research

Like others, we’ve noted a recent uptick in research implemented using Jax. You might chalk it up as yet another ML platform, but Jax is emerging as the tool of choice for faster research iteration at DeepMind. After exploring for ourselves, we’re excited to find Jax is principally designed for fast differentiation. Excited because differentiation is foundational to gradient-based learning strategies supported in many ML algorithms. Moreover, the derivative is also ubiquitous in scientific computing, making Jax one powerful hammer!...

In a matter of months, the COVID-19 pandemic has besieged humanity and now the world wrestles to manage the population health challenges of a novel coronavirus with remarkable infectivity. Organizing an effective response to blunt the impact of such a large, complex challenge demands a principled and scientific approach. Better Planning by Forecasting Infections Reliable forecasting is crucial for planning and allocating limited resources efficiently and minimizing casualties....

Advances in methods to generate photorealistic but synthetic images have prompted concerns about abusing the technology to spread misinformation. In response, major tech companies like Facebook, Amazon, and Microsoft partnered to sponsor a contest hosted by Kaggle to mobilize machine learning talent to tackle the challenge. With $1 million in prizes and nearly half a terabyte of samples to train on, this contest requires the development of models that can be deployed to combat deepfakes....

Check out the repo and the video! “Everybody Dance Now” offers a sensational demonstration in combining image-to-image translation with pose estimation to produce photo-realistic ‘do-as-i-do’ motion transfer. Researchers used roughly 20 mins of video shot at 120 fps of a subject moving through a normal range of body motion. It is also important for source and target videos to be taken from similar perspectives. Generally, this is a fixed camera angle at a third person perspective with the subject’s body occupying most of the image....

Check out the repo and enjoy the video on YogAI and ActionAI Wanting a personal trainer to help track our fitness goals, we figured we could build our own. The goal was to build an application that could track how we were exercising and began with Yoga as a simple context. We dubbed our first iteration of this application as YogAI. We thought about the YogAI concept for some time....

GANs represent the state of the art in image-to-image translation. However, it can be difficult to acquire aligned image pairs to learn the mapping between image domains. CycleGANs introduced the “cycle consistency” constraint to learn to transfigure images, transfer style, and enhance photos from unaligned source and target domain samples. This technique has been used to render historic black & white images in full color or to represent an image in greater resolution but here, we explore applications in agriculture....