Ford v Ferrari to ChatGPT v Bard
The primary drivers of AI advancements right now are not addressing user needs or information access problems; they are, rather, driven by competition.
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The primary drivers of AI advancements right now are not addressing user needs or information access problems; they are, rather, driven by competition.
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As an AI language model, ChatGPT can offer several suggestions and guidelines that can help you write better-quality code.
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Our study reveals that the potential for bias within AI-driven language models, such as GPT-3, poses a significant threat to the integrity of science. These models are trained on vast amounts of data, primarily from the internet, which can lead to a bias in the data. For example, if the data source is biased or incomplete, this bias will be reflected in the model’s output.
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Introduces ChatGPT and discusses the academic integrity implications and concerns raised by researchers and educational institutions and the importance of rethinking learning assessment approaches and strategies.
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ChatGPT is a simple-to-use conversation agent developed by OpenAI. Of course, this is not the first time we have seen an AI agent that generates information. Google’s LaMDA and Meta’s Galactica are some recent examples for text generation.
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Have you ever wondered how Google helps you complete your search query by suggesting the next terms of your query? Large Language Models (LLMs) power this feature. But LLMs go beyond that feature. Today, LLMs are used in building AI systems and applications ranging from recognizing speech to writing poetry. They have become very powerful, but there are also pitfalls.
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