skysight-inc/HackerNews huggingface dataset:
Yeah but you raise capital, dont have a boss, and get some psuedo elite social status. You get to look down on others, tweet on twitter, act like you had a hand in developing AI. You get to code random software you come up with off the top of your head, try to the newest frameworks. You develop intuition for understanding capital markets, innovation, and what to value. You get to hire people that work the same hours as you, and are probably equally as talented, except they get 10-20x less equity. What a great way to be employed.
Don't get caught up in the hype. The technology is becoming commoditized, and only startups with unique advantages will survive. Look for startups with proprietary data, special algorithms, or deep domain expertise. Avoid ones that are just gluing together APIs or building generic applications. And don't chase the hype train. Invest in startups with a real chance of success.
NNs are typically continuous/differentiable so you can do gradient-based learning on them. We often want to use some of the structure the NN has learned to represent data efficiently. E.g., we might take a pre-trained GPT-type model, and put a passage of text through it, and instead of getting the next-token prediction probability (which GPT was trained on), we just get a snapshot of some of the activations at some intermediate layer of the network. The idea is that these activations will encode semantically useful information about the input text. Then we might e.g. store a bunch of these activations and use them to do semantic search/lookup to find similar passages of text, or whatever.

Quantized embeddings are just that, but you introduce some discrete structure into the NN, such that the representations there are not continuous. A typical way to do this these days is to learn a codebook VQ-VAE style. Basically, we take some intermediate continuous representation learned in the normal way, and replace it in the forward pass with the nearest "quantized" code from our codebook. It biases the learning since we can't differentiate through it, and we just pretend like we didn't take the quantization step, but it seems to work well. There's a lot more that can be said about why one might want to do this, the value of discrete vs continuous representations, efficiency, modularity, etc...
I suspect the main effect of "modern practices" is to make it much easier to make mistakes at scale. Maybe not the exact same mistake as here, but some other one.

By the way, have we heard from Google about how they managed to roll back 6 months of customer data yesterday?
Despite its success, it still had a lower attach rate than the Famicom Disk System. In terms of software, after the first year no one could make any good money selling Kinect titles.
What I inferred from the article is that this is a step towards fusion. During their research, they discovered a better way to create radio-isotopes that are used in medical procedures. It seems to me they will sell this technology/system to fund their fusion research. It’s a good idea. Like - what does SkyLink have to do with going to Mars? Exactly this. (It is funding Starship development).
Now I'm imagining a self destructing roborock vacuum burning down my house when China goes deep in anti US territory.

Best policy I abide by is to prevent any data from exiting my network or remote control period. I don't care who is spying.
A great typing system is generally a good thing if many people work on the same large project. I love how nim typings gets out of your way but are flexible enough to not tie you down.

That being said - by Rich Hickey - typing also add a lot of complexity and non-optimal bindings between stuff. Untyped incremental development with just simple scalar types, and a single list, map and set type is wonderful. Large refactorings, not so much.

Adding gradual typing to a project often gives you the worst of the two worlds. You still fear changing stuff, _and_ have lots of overhead doing all the typing. Either your project is fully type checked at compile time or it isn't.

Python match statements are useful for checking structure and de-duplicating the container name:

result = {}
for temperature in temperatures:
match temperature:
case {"city": city, "temp": temp}:
if temp >= max_temp:
result[city] = temp

Oh, and python typing has come a long way:

from typing import List, TypedDict, Dict

class Temperature(TypedDict):
city: str
temp: int

def filter_temperatures(temperatures: List[Temperature], min_temp: int) -> Dict[str, int]:
result = {}

for temperature in temperatures:
match temperature:
case {"city": city, "temp": temp}:
if temp >= min_temp: # Most of the time >= is what people mean.
result[city] = temp
case _:
raise ValueError(f"Wrong temperature format: {temperature}")

return result

my_temperatures: List[Temperature] = [
{"city": "City1", "temp": 19},
{"city": "City2", "temp": 22},
{"city": "City3", "temp": 21},
]

print(filter_temperatures(my_temperatures, 20))
print(filter_temperatures([{"typecheck error": "and runtimeerror"}], 20))
If SEO was so easily gamed, GOOGLE competitors would’ve sidelined it by offering more relevant results.

This is clearly not the case. Google heavily prioritizes users actually finding what they are looking for.
The scenario is a customer opens a chat box on your website and asks some questions for the LLM.

You wouldn't expect your customers to search your internal Confluence pages. The LLM would be trained on all of your internal documentation which is not exposed publicly.

Hallucination is mostly a problem with insufficient training with the current generation of LLMs.

Edit: Maybe not "all" of your internal docs should be exposed via LLM. But the idea is this is an interactive support agent for customers.
Well, they don't let you sell snake oil in their jurisdiction, so that's to be expected.
Climate Summit: As in a bunch of 1%er billionaires fly their private jets to eat expensive food and drink lavishly while figuring out how to lecture everyone else about climate change?
OpenAI: Increased errors across API and ChatGPT
zaf 14, ngf uf ue zaf ea tmdp fa ruzp agf itmf dafmfuaz kag pup
Indeed. TV is just one of many possible negative passive addictions.
This. Increasing renewables without decreasing non-renewables just means... more net emissions. I think statistics on usage of non-renewables are a better indicator of progress than stats on usage of renewables
But how do you read "How to Read a Paper"?
> Folks still enjoy doing woodworking and make boxes, tables, benches, etc. -- even though they could easily buy them new, used, or for pretty cheap (say, at IKEA).

For what it's worth, many woodworkers prefer making their own stuff because it is of far higher quality than what you can buy at IKEA (and similar stores). With the exception of extremely high end and expensive stuff, most furniture is complete junk. Making a coffee table out of a solid slab of walnut, for example, will last a lifetime compared to the cheap MDF table at IKEA.

Obviously I nor anyone else can predict the future, but I wouldn't be surprised for a similar divide to appear with AI generated software vs. completely hand written software where the hand written software is of higher quality for those that desire such things.
when i logged in to my aws panel this morning, Q popped up with example prompts that make it look like this is what it's supposed to do:
https://imgur.com/a/PXGAv27

but when i tried "why can't i ssh into my instance named test-runner", it couldn't tell me the instance is stopped. all it can do is give me a link to the reachability analyzer.
> I really liked ThreadX when I was working with it a while ago. Calling it an "operating system" is charitable in the sense that it's an interrupt service routine and a bunch of functions to handle 'creating threads' and managing memory allocations.

Yes, that's called an RTOS.
I did enjoy most of those games, but wouldn’t use them as examples of equivalents of Half-Life. Some did some things better than Half-Life but others were worse in every category and were superseded (e.g. Unreal.) Great list of memories!
Microsoft knew add-ons simply do not work long-term. That's why they put a Kinect in every Xbox One's box. Didn't solve the problem of everybody was over with the concept though.
>How about we first just get rid of the coal power plants and replace them with nuclear/renewables?
I disagree. I think the Cybertruck is going to fundamentally change what a pickup truck is and immediately antiquate the F-150-style truck that we all know and (were kind-of forced to) love.

This is validated by the absolutely insanely long line queueing up to buy this thing.

I predict that we'll see many more Cybertruck looking trucks in five years, just like we're seeing many more Model Y looking EVs now.
It's rad. I use it for everyday expenses. I have it set up as a shared card with my spouse, we each have our own physical and digital cards. The integration with the Apple ecosystem is pretty great if that's what you are into; we get notifications on each other's transactions, and the categorized spending breakdowns in the wallet app help us with budgeting. Paying credit card bills is easy with the app. Disputing a charge is easy with the app.
To add contention: if you find LLMs are super useful for helping you do your job, you should start looking for a new job.

Not necessarily a completely different job, just one where AI won't be able to help all that much without another technological breakthrough, like working with large (several million LOC) codebases.
Humidity is unlikely to help: I have temperature/humidify BLE sensors all through my house and humidity varies wildly. You'd have to do some sort of calibrated long-term machine learning thing to maybe pull out the data.

Much better would simply be digital water meter tracking (which is still amazingly hard to actually do) since when all the taps are off, if you still have substantial water use then you probably have a leak (I would really love a decently accurate ESP-based water meter with like, Sharkbite fittings on it so I could check the water flow out of all my taps or something).
I was of the opposite opinion--does OpenAI's paid services prevent your queries and data from being used internally?
Forgot the link: https://blog.acolyer.org/archives/
the difference is that runway allows you to generate a few seconds versus zero for pika
Too late to edit but I also use ublock origin. I feel like that couldn't be it or it would've made the news already...
I don't get the Intel example. That business has been a duopoly since the 90s, but he's using it as an example of something that won't be able to create and maintain a large advantage for decades?
Good SIMD code requires careful consideration of how your data is laid out in memory. This makes auto vectorization really difficult since the compiler can’t fix your data for you outside of very local contexts
My friend Ben has an almost unhealthy love of Regex. I've learned a lot from his blog. When he said on X that he used Regex every single day I thought to myself what a great idea for a blog post.

He is also coming out with a book on feature flags fwiw. It will be on my holiday reading list.

https://featureflagsbook.com/
What exactly is your plan OP?

Here's the common way to work through this scenario:

Introduce Definition of Done for all coding tasks

Introduce NFRs

Introduce 2-week Sprints

Introduce product owners, standups, demos, retros
What if it was fully opensource and self-hostable?
> but those do move slow anyways, it's not WebTorrent's fault

Given how complicated WebRTC is, I wouldn't put the blame on torrent clients either. libwebrtc by Google is the de-facto standard, and afaik you need to compile all of it (including video and audio codecs) even though WebTorrent only cares about data streams.

Even for Node.js, which should be an easy choice since webtorrent is written in JS, your choice is to either use wrtc (native addon that has to either be built from source or use a prebuilt binary - this is what webtorrent-hybrid uses - and this library hasn't seen an update in last 3 years) or electron (which bundles libwebrtc as part of Blink engine - afaik this is what webtorrent-desktop uses).

I wish there was a better web API for P2P traffic - sadly WebTransport is not meant for P2P use cases, i.e. doesn't punch firewalls etc. Then we could see some real improvements done to P2P ecosystem, instead of everyone wasting time on figuring out how to build, use and ship libwebrtc.
Earlier post https://news.ycombinator.com/item?id=38429603
How's that different from any other tech startup?

Tech and software have always been a commodity. Twitter is barely more than a CRUD. You always had to build your moat, i.e. network effect or data.

The only difference is whereas we used to do "tech" with "algorithms" now replace that word with "AI", and it works a lot better. Seriously, replace all instances of "AI" with "algorithms" in this article and it could've been written 20 years ago.

IMO very empty virtue signaling article.
That's why it is revolutionary :-).
reminds me of Brat Pitts famous role in Snatch
Anything currently private that these companies can't access and train their models on is the one valuable competitive advantage you have going for you, giving them access to it for a bit of convenience seems short sighted.
>> Groening has also said it's pretty much in Oregon, especially since so much in the fictional town is taken from there, where he grew up.

> Well yeah, I stated he grew up in Portland in the comment you are replying to and asking that question...what the heck?

You did not.
Welcome to Amazon!
Ah yes, the panspermia making tentacle sex possible hypothesis.
Has anyone here a usecase which would perform better with this new S3 Express Tier?

And a second question, would it be worth the 8x times surcharge?
Intro to Large Language Models (Notes on Karpathy's Talk)
> Technical documentation is probably one of the worst usecases for GenAI, I'm not sure why so many companies are rushing to add it.

Why?
Designing / building an entire modern(ish) SoC is an order of magnitude different than building a microcontroller (or even something as ambitious as RP1)—I don't think it's impossible for Raspberry Pi someday, but certainly not at their current size / staffing!
Could you disclose where you work, or some of the orgs you see yourself working at?
Use LLMs to package libraries for Lisp, then! Ecosystem size won't be Lisp's barrier to adoption anymore.
I doubt that having a -1 in the metric is the defining characteristic of a time dimension, I could have a static universe without time and still a -1 in the metric. As I said, I am not sure what truly makes time time, but the sign in the metric seems not sufficient, not even sure if it is necessary.

Are you sure that it is impossible to build something consistent on top of denying the law of identity?
Increasingly I think the answer to things like this is different divisions. Have an AI-supported leaderboard, have a Cyborg/Pharmacist Olympics, provide roughly equal venues so that people self-bifurcate. You won't stop all cheating in the non-augmented divisions, but you greatly reduce the incentives by providing alternative outlets. You also getting much better data to identify what augmented activity looks like (since it is done the open) to stop a lot of the cheating if it occurs.
NumPy roadmap:
https://numpy.org/neps/roadmap.html :

> Improvements to NumPy’s performance are important to many users. We have focused this effort on Universal SIMD (see NEP 38 — Using SIMD optimization instructions for performance) intrinsics which provide nice improvements across various hardware platforms via an abstraction layer. The infrastructure is in place, and we welcome follow-on PRs to add SIMD support across all relevant NumPy functions

"NEP 38 — Using SIMD optimization instructions for performance" (2019)
https://numpy.org/neps/nep-0038-SIMD-optimizations.html#nep3...

NumPy docs > CPU/SIMD Optimizations:
https://numpy.org/doc/stable/reference/simd/index.html

std::simd:
https://doc.rust-lang.org/std/simd/index.html

"Show HN: SimSIMD vs SciPy: How AVX-512 and SVE make SIMD nicer and ML 10x faster" (2023-10)
https://news.ycombinator.com/item?id=37808036

"Standard library support for SIMD" (2023-10)
https://discuss.python.org/t/standard-library-support-for-si...
That's not why. Template processing happens during processing of the translation unit, so it would be expensive even if you only had a single TU in your build. It's true that a template has to be reprocessed for each instantiation, however, that's not merely from one TU to the next, but even inside each TU! For every distinct value of T for std::vector<T> in a single TU, the compiler has to process and generate std::vector entirely
It takes many dozens of hours, sometimes hundreds, to write a paper (just the writing not the technical work). People will spend a long time trying to improve the expositions. I have seen papers where co-authors have fought for weeks about the accuracy of a single sentence. I have seen papers where there were over twenty draft-revision cycles.

But there are natural limits. Usually, after working for years on a problem, you become so close to it that describing to a general technical audience is very difficult. Often, after you publish the work, someone else will do the difficult work of understanding your paper, and then write a more readable exposition as part of a review paper or book.
> Good execution remains differentiated.

Levels is a good example of this.

While we're sitting here waxing poetic about moat or no moat and what to do with these AI things, he's made some 7 figures in cold hard cash revenue from building and shipping things people want.

https://twitter.com/levelsio/status/1669269424543793153
Even something one might think would be an equal-opportunity population-reducer like COVID is confounded by socio-economic factors, so it ends up harming those with less access to healthcare more.

Another perspective is whether not doing anything (and by "doing" I mean simple public health measures like free condom distribution and family planning, education about the impact of human population, or, more succinctly, "no Hitler-y stuff") would ultimately yield more harm to minorities as they'd be the first to feel the impacts of population stress.
This is maybe a very unpopular opinion, but if you go from C to a higher level language, I would advise to steer away from C++, certainly if it's would be your first OO language.
Another thing to note here is this looks to be around seven total days of training on at most 4 A100s. Not all really cutting edge work requires a data center sized cluster.
Designing the Moneyverse
personally I'd be happy with a non-startup "perfectly ok businesses"
> Who are you to say that providing folks with good food and pleasant hospitality they want to keep coming back to and enjoying is somehow a psychologically draining career?

Someone who has experience in those careers, not in Spain/Italy/Japan, but in America. And I've never heard on them being unionized in my particular corner of the country. The only place I've heard of it is in Las Vegas, and yes, the people in those jobs seem to do ok financially and do a good job.

In several of these crap employers I was forced to sit through their anti-union training which I have to was the best proof I ever encountered about how useful a union must be.

It's not just the crap pay, irregular hours and lack of health insurance either. The contempt from customers (I'm sure not you and not all of them) is palpable. Honestly, I'm becoming a bit upset just thinking about it now well over a decade since I last held down a retail counter or slung a burger and fries. I wish all the jobs were as nice as your brother's, but I assure you that the people who work them are unhappy in them for a reason.
You didn't say what language(s) or if you needed an offline solution.
Here are two online REPLs that I sometimes use on my phone when I have coding ideas on the train:

1. https://www.online-python.com/ - Python IDE
2. https://jsitor.com/ - JavaScript IDE
Content farms aren't new - but now they are cheaper and better. I'd think that SEO would have already made a market beneficial to "qualified" content sources - like traditional or branded media. So, a site like vox.com, which has relative to GPT chum, high quality content, asks for donations, but is nominally free. I assume they make money from ads. If a qualified publisher doen't make enough money on ads and donations/subscriptions to cover their editorial costs, and if they do generate enough ad revenue for Google, is there an incentive for Google to help fund the publisher? Is there a case where Google pays for high trust content against which to serve higher margin ads? I clearly don't know how this business works...
You're likely right. If not solvable, Google could still do a lot better.

Anecdote: just today, I searched for a restaurant by named and town. The first several resultscwere sites like TripAdvisor. The restaurant's own site was far down the list. Why? Bet: Google makes good money off TripAdvisor&Co, because they also advertise, but probably none from the restaurant.

Google has allowed their ad business to drive their priorities. Everything else is secondary.
I read the other 4 sections and they were true pre chatgpt too. It all still applies. There are so many companies out there that I look at and think "how does this business still exist? How has this not been copied? Why hasn't big tech just killed this thing with a clone?"

I think people who know how to code and code for their day job really underestimate how hard it is to build these things. Even the weekend projects. A ton of these "weekend" projects, took a weekend to build, plus years of learning and research into the best most efficient ways of building those kinds of apps.

Building a startup is completely different from your faang / unicorn software engineer dayjob. Where everything is perfectly and comfortable setup for you. There is a team dedicated to making sure your code is deployed every day. The test harnesses are already built. You have dedicated designers telling you exactly how everything should look. It's all easy.

This is like the twitter clone effect. It's a cliche at this point, the casual "I could build twitter in a weekend". Why aren't there a million reddit clones? Why aren't there a million instagram clones? Why aren't there a million notion / canva / figma clones?

If it were that easy to replicate these things they would be out there.
This is the only part of AI that actually terrifies me.

I’ve run into people on this very site who use LLMs as a doctor, asking it medical questions and following its advice.

The same LLMs that hallucinate court cases when asked about law.

The same LLMs that can’t perform basic arithmetic in a reliable fashion.

The same LLMs that can’t process internally consistent logic.

People are following the medical “advice” that comes out of these things. It will lead to deaths, no questions asked.
>potatoes have the uncommon, and under acknowledged, virtue of being very nearly nutritionally-complete.

I think peanuts give potatoes a lot of competition there -- although peanuts are more nutritionally dense, with more calories and other nutrients per gram.[0] Maybe for weight loss purposes, potatoes are therefore preferable, as they are more filling.

I was also looking for more information about what other ingredients were allowed on the potato diet - only one vague reference in TFA regarding olive oil and salt.

[0]https://foodstruct.com/compare/potato-vs-peanut
SDXL Turbo: A Real-Time Text-to-Image Generation Model
It’s not even extra work in most cases. You can just let your lawnmower spit out your lawn clippings back onto your lawn for instance.
> the president of the United Nations climate conference, who is an oil executive in the United Arab Emirates

How does such an obvious case of the fox guarding the hen house come to be?

What a farce...
Entrepreneurs are boring. Try programmers.