PandaRider

> ... But we expect, in the next few months and years, people will focus way more on the specifications, on the models, on the properties you want the software to have.

Does anyone have resources on learning modelling for formal verification? (Does not have to be in Lean)

I have studied algorithms in college. I believe the goals of leetcode vs the goals of graph theory may be against each other.

A good graph theory course abstracts away the details of code and pursues the goal of understanding how many problems can be expressed concisely and clearly through graphs.

A good leetcode practice ... honestly just hones how patient you are in debugging and memorising various code patterns.

If you want to pursue money, it's almost always better to pursue leetcode exclusively

I'm curious if increased adoption of formal verifications would increase migration of legacy COBOL to modern systems.

I believe every death is unique and not a statistic.

However, since the article is about "men" and "suicide". There is substantial evidence that suggest women (especially young girls) attempt suicide more than men... while men are are more likely to die from a suicide [1]

Does gender have a role in suicide? Maybe. But I would hesitate to generalize too much.

[1] I asked chatgpt to back up my claims. Please correct me if I'm wrong.

Terminologies:

1. Someone whose life choices can either defeat every poverty or bring the downfall of humankind - Main characters

2. Someone whose actions are in a loop - NPC

3. Someone whose actions are in a loop but we choose to - NPC-by-choice

Is this terminology better? Correct me if I'm wrong!

Thank you for the recommendations! The 2 books seem to be a little more detailed than the average general-audience book but not too intense and deep like a textbook.

Would definitely take a look!

For most folks, the incentive of learning at 100% speed [1] is getting better grades in school. It's a huge ego boost to walk in to an exam hall with zero handwritten cheat sheets while everyone others have font 6 cheat sheets.

As a working adult, we hardly get this kind of ego boost unless we somehow know our colleagues salary. Even so, there are many other factors outside of knowledge storage that determine one's salary (e.g. feedback from teammates, number of closed sales etc)

[1] Actually, it's not 100% speed but 1 step back and 2 steps forward. Because the initial time and motivation cost is non-trivial.

> From this perspective, fields that require deep understanding, like math, require memory just as fields with a breadth of shallow knowledge do, though in different ways.

I'm interested in understanding how others use Anki for conceptual subjects like pure math or physics. I believe many fundamental rules in Spaced Repetition (e.g. like keeping cards concise) are thrown out the window for conceptual subjects.

The goat. Probably a required reading for all academics.

However, I wonder if this workshop is still relevant in the age of LLMs...?

Is the title editorialized?