Latest from Google AI – Announcing the ICDAR 2023 Competition on Hierarchical Text Detection and Recognition

Posted by Shangbang Long, Software Engineer, Google Research The last few decades have witnessed the rapid development of Optical Character Recognition (OCR) technology, which has evolved from an academic benchmark task used in early breakthroughs of deep learning research to tangible products available in consumer devices and to third party developers for daily use. These…

Latest from Google AI – Universal Speech Model (USM): State-of-the-art speech AI for 100+ languages

Posted by Yu Zhang, Research Scientist, and James Qin, Software Engineer, Google Research Last November, we announced the 1,000 Languages Initiative, an ambitious commitment to build a machine learning (ML) model that would support the world’s one thousand most-spoken languages, bringing greater inclusion to billions of people around the globe. However, some of these languages…

Latest from Google AI – Performer-MPC: Navigation via real-time, on-robot transformers

Posted by Krzysztof Choromanski, Staff Research Scientist, Robotics at Google, and Xuesu Xiao, Visiting Researcher, George Mason University Despite decades of research, we don’t see many mobile robots roaming our homes, offices, and streets. Real-world robot navigation in human-centric environments remains an unsolved problem. These challenging situations require safe and efficient navigation through tight spaces,…

Latest from MIT : Large language models are biased. Can logic help save them?

Turns out, even language models “think” they’re biased. When prompted in ChatGPT, the response was as follows: “Yes, language models can have biases, because the training data reflects the biases present in society from which that data was collected. For example, gender and racial biases are prevalent in many real-world datasets, and if a language…

Latest from MIT Tech Review – The inside story of how ChatGPT was built from the people who made it

When OpenAI launched ChatGPT, with zero fanfare, in late November 2022, the San Francisco–based artificial-intelligence company had few expectations. Certainly, nobody inside OpenAI was prepared for a viral mega-hit. The firm has been scrambling to catch up—and capitalize on its success—ever since. It was viewed in-house as a “research preview,” says Sandhini Agarwal, who works…

Latest from MIT : Robot armies duke it out in Battlecode’s epic on-screen battles

In a packed room in MIT’s Stata Center, hundreds of digital robots collide across a giant screen projected at the front of the room. A crowd of students in the audience gasps and cheers as the battle’s outcome hangs in the balance. In an upper corner of the screen, the people who have programmed the…

Latest from Google AI – Distributed differential privacy for federated learning

Posted by Florian Hartmann, Software Engineer, and Peter Kairouz, Research Scientist, Google Research Federated learning is a distributed way of training machine learning (ML) models where data is locally processed and only focused model updates and metrics that are intended for immediate aggregation are shared with a server that orchestrates training. This allows the training…

Latest from MIT : Integrating humans with AI in structural design

Modern fabrication tools such as 3D printers can make structural materials in shapes that would have been difficult or impossible using conventional tools. Meanwhile, new generative design systems can take great advantage of this flexibility to create innovative designs for parts of a new building, car, or virtually any other device. But such “black box”…

Latest from Google AI – Teaching old labels new tricks in heterogeneous graphs

Posted by Minji Yoon, Research Intern, and Bryan Perozzi, Research Scientist, Google Research, Graph Mining Team Industrial applications of machine learning are commonly composed of various items that have differing data modalities or feature distributions. Heterogeneous graphs (HGs) offer a unified view of these multimodal data systems by defining multiple types of nodes (for each…

Latest from Google AI – Datasets at your fingertips in Google Search

Posted by Natasha Noy, Research Scientist, and Omar Benjelloun, Software Engineer, Google Research Access to datasets is critical to many of today’s endeavors across verticals and industries, whether scientific research, business analysis, or public policy. In the scientific community and throughout various levels of the public sector, reproducibility and transparency are essential for progress, so…