A few days ago a manager from a sister team asked me why I have “Chaotic good” in that field “What I do” of my work profile. The question now occupies my mind so I need to drain it into something.
In short, it is a silly meme from a few years ago as I decided to use as a work motto instead of “stupidity and courage” as I fell that the new one better reflects the type of work was doing at the time.
I have no clue how much of ingredients you will need all measurements are approximate.
Mix everything together and stir for a minute till the emulsion built up.
I used to work close with incredibly smart people who was dealing with things like data sharding on daily basis from them I learned a lot on that topic. Later I moved to a different role where that knowledge was not needed and faded away over the time. Here I’m trying to reclaim to myself that long forgotten knowledge.
Sharding is a process of assigning an item to a shard - a smaller chunk of data out of a large database or other service. The general idea is that we can distribute data or service across multiple locations and handle large volumes of data or handle more requests and with replication we can scale even more and make the system more resilient etc. But we need to have clear rules on how we assign partitions aka shards so that we can route requests to the right location.
One of the question I often ask in my interview is to design a log processing library:
You need to write a library for processing logs in the following format:
timestamp<TAB>messageThe library will be handed over to a different team for further maintenance and improvements and so maintainability and expandability is the most most important requirements.
The library need to support the following operations out of the box:
The original version also included some language and background specific expectations I never include in my assessment because I feel that they put the candidate into a position when they need to read my mind to meet those expectations.
One of the questions are really love asking during coding interviews is this:
Given a continuous stream of words, a dictionary on disk and cost associated to read from disk, create a stream processor that returns true when a word exists in the dictionary while minimizing the cost of reading from disk. Example:
Dictionary: {Dog, Cat, Bird, Lion, ...}
Input: [Dog, Cat, Aghd, ...]
Output: [True, True, False, ...]The output is true, true, false because dog and cat exist in the dictionary of words while Aghd is not considered a word.
Recently I was reading though a bunch of technical designs and I’ve noticed a common mistake when it comes to writing user-stories and requirements - assuming a solution. The biggest issue for me when I write requirements myself is that than whenever I include a part of a solution I’m thinking about into the requirements it limits my ability to innovate since I’m bound to a specific solution. In many cases I observed improvements in my designs when I was focused on what the customer needs rather on fulfilling requirement tied to my first and probably not a bright idea.
It is interesting to observe that any endeavor where attention is one of key metrics or key drivers. Regardless of the company size end up in the same hell pit of attention craving and optimization for it. Even small single person blogs that teach us to be a better person, engineer, or somethings are prone to that. Many of them, those I used, slowly became “Energy Vampires” to me constantly seeking for my attention.
Every so often I interview senior software engineers for Amazon. Where I ask more or less same questions in each interview. One of them requires adding a caching logic to get better results. I’ve noticed that the interviewee make one of to mistakes that blocks them from standing out as a software engineers:
Here, we will try to address those issues.
This time we explore the wonderful world of ultra-locality in decision-making and its connection to free will, good, evil, and God.
The same Joscha Bach: Life, Intelligence, Consciousness, AI & the Future of Humans | Lex Fridman Podcast #392 podcast I mentioned in the previous post AI, people, trees, and mushrooms: the same software different hardware triggered another chain of thought. Joscha was talking about how our neurons always operate using data available right here and right now. That is enough to build complex systems like the human brain. Working together, neurons form parts responsible for memories, image processing, data buses, etc. But ultimately, each of them individually works only with data provided by other neurons. In a similar fashion, neural networks in GPTs are just a multiplication of matrices connected with each other, forming memories, attention, generation, etc.
Exploring the idea that all living things have spirit or the ability to run neurological signals.
Recently, I listened to Joscha Bach: Life, Intelligence, Consciousness, AI & the Future of Humans | Lex Fridman Podcast #392 where Joscha and Lex discussed different ideas about consciousness, neurology, and AI. At one point, they talked about the ability of all types of cells to process neurological signals. The key difference is that neurons can process data much faster, over longer distances, and interact with more neighbors at once.