In a recent YouTube Video I discuss how a cool feature from Amazon could be implemented with Large Language Models.
The “Customer Says” feature, as picture here:
allows one to
In the video above, I explain how this feature can be broken down into a bunch of sub-problems, each of which can be solved with LLMs.
Unfortunately (or perhaps, fortunately), we are still far from the days where we can ask a computer to write proofs for us. However, there are tools available today that can concretely assist with writing mathematics.
I made a video on the topic, with blog post below.
While I left research mathematics some time ago, I still find myself typing up some math from time to time. For me this has become a bit easier with Github Copilot.
I am now VSCode as my text editor to write LaTex. VSCode is a free and powerful IDE used by millions of software engineers. With it, one can access GitHub Copilot (for $100/year).
GitHub Copilot saves quite a bit of time in Latexing. Let’s see it in action suggesting useful LaTex code for a matrix.
The lighter text “\begin{pmatrix}” is what is suggested by Github Copilot. You can simply hit tab to accept the suggestion or keep typing to reject it. Let’s keep accepting:
This eventually gives the final result.
As you can see it quite accurately gives the LaTex code for a matrix, and only takes about 3 seconds real-time to do so.
Funny enough, it suggests some non-sense afterwards, about 
Vscode has a lot of flexibility in itself. There are many extensions that are useful. For instance, to work with latex, you’ll at the very least need a latex and pdf viewer extension. There is also git integration, which allows you to store your work remotely with the click of a couple of buttons.
Another reason to get familiar with VSCode is that it is a powerful tool for programming. That way, if you do every need to do some programming, you will already have a leg up on getting started!
I am happy to announce that I just posted my first video to a new YouTube Channel. The result is an interview with Xavier Garcia about how Chat GPT works.
I’ll continue to post videos surrounding Machine Learning, Data Science, and perhaps elsewhere. I plan to do more interviews, individual videos about relevant topics, as well as some educational material.
I was already meeting with Xavier regularly to discuss Machine Learning topics, and so I thought to myself that other people might benefit from our discussions.
Our discussion for the video was perhaps a bit altered than the usual, as we were a bit less likely to say things “off the cuff.” I’ll be looking to make this easier going forward, as I think a lot of valuable insight lie here.
There was/is a learning curve in making videos, and I’ll definitely be looking to improve the quality as time goes forward. From zero to published video took a couple months (of course not doing this full time). Also, I got lucky and found a very helpful video editor which made things a lot easier. Things like sound quality, video quality, and lighting are not things I’ve had to worry about too much in the past. I didn’t invest too much in equipment, just trying to make use of what I had.