Meta’s free GPT-3 replica exposes the business benefits of AI transparency

May04
by on May 4, 2022 at 8:16 pm
Posted In: Insider


The notoriously secretive Meta has set a milestone for transparency. The company this week offered the entire research community access to a fully-trained large language model (LLM). Named the Open Pretrained Transformer (OPT), the system mirrors the performance and size of OpenAI’s vaunted GPT-3 model. This mimicry is deliberate. While GPT-3 has a stunning ability to produce human-like text, it also has a powerful capacity for biases, bigotry, and disinformation. OPT’s creators said their system can reduce these risks: Our aim in developing this suite of OPT models is to enable reproducible and responsible research at scale, and to bring…

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What’s the transformer machine learning model? And why should you care?

May03
by on May 3, 2022 at 2:26 pm
Posted In: Insights


This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI. (In partnership with Paperspace) In recent years, the transformer model has become one of the main highlights of advances in deep learning and deep neural networks. It is mainly used for advanced applications in natural language processing. Google is using it to enhance its search engine results. OpenAI has used transformers to create its famous GPT-2 and GPT-3 models. Since its debut in 2017, the transformer architecture has evolved and branched out into many different variants, expanding beyond language…

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Is it ethical to use AI-generated content without crediting the machine?

May02
by on May 2, 2022 at 7:26 pm
Posted In: artificial intelligence


A team of researchers recently developed an algorithm that generates original reviews for wines and beers. Considering that computers can’t taste booze, this makes for a curious use-case for machine learning. The AI sommelier was trained on a database containing hundreds of thousands of beer and wine reviews. In essence, it aggregates those reviews and picks out keywords. When the researchers ask it to generate its own review for a specific wine or beer, it generates something similar to previous reviews. According to the researchers, its output is comparable to, and often indistinguishable from, reviews created purely by humans. The…

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