Examples of AI generated images
Nvidia

GANs for Smaller Data

Trained on a small dataset, generative adversarial networks (GANs) tend to generate either replicas of the training data or noisy output. A new method spurs them to produce satisfying variations.
Graphs and data related to RubiksShift
Nvidia

More Efficient Action Recognition

Recognizing actions performed in a video requires understanding each frame and relationships between the frames. Previous research devised a way to analyze individual images efficiently known as Active Shift Layer (ASL). New research extends this technique to the steady march of video frames.
AI chip and graphics processing unit
Nvidia

AI Chip Leaders Join Forces

A major corporate acquisition could reshape the hardware that makes AI tick.What’s new: U.S. processor giant Nvidia, the world’s leading vendor of the graphics processing units (GPUs) that perform calculations for deep learning, struck a deal to purchase UK chip designer Arm for $40 billion.
Graphs and data related to AI chips
Nvidia

Built for Speed

Chips specially designed for AI are becoming much faster at training neural networks, judging from recent trials. MLPerf, an organization that’s developing standards for hardware performance in machine learning tasks, released results from its third benchmark competition.
Replica of the video game Pac-Man generated by a GAN
Nvidia

Playing With GANs

Generative adversarial networks don’t just produce pretty pictures. They can build world models, too. A GAN generated a fully functional replica of the classic video game Pac-Man.
Information and images related to 6D-Pose Anchor-based Category-level Keypoint-tracker (6-PACK)
Nvidia

Deep Learning for Object Tracking

AI is good at tracking objects in two dimensions. A new model processes video from a camera with a depth sensor to predict how objects move through space.
Capture of the report on trends in machine learning from market analyst CB Insights
Nvidia

Business Pushes the Envelope

The business world continues to shape deep learning’s future. Commerce is pushing AI toward more efficient consumption of data, energy, and labor, according to a report on trends in machine learning from market analyst CB Insights.
Anima Anandkumar
Nvidia

Anima Anandkumar: The Power of Simulation

We’ve had great success with supervised deep learning on labeled data. Now it’s time to explore other ways to learn: training on unlabeled data, lifelong learning, and especially letting models explore a simulated environment before transferring what they learn to the real world.
Information related to Implicit Reinforcement without Interaction at Scale (IRIS)
Nvidia

Different Skills From Different Demos

Reinforcement learning trains models by trial and error. In batch reinforcement learning (BRL), models learn by observing many demonstrations by a variety of actors. But what if one doctor is handier with a scalpel while another excels at suturing?
Drone race
Nvidia

Autonomous Drones Ready to Race

Pilots in drone races fly souped-up quadcopters around an obstacle course at 120 miles per hour. But soon they may be out of a job, as race organizers try to spice things up with drones controlled by AI.

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