Recommended introduction and practical video tutorials for the latest 5 WeChat mini programs in 2021

Diffusion can not only imitate better, but also "create". The diffusion model (DiffusionModel) is an image generation model. Compared with the well-known algorithms such as GAN and VAE in the field of AI, the diffusion model takes a different approach. Its main idea is a process of first adding noise to the image and then gradually denoising it. How to denoise and restore the original image is the core part of the algorithm. The final algorithm is able to generate an image from a random noisy image. In recent years, the phenomenal growth of generative AI has enabled many exciting applications in text-to-image generation, video generation, and more. The basic principle behind these generative tools is the concept of diffusion, a special sampling mechanism that overcomes the limitations of previous methods.

Kimi: In just one sentence, in just ten seconds, a PPT will be ready. PPT is so annoying! To hold a meeting, you need to have a PPT; to write a weekly report, you need to have a PPT; to make an investment, you need to show a PPT; even when you accuse someone of cheating, you have to send a PPT. College is more like studying a PPT major. You watch PPT in class and do PPT after class. Perhaps, when Dennis Austin invented PPT 37 years ago, he did not expect that one day PPT would become so widespread. Talking about our hard experience of making PPT brings tears to our eyes. "It took three months to make a PPT of more than 20 pages, and I revised it dozens of times. I felt like vomiting when I saw the PPT." "At my peak, I did five PPTs a day, and even my breathing was PPT." If you have an impromptu meeting, you should do it

In the early morning of June 20th, Beijing time, CVPR2024, the top international computer vision conference held in Seattle, officially announced the best paper and other awards. This year, a total of 10 papers won awards, including 2 best papers and 2 best student papers. In addition, there were 2 best paper nominations and 4 best student paper nominations. The top conference in the field of computer vision (CV) is CVPR, which attracts a large number of research institutions and universities every year. According to statistics, a total of 11,532 papers were submitted this year, and 2,719 were accepted, with an acceptance rate of 23.6%. According to Georgia Institute of Technology’s statistical analysis of CVPR2024 data, from the perspective of research topics, the largest number of papers is image and video synthesis and generation (Imageandvideosyn

We know that LLM is trained on large-scale computer clusters using massive data. This site has introduced many methods and technologies used to assist and improve the LLM training process. Today, what we want to share is an article that goes deep into the underlying technology and introduces how to turn a bunch of "bare metals" without even an operating system into a computer cluster for training LLM. This article comes from Imbue, an AI startup that strives to achieve general intelligence by understanding how machines think. Of course, turning a bunch of "bare metal" without an operating system into a computer cluster for training LLM is not an easy process, full of exploration and trial and error, but Imbue finally successfully trained an LLM with 70 billion parameters. and in the process accumulate

Title: A must-read for technical beginners: Difficulty analysis of C language and Python, requiring specific code examples In today's digital age, programming technology has become an increasingly important ability. Whether you want to work in fields such as software development, data analysis, artificial intelligence, or just learn programming out of interest, choosing a suitable programming language is the first step. Among many programming languages, C language and Python are two widely used programming languages, each with its own characteristics. This article will analyze the difficulty levels of C language and Python

Editor of the Machine Power Report: Yang Wen The wave of artificial intelligence represented by large models and AIGC has been quietly changing the way we live and work, but most people still don’t know how to use it. Therefore, we have launched the "AI in Use" column to introduce in detail how to use AI through intuitive, interesting and concise artificial intelligence use cases and stimulate everyone's thinking. We also welcome readers to submit innovative, hands-on use cases. Video link: https://mp.weixin.qq.com/s/2hX_i7li3RqdE4u016yGhQ Recently, the life vlog of a girl living alone became popular on Xiaohongshu. An illustration-style animation, coupled with a few healing words, can be easily picked up in just a few days.

Retrieval-augmented generation (RAG) is a technique that uses retrieval to boost language models. Specifically, before a language model generates an answer, it retrieves relevant information from an extensive document database and then uses this information to guide the generation process. This technology can greatly improve the accuracy and relevance of content, effectively alleviate the problem of hallucinations, increase the speed of knowledge update, and enhance the traceability of content generation. RAG is undoubtedly one of the most exciting areas of artificial intelligence research. For more details about RAG, please refer to the column article on this site "What are the new developments in RAG, which specializes in making up for the shortcomings of large models?" This review explains it clearly." But RAG is not perfect, and users often encounter some "pain points" when using it. Recently, NVIDIA’s advanced generative AI solution

PHP Practice: Code Example to Quickly Implement the Fibonacci Sequence The Fibonacci Sequence is a very interesting and common sequence in mathematics. It is defined as follows: the first and second numbers are 0 and 1, and from the third Starting with numbers, each number is the sum of the previous two numbers. The first few numbers in the Fibonacci sequence are 0,1,1.2,3,5,8,13,21,...and so on. In PHP, we can generate the Fibonacci sequence through recursion and iteration. Below we will show these two