Before a machine-learning model can complete a task, such as identifying cancer in medical images, the model must be trained. Training image classification models typically involves showing the model millions of example images gathered into a massive dataset. However, using real image data can raise practical and ethical concerns: The images could run afoul of…
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. When Meta launched Galactica, an open-source large language model designed to help scientists, the company—reeling from criticism of its expensive metaverse investments and its recent massive layoffs—was hoping for a big PR win. Instead,…
When Ananye Agarwal took his dog out for a walk up and down the steps in the local park near Carnegie Mellon University, other dogs stopped in their tracks. That’s because Agarwal’s dog was a robot—and a special one at that. Unlike other robots, which tend to rely heavily on an internal map to get…
Posted by Mohammad Saleh, Software Engineer, Google Research, Brain Team, and Yinan Wang, Software Engineer, Google Workspace Information overload is a significant challenge for many organizations and individuals today. It can be overwhelming to keep up with incoming chat messages and documents that arrive at our inbox everyday. This has been exacerbated by the increase…
On November 15 Meta unveiled a new large language model called Galactica, designed to assist scientists. But instead of landing with the big bang Meta hoped for, Galactica has died with a whimper after three days of intense criticism. Yesterday the company took down the public demo that it had encouraged everyone to try out….
Posted by Mahima Pushkarna, Senior Interaction Designer, and Andrew Zaldivar, Senior Developer Relations Engineer, Google Research As machine learning (ML) research moves toward large-scale models capable of numerous downstream tasks, a shared understanding of a dataset’s origin, development, intent, and evolution becomes increasingly important for the responsible and informed development of ML models. However, knowledge…
Posted by Yanqi Zhou, Research Scientist, Google Research Brain Team The capacity of a neural network to absorb information is limited by the number of its parameters, and as a consequence, finding more effective ways to increase model parameters has become a trend in deep learning research. Mixture-of-experts (MoE), a type of conditional computation where…
Although the world population has continued to steadily increase, farming practices have largely remained the same. Amid this growth, climate change poses great challenges to the agricultural industry and its capacity to feed the world sustainably. According to the World Bank, 70% of the world’s fresh water is used in agriculture and droughts and heat…
Last year, MIT researchers announced that they had built “liquid” neural networks, inspired by the brains of small species: a class of flexible, robust machine learning models that learn on the job and can adapt to changing conditions, for real-world safety-critical tasks, like driving and flying. The flexibility of these “liquid” neural nets meant boosting…
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Lately I’ve lost a lot of sleep over climate change. It’s just over five weeks until Christmas, and last weekend in London, it was warm enough to have a pint outside without…