Favorite Creating high-performance machine learning (ML) solutions relies on exploring and optimizing training parameters, also known as hyperparameters. Hyperparameters are the knobs and levers that we use to adjust the training process, such as learning rate, batch size, regularization strength, and others, depending on the specific model and task at
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Shared by AWS Machine Learning November 11, 2023
Favorite In the recent past, using machine learning (ML) to make predictions, especially for data in the form of text and images, required extensive ML knowledge for creating and tuning of deep learning models. Today, ML has become more accessible to any user who wants to use ML models to
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Shared by AWS Machine Learning November 11, 2023
Favorite We are witnessing a rapid increase in the adoption of large language models (LLM) that power generative AI applications across industries. LLMs are capable of a variety of tasks, such as generating creative content, answering inquiries via chatbots, generating code, and more. Organizations looking to use LLMs to power
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Shared by AWS Machine Learning November 11, 2023
Favorite Posted by Chintan Ghate, Software Engineer, and Diana Mincu, Research Engineer, Google Research As consumer technologies like fitness trackers and mobile phones become more widely used for health-related data collection, so does the opportunity to leverage these data pathways to study and advance our understanding of medical conditions. We
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Shared by Google AI Technology November 10, 2023
Favorite How Google Translate’s neural model taught it to understand bass from bass. View Original Source (blog.google/technology/ai/) Here.
Favorite Linked below is an excellent video on the 2022 KM strategy from the UN Development program. Good to see the focus on culture and networks. View Original Source (nickmilton.com) Here.
Favorite Generative AI models for coding companions are mostly trained on publicly available source code and natural language text. While the large size of the training corpus enables the models to generate code for commonly used functionality, these models are unaware of code in private repositories and the associated coding
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Shared by AWS Machine Learning November 10, 2023
Favorite Building out a machine learning operations (MLOps) platform in the rapidly evolving landscape of artificial intelligence (AI) and machine learning (ML) for organizations is essential for seamlessly bridging the gap between data science experimentation and deployment while meeting the requirements around model performance, security, and compliance. In order to
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Shared by AWS Machine Learning November 10, 2023
Favorite Posted by Katherine Heller, Research Scientist, Google Research, on behalf of the CAIR Team Artificial intelligence (AI) and related machine learning (ML) technologies are increasingly influential in the world around us, making it imperative that we consider the potential impacts on society and individuals in all aspects of the
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Shared by Google AI Technology November 9, 2023
Favorite Posted by Kevin Miao and Matt McEwen, Research Scientists, Quantum AI Team The qubits that make up Google quantum devices are delicate and noisy, so it’s necessary to incorporate error correction procedures that identify and account for qubit errors on the way to building a useful quantum computer. Two
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Shared by Google AI Technology November 9, 2023
Shared by AWS Machine Learning November 11, 2023
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