"AI" is the buzzword for just about everything this year. Nvidia is probably the biggest benefactor of the AI trend, but it's not content to sit on its laurels and sell billions of dollars in silicon. The company's newest developer tool, the Avatar Cloud Engine, could help game devs make non-player characters in a fraction of the time it takes today. On PCWorld's The Full Nerd podcast, Nvidia Senior Product Manager Seth Schneider joins Adam and Will to show off this remarkable tech. The Avatar Cloud Engine (ACE) goes beyond standard text and voice simulation to allow developers to customize NPCs with a range of contextual actions, giving each one a custom-tailored personality that reacts to the in-game environment.

Nvidia's latest AI demo is pretty impressive: a tool that quickly turns a "few dozen" 2D snapshots into a 3D-rendered scene. In the video below you can see the method in action, with a model dressed like Andy Warhol holding an old-fashioned Polaroid camera. The tool is called Instant NeRF, referring to "neural radiance fields" -- a technique developed by researchers from UC Berkeley, Google Research, and UC San Diego in 2020. If you want a detailed explainer of neural radiance fields, you can read one here, but in short, the method maps the color and light intensity of different 2D shots, then generates data to connect these images from different vantage points and render a finished 3D scene. In addition to images, the system requires data about the position of the camera. Researchers have been improving this sort of 2D-to-3D model for a couple of years now, adding more detail to finished renders and increasing rendering speed.

NVIDIA HAS been teaching MPs how to create neural networks as part of an AI Workshop organised in conjunction with the Big Innovation Centre. A cross-party group including Stephen Metcalf MP and Lord Clement Jones CBE, co-chairs of the All Party Parliamentary Group on Artificial Intelligence (APPG AI), was tasked with learning about AI, what it really means, and then taking the information back to inform the discussion with constituents. Of course, that doesn't just mean being able to respond if an MP's surgery bears the question "So, do I need to live in fear of Skynet?" but also more practical pursuits like a local business looking at bringing AI to their business. Stuart Wilson, AI and Supercomputing director at Nvidia, said: "Artificial intelligence represents the biggest technological and economic shift in our lifetime. It is of national importance that policymakers understand the core components, capabilities and limitations surrounding the modern AI boom."

For those curious how NVIDIA's DRIVE PX 2 system is working and how their self-driving car efforts are progressing, they've published a new video today showing their self-driving car that's taught by deep learning with analyzing human driving patterns. NVIDIA's approach to self-driving vehicles is working out well so far and from the deep learning off human driving data is working for driving on unmarked roads, rain conditions, night time driving, around cones, etc. It's also exciting to see how NVIDIA's deep learning efforts have come and that they are Linux powered (Ubuntu still, last I heard from them).

U.S. chipmaker Nvidia nvda showed off on Monday a smaller and more efficient artificial intelligence computer for self-driving cars, saying it would power Baidu's bidu mapping and autonomous vehicle technology. Chinese web services company Baidu will deploy Nvidia's new Drive PX 2 as its in-vehicle car computer for its self-driving system, Nvidia said in a press release as it unveiled the computer at the GPU Technology Conference in Beijing. As more carmakers develop plans for self-driving technology to roll out in their vehicles in the next decade or less, Nvidia is trying to lower the barriers to entry, providing powerful computers to help automakers enter the market. Earlier this month, Nvidia and Baidu announced a partnership to develop a full self-driving car architecture from the cloud to the vehicle using both companies' expertise in artificial intelligence (AI). Nvidia said its new Drive PX 2 computer uses 10 watts of power and is half the size of the original version, launched in January.

US chipmaker Nvidia Corp showed off on Monday a smaller and more efficient artificial intelligence computer for self-driving cars, saying it would power Baidu's mapping and autonomous vehicle technology. Chinese web services company Baidu will deploy Nvidia's new Drive PX 2 as its in-vehicle car computer for its self-driving system, Nvidia said in a press release as it unveiled the computer at the GPU Technology Conference in Beijing. As more carmakers develop plans for self-driving technology to roll out in their vehicles in the next decade or less, Nvidia is trying to lower the barriers to entry, providing powerful computers to help automakers enter the market. Earlier this month, Nvidia and Baidu announced a partnership to develop a full self-driving car architecture from the cloud to the vehicle using both companies' expertise in artificial intelligence (AI). Nvidia said its new Drive PX 2 computer uses 10 watts of power and is half the size of the original version, launched in January.

SAN JOSE, Calif.--Nvidia for much of its two-plus decades of life made most of its money by manufacturing and selling GPUs for gaming systems. While the bulk of the company's revenues still come from its mainstream graphics technologies, Nvidia over the past several years has been aggressively pushing into new growth areas, particularly virtual reality (VR), connected cars, and deep learning and artificial intelligence (AI). That pivot into these emerging markets has been on full display here this week at the company's GPU Technology Conference (GTC), an event whose growth has mirrored the rise in importance of GPUs in such areas as accelerated computing and high-performance computing (HPC). In 2012, 2,350 people attended GTC; this year, more than 5,000 are here. In his keynote address April 5, CEO Jen-Hsun Huang made announcements in all the new target areas, from technologies designed to make VR worlds more real to products aimed at accelerating innovation in deep learning.