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Latest from Google AI – PaLI: Scaling Language-Image Learning in 100+ Languages
Posted by Xi Chen and Xiao Wang, Software Engineers, Google Research Advanced language models (e.g., GPT, GLaM, PaLM and T5) have demonstrated diverse capabilities and achieved impressive results across tasks and languages by scaling up their number of parameters. Vision-language (VL) models can benefit from similar scaling to address many tasks, such as image captioning,…
Latest from Google AI – PaLM-E: An embodied multimodal language model
Posted by Danny Driess, Student Researcher, and Pete Florence, Research Scientist, Robotics at Google Recent years have seen tremendous advances across machine learning domains, from models that can explain jokes or answer visual questions in a variety of languages to those that can produce images based on text descriptions. Such innovations have been possible due…
Latest from MIT Tech Review – AI models can outperform humans in tests to identify mental states
Humans are complicated beings. The ways we communicate are multilayered, and psychologists have devised many kinds of tests to measure our ability to infer meaning and understanding from interactions with each other. AI models are getting better at these tests. New research published today in Nature Human Behavior found that some large language models (LLMs)…
Latest from Google AI – Scanned Objects by Google Research: A Dataset of 3D-Scanned Common Household Items
Posted by Laura Downs and Anthony Francis, Software Engineers, Robotics at Google Many recent advances in computer vision and robotics rely on deep learning, but training deep learning models requires a wide variety of data to generalize to new scenarios. Historically, deep learning for computer vision has relied on datasets with millions of items that…
Latest from MIT : Study could lead to LLMs that are better at complex reasoning
For all their impressive capabilities, large language models (LLMs) often fall short when given challenging new tasks that require complex reasoning skills. While an accounting firm’s LLM might excel at summarizing financial reports, that same model could fail unexpectedly if tasked with predicting market trends or identifying fraudulent transactions. To make LLMs more adaptable, MIT…
Latest from Google AI – Learning to Route by Task for Efficient Inference
Posted by Sneha Kudugunta, Research Software Engineer and Orhan Firat, Research Scientist, Google Research Scaling large language models has resulted in significant quality improvements natural language understanding (T5), generation (GPT-3) and multilingual neural machine translation (M4). One common approach to building a larger model is to increase the depth (number of layers) and width (layer…