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GPT-2

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GPT-2, short for Generative Pretrained Transformer 2, is a sophisticated artificial intelligence[1] model designed for natural language processing tasks. Developed and introduced by OpenAI[2] in February 2019, it’s notable for its ability to generate diverse types of text, with capabilities extending to answering questions and autocompleting code. GPT-2 was trained on a large corpus of online text, known as WebText, and is powered by a whopping 1.5 billion parameters. While its deployment can be resource-intensive, it has been used in various unique applications, including text-based adventure games and subreddit simulations. Despite initial fears of misuse, the full GPT-2 model was released in November 2019 after concerns didn’t materialize. However, a smaller model, DistilGPT2, was created to alleviate resource issues. Looking forward, the breakthroughs with GPT-2 pave the way for future advancements in AI text generation.

Terms definitions
1. artificial intelligence.
1 Artificial Intelligence (AI) refers to the field of computer science that aims to create systems capable of performing tasks that would normally require human intelligence. These tasks include reasoning, learning, planning, perception, and language understanding. AI draws from different fields including psychology, linguistics, philosophy, and neuroscience. The field is prominent in developing machine learning models and natural language processing systems. It also plays a significant role in creating virtual assistants and affective computing systems. AI applications extend across various sectors including healthcare, industry, government, and education. Despite its benefits, AI also raises ethical and societal concerns, necessitating regulatory policies. AI continues to evolve with advanced techniques such as deep learning and generative AI, offering new possibilities in various industries.
2 Artificial Intelligence, commonly known as AI, is a field of computer science dedicated to creating intelligent machines that perform tasks typically requiring human intellect. These tasks include problem-solving, recognizing speech, understanding natural language, and making decisions. AI is categorised into two types: narrow AI, which is designed to perform a specific task, like voice recognition, and general AI, which can perform any intellectual tasks a human being can do. It's a continuously evolving technology that draws from various fields including computer science, mathematics, psychology, linguistics, and neuroscience. The core concepts of AI include reasoning, knowledge representation, planning, natural language processing, and perception. AI has wide-ranging applications across numerous sectors, from healthcare and gaming to military and creativity, and its ethical considerations and challenges are pivotal to its development and implementation.
2. OpenAI ( OpenAI ) OpenAI is a prominent artificial intelligence (AI) research organization that was established in December 2015. It was founded by a group of technology entrepreneurs, including Elon Musk and Sam Altman, to develop and promote friendly AI for the benefit of all of humanity. As an organization, OpenAI places a significant emphasis on openness, collaboration, and transparency, often partnering with other institutions in their research. OpenAI has been funded with over $1 billion and is based in San Francisco. The organization has developed various AI platforms, such as OpenAI Gym and Universe, and has also introduced several groundbreaking AI models, including GPT-3 and DALL-E. In a significant shift in 2019, OpenAI transitioned to a capped for-profit model to attract more funding, with profits capped at 100 times the investment. They have also collaborated with Microsoft on a $1 billion investment. OpenAI's research and models have wide-ranging commercial applications, driving the future of AI technology.
GPT-2 (Wikipedia)

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 a dataset of 8 million web pages. It was partially released in February 2019, followed by full release of the 1.5-billion-parameter model on November 5, 2019.

Generative Pre-trained Transformer 2 (GPT-2)
Original author(s)OpenAI
Initial release14 February 2019; 5 years ago (14 February 2019)
Repositoryhttps://github.com/openai/gpt-2
PredecessorGPT-1
SuccessorGPT-3
Type
LicenseMIT
Websiteopenai.com/blog/gpt-2-1-5b-release/

GPT-2 was created as a "direct scale-up" of GPT-1 with a ten-fold increase in both its parameter count and the size of its training dataset. It is a general-purpose learner and its ability to perform the various tasks was a consequence of its general ability to accurately predict the next item in a sequence, which enabled it to translate texts, answer questions about a topic from a text, summarize passages from a larger text, and generate text output on a level sometimes indistinguishable from that of humans, however it could become repetitive or nonsensical when generating long passages. It was superseded by GPT-3 and GPT-4 models, which are not open source anymore.

GPT-2 has, like its predecessor GPT-1 and its successors GPT-3 and GPT-4, a generative pre-trained transformer architecture, implementing a deep neural network, specifically a transformer model, which uses attention instead of older recurrence- and convolution-based architectures. Attention mechanisms allow the model to selectively focus on segments of input text it predicts to be the most relevant. This model allows for greatly increased parallelization, and outperforms previous benchmarks for RNN/CNN/LSTM-based models.

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