toteno

Actually, the VS Code approach is closer to the first one (Clear API boundaries). VS Code extensions don't have direct access to internals, no direct access to the UI [1], and extensions can control VS Code only via the Extension API [2]. However, extensions have access to many standard JS functionalities that could be used in the wrong way.

By the way, Figma plugins can also send arbitrary information (such as file contents) to external servers.

That said, I think it's good idea to add to extensions permissions/capabilities security like in mobile apps.

P.S. If the Extension API doesn't have what you need, there are Proposed APIs [3], but you can't use them in published extensions, and sometimes proposals move very slowly.

[2] https://code.visualstudio.com/api/extension-capabilities/ove... [1] https://code.visualstudio.com/api/references/vscode-api [3] https://code.visualstudio.com/api/advanced-topics/using-prop...

I noticed that some people expect AGI to have some superhuman intelligence instead of just intelligence similar to that of humans. I have seen some posts arguing that an AI can only be called AGI if it is better than any human being on every task.

It's nice to see that this article doesn't fall into that.

You can get API keys from the page https://platform.openai.com/account/api-keys (which you can find open by clicking on your avatar and selecting "View API keys").

I agree with you overall.

Just a small nitpick: most ad networks optimize for price of impression, so at the end of the day they charge for impressions (just not always directly).

If your ad has low click rate and average price then it just won't be shown, because it's more profitable for an ad network to show ad with better click rate or with better price (i.e. with better price for impression) .

Sadly, seem like the decision in that case was changed. From your link:

> In a November 2022 ruling the Ninth Circuit ruled that hiQ had breached LinkedIn's User Agreement and a settlement agreement was reached between the two parties.

I really like timeanddate [1] website for looking at past weather. For most cities you can check up to 12 years before.

It's also useful if you want to check what's typical weather in some city.

[1] https://www.timeanddate.com/weather/france/paris/historic

Accroding to the results from this paper (page 34) performance of NativeScript is better than React Native, and both are better in performance than Flutter.

The results was quite surprising for me. My expectation was that Flutter will be the best (after Native) followed by React Native.

I found other small benchmarks that shows Flutter is better on CPU-intensive tasks but React Native is better on typical UI side. I didn't found other useful benchmarks about NativeScript.

Actually I'm using it on bare metal and it works. Initial setup wasn't very hard but I think it could be more intuitive. Overall I think documentation for self-hosting kubernetes sometimes a bit incomplete.

Yes, I need to add A records with IPs for each domain, but that's one time setup. I did it manually, but you can automate it [1] (depends on what you use for DNS provider but you can extend it to support your provider or maybe there is another existing solution).

I'm not sure that one server in front of the cluster is more reliable than using all cluster nodes for load balancing. I guess that in automated solutions like [1] cluster's node could be automatically deleted from DNS if it went down.

My setup is not so big so I don't have real need for load balancing, but it seems possible with existing solutions.

[1] https://github.com/kubernetes-sigs/external-dns

> What I want is to declare I want this service to be under this domain and this IP - so for that you still need to configure your load balancer (bare metal) manually, setup certificates etc. I am writing a tool to automate this, but it's been a pain.

After initial setup you can do it quite easily.

Exposing a service on selected domain is several lines in Ingress and adding certificates is several more. Example: https://cert-manager.io/docs/tutorials/acme/nginx-ingress/#s...

> Copilot is completely depending on the legal theory of being effectively exempt from copyright, under fair use doctrine; if that legal theory falls apart, the entire space (and a lot of other machine learning stuff) is utterly doomed.

That's really depends on the country.

For example Japan has a law[0] that's allows usage of any copyrighted materials for machine learning and other data analysis. You can also do it for commercial purposes. There are some limitations (you can't share the dataset itself, but you can share the model), but overall it sounds good.

[0] https://storialaw.jp/en/service/bigdata/bigdata-12