skysight-inc/HackerNews huggingface dataset:
You're situation is related to this: https://pypackaging-native.github.io/key-issues/native-depen...
Where it is incredibly hard to align various pieces of software spanning OSes, architectures, programming languages. The result is that you have to compile the whole universe for them to work together. In your case that universe is stuck on 2.7 and it will require a large effort to get everything up compatible with a recent Python version
I was something like that in a previous role. I had no official title, but I was a sort of JIRA secretary. I chased people around to gather clear requirements, and cut them into understandable tickets. I babysat tickets to completion and did QA as needed. I made meetings redundant by doing the backlog grooming and requirements gathering in parallel. I chased information on behalf of developers, and made sure they didn't get stuck. I attended meetings and passed the relevant bits to devs.

Basically, I kept the backlog in sync with reality, and vice versa. I was the facilitator I wish scrum masters would be.

However I also met my fair share of post it fetishists who don't seem to get much done. They seem like the priests of a modern religion, bringing their tabernacle filled with coloured markers and helping us pray to the productivity gods.
I don't see any of these companies caring about artists, but something like Stable Diffusion is more of a weird accident. Like how IBM managed to create a platform with that became an open standard, something almost diametrically opposed to their own corporate values.

Good quality data and more of it means better output. Disney is almost certainly doing their own thing internally, benefiting from their ability to use both free as well as their own IP and the capital to hire cheap workers to train it directly.

It's not that I don't understand why artists might be upset about a company scraping copyrighted art, I just think that the longer term effects of legally kneecapping open source variants while handing over the most powerful versions of it to the existing intellectual property giants are A Bad Thing.
Thank your for introducing me to books by the US navy. A treasure trove!
I don't think those ai are able to have reason and to understand the data they're given. They just reshape the data without understanding it. It's still artificial.

Unless there is a breakthrough in analyzing those neural blackbox, I would not hope a lot of those ai.
I read the web page and the PDF paper quickly (https://arxiv.org/pdf/2210.13382.pdf) and it seems that there are no examples of the prompts they used. It would be great to see which technique they are using or is it obvious for experts of the field?

It would help with reproducibility too.
Very good summary of the situation, I hope something good will come out of it.

I've used pipenv, pyenv, poetry and settled for my own use-cases on just pip with virtualenvwrapper.
So any program goes into its dedicated folder with requirements and virtualenv.
However there's something that I've never managed to get working.
You have say a 3.8 virtualenv, and package file mentions python should be >=3.8.
But when calling python -m build, the build process creates a new environment using the system python.
So if you are on an old system that is on Python 3.7, the resulting package cannot be installed because of the inconsistency between declared python version and the one that has been used.
It may be a very stupid problem, but I haven't been able to find any documentation for it.
Any search engine is just too happy to throw any 'python packaging result' before anything so specific.
Maybe I should use one other tool for that? But there's no clear (default?) path documented.
> On the other hand, only 4.0% (780) of all cities had a population of 50,000 or more in 2019, yet nearly 39% of the U.S. population (127.8 million) live in those cities.
1. Seems to be more than four years out of date [1](page 9) :

> China has been transformed from being a significant importer of all nutrients in the mid-1990s to a major exporter today.

> A program to develop China’s domestic resources was implemented, and China rapidly invested in nitrogen, phosphate and more recently potash capacity.

(Nitrogen)

> China has relatively limited natural gas resources, so gas based plants account only for a quarter of total urea capacity. Instead, it has turned to its relatively abundant resources of coal, which make up three quarters of urea capacity.

etc.

( Also, China has been overusing fertilizer and has recently cut back and still increased yeild [2] )

2. Yes. China has a strong GDP growth (for what that's worth as a metric) on the back of importing, processing, and exporting to the benefit of China - as a country it is still able to survive well enough on its own (perhaps to the chagrin of the the growing Chinese middle class who demand more and more 'luxury' items).

3. China is quite capable of producing high quality steel - they have some of the highest grade iron ore imports available about the globe and they do produce plenty of high grade steel. Where we agree is that China makes an awful lot of money selling an awful lot of low grade steel.

IIRC China imports 16x the tonnage of US iron ore annual production capacity from Western Australia alone - the Chinese high grade steel production can easily dwarf the capacity of US high grade steel production capacity .. and still lose that total tonnage in the magnitude higher production of low grade steel.

It's a chicken and egg story - are we blaming the Chinese for selling low quality goods, or the world for being satisfied to hand over substantial amounts of money for low grade goods? (If they'll pay for crap, why export better?)

[1] https://gpca.org.ae/wp-content/uploads/2018/07/China-Fertili...

[2] https://www.weforum.org/agenda/2018/03/this-is-how-china-cut...
I wonder if the Arthurian legend of Excalibur being thrown back to the Lady of the Lake as an offering is some distant echo of that (far older) Celtic tradition.
So now GTA:O hackers have found an irl money glitch /j
FTX Started Paying Bankruptcy Lawyers Months Before Filing
But we don't want poor innocent microsoft to train models on their own code, do we?
I can add to this as I've read parts of the 3rd edition.

First off, it's a one thousand page textbook so it's not a short read. However, the second chapter is just called "Theory" and it's about 200 pages long, and that single chapter is an excellent primer on electrical engineering.

Don't get the kindle version, it's too hard to read on Kindle.
Show HN: CLI tool to perform cost analysis on your AWS account
Right. Not that long ago artists were rallying against Disney and the Music Industry for weaponizing Copyright against Artistic Freedom. Now it seems some artists have decided to use the same tactic.
Interesting. Only covers ASCII, umlauts etc get ignored.

It seems like a lost opportunity not to have diagonal lines.
After LISP, sh, TCL, and Lua all took a run at that fence, I'm glad something finally cleared it.

cf https://news.ycombinator.com/item?id=34431984
Are you sure the lockfiles are platform-specific?

I spent a long time migrating a project to use poetry. One of the reasons I opted for poetry over others was that the lockfile retained all of the environment markers in the packaging metadata, so that the lockfile could support multiple interpreters and interpreter versions, multiple platforms, etc.
I don't know from which weird country you're from, but in mine profiting from it changes things a lot.
You can get a used 2080Ti for under $300 on eBay
And sometimes it mixes just from one. See github copilot.
> “You should know that training on millions of books is not the only way GPT-3 learns. It is just the foundation of its knowledge.”

I’m not a lawyer, but to me it seems within the realm of possibility that a U.S. court eventually finds strongly in favor of the copyright holders, the Supreme Court agrees (because Big Tech has so few friends left), and OpenAI will be required to destroy the GPT-3 model and all copies of the training data because they can’t filter out copyrighted works.
Sam's biggest success seems to be raising 30M USD. Everything else in his career is mediocre.
I think - it was a very very long time ago when I read this - but a bad person can put someone into a stasis field without their consent. The stasis field is the shape of a perfect bubble or ball. IIRC it's also perfectly reflective. Anything inside the stasis field simply doesn't participate in time.

Once Bob puts Alice into statis, the stasis ball is impenetrable, so the cops don't know if Alice was alive or dead when she was involuntarily put into stasis.

However, they do know that the stasis bubble containing Alice will eventually open up and pop Alice back into the current time. And they know when that will happen. So, the state puts Bob (the guilty party) into stasis too; with Bob's stasis timed to end when Alice's ends.

In this way, both stasis fields pop at roughtly the same time, and Bob can be tried either for murder, or for whatever the name is when you transport someone into the future against their wishes.
Many thanks to the OP, can't wait to try this out! I have a question I'm hoping to slide in here: I remember there were also solutions for doing things like "take this character and now make it do various things". Does anyone remember what the general term for that was, and some solutions (pretty sure I've seen this on here, apparently forgot to bookmark).

PS: I'm not trying to make a comic book, I'm trying to help a friend solve a far more basic business problem (trying to get clients to pay their bills on time).
Train on data: sure… but sell the output? Different question altogether.
Doesn't follow. Why would a tool built in Japan limit itself to Japanese? ChatGPT doesn't limit itself to English.
[Disclaimer: PRQL core dev here]

I'm hoping that PRQL [0] will one day become the universal API for tabular/relational data. We're targeting SQL as the backend in the first iteration given it's universality but there are early plans to support other backends.

You can already use PRQL with Pandas, the tidyverse, shell and pretty much any database. See my presentation [1]. PRQL reads very similarly to dplyr, and in my (biased) opinion, actually a bit better than dplyr because it can do away with some of the punctuation due to being its own language.

For questions see our Discord [2] and if you would like to see PRQL in more places, file an issue on Github [3].

Some examples below:

## Pandas

```python
#!pip install pyprql
import pandas as pd
import pyprql.pandas_accessor

df = pd.read_csv("data/customers.csv")
df.prql.query('filter country=="Germany"')
```

## tidyverse

```sh
mkdir -p ~/.local/R_libs
R -q -e 'install.packages("prqlr", repos = "https://eitsupi.r-universe.dev", lib="~/.local/R_libs/")'
```

```R
library(prqlr, lib.loc="~/.local/R_libs/")
library("tidyquery")
"
from mtcars
filter cyl > 6
sort [-mpg]
select [cyl, mpg]
" |> prql_to_sql() |> query()
```

### PRQL

```prql
from employees
filter start_date > @2021-01-01
derive [
gross_salary = salary + (tax ?? 0),
gross_cost = gross_salary + benefits_cost,
]
filter gross_cost > 0
group [title, country] (
aggregate [
average gross_salary,
sum_gross_cost = sum gross_cost,
]
)
filter sum_gross_cost > 100_000
derive id = f"{title}_{country}"
derive country_code = s"LEFT(country, 2)"
sort [sum_gross_cost, -country]
take 1..20
```

[0]: https://prql-lang.org/

[1]: https://github.com/snth/normconf2022/blob/main/notebooks/nor...

[2]: https://discord.gg/N63hWUhw

[3]: https://github.com/prql/prql
Gosh. Can somebody help me to understand how a LLM has achieved this capability.

I had thought that a LLM was essentially only doing completions under the hood using statistical likelihood of next words, wrapped in some lexical sugar/clever prompt mods. But evidently far more is going on here since, in OP’s example, some of its output (eg future time stamps) will not be present in its training data. Even with several billion parameters that seems impossible to me. (Clearly not!)

Could somebody join the dots for me on the nature of whatever framework the LLM is embedded inside that allows it to achieve these behaviours that emulate logic and allow generation of unique content.
Accessibility and presentation
The book A philosophy of software design https://www.amazon.co.uk/Philosophy-Software-Design-John-Ous...
Points out that TDD can inadvertently lead to tactical design rather than strategic design. In my experience, this can be true. I'd never noticed until it was pointed out.

Im on a team that is currently attempting shift left. One part of this has been an argument that testers should review unit tests. I think this is not a good idea. Unit tests tend not to focus on the behaviour of system as a whole.
Not for mobile apps, where the second-best language to use is TypeScript
Roblox wants an older audience, but it’s leaving younger players behind
But is a programming language really a tool? I guess it's a tool that creates other tools..
US copyright law only applies in the US. AI can be developed outside of the US where other laws apply. So, the US using the straight jacket of copyright law to stifle innovation would only cause AI companies to move their business; or non US companies stepping up. I don't think that's actually going to happen though. The stakes are too high for that and this case seems quite weak.

Copyright law has its limitations. But it also has a long history of being applied and interpreted that you can't just wish away. New legal interpretations have to be reconciled with that. So, any radical changes in that are not very likely to happen. Nor will politicians step up and change the law. First of all, few of them actually care or even understand most of this stuff. And secondly, they have plenty of other distractions and a worse attention span than a toddler. Mostly they just do what big companies tell them to do.

So, the most likely outcome here is that these cases won't get very far. At best it might drag on for a few years while nothing really changes. During that time, AI will continue to develop and will get more embedded in society.

And lets face it, this is not Oracle with really deep pockets unleashing an army of lawyers against the likes of Google but some isolated individuals. As legal cost ramps up, their enthusiasm might suffer a bit. Especially if they start losing cases.
I'd like to train an AI on microsoft's leaked code and put the model online. And see what microsoft thinks of that…
The USA would lose in Taiwan, or would lose a greater war.

The first seems reasonable enough given the proximity to China and Chinese hypersonic missles. The second seems rather fuzzy.
"The collage output"? What?
Can you stop writing these garbage GPT comments, please? No one wants to waste time reading this shit.
The Chess World’s New Villain: A Cat Named Mittens
Also, people occasionally invent new concepts, ai doesn't.
I mean, that's really the mystery of it. One of the most notable advances of recent LLMs has been emergent, one-shot, and highly-contextually-aware behaviors that seem to only manifest in models with extremely large numbers of parameters.

Cleary the latent space of the model is able to encode some sort of reasoning around how time flows, typical information about houses, understanding how to transform and format information in a JSON snippet, etc. That's the "magic" of it all; amazing and powerful emergent behaviors from billions of weights.

Of course, that's also the limitation. They're opaque and incredibly difficult (impossible?) to inspect and reason about.
We don't need to shut down these technologies. But there needs to be a clear ruling to which extend they can use copyrighted materials without the consent of the copyright holder. And establish a framework on how such a consent could be established in case it is required.
The mistitling is likely deliberate SEO to pull in traffic off the back of the popularity of ChatGPT
MIT license says that the author must be cited within the copyright section.

So you should know and list all of the authors that contributed to that code being generated.

And that's the least restrictive software license…
I'm getting mixed results, and for a given topic it seems to invariably give a better result first time you ask, then not so good if you ask again.

It could be random and my imagination, but seems that way.
It's simultaneously a good and a bad thing Git is so dominating nowadays. On one hand everyone can just jump on everywhere as the tooling is familiar, but on the other hand there's so much more out there. Fossil looks really nice, but I see no use (for me) as long as there's Git and surrounding tooling (Github and similar).
I do not fully get the speed argument. If the dataset is small'ish, it does not significantly matter (given you only use the vectorized functions, of course). And if it's big data, I do not use pandas but Spark/a cloud data warehouse solution. For this reason I also do not get the use case for duckdb.

Beyond this, a dataframe api/syntax, compared to SQL syntax, is to me way easier to follow and to debug.
Chris DiBona – Former Google Open Source Director
Because the world has had thousand years to evolve, adapt and settle around the capabilities and limitations of the human brain. It is somewhat stable and predictable.

Now if a new species of humans suddenly emerged with a brain not only has capable as our but faster, more adaptable and extensible, it would disrupt the world.
Well microsoft claims that if you infringe it's your fault and not theirs.

However they don't give you any way of NOT infringing when using their tool.
I've seen this site before, it looks really good but is there a downloadable/PDF version?
Class of 2021 UC Berkeley CS grad chiming in. It is untrue that it’s in Haas Pavilion, the course scaled by making lectures available online. The semester I took the course, it had over 2000 students and somewhere around 100 TAs IIRC.
Probability is hard to understand and it means different things in different contexts.
(is it only about knowledge or is it out there in the world)

If it is hard for Andrew Gelman it may be too hard for most of us.

"Court of Appeal bans Bayesian probability (and Sherlock Holmes)"

https://understandinguncertainty.org/court-appeal-bans-bayes...
Counterfeit Monkey is my all-time favorite. I like it so much, I made a mobile-friendly demo:

https://memalign.github.io/m/counterfeitmonkey/index.html
A significant number of tools are created to create other tools
One of the big eye openers here is not the use of OpenAI, but how dumb and limited Siri seems by comparison (especially its inability to grasp context). Apple, Amazon and (to a lesser extent) Google’s voice assistants never evolved past simple intent and keyword matching, and this hack puts their product teams to shame…
I think the underlying question is one of "degrees of derivation".

There's a famous Carl Sagan quote: “If you wish to make an apple pie from scratch, you must first invent the universe” which hints at the problem: Nothing is created in a vacuum.

Let's compare what Stable Diffusion does with what Franz von Holzhausen, head of design at Tesla, does. Franz didn't come into existence out of nothing and knew how to design cars. Instead he studied transportation design and worked at Volkswagen, General Motors and Mazda before joining Tesla. All these steps trained his (actual) neural network with inputs from copyrighted car designs.

Based on these inputs he was able to create the designs for the Model S, Model 3, Model X and others. Does this mean that Mazda can now levy a copyright lawsuit against Tesla? It could, based on the reasoning employed in some of the Stable Diffusion suits, but it won't based on the lack of similarity between the cars of both brands.

I believe that the law around AI will come to a similar conclusion. AI learning is neither fundamentally add odds with copyrighted material, nor confirming it. It will be a matter of degrees of derivation - how different is the output of the AI from its copyrighted inputs.
> Nobody considered copyright when they recited Homer

Really? Curious that we know the author's name then… seems like… attribution?
Implementing a zero-trust architecture with a trust-score system for users and a dynamic policy for accessing resources can help to limit potential damage in the event of a security incident. But I agree that the balance between protecting against attacks and maintaining productivity can be delicate.
The headline and the heavy promotional verbiage on the site seems to be claiming this is some new functionality we didn’t have before. Image2image with text instructions isn’t new as the headline implies.

InvokeAI (and a few other projects as well) already does all this stuff much better unless I’m missing something. There are plenty of stable diffusion wrappers. Why not help improve them instead of copying them?

I’m not against having enthusiasm for one’s project, but tell us why this is different and please don’t pretend the other projects don’t have this stuff.
Any multi step process is guaranteed to produce random assortments of workflow tools to manage those steps which will seek to replace the original process as the one true process.

If there two steps, one part of the community will insist they belong in: a makefile, bash script, python script, lambda network service, bazel, pants, scons, terraform, ansible, npm …
Dr. OpenAI Lied to Me
This was my thinking too!

It’s less shady and more a simple reinvention of the marketplace model.

The shady bit is the fake reviews and also an element of “fake it til you make it”

So they’ve also reinvented the trad VC-backed business model!
Not sure it will go deep enough for what you’re asking here but the “Practical Engineering” YouTube channel (which has some great videos about random bits of civil infrastructure) recently released a book “Engineering in Plain Sight”

https://practical.engineering/book
Do the multispectral images cover (part of) the infrared range? That might allow to detect heat loss through the roof
I'm intrigued to see if anyone can squeeze out similar quality with a smaller dataset (Microsoft's implementation was trained on 60,000 hours apparently).

Not that that's impossible to get your hands on nowadays, but it still takes quite a long time to train on decent (though admittedly not extremely high-end) hardware.
Can't speak for the parent but since I also use a docker-compose & traefik based setup I can describe my migration process (executed by ansible in my case, could easily be done manually though):

1. Copy docker-compose.yml (for my private stuff there is a single one containing all services + traefik) and config files (host-mounted into services from a config dir) to new host.

2. Start services (docker-compose up).

3. Restore runtime data (in my case I mostly pull some db dumps from my restic repos and load them into the db containers).
No, a description of why personal anecdotes from victims of violence often contradict the total absence of data showing the purported benefits often used by said victims to try to justify and make sense of the abuse they were subjected to.

If there were data showing improved outcomes among this group compared to those not subjected to violence, there'd be reason to listen to their accounts, but since there isn't independent evidence to support these claims, and it's not a controlled sample, their anecdotes have little value.
Thanks for playing and sharing it!

Direct link to the game:

https://memalign.github.io/m/dungeon/index.html