I use Visual Studio Code as my main editor and I am on Windows 7. I like to use emojis but those aren't properly rendered under Windows 7. Can I have pretty emojis in Visual Studio Code somehow?
To do this, the extension makes use of the
createTextEditorDecorationType method available on the
window object in order to inject CSS that adds a background image where the text emoji would be rendered.
The extension listens to two events to determine in which editor it needs to do the replacement:
workspace.onDidChangeTextDocument. In the first case we update the editor that is now the active one, in the second, we update the active document when the text content changed.
How can you onboard users to use your library as fast as possible?
You need to make it as frictionless as possible for them to use your library.
First, they need to know the value proposition of the library. They need to know why they should use your library and not find another one available online. It needs to be convincing and to touch on the tasks they need to accomplish. The closer your vocabulary is to theirs, the easier it will be.
Second, the installation process needs to be as painless as possible. If you use a language with a package manager, give instructions on how to install your package using the package manager. If there are multiple popular package managers for the language in which the package was written, make sure to cover the most used ones.
Third, when users do not understand how to do certain tasks using your library (when it is in its early stage of development), take note of those questions, especially the wording. You want to capture what they were trying to do, how they described what they wanted to do, and why they were trying to do it. With this information in hand it should be easy for you to determine whether your library supports (or should support) the use case they tried to accomplish. If your library is not going to support the use case, make sure to indicate it early in the documentation so that users do not have the wrong expectation that your library will help them with this use case.
Finally, try to learn as much from your users as possible. Try to understand what it is they are trying to accomplish and whether it is valuable to most of them if you were to support new use cases. If you can document the most common use cases so that they can read the steps they'll have to go through, it will be simpler for them to evaluate the process before going through it.
I want to learn a new topic but it feels overwhelming. How can I do it?
When I wanted to learn about artificial general intelligence (AGI), I knew almost nothing about the field. I had a background in software engineering and I was curious about intelligence as a whole, but I had no clue what I would need to know in order to work on artificial general intelligence.
My initial approach was to read a lot about the topic. It allowed me to learn about a variety of concepts and the vocabulary associated with AGI. However, as I was doing that, I felt overwhelmed by the amount of information I would have to learn. In 2014 I was reading Artificial Intelligence: A Modern Approach, then in 2017 the Deep Learning book. It was hard to reconcile how the new concepts I was learning and how they were all connected.
At the time I already knew of mind maps. I thought it would make sense to try and map out all the knowledge I had acquired so that I could make sense of it and be able to refer to it as I would work.
I initially built a very large concept map using yEd that included everything I could think of that touched on the topic of AGI: machine learning, mathematics, computer science, neuroscience, etc. As the map got larger and larger, I started thinking about how I would organize it so that it was clearer to understand and that it was possible to progress through it if someone else wanted to learn from my experience. Thus, I extracted the machine learning, computer science and mathematics concept maps to their own respective concept maps.
The approach has been to spend time to write down what I knew, create a node in the graph with the term, then try to associate it with other terms already in the graph. As I learned new terms I would add them to the graph. I would also dedicate a bit of time during the week to try to brain dump whatever I might have learned or I knew about that could be added to the graph. This is an iterative process, so the graph itself is never really completed. However given this graph, it is now possible to know what I have already explored and the areas where I need to do more exploration because my understanding is lacking.
What are the different ways to measure intelligence?
We can measure intelligence as:
- the number of CPU cycles necessary to solve a problem. Less is better.
- the amount of energy spent by a system to solve a problem. Less is better.
- the time necessary to solve a problem. Less is better.
- the space (memory, RAM, atoms) necessary to solve a problem. Less is better.
The benefit of all those measurements is that they are scalar and thus ordinal, creating an order between the different agents that can successfully solve the problem.
Those values can be taken separately as one axis of intelligence. Taken together, they become a complex measurement of intelligence where there's no clear ordering between the different approaches. The agent with the "highest intelligence" is defined by the requirements of the environment: if energy sources are abundant in the environment, then using little energy is less important than using less time or space.
I use Omnifocus but I'd like to have access to the underlying data and use it in another application. How can I do that?
The first step to solve this problem is figuring out if we can access the underlying data easily. Sometimes we're lucky and the data is just a single file with the data in a format that we need to manipulate a little. In other cases, like for the ofocus format, files are organized in a single directory that contains zip archives. Unzipping some of those files we can observe there are two kinds: a master file and many transaction files. By playing around a bit with Omnifocus, we can make all the transactions files disappear, effectively merging them into the master file.
The next step is to look at the content of the master file. This file contains most of what we would expect to find when we use Omnifocus, namely contexts, folders and tasks. By inspecting multiple copies of the same type of entry it is possible to collect the different attributes that constitute them and whether some are optional while others are always present.
When I tried to reverse-engineer the format of ofocus files, I used my own database which contained many entries. This allowed me to quickly find most of the attributes of each type of entry. Another approach would've been to start with a clean database and to create each of the types of entry and create two variants: one with all the attributes defined, the other one with the least amount of attributes necessary.
Once the structure of those entries is identified, it is not too difficult to use reasoning to determine from where certain values come from. In some cases, values are references to other entries, similar to how you would have foreign keys in a database.
With all this knowledge now available to us, it is easy to simply convert the XML file into a JSON file. Once the data is available in JSON, it's slightly easier to work with it in PHP than using XML. By understanding the structure and relationships within the data, it is possible to make use of this data to build your own application that would reproduce the hierarchy of folders/tasks that are displayed inside Omnifocus.