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Artificial Intelligence Boom
The AI boom is an ongoing period of rapid progress in the field of artificial intelligence (AI) that started in the late 2010s before gaining international prominence in the early 2020s. Examples include large language models and generative AI applications developed by OpenAI as well as protein folding prediction led by Google DeepMind. This period is sometimes referred to as an AI spring, to contrast it with previous AI winters. History In 2012, a University of Toronto research team used artificial neural networks and deep learning techniques to lower the error rate below 25% for the first time during the ImageNet challenge for object recognition in computer vision. The event catalyzed the AI boom later that decade, when many alumni of the ImageNet challenge became leaders in the tech industry. In March 2016, AlphaGo beat Lee Sedol in a five-game match, marking the first time a computer Go program had beaten a 9-dan professional without handicap. This match led to sig ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
News Magazine
A news magazine is a typed, printed, and published magazine, radio, or television program, usually published weekly, consisting of articles about current events. News magazines generally discuss stories in greater depth than newspapers or newscasts do, and aim to give the consumer an understanding of the important events beyond the basic facts. Broadcast news magazines Radio news magazines are similar to television news magazines. Unlike radio newscasts, which are typically about five minutes in length, radio news magazines can run from 30 minutes to three hours or more. Television news magazines provide a similar service to print news magazines, but their stories are presented as short television documentaries rather than written articles; in contrast to a daily newscast, news magazines allow more in-depth coverage of specific topics, including Current affairs (news format), current affairs, investigative journalism (including hidden camera investigations), major interviews ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
AlexNet
AlexNet is a convolutional neural network architecture developed for image classification tasks, notably achieving prominence through its performance in the ImageNet Large Scale Visual Recognition Challenge (ILSVRC). It classifies images into 1,000 distinct object categories and is regarded as the first widely recognized application of deep convolutional networks in large-scale visual recognition. Developed in 2012 by Alex Krizhevsky in collaboration with Ilya Sutskever and his Ph.D. advisor Geoffrey Hinton at the University of Toronto, the model contains 60 million parameters and 650,000 neurons. The original paper's primary result was that the depth of the model was essential for its high performance, which was computationally expensive, but made feasible due to the utilization of graphics processing units (GPUs) during training. The three formed team SuperVision and submitted AlexNet in the ImageNet Large Scale Visual Recognition Challenge on September 30, 2012. The network ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Stanford University
Leland Stanford Junior University, commonly referred to as Stanford University, is a Private university, private research university in Stanford, California, United States. It was founded in 1885 by railroad magnate Leland Stanford (the eighth List of governors of California, governor of and then-incumbent List of United States senators from California, United States senator representing California) and his wife, Jane Stanford, Jane, in memory of their only child, Leland Stanford Jr., Leland Jr. The university admitted its first students in 1891, opening as a Mixed-sex education, coeducational and non-denominational institution. It struggled financially after Leland died in 1893 and again after much of the campus was damaged by the 1906 San Francisco earthquake. Following World War II, university Provost (education), provost Frederick Terman inspired an entrepreneurship, entrepreneurial culture to build a self-sufficient local industry (later Silicon Valley). In 1951, Stanfor ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Transformer (machine Learning Model)
The transformer is a deep learning architecture based on the multi-head attention mechanism, in which text is converted to numerical representations called tokens, and each token is converted into a vector via lookup from a word embedding table. At each layer, each token is then contextualized within the scope of the context window with other (unmasked) tokens via a parallel multi-head attention mechanism, allowing the signal for key tokens to be amplified and less important tokens to be diminished. Transformers have the advantage of having no recurrent units, therefore requiring less training time than earlier recurrent neural architectures (RNNs) such as long short-term memory (LSTM). Later variations have been widely adopted for training large language models (LLM) on large (language) datasets. The modern version of the transformer was proposed in the 2017 paper " Attention Is All You Need" by researchers at Google. Transformers were first developed as an improvement ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Diffusion Model
In machine learning, diffusion models, also known as diffusion-based generative models or score-based generative models, are a class of latent variable model, latent variable generative model, generative models. A diffusion model consists of two major components: the forward diffusion process, and the reverse sampling process. The goal of diffusion models is to learn a diffusion process for a given dataset, such that the process can generate new elements that are distributed similarly as the original dataset. A diffusion model models data as generated by a diffusion process, whereby a new datum performs a Wiener process, random walk with drift through the space of all possible data. A trained diffusion model can be sampled in many ways, with different efficiency and quality. There are various equivalent formalisms, including Markov chains, denoising diffusion probabilistic models, noise conditioned score networks, and stochastic differential equations. They are typically trained ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Generative Adversarial Network
A generative adversarial network (GAN) is a class of machine learning frameworks and a prominent framework for approaching generative artificial intelligence. The concept was initially developed by Ian Goodfellow and his colleagues in June 2014. In a GAN, two neural networks compete with each other in the form of a zero-sum game, where one agent's gain is another agent's loss. Given a training set, this technique learns to generate new data with the same statistics as the training set. For example, a GAN trained on photographs can generate new photographs that look at least superficially authentic to human observers, having many realistic characteristics. Though originally proposed as a form of generative model for unsupervised learning, GANs have also proved useful for semi-supervised learning, fully supervised learning, and reinforcement learning. The core idea of a GAN is based on the "indirect" training through the discriminator, another neural network that can tell ho ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Graphics Processing Unit
A graphics processing unit (GPU) is a specialized electronic circuit designed for digital image processing and to accelerate computer graphics, being present either as a discrete video card or embedded on motherboards, mobile phones, personal computers, workstations, and game consoles. GPUs were later found to be useful for non-graphic calculations involving embarrassingly parallel problems due to their parallel structure. The ability of GPUs to rapidly perform vast numbers of calculations has led to their adoption in diverse fields including artificial intelligence (AI) where they excel at handling data-intensive and computationally demanding tasks. Other non-graphical uses include the training of neural networks and cryptocurrency mining. History 1970s Arcade system boards have used specialized graphics circuits since the 1970s. In early video game hardware, RAM for frame buffers was expensive, so video chips composited data together as the display was being scann ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Generative Artificial Intelligence
Generative artificial intelligence (Generative AI, GenAI, or GAI) is a subfield of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. These models Machine learning, learn the underlying patterns and structures of their training data and use them to produce new data based on the input, which often comes in the form of natural language Prompt (natural language), prompts. Generative AI tools have become more common since an "AI boom" in the 2020s. This boom was made possible by improvements in transformer (machine learning model), transformer-based deep learning, deep neural networks, particularly large language models (LLMs). Major tools include chatbots such as ChatGPT, Microsoft Copilot, Copilot, Gemini (chatbot), Gemini, Grok (chatbot), Grok, and DeepSeek (chatbot), DeepSeek; text-to-image models such as Stable Diffusion, Midjourney, and DALL-E; and text-to-video models such as Sora (text-to-video model), Sora and Veo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
YouTube
YouTube is an American social media and online video sharing platform owned by Google. YouTube was founded on February 14, 2005, by Steve Chen, Chad Hurley, and Jawed Karim who were three former employees of PayPal. Headquartered in San Bruno, California, it is the second-most-visited website in the world, after Google Search. In January 2024, YouTube had more than 2.7billion monthly active users, who collectively watched more than one billion hours of videos every day. , videos were being uploaded to the platform at a rate of more than 500 hours of content per minute, and , there were approximately 14.8billion videos in total. On November 13, 2006, YouTube was purchased by Google for $1.65 billion (equivalent to $ billion in ). Google expanded YouTube's business model of generating revenue from advertisements alone, to offering paid content such as movies and exclusive content produced by and for YouTube. It also offers YouTube Premium, a paid subs ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Go Ranks And Ratings
There are various systems of Go ranks and ratings that measure the skill in the traditional board game Go. Traditionally, Go rankings have been measured using a system of dan and kyu ranks. Especially in amateur play, these ranks facilitate the handicapping system, with a difference of one rank roughly corresponding to one free move at the beginning of the game. This system is also commonly used in many East Asian martial arts, where it often corresponds with a belt color. With the ready availability of calculators and computers, rating systems have been introduced. In such systems, a rating is rigorously calculated on the basis of game results. Kyu and dan ranks Traditionally, the level of players has been defined using ''kyu'' and ''dan'' ranks. Kyu ranks are considered ''student'' ranks. Dan ranks are considered ''master'' ranks. Beginners who have just learned the rules of the game are usually around 30th kyu. As they progress, they advance numerically downwards throug ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
AlphaGo Versus Lee Sedol
AlphaGo versus Lee Sedol, also known as the DeepMind Challenge Match, was a five-game Go (game), Go match between top Go player Lee Sedol and AlphaGo, a computer Go program developed by DeepMind, played in Seoul, South Korea between the 9th and 15 March 2016. AlphaGo won all but the fourth game; all games were won by resignation. The match has been compared with the historic chess match between Deep Blue versus Garry Kasparov, Deep Blue and Garry Kasparov in 1997. The winner of the match was slated to win $1 million. Since AlphaGo won, Google DeepMind stated that the prize would be donated to charities, including UNICEF, and List of Go organizations, Go organisations. Lee received $170,000 ($150,000 for participating in the five games and an additional $20,000 for winning one game). After the match, The Korea Baduk Association awarded AlphaGo the highest Go grandmaster rank – an "honorary Go ranks and ratings, 9 dan". It was given in recognition of AlphaGo's "sincere efforts" t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Lee Sedol
Lee Sedol (; born 2 March 1983), or Lee Se-dol, is a South Korean former professional Go player of 9 dan rank. As of February 2016, he ranked second in international titles (18), behind only Lee Chang-ho (21). His nickname is "The Strong Stone" ("Ssen-dol"). In March 2016, he played a notable series of matches against the program AlphaGo that ended in Lee losing 1–4. Lee announced his retirement from professional play in November 2019, stating he could never be the top overall player of Go due to the increasing dominance of AI, which he called "an entity that cannot be defeated". Lee shared in a 2024 interview, "losing to AI, in a sense, meant my entire world was collapsing. ... I could no longer enjoy the game. So I retired." Biography Lee was born in South Korea in 1983. He is known as 'Bigeumdo Boy' because he was born and grew up on Bigeumdo Island. He studied at the Korea Baduk Association. He is the fifth-youngest (12 years 4 months) to become a profession ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
