414. Graph Neural Network Basics

▮ GNNS For this post, I’d like to share the basics of Graph Neural Networks. ▮ Graphs First let’s look through the main elements of a graph in order to understand GNN’s. Nodes (Vertices) Edges: the connection between nodes Adjacency…

413. Tips For Developing Vector Databases

▮ Using Vector Stores The combination of vector databases and LLMs, such as retrieval-augmented generation, has created a massive impact on the AI industry. When adopting these technologies, how you develop and maintain your personal vector databases becomes significantly important.…

412. Augmenting LLMs with Private Data

▮ Augmenting LLMs One of the key questions that everyone has when utilizing LLMs is “How do we best augment LLMs with our own private data?”. So for this post, I’d like to share the approach we can take and…

411. Procedures For Text Generation Projects

▮ Framework I am currently involved in several text-generation model development for non-creative tasks. So for this post, I’d like to share what I’ve learned on how to proceed text-generation projects. If you can specifically define all the elements in…

410. LLM Reasoning

▮ LLM Reasoning Despite the impressive performance of LLMs across many tasks, their reasoning processes can still inadvertently introduce hallucinations and accumulated errors. For this post, I’d like to share what I’ve learned from several state-of-the-art research in this field,…

409. Multi-Stage-Reasoning Using LLMs

▮ LLM Tasks VS LLM-Based Workflows LLMs are great at single tasks, but when we want to utilize LLMs in real-world applications, there is rarely a case where there is only 1 task. Typical applications are more than just a…

408. What LLMs Suck At

▮ LLMs Generative AI has been trending for quite a while, and I’ve been curious about the actual credibility of these models. The outputs these models create are so persuasive that it seems too good to be true. So for…

407. Stable Diffusion Fine-Tune Methods

▮ Stable Diffusion There are several fine-tuning methods for text-to-image stable diffusion models and it is hard to intuitively understand the difference between them. So for this post, I’d like to share a visual representation of each fine-tuning method. ▮…

406. Evaluating Generative Models

▮ Generative Model Trends I’ve had so many requests from multiple clients that they want to integrate generative models such as ChatGPT and Stable Diffusion into their current workflow. Despite the trend, one of the difficulties of adopting such models…

405. POCs For ML Projects

▮ My Mistakes I’ve finished a couple of POCs(Proof Of Concept; a phase where we create a prototype to check the feasibility of the machine learning project) this year as a Data Scientist/Project Manager for computer vision tasks, and I’d…