Latest from Google AI – Learning to Walk in the Wild from Terrain Semantics

Posted by Yuxiang Yang, Student Researcher, Robotics at Google An important promise for quadrupedal robots is their potential to operate in complex outdoor environments that are difficult or inaccessible for humans. Whether it’s to find natural resources deep in the mountains, or to search for life signals in heavily-damaged earthquake sites, a robust and versatile…

Latest from Google AI – A Multi-Axis Approach for Vision Transformer and MLP Models

Posted by Zhengzhong Tu and Yinxiao Li, Software Engineers, Google Research Convolutional neural networks have been the dominant machine learning architecture for computer vision since the introduction of AlexNet in 2012. Recently, inspired by the evolution of Transformers in natural language processing, attention mechanisms have been prominently incorporated into vision models. These attention methods boost…

Latest from MIT : AI system makes models like DALL-E 2 more creative

The internet had a collective feel-good moment with the introduction of DALL-E, an artificial intelligence-based image generator inspired by artist Salvador Dali and the lovable robot WALL-E that uses natural language to produce whatever mysterious and beautiful image your heart desires. Seeing typed-out inputs like “smiling gopher holding an ice cream cone” instantly spring to…

Latest from MIT : Collaborative machine learning that preserves privacy

Training a machine-learning model to effectively perform a task, such as image classification, involves showing the model thousands, millions, or even billions of example images. Gathering such enormous datasets can be especially challenging when privacy is a concern, such as with medical images. Researchers from MIT and the MIT-born startup DynamoFL have now taken one…

Latest from Google AI – Digitizing Smell: Using Molecular Maps to Understand Odor

Posted by Richard C. Gerkin, Google Research, and Alexander B. Wiltschko, Google Did you ever try to measure a smell? …Until you can measure their likenesses and differences you can have no science of odor. If you are ambitious to found a new science, measure a smell.— Alexander Graham Bell, 1914. How can we measure…

Latest from MIT : Analyzing the potential of AlphaFold in drug discovery

Over the past few decades, very few new antibiotics have been developed, largely because current methods for screening potential drugs are prohibitively expensive and time-consuming. One promising new strategy is to use computational models, which offer a potentially faster and cheaper way to identify new drugs. A new study from MIT reveals the potential and…

Latest from MIT : Using machine learning to identify undiagnosable cancers

The first step in choosing the appropriate treatment for a cancer patient is to identify their specific type of cancer, including determining the primary site — the organ or part of the body where the cancer begins. In rare cases, the origin of a cancer cannot be determined, even with extensive testing. Although these cancers…

Latest from Google AI – Announcing the Patent Phrase Similarity Dataset

Posted Grigor Aslanyan, Software Engineer, Google Patent documents typically use legal and highly technical language, with context-dependent terms that may have meanings quite different from colloquial usage and even between different documents. The process of using traditional patent search methods (e.g., keyword searching) to search through the corpus of over one hundred million patent documents…

Latest from MIT Tech Review – What does GPT-3 “know” about me? 

For a reporter who covers AI, one of the biggest stories this year has been the rise of large language models. These are AI models that produce text a human might have written—sometimes so convincingly they have tricked people into thinking they are sentient.  These models’ power comes from troves of publicly available human-created text…

Latest from MIT : AI that can learn the patterns of human language

Human languages are notoriously complex, and linguists have long thought it would be impossible to teach a machine how to analyze speech sounds and word structures in the way human investigators do. But researchers at MIT, Cornell University, and McGill University have taken a step in this direction. They have demonstrated an artificial intelligence system…