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DeepSeek [a] (Chinese: 深度求索; pinyin: Shēndù Qiúsuǒ) is a Chinese artificial intelligence company that develops open-source large language models (LLMs). Based in Hangzhou, Zhejiang, it is owned and funded by Chinese hedge fund High-Flyer, whose co-founder, Liang Wenfeng, established the company in 2023 and serves as its CEO.
GitHub CEO Thomas Dohmke is right on the front line of artificial intelligence. GitHub, a software development platform, has been leading the charge in a key area that generative AI will ...
Windows 10 build 14316: Windows 10 version 1607 (Anniversary Update) WSL (no longer Beta) Windows 10 build 16251: Windows 10 version 1709 (Fall Creators Update) WSL 2 (lightweight VM) Windows 10 build 18917: Windows 10 version 2004 (also backported to 1903 and 1909) WSL 2 GPU support: Windows 10 build 20150: Windows 11 (also Windows 10 21H2 ...
The Transformer architecture, being modular, allows variations. Several common variations are described here. [61] An "encoder-only" Transformer applies the encoder to map an input text into a sequence of vectors that represent the input text. This is usually used for text embedding and representation learning for downstream applications.
GPT-4o ("o" for "omni") is a multilingual, multimodal generative pre-trained transformer developed by OpenAI and released in May 2024. [1] GPT-4o is free, but ChatGPT Plus subscribers have higher usage limits. [2]
Generative Pre-trained Transformer 2 (GPT-2) is a large language model by OpenAI and the second in their foundational series of GPT models. GPT-2 was pre-trained on a dataset of 8 million web pages. [ 2 ]
Transformer architecture is now used in many generative models that contribute to the ongoing AI boom. In language modelling, ELMo (2018) was a bi-directional LSTM that produces contextualized word embeddings, improving upon the line of research from bag of words and word2vec. It was followed by BERT (2018), an encoder-only Transformer model. [33]
According to OpenAI, Sora is a diffusion transformer [10] – a denoising latent diffusion model with one Transformer as the denoiser. A video is generated in latent space by denoising 3D "patches", then transformed to standard space by a video decompressor.