Understanding artificial intelligence and how it relates to matters of national security has become a top priority for military and government leaders in recent years. A new three-day custom program entitled “Artificial Intelligence for National Security Leaders” — AI4NSL for short — aims to educate leaders who may not have a technical background on the basics of…
Chart captions that explain complex trends and patterns are important for improving a reader’s ability to comprehend and retain the data being presented. And for people with visual disabilities, the information in a caption often provides their only means of understanding the chart. But writing effective, detailed captions is a labor-intensive process. While autocaptioning techniques…
Posted by Fabian Pedregosa and Eleni Triantafillou, Research Scientists, Google Deep learning has recently driven tremendous progress in a wide array of applications, ranging from realistic image generation and impressive retrieval systems to language models that can hold human-like conversations. While this progress is very exciting, the widespread use of deep neural network models requires…
Posted by Yang Zhao and Tingbo Hou, Software Engineers, Core ML In recent years, diffusion models have shown great success in text-to-image generation, achieving high image quality, improved inference performance, and expanding our creative inspiration. Nevertheless, it is still challenging to efficiently control the generation, especially with conditions that are difficult to describe with text….
<!– –>Figure 1: CoarsenConf architecture. <!– (I) The encoder $q_phi(z| X, mathcal{R})$ takes the fine-grained (FG) ground truth conformer $X$, RDKit approximate conformer $mathcal{R}$ , and coarse-grained (CG) conformer $mathcal{C}$ as inputs (derived from $X$ and a predefined CG strategy), and outputs a variable-length equivariant CG representation via equivariant message passing and point convolutions. (II)…
Computers possess two remarkable capabilities with respect to images: They can both identify them and generate them anew. Historically, these functions have stood separate, akin to the disparate acts of a chef who is good at creating dishes (generation), and a connoisseur who is good at tasting dishes (recognition). Yet, one can’t help but wonder:…
Disinformation generated by AI may be more convincing than disinformation written by humans, a new study suggests. The research found that people were 3% less likely to spot false tweets generated by AI than those written by humans. That credibility gap, while small, is concerning given that the problem of AI-generated disinformation seems poised to…
In a recent speech, Microsoft CEO Satya Nadella evoked the lofty power of artificial intelligence (AI) to accelerate progress, prosperity, and standards of living. “This technology reaches everyone in the world,” he said. Generative AI takes an idea born in tech communities such as Silicon Valley and Tel Aviv—the ability of algorithmic engines to synthesize…
When Erik Duhaime PhD ’19 was working on his thesis in MIT’s Center for Collective Intelligence, he noticed his wife, then a medical student, spending hours studying on apps that offered flash cards and quizzes. His research had shown that, as a group, medical students could classify skin lesions more accurately than professional dermatologists; the…
Posted by Kuniaki Saito, Student Researcher, Cloud AI Team, and Kihyuk Sohn, Research Scientist, Perception Team Pre-training visual language (VL) models on web-scale image-caption datasets has recently emerged as a powerful alternative to traditional pre-training on image classification data. Image-caption datasets are considered to be more “open-domain” because they contain broader scene types and vocabulary…