Dig deeper into AI world. Learn about artificial intelligence in the right place

In today fast-paced financial landscape, harnessing the power of machine learning algorithms is a promessing approach for decision-making in the stock market. However, before diving into the realm of predictive analytics and algorithmic trading, one must first master the foundational step - acquiring reliable and comprehensive stock market data. In this introductory guide, we'll explore how to get started with fetching stock market data using Python, laying the groundwork for subsequent machine learning applications in finance.

Just a few days ago, a new model of the Yolo family was presented. Its main trick is that, unlike its older brothers, it is able to recognize virtually any object in the image (which are of interest to a person) without prior training and it does it in real-time mode! Sounds pretty good, doesn't it? In this article we will try to understand what magic is hiding inside the new architecture. I would like to say that this article will be more of an introductory one, so I recommend those who like strict math to read the original article after reading it. But before we start the review, let's learn/remember the main types of object detection tasks in an image.

StreamDiffusion is a new diffusion pipeline for real-time interactive image generation, enabling higher performance for live streaming and other similar scenarios. It replaces traditional sequential denoising with a faster batch process and introduces a parallel I/O queue for smoother operation.

Danger lurks everywhere. Any human activity, be it work or pleasure, can be a source of great problems or even lethal consequences. It sounds quite frightening and extremely pessimistic. If one is afraid of everything in the world, then life loses its meaning, but no one forbids using caution where it is necessary. And within the framework of alcohol consumption, caution is simply inherent. Researchers from the University of Michigan (Ann Arbor, Michigan, USA) conducted a study that suggests that using artificial intelligence to scan surgical patients medical records for signs of risky alcohol use could help identify those whose alcohol use increases their risk of problems during and after surgery. How was the AI configured, how did the AI perform, and what new things did the AI tell us? We find the answers to these questions in the researchers' report.

Machine learning large language models on custom datasets makes the models much smarter. There is a success story of the Alpaca dataset. It works wonders with models that at first, if they could do something, they did it very badly. We set out to understand how it iss done, and more importantly, what the challenges are along the way and whether newbies like us can figure it out.