Google operates at such a scale with a wide surface area of serious production considerations that even “ergonomic” solutions internally feel extremely heavyweight externally.
Source: I’m an Xoogler
121 karma · joined February 19, 2015
Previously: * Google Search * Amazon Alexa * HFT
Google operates at such a scale with a wide surface area of serious production considerations that even “ergonomic” solutions internally feel extremely heavyweight externally.
Source: I’m an Xoogler
This is one of the best technical articles I’ve read. And I came away a lot more knowledgable about a technology I have used daily for over a decade and consider myself adept at. Kudos to the author.
I've been seeing the same thing. Where agents are great solving the immediate task, but as changes compound they run into software & architectural design problems. I created https://github.com/andonimichael/arxitect to help at least have coding agents self reflect on their software design. But I really like your approach to self-modification and improving the agent itself instead of just teaching it another skill in it's context.
Also note that there are several competitors from the other-side that provide whole furnished apartments for rent such as Blueground. You seem to be in between the “rent single pieces of furniture” and “rent a whole apartment” spaces and need to ensure that the space is carved out enough and the market is there.
Congrats for being accepted into YC! You now have a large journey ahead of you!
My OCD wishes they would have said Rivest, Shamir, and Adleman like the algorithm is named after
You have to get invited to it (via searching the correct keywords, etc. I got invited when googling about dependency injection). It is a series of programming challenges that get really difficult. But after completing them, I got a final round interview at Google, which was pretty cool.
Classifying traversal and 2-D games is not a new thing, and they simply apply previous methodologies and proofs to classic Nintendo games. They do not do this via "proofs by obscurity" but rather by classical NP-Hard proofs built upon previous theorems. Specifically, I will point you to the following two papers on fundamentals of proving NP-Hardness of 2-D and traversal games respectively:
- http://link.springer.com/article/10.1007%2Fs00224-013-9497-5
- http://link.springer.com/chapter/10.1007%2F978-3-642-13122-6...
They chose the collection of games because of their relevance to the authors. They wanted to study classic Nintendo games. Other games have also been studied including some, if not all, of the games you mentioned. If you did your research, you would already know the answers to the complexity of games like Tetris or Pong.
If you're genuinely interested in the underlying proofs or the theory behind game complexity, I urge you to read through the papers and their citations first before jumping to conclusions.
> For these games, we consider the decision problem of reachability: given a stage or dungeon, is it possible to reach the goal point t from the start point s? Our results apply to generalizations of the games where we only generalize the map size and leave all other mechanics of the games as they are in their original settings. Most of our NP-hardness proofs are by reduction from 3-SAT.