Polymath Engineer Weekly #88
Polymath Engineer Weekly #88
Finance, GPTs Illustrated, Fungi, Go Pointers, Category Theory, SSDs and Kevin Mitnick
Hello again. Hey, please answer the survey down below. It’ll help me a lot to bring relevant content to you ;)
Comic of the week
Links of the week
Jane Street is a quantitative prop-trading firm, i.e. they use their internal capital to make markets in liquid assets around the world, balancing completely automated strategies with human intervention. In terms of expected value, this might be the single best field for a smart and technical person to work in. […]
The history of finance in general and quantitative finance in particular is littered with examples of very smart people who had good track records and then blew up. The brilliant people are table stakes. Building a lasting institution means embedding risk awareness into everything.
⏯ But what is a GPT? Visual intro to Transformers
I’m a simple man. 3Blue1Brown posts a video, I watch it.
It's hearty, it's meaty, it's mold - Hacking the genome of fungi for smart foods of the future
Hill-Maini's next objective is to make the fungi even more appealing by tuning the genes that control the mold's texture. "We think that there's a lot of room to explore texture by varying the fiber-like morphology of the cells. So, we might be able to program the structure of the lot fibers to be longer which would give a more meat-like experience. And then we can think about boosting lipid composition for mouth feel and further nutrition"
⏯ Go: Pointers for Performance?
You should not use pointers solely on the assumption they will improve performance. When using runtime languages, sometimes the trade-offs are not obvious or intuitive.
Copying memory in the stack is usually very fast compared to the overhead of heap management, even more when you have a garbage collector involved.
Neural Networks, Pre-Lenses, and Triple Tambara Modules
Neural networks are an example of composable systems, so it’s no surprise that they can be modeled in category theory, which is the ultimate science of composition. Moreover, the categorical ideas behind neural networks can be immediately implemented and tested in a programming language. In this post I will present the Haskell implementation of parametric lenses, generalize them to pre-lenses and introduce their profunctor representation. Using the profunctor representation I will build a working multi-layer perceptron.
All HDDs, SSDs and flash drives have an internal controller. It's the way that the storage device can be, in the words of Microsoft, abstracted from the host. That abstraction is done by logical block addressing, where each cluster capable of being addressed on the storage device is known to the host by an ascending number (the LBA). The storage device controller maps that number to the sectors or pages on the device. To the host this mapping is constant - a cluster remains mapped to the same LBA until the host changes it. On an HDD this relationship is physical and fixed: in its simplist deconstruction an HDD controller just reads and writes whatever sectors the host asks it to. It doesn't have to think about what was there before, it just does what it's told and writes new data on top of the old. It does that because it can, there's nothing preventing a new cluster being written directly on top of the same sectors of an old one. On an SSD it's different.
I have created a survey to get feedback from you. It takes only 2 minutes.
Book of the Week
Do you have any more links our community should read? Feel free to post them on the comments.
Have a nice week. 😉
Have you read last week's post? Check the archive.