Linking pages
- AI21 Labs trains a massive language model to rival OpenAI's GPT-3 | VentureBeat https://venturebeat.com/2021/08/11/ai21-labs-trains-a-massive-language-model-to-rival-openais-gpt-3/ 5 comments
- Microsoft and Nvidia team up to train one of the world's largest language models | VentureBeat https://venturebeat.com/2021/10/11/microsoft-and-nvidia-team-up-to-train-one-of-the-worlds-largest-language-models/ 0 comments
- 2021 was a breakthrough year for AI | VentureBeat https://venturebeat.com/2021/12/29/2021-was-a-breakthrough-year-for-ai/ 0 comments
Linked pages
- Huawei tested AI software that could recognize Uighur minorities and alert police, report says - The Washington Post https://www.washingtonpost.com/technology/2020/12/08/huawei-tested-ai-software-that-could-recognize-uighur-minorities-alert-police-report-says/ 2903 comments
- Gradio https://gradio.app/ 29 comments
- Timnit Gebru: Google's 'dehumanizing' memo paints me as an angry Black woman | VentureBeat https://venturebeat.com/2020/12/10/timnit-gebru-googles-dehumanizing-memo-paints-me-as-an-angry-black-woman/ 6 comments
- MIT researchers warn that deep learning is approaching computational limits | VentureBeat https://venturebeat.com/2020/07/15/mit-researchers-warn-that-deep-learning-is-approaching-computational-limits/ 2 comments
- [2104.12369] PanGu-$α$: Large-scale Autoregressive Pretrained Chinese Language Models with Auto-parallel Computation https://arxiv.org/abs/2104.12369 0 comments
- [2103.03874] Measuring Mathematical Problem Solving With the MATH Dataset https://arxiv.org/abs/2103.03874 0 comments
- Training a single AI model can emit as much carbon as five cars in their lifetimes | MIT Technology Review https://www.technologyreview.com/2019/06/06/239031/training-a-single-ai-model-can-emit-as-much-carbon-as-five-cars-in-their-lifetimes/ 0 comments
- [2102.02503] Understanding the Capabilities, Limitations, and Societal Impact of Large Language Models https://arxiv.org/abs/2102.02503 0 comments
- [2101.05783] Persistent Anti-Muslim Bias in Large Language Models https://arxiv.org/abs/2101.05783 0 comments
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