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- MIT Team Introduces Sybil: A Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomography - MarkTechPost https://www.marktechpost.com/2023/01/24/mit-team-introduces-sybil-a-deep-learning-model-to-predict-future-lung-cancer-risk-from-a-single-low-dose-chest-computed-tomography/ 1 comment
- Top Large Language Models (LLMs) in 2023 from OpenAI, Google AI, Deepmind, Anthropic, Baidu, Huawei, Meta AI, AI21 Labs, LG AI Research and NVIDIA - MarkTechPost https://www.marktechpost.com/2023/02/22/top-large-language-models-llms-in-2023-from-openai-google-ai-deepmind-anthropic-baidu-huawei-meta-ai-ai21-labs-lg-ai-research-and-nvidia/ 1 comment
- 5 GANs Concepts You Should Know About in 2023 - MarkTechPost https://www.marktechpost.com/2023/02/04/5-gans-concepts-you-should-know-about-in-2023/ 0 comments
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- Transformer models: an introduction and catalog — 2023 Edition - AI, software, tech, and people, not in that order… by X https://amatriain.net/blog/transformer-models-an-introduction-and-catalog-2d1e9039f376/ 4 comments
- What is Field Programmable Gate Array (FPGA): FPGA vs. GPU for Artificial Intelligence (AI) - MarkTechPost https://www.marktechpost.com/2023/01/14/what-is-field-programmable-gate-array-fpga-fpga-vs-gpu-for-artificial-intelligence-ai/ 3 comments
- Visualizing A Neural Machine Translation Model (Mechanics of Seq2seq Models With Attention) – Jay Alammar – Visualizing machine learning one concept at a time. https://jalammar.github.io/visualizing-neural-machine-translation-mechanics-of-seq2seq-models-with-attention/ 1 comment
- Artificial Intelligence (AI) Research Innovations in 2022 from Google, NVIDIA, Salesforce, Meta, Apple, Amazon, and AI2 - MarkTechPost https://www.marktechpost.com/2023/01/10/artificial-intelligence-ai-research-innovations-in-2022-from-google-nvidia-salesforce-meta-apple-amazon-and-ai2/ 0 comments
- Best Practices For Machine Learning Model Monitoring - MarkTechPost https://www.marktechpost.com/2023/01/22/best-practices-for-machine-learning-model-monitoring/ 0 comments
- https://proceedings.neurips.cc/paper/2017/file/3f5ee243547dee91fbd053c1c4a845aa-Paper.pdf 0 comments
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