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As content becomes more and more freely available, it has become kind of a full time job to identify what to watch next. The streaming services have their own recommendation algorithms but they work in silos. In this article we are going to build a bare bones recommendation system using Qdrant vector search. We will be using semantic similarity to find movie and tv show recommendations. Disclaimer: I am no expert in AI, recommendation systems or vector databases. This post is an experiment to move towards that point in this high dimensional vector space. ...

A mixin is a class that provides some functionality that can be easily incorporated in other classes. Mixins usually provide some standalone functionality that can be reused in many different classes. Python supports Multiple inheritance. Multiple inheritance means that a class can inherit from multiple parents. Multiple inheritance also implies that the order of parent classes becomes important. Python has the concept of MRO. MRO or Method Resolution Order is the order in which Python looks for a method in a hierarchy of classes. The order goes from left to right, which means the right most can be considered as the base(-est) class. The methods in the classes on the right will get over written by the methods in the classes on the left. ...

A Tensor is a container that can hold an N dimensional data structure. Neural Networks love numbers. In fact that’s all they understand. GPUs are great at handling numbers. And they can operate on many numbers in parallel. Therefore a key idea in machine learning is to group numbers together and create a Tensor that can be handed over to the GPU. Arrays and tensors An array is a one dimensional data structure and a tensor that has a single dimension is called a rank 1 tensor. A matrix is a two dimensional data structure and a tensor that has two dimensions is called a rank 2 tensor. A stack of matrices can be thought of as a three dimensional data structure and a tensor that three dimensions is called a rank 3 tensor. Enough text, let’s look at some code. ...

Langchain is the probably the easiest way for building LLM based applications. According to Andrej Karpathy LLMs are like Operating systems that allow developers to build apps using their broad ranging capabilities. If we build on that analogy Langchain would be analogous to a framework as .Net or Django or Express. As per the Langchain’s State of AI 2023 report: 42% of LLM applications involve some kind of retrieval system 17% involve an agentic system. There is a huge push towards agentic systems from a lot of gaints of AI, including people like Andrew Ng and Andrej Karpathy. ...

I have been a software engineer for the past 12 years now. I recently caught the AI bug and have decided to go all in on AI. While the thought of making this shift is intimidating at times, it has been a few years in the coming. At this point I am more okay with learning AI and falling flat on my face than continuing to wonder how wonderful it would be if I somehow became an expert magically. ...