Machine learning (ML) is now mission critical in every industry. Business leaders are urging their technical teams to accelerate ML adoption across the enterprise to fuel innovation and long-term growth. But there is a disconnect between business leaders’ expectations for wide-scale ML deployment and the reality of what engineers and data scientists can actually build…
Posted by Xin Wang, Software Engineer, and Nishanth Dikkala, Research Scientist, Google Research Contemporary deep learning models have been remarkably successful in many domains, ranging from natural language to computer vision. Transformer neural networks (transformers) are a popular deep learning architecture that today comprise the foundation for most tasks in natural language processing and also…
Connectomics, the ambitious field of study that seeks to map the intricate network of animal brains, is undergoing a growth spurt. Within the span of a decade, it has journeyed from its nascent stages to a discipline that is poised to (hopefully) unlock the enigmas of cognition and the physical underpinning of neuropathologies such as…
Posted by Xingchen Wan, Student Researcher, and Ruoxi Sun, Research Scientist, Cloud AI Team Recent advances in large language models (LLMs) are very promising as reflected in their capability for general problem-solving in few-shot and zero-shot setups, even without explicit training on these tasks. This is impressive because in the few-shot setup, LLMs are presented…
Posted by Sara Ahmadian and Mehran Kazemi, Research Scientists, Google Research Clustering is a fundamental, ubiquitous problem in data mining and unsupervised machine learning, where the goal is to group together similar items. The standard forms of clustering are metric clustering and graph clustering. In metric clustering, a given metric space defines distances between data…
The School of Engineering has selected 13 new Takeda Fellows for the 2023-24 academic year. With support from Takeda, the graduate students will conduct pathbreaking research ranging from remote health monitoring for virtual clinical trials to ingestible devices for at-home, long-term diagnostics. Now in its fourth year, the MIT-Takeda Program, a collaboration between MIT’s School…
Talking with retail executives back in 2010, Rama Ramakrishnan came to two realizations. First, although retail systems that offered customers personalized recommendations were getting a great deal of attention, these systems often provided little payoff for retailers. Second, for many of the firms, most customers shopped only once or twice a year, so companies didn’t…
When considering the potential for AI systems to change manufacturing, Ritu Jyoti, global AI research lead at market-intelligence firm IDC, points to windmill manufacturers. To improve windmills before AI, she says, the company analyzed data from observing a functioning prototype, a process that took weeks. Now, the manufacturer has dramatically shortened the process using a…
Posted by Samier Merchant, Google Research, and Nal Kalchbrenner, Google DeepMind Forecasting weather variables such as precipitation, temperature, and wind is key to numerous aspects of society, from daily planning and transportation to energy production. As we continue to see more extreme weather events such as floods, droughts, and heat waves, accurate forecasts can be…
It’s a stormy holiday weekend, and you’ve just received the last notification you want in the busiest travel week of the year: the first leg of your flight is significantly delayed. You might expect this means you’ll be sitting on hold with airline customer service for half an hour. But this time, the process looks…