Posted by Hussein Hazimeh, Research Scientist, Athena Team, and Riade Benbaki, Graduate Student at MIT Modern neural networks have achieved impressive performance across a variety of applications, such as language, mathematical reasoning, and vision. However, these networks often use large architectures that require lots of computational resources. This can make it impractical to serve such…
Prior to receiving a PhD in computer science from MIT in 2017, Marzyeh Ghassemi had already begun to wonder whether the use of AI techniques might enhance the biases that already existed in health care. She was one of the early researchers to take up this issue, and she’s been exploring it ever since. In…
Compared to other imaging modalities like X-rays or CT scans, MRI scans provide high-quality soft tissue contrast. Unfortunately, MRI is highly sensitive to motion, with even the smallest of movements resulting in image artifacts. These artifacts put patients at risk of misdiagnoses or inappropriate treatment when critical details are obscured from the physician. But researchers…
In a near-future war—one that might begin tomorrow, for all we know—a soldier takes up a shooting position on an empty rooftop. His unit has been fighting through the city block by block. It feels as if enemies could be lying in silent wait behind every corner, ready to rain fire upon their marks the…
Posted by Eltayeb Ahmed, Research Engineer, and Subhrajit Roy, Senior Research Scientist, Google Research Reading has many benefits for young students, such as better linguistic and life skills, and reading for pleasure has been shown to correlate with academic success. Furthermore students have reported improved emotional wellbeing from reading, as well as better general knowledge…
Artificial neural networks, ubiquitous machine-learning models that can be trained to complete many tasks, are so called because their architecture is inspired by the way biological neurons process information in the human brain. About six years ago, scientists discovered a new type of more powerful neural network model known as a transformer. These models can…
To follow up on our previous survey about low-code and no-code tools, we decided to run another short survey about tools specifically for software developers—including, but not limited to, GitHub Copilot and ChatGPT. We’re interested in how “developer enablement” tools of all sorts are changing the workplace. Our survey 1 showed that while these tools…
Posted by Sandeep Tata, Software Engineer, Google Research, Athena Team The last few years have seen rapid progress in systems that can automatically process complex business documents and turn them into structured objects. A system that can automatically extract data from documents, e.g., receipts, insurance quotes, and financial statements, has the potential to dramatically improve…
In late May, the Pentagon appeared to be on fire. A few miles away, White House aides and reporters scrambled to figure out whether a viral online image of the exploding building was in fact real. It wasn’t. It was AI-generated. Yet government officials, journalists, and tech companies were unable to take action before the…
Posted by Fuzhao Xue, Research Intern, and Mostafa Dehghani, Research Scientist, Google Adaptive computation refers to the ability of a machine learning system to adjust its behavior in response to changes in the environment. While conventional neural networks have a fixed function and computation capacity, i.e., they spend the same number of FLOPs for processing…