/AI Weekly/Issue 70
OpenAI unveils a model that can fact-check itself
Published Tuesday, September 17, 2024
ChatGPT maker OpenAI has announced its next major product release: An generative AI model code-named Strawberry, officially called OpenAI o1. To be more precise, o1 is actually a family of models. Two are available today, o1-preview and o1 mini, in both chatbot form and OpenAI’s API.
Large language models (LLMs) have achieved unprecedented accuracy on medical question-answering benchmarks, showcasing their potential to revolutionize healthcare by supporting clinicians and patients. However, these benchmarks often fail to capture the full complexity of real-world medical scenarios.
Federated Learning (FL) is a novel machine learning approach that allows the model trainer to access more data samples, by training the model across multiple decentralized data sources, while data access constraints are in place. Such trained models can achieve significantly higher performance beyond what can be done when trained on a single data source. As part of FL's promises, none of the training data is ever transmitted to any central location, ensuring that sensitive data remains local and private. These characteristics make FL perfectly suited for large-scale applications in healthcare, where a variety of compliance constraints restrict how data may be handled, processed, and stored. Despite the apparent benefits of federated learning, the heterogeneity in the local data distributions pose significant challenges, and such challenges are even more pronounced in the case of multilingual data providers. In this paper we present a federated learning system for training a large-scale multi-lingual model suitable for fine-tuning on downstream tasks such as medical entity tagging. Our work represents one of the first such production-scale systems, capable of training across multiple highly heterogeneous data providers, and achieving levels of accuracy that could not be otherwise achieved by using central training with public data. Finally, we show that the global model performance can be further improved by a training step performed locally.
Join us in this episode where we talk with Ayça Baş, Senior Cloud Advocate at Microsoft about Teams AI library and building custom engine copilots for M365.
Dive into the future with Abdul Rasheed Feroz Khan, a Microsoft MVP on Azure and CEO of CodeSizzler! Discover how AI is revolutionizing industries from healthcare to logistics and adding immense value every day.
French AI startup Mistral has released its first model that can process images as well as text. Called Pixtral 12B, the 12-billion-parameter model is roughly 24GB size. (Parameters roughly correspond to a model’s problem-solving skills, and models with more parameters generally perform better than those with fewer parameters.) Available on GitHub as well as the AI and machine […]
A visual neuroscientist realized he saw green and blue differently to his wife. He designed an interactive site that has received over 1.5m visits It started with an argument over a blanket. “I’m a visual neuroscientist, and my wife, Dr Marissé Masis-Solano, is an ophthalmologist,” says Dr Patrick Mineault, designer of the viral web app ismy.blue. “We have this argument about a blanket in our house. I think it’s unambiguously green and she thinks it’s unambiguously blue.”
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