascent stage and the future of HTMX would greatly depend on how the community drives forward.
Is it that bad to have been a mgmt consultant? My goodness
To add to this, Microsoft is really really good at understanding businesses, in a way Google will probably never be I think.

Having on premise hosting options for Exchange and all their core services is an example of that, even as they're also pushing for 365 in the cloud. I remember them being earlier than GCP to deal with GDPR and the in EU requirements as well but my memory might be failing.