Financial risk management is a great industry for data science. I've been doing it for 15+ years. It is amazing the data rich environment which includes credit bureaus, customer transaction history, call center dynamics, and of course finances. It is a gold mine of opportunity to find new and fresh ways to observe the organization. This is also what makes risk management difficult as well. There is so much to know. LLMs are going to change risk management as it is changing every other industry. It will be interesting to see where it is headed.

That is not what Eric S. Raymond (esr) was describing.

GNUnix was developed using the Cathedral-style, Linux was developed using the bazaar-style. How Linux development was coordinated was thought to be impossible for something that had to be as solid as an operating system. The essay is a deep dive, exploring the conditions that the Linux project needed to ship an OS.

But ESR believed in right wing, libertarian adjacent politics. He's advocating for deregulated, free market ideas in the form of criticizing GNU. In doing this, he was seeking out the preferred metaphor and working backwards, rather than describing what is.

Adding the letter archive into a LLM prompt is a good read. you can use this as a source https://www.berkshirehathaway.com/letters/letters.html

perhaps I'm missing something. Why not start the learning at a later state?

If the goal is to achieve end-to-end learning that would be cheating.

If you sat down to solve a problem you’ve never seen before you wouldn’t even know what a valid “later state” looking like.

Why is it cheating? We literally teach sports this way? Often times you teach sports by learning in scaled down scenarios. I see no reason this should be different.

If the goal is to learn how to solve a Rubik's Cube when you've never seen a Rubik's Cube before, you have no idea what "halfway solved" even looks like.

This is precisely how RL worked for learning Atari games: you don't start with the game halfway solved and then claim the AI solved the end-to-end problem on its own.

The goal in these scenarios is for the machine to solve the problem with no prior information.

This isn't accurate, though? Halfway solved, for most teachings, is to have the first layer solved.

Indeed, this is a key to teaching people to know how to advance. Do not focus on a side, but learn to advance a layer.

That's effectively what you get in either case. With MLM, on the first learning iteration you might only mask exactly one token per sequence. This is equivalent to starting learning at a later state. The direction of the curriculum flows toward more and more of these being masked over time, which is equivalent to starting from earlier and earlier states. Eventually, you mask 100% of the sequence and you are starting from zero.

behind paywall. Amateur sleuth from West Virginia may have decoded the Z13 cipher and solved the mystery of the Zodiac killings identity.

Should change the name to Matrix Processing Units

The US Constitutional government is meant to be slow, methodical and gridlocked. It is supposed to take enormous compromise to get any decision created into law.

"If Tyranny and Oppression come to this land, it will be in the guise of fighting a foreign enemy" -James Madison

Very close. In fact you could still say that it still is competing with Python for users. There is still an active community of developers.

While the 1 hour rule is mostly true be careful with discount airlines. Frontier Airlines does do a 1 hour boarding. I've heard of cases that if you are late to boarding, even if half hour ahead of departure, they will not let you board the plane. I'm sure it depends on specific airport agents protocols. My point is I'm not sure you can always use the 1 hour buffer.

I was definitely stopped from boarding when I arrived to the airport 45 minutes before departure when on Spirit. That was the last time I used Spirit.