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I don't know what you mean.

Data from the Copernicus program has always been fully available, served with a nice web UI, API for both near real time data and archives.

It's the best source of open satellite data by far.

As for the licensing, I never actually looked it up, so maybe you're right.


There are two aspects to this.

The licensing commonly restricts you to small hobbyist use cases. There are typically restrictions on use of data, the amount of data, and retention of data. I've never looked at Copernicus data before but it appears to have the same kinds of restrictions. This is the licensing equivalent of "source available" rather than true "open source". Hopefully they are improving on this front.

While the data may be available in theory, no one ever invests in the data infrastructure that would allow people to access it in practice. They always have a nice website and API but it is like trying to watch Youtube over a dial-up modem. Usable access is reserved for researchers with an approved use case.

The US government does an unusually good job at both of these in my experience. Even when US public data sets that are not readily available online, you have to contact someone, it is usually for good reason. For example, because they are multi-exabyte data sets sitting on tape somewhere that almost no one ever asks for.


Well it makes sense the public API has restrictions. They probably have separate enterprise licensing.


Totally agree but I think it's only part of it, other problems probably take par in this:

- spammers are getting better and Google is less able and willing to moderate - the use of AI without much design around it. It's speculation since who knows how their algorithm works, but from what I've read and the general mindset in ML these days, it's very possible that they just use a recommendation AI with a single target (I've heard watch time, but again, who knows) with little to not design around it. This just does not work, especially if the AI is good at his job. It's a similar problem to decision makers blindly following KPIs, knowing if you did well and choosing criterias can be as hard as taking the decision itself, and an AI can't do that, you can't avoid designing your product.


French salaries are much lower.

On the up side, a lot of things are much cheaper or free (medical fees, internet, life in general except maybe the housing, depending where in the US and in France).

But yes, for your income bracket, you're likely to be worst off.

Keep looking, because salaries in tech are wildly variable, literally 25k to 100k+.

Keep in mind, high salaries are likely to be in Paris, but life their is expensive, especially housing.

And finally, it's your choice. Money is not everything in life, and since you'll be confortable either way, you can choose to gain less for an experience you want to live. Only you can answer if it's worth it or not ;)


Not sure it's true that we train that many engineers or that it's because of Napoleon, but most prestigious schools (in particular in Engineering) where created during his reign.


I take advantage of the post to ask.

Anyone has a good introduction to trading for engineers/mathematicians/programmers?

Something that goes into the theorics and the math of the thing. Like an MIT open course or something. I'm always a bit lost with these things.


Patrick Boyle's books are a good start.

Generally I would discourage people from trading - 99% of people who try fail.


The only real protection against theft is not having your bike among the most valuable and/or least secure ones on the rack.

Most protection can be circonvented if the thief is savy and equipped.


Hot take: there is no "bad" data.

It's a term we often hear, that implies there is "good" and "bad" data.

A dataset can have errors in labeling, be very small, be unbalanced, but all that can be managed with the proper methods.

THE biggest problem is when you training data does not correspond to the production use-case.

It's not that the dataset is "bad", it's just that the problem you're solving with your ML algorithm trained on that data does not correspond to the problem you're trying to solve.

The most "perfect" ML algorithm trained on the most "perfect" dataset for self-driving cars for example (for detection, segmentation of objects or whatever) made the US will have problems when the cars drive in an other country. Your MNIST-trained NN will have problems in a country where numbers are written slightly differently. Some people will put pictures of cats in your car model classification software. Pictures taken on a smartphone by your users will be different than your dataset scrapped on the web.

There is no bad data, just badly used data. And most of the work (and the most interesting part IMO) in ML is to identify, quantify and neutralize biases in models and differences between the data you have and the data the production system will work with.


> How could something so mundane as a metal detector be banned?

Obviously it's not...

The actual law says: "Nul ne peut utiliser du matériel permettant la détection d'objets métalliques, à l'effet de recherches de monuments et d'objets pouvant intéresser la préhistoire, l'histoire, l'art ou l'archéologie, sans avoir, au préalable, obtenu une autorisation administrative délivrée en fonction de la qualification du demandeur ainsi que de la nature et des modalités de la recherche." [Code du patrimoine Article L542-1]

"No one can use material allowing detection of metal objects to look for monuments and objects which can interest prehistory, history, art or archeology, without having, beforehand, obtained an administrative authorization delivered depending the qualifications of the applicant and the nature and modalities of the search."

So basically you cannot use a metal detector to do illegal archeological search. This law is weird though, since it actually condemn the intent and not the act. I'm no lawyer but I'm guessing it's pretty hard to condemn anyone with this law since anyone thoughtful enough can hide his intent (or at least prevent producing any proof of such intent).

https://www.legifrance.gouv.fr/codes/article_lc/LEGIARTI0000...


Casual technical diver here. It's lime (maybe something else sometime, not 100%).

The process of making lime from limestone actually produces CO2, so it's use in CO2 scrubbers are more or less carbone neutral.


Casual technical diver here. It's lime (maybe something else sometime, not 100%).

The process of making lime from limestone actually produces CO2, so it's use in CO2 scrubbers are more or less carbone neutral.


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