Ask a Techspert: What is generative AI?
Favorite A Google AI expert answers common questions about generative AI, large language models, machine learning and more. View Original Source (blog.google/technology/ai/) Here.
Towards ML-enabled cleaning robots
Favorite Posted by Thomas Lew, Research Intern, and Montserrat Gonzalez Arenas, Research Engineer, Google Research, Brain Team Over the past several years, the capabilities of robotic systems have improved dramatically. As the technology continues to improve and robotic agents are more routinely deployed in real-world environments, their capacity to assist
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Shared by Google AI Technology April 7, 2023
Directing ML toward natural hazard mitigation through collaboration
Favorite Posted by Oren Gilon, Software Engineer, and Grey Nearing, Research Scientist, Google Research Floods are the most common type of natural disaster, affecting more than 250 million people globally each year. As part of Google’s Crisis Response and our efforts to address the climate crisis, we are using machine
Read More Shared by Google AI Technology April 7, 2023
How Project Starline improves remote communication
Favorite Posted by Greg Blascovich and Eric Gomez, User Researchers, Google As companies settle into a new normal of hybrid and distributed work, remote communication technology remains critical for connecting and collaborating with colleagues. While this technology has improved, the core user experience often falls short: conversation can feel stilted,
Read More Shared by Google AI Technology April 6, 2023
Pre-trained Gaussian processes for Bayesian optimization
Favorite Posted by Zi Wang and Kevin Swersky, Research Scientists, Google Research, Brain Team Bayesian optimization (BayesOpt) is a powerful tool widely used for global optimization tasks, such as hyperparameter tuning, protein engineering, synthetic chemistry, robot learning, and even baking cookies. BayesOpt is a great strategy for these problems because
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Scaling vision transformers to 22 billion parameters
Favorite Posted by Piotr Padlewski and Josip Djolonga, Software Engineers, Google Research Large Language Models (LLMs) like PaLM or GPT-3 showed that scaling transformers to hundreds of billions of parameters improves performance and unlocks emergent abilities. The biggest dense models for image understanding, however, have reached only 4 billion parameters,
Read More Shared by Google AI Technology March 31, 2023
Data-centric ML benchmarking: Announcing DataPerf’s 2023 challenges
Favorite Posted by Peter Mattson, Senior Staff Engineer, ML Performance, and Praveen Paritosh, Senior Research Scientist, Google Research, Brain Team Machine learning (ML) offers tremendous potential, from diagnosing cancer to engineering safe self-driving cars to amplifying human productivity. To realize this potential, however, organizations need ML solutions to be reliable
Read More Shared by Google AI Technology March 30, 2023
Watch Katie Couric and Think with Google’s new interview series
Favorite Katie Couric hosts Future Ready by Think with Google, a new interview series featuring experts in AI, cybersecurity and psychology. View Original Source (blog.google/technology/ai/) Here.
Leveraging transfer learning for large scale differentially private image classification
Favorite Posted by Harsh Mehta, Software Engineer, and Walid Krichene, Research Scientist, Google Research Large deep learning models are becoming the workhorse of a variety of critical machine learning (ML) tasks. However, it has been shown that without any protection it is plausible for bad actors to attack a variety
Read More Shared by Google AI Technology March 28, 2023
A shared agenda for responsible AI progress
Favorite AI can be hugely beneficial to society if citizens, educators, academics, civil society and governments unite to shape it responsibly. View Original Source (blog.google/technology/ai/) Here.