Vuizur

I think migrating away from office is not realistic for many companies. They run on Excel, and just breaking one vital table because it uses a macro can cost much more money than the entire office suite for many users over years. The Munich story was doomed to fail. (Of course there are lots of things that work, the open source mail or Zoom or Slack replacements are totally fine in my opinion.)

It is not very good at hard tasks, its ranking is much worse there.

The next question is if LLMs are actually more sexist than the average human working in HR. I am not so sure...

No, for this you need https://github.com/rmcrackan/Libation

Grok-2 is rank 2 on LLM arena, it's basically as good as the best Gemini model. They already caught up. Only the latest ChatGPT model is a tiny bit better.

I once wanted to compile a program that used Xapian on Windows. It was basically impossible for mortals.

Imo people should use cross-platform alternatives.

It will likely be amazing, Sam Altman said that the step between 4 and 5 will be like the one between 3.5 and 4. You can of course doubt him, but we'll see...

I guess it will be this year, some guy working at OpenAI already posted "4+1=5" on Twitter, which is suggestive.

Wikimedia is unfortunately becoming one of the worst places to give your money to. They have their closed-source infrastructure, which now for years has not been able to generate HTML dumps without a significant percentage of articles missing.

They have know of the bug for ages, but still...

WMF don't care about their products at all, they give much more funding to vanity workshops in Africa while utterly ignoring the requests of the Wiktionary community, for example.

There is also PyApp, which I think is really promising. The docs there are not that comprehensive yet and maybe a bit confusing, but the packaged programs usually work out of the box, unlike with pyinstaller.

>executing large-scale changes in entire repositories in 3 years

You can look at SWE-Agent, it solved 12 percent of the GitHub issues of their test dataset. It probably depends on your definition of large-scale.

This will get much better, it is a new problem with lots of unexplored details, and we will likely get GPT-5 this year, which is supposed to be a similar jump in performance as from 3.5 to 4 according to Altman.

It is impossible to remove personal data ("any information which are related to an identified or identifiable natural person") from the LLM training data.

As far as I understand it ChatGPT and all other similar systems are blatantly violating GDPR, they would have to for example publish their related training data to conform.

I guess the EU authorities don't do anything for now because they don't want to admit that their funny law basically bans all state-of-the-art AI.

(Ok, Openai also broke the law in almost all countries by downloading shadow libraries, but here they at least have more plausible deniability.)

You can use DBeaver to get a good diagram for almost all RDBMs.

Everybody who has released a decent model has used a shadow library dump for training. Are they going to admit that they illegally downloaded more than 20 million books?

Scholz does not stall support for Ukraine, Germany has given about 10 times as much military aid as France to Ukraine: https://www.politico.eu/article/military-aid-ukraine-france-...

Also compared to the US, Germany has given about 60 billion total aid (including the EU share + refugee cost) if I calculate it correctly, while the US has given 75 billion. So it gives much more per GDP.

Reading the GitHub issue about this is somewhat entertaining: https://github.com/docker/for-linux/issues/690

People are getting hacked a lot because of this, and docker doesn't seem to care all that much.

Do you mean direct air capture (DAC) or carbon capture and storage from burning fossil fuels?

He's talking about the new C# extension, Pyright and Pylance are free for everyone.

The head of the Eclipse foundation said that they are aware, but that they thought that it would be too expensive for small businesses to get the verification. So the open source devs should do it for free.

Related timestamp: https://youtu.be/AmsM5_5QO5A?t=1528

When you look at open source AI, for example, EU laws are a huge problem: Not only the act you mentioned, but also GDPR, where it is not clear so far how the "right to be informed" or the "right to deletion" can/must conceivably be implemented. (From my interpretation I also don't see how OpenAI can conform to the "right to be informed" without publishing its training data).

And of course the AI act, which might make it possible for the publishers of open models to be sued if a third party misuses it: https://techcrunch.com/2022/09/06/the-eus-ai-act-could-have-...

He apparently got divorced and moved out of his home country. And here he has no social circle. There are of course hopeless cases, but he is not mentally ill, only alcoholic. It is possible that he will never overcome alcoholism, but it didn't look like he tried treating it or anyone suggested it to him.

It is easy to be lonely, I have talked to several charismatic and very cool people who complained about how hard it is to make friends in a new city. This combined with other negative factors can cause people to fall in a hole. (Of course, people who are delusional about their AI girlfriends like in /r/replika are also sad.)

There are very few real-world-tasks where GPT-4 is worse at reasoning than the average person, right now only long-term memory, latency, TTS and STT makes virtual people suck. Once that is solved we should of course give them to old lonely disabled people.

I once met one, and it is extremely depressing. He was even rich, but had no idea how to get his life in order, and nobody cared about him. A helpful AI might tell him to go to alcohol therapy, hire people to clean up his house, explain bureacracy... That would help a lot.

Decent local LLMs such as Vicuna-7B are already able to run on phones with 8 GB RAM: https://mlc.ai/mlc-llm/

Right now it's a prototype, but in the future local LLMs will be everywhere.

Currently many for-profit companies try to do the same, but additionally emotionally manipulate the user into giving them as much money as possible. (To not even mention automated catfishing...)

This project is much better, but still might turn out badly. Hard to say...

It is a community newspaper that is (apparently) independent of the WMF, and they don't have quarrels about hosting WMF-critical articles.

Anti-WMF sentiment is surprisingly common on some Wikimedia projects.

I think this applies to people with a university degree, it is rare for them to speak bad or no English. (Many speak it absurdly well.)

But an average young nurse will probably only speak bad English and can maybe say a few broken sentences.

Similar to ChatGPT it also fails the "What is heavier, one pound of feathers or two pounds of lead?" test. So far only GPT-4 passes that one.

I could replicate the refusal, but all it took to get the model to reply properly was replacing "evil hacker" with "hacker". Paternalism is not that big of a deal right now, especially when compared to ChatGPT/Bing Chat. The fine tuning data doesn't contain a lot (any?) task refusal.

I think it is a great idea. The problem is that institutions/decision makers have very little knowledge about open source software so it is really hard to convince them to do this. I can only speak about Germany, but I recently read a newspaper by some IT government official that only contained buzzwords, where it was clear that he did not know what he was talking about. There are exceptions, someone got the government to fund Curl and OpenSSH (both between 50k-500k). So that is great. But you also have a second fund where everyone can apply, and looking at the responsible team you see that out of 5 people, none has a STEM degree, but instead graduated in fields like cultural studies. I doubt that they know/care enough about the threat of supply chain attacks to direct funds there.