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Ministry of Silly Walks

TheVOJCited 3× on HN, 2021-2023
YouTube
3.4M views · 9 years ago · comedy · evergreen

The classic Monty Python sketch 'The Ministry of Silly Walks', in which a civil servant applies for a grant to develop his silly walk. It is a short, absurdist British comedy clip.

Mostly dropped in as a joke or a cultural reference when a thread touches on bureaucracy or walking.

Stand-up & sketch comedy#montypython#sketch#absurdisthumor#bureaucracy

3 comments from Hacker News

@agnosticmantis2023 · in “23andMe confirms hackers stole ancestry data on 6.9M users”

> Machine learning algorithms are learning to identify people just by their walk... Turns out the UK government was working on privacy-preserving walks decades ago: ▶ this video

JokeView on HN
@matt_s2023 · in “How to Dynamically Create Instance Variables in Ruby”

I mean if we talk about the creators/inspiration around these languages we have creators of Ruby from Japan where things are tidy, elegant and mindful of others. An inspiration for the name of Python is from Monty Python creators of the Ministry of Silly Walks which is kinda clunky looking when you watch it. ▶ this video Thanks for reading my highly technical analysis.

JokeView on HN
@YeGoblynQueenne2021 · in “Deep reinforcement learning is a waste of time (2019)”

Why do you have to start your comment by accusing me of moving the goal posts? I don't even like ball games. Why is it so hard to have a decent conversation on the internet? It's a serious concern and I stand by it. It's perfectly possible -it's even easy- to make algorithms, systems, programs, what have you, that can solve one problem, perform one task, and do nothing else. Hell, you can train a dog to perform one task. Sit boy! Boy sits. And that's all it knows to do. 80% of AI research output, ever since Dartmouth, has been like that. 99% of AI research output in the last ten years is like that. My entire phylum of AI research (I'm a PhD student studying Inductive Logic Programming and even knowing nothing about that, the name should give you an idea) is roundly dismissed today as a "failure" because it couldn't get from "we can solve an instance of this problem" to "we can solve any instance of this problem" quickly enough. Researchers promised it was just a matter of "generalising" like you say, tuning and tuning until everything worked in the real world as well as it worked in blocks worlds, but the sources of funding didn't listen and then we had a winter [1]. Why is what you're doing any different when you look at it from the present? We haven't seen the future yet. In the present, you have a robot that can open one door. In the future, you have a lot of doors that wait for robots to open them. Actually, looking at your paper, you don't even have a robot that can open

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