- 14916396 reads
3D News
Recent Blog Entries
Type “teenage angst” into whatismymovie.com, and the search engine will recommend titles such as Heathers, Rebel Without a Cause and The Basketball Diaries.
Change the search to “elephants” and the results will include titles ranging from Dumbo and The Elephant Man to Smokey and the Bandit II (in which the transporting of an elephant figures prominently).
Intended as a tech demo, whatismymovie.com isn’t your typical movie search engine. It’s powered by an AI-infused algorithm that combines natural language understanding as well as text and pattern recognition to understand the contents of video files. This makes it possible to match queries and results in new ways, and expose data that hadn’t been searchable previously.
The technology behind the site is the work of AI video startup Valossa, a spinoff from the University of Oulu in Finland and member of NVIDIA’s Inception program. While the company’s aspirations are much more ambitious than helping people find movies, CEO and co-founder Mika Rautiainen gets a kick out of the impact whatismymovie.com is having on those who find it.
“People are finding their long-lost movies they couldn’t remember the name of by describing them,” said Rautiainen.
Beyond matching fans with movies, Valossa is focused on applying its technology to help media companies understand their media assets better, and ultimately gain insight into how viewers are affected by what they watch. For instance, how their emotions change when a certain actor is on screen.
Eventually, this could lead to content being adjusted on the fly as viewer attention wanes, more entertaining (and effective) advertising and better monetization of content in online distribution.
“Broadcasters and other video content companies can extract data from what’s happening at every second of playback and correlate it with behavior,” said Rautiainen. “They’re looking for every possible piece of information that helps them make a bigger impact with their content.”
More Than Movie SearchRautiainen first started working on “semantic video understanding” while on a research exchange program at the University of Maryland. There, he worked on algorithms for detecting objects and activities, such as explosions, in video content, and making search engines that were benchmarked against standardized video search problems. In 2010, he and his research team started collaborating with Finland’s national broadcaster, Yle, on indexing broadcast video and making it discoverable.
When the next generation of machine learning and AI were first building steam in the scientific community, Rautiainen started looking at how he could combine his work with the new breed of AI, and he began assembling the team that would become Valossa. He opted to locate the company in Oulu, a former Nokia town, because of the abundant availability of highly skilled video engineers and computer vision researchers.
Valossa’s initial product, Valossa AI, is a cloud service accelerated by a GPU cluster running in the Amazon Web Services cloud. It enables media companies to gain an understanding of things such as who are the most prominent actors in a video, when and where they’re on screen, and visual context such as the presence of foliage or urban structures.
It also analyzes and indexes what’s being said as well as background sounds. They recently released video insight tools that enable inspection of video content through visual reports, scene-level search and overview dashboards. Combining these insights with behavioral data on users can inform content decisions.
Internally, the company is using NVIDIA GPUs, both on premise and in the cloud, to speed the training of its deep learning algorithms — boosting performance by at least 30x compared to CPUs.
Speeding Up TimeThis vast speed-up allows the Valossa AI engine to index and annotate everything it sees in a 60-minute video in just 10 minutes — a task that could take CPUs over two hours, at much greater cost. Anyone can see the technology in action by visiting the Valossa site and signing up to run videos through the company’s deep learning-infused cluster for free.
Companies can pay for the service based on processing time for the minutes and hours of content consumed, or as a subscription model for customers with ongoing high-volume video needs. Interactive video insight tools are available as a preview for people signing in to the portal. Valossa also offers on-premise installations for enterprise use.
Down the line, Rautiainen anticipates Valossa’s technology will be of interest to far more than media companies, as more businesses look to extract value using video intelligence. They’ll be able to understand how presentations are affecting viewers and make real-time adjustments.
Said Rautiainen: “We’re allowing people to understand how their content data is structured and, moreover, find relationships between these structures and actual impact.”
Valossa is one of more than 2,200 startups in our Inception program. The virtual accelerator program provides startups with access to technology, expertise and marketing support.
The post Movie Maven: How AI Is Helping Divine Viewer Behavior from Video Data appeared first on The Official NVIDIA Blog.
Before oil and gas companies recover a single drop of oil, they have to deal with data. Oceans of data.
NVIDIA and Baker Hughes, a GE company (BHGE), are partnering to use AI and GPU-accelerated computing to help the oil and gas industry distill this data in real time — and dramatically reduce the cost of finding, extracting, processing and delivering oil.
From seismic modeling and automated well planning to predicting machinery failure and optimizing supply chains, deep learning neural networks can unlock insights from data that were previously as hidden as the oil underground.
As the adjacent infographic shows, NVIDIA and BHGE’s collaboration spans the operations of oil companies. And it does so using the full breadth of our AI solutions. This includes NVIDIA DGX-1 AI supercomputers in data centers for model training; NVIDIA DGX Stations for supercomputing at the deskside — or even on remote offshore platforms where bandwidth is limited; and NVIDIA Jetson AI supercomputers-on-a-module for real-time, continuous deep learning and inferencing at the edge.
These technologies allow oil and gas companies to transform their operations, primarily using two GPU-fueled advancements: accelerated analytics and deep learning.
With GPU-accelerated analytics, well operators can visualize and analyze massive volumes of production and sensor data such as pump pressures, flow rates and temperatures. This can give them better insight into costly issues, such as predicting which equipment might fail and how these failures could affect wider systems.
Using deep learning and machine learning algorithms, oil and gas companies can determine the best way to optimize their operations as conditions change. For example, they can turn large volumes of seismic data images into 3D maps to improve the accuracy of reservoir predictions. More generally, they can use deep learning to train models to predict and improve the efficiency, reliability and safety of expensive drilling and production operations.
NVIDIA’s work with BHGE is part of a broader strategy to work with leading companies to bring AI into every industry. Among these efforts are collaborations with GE Healthcare and Nuance in the area of healthcare; with Audi, Bosch, Mercedes-Benz, Uber and Volkswagen in automotive; FANUC in robotics; and Komatsu in construction and mining.
See Demos at BHGE’s Annual MeetingAmid constrained IT resources and limited in-house skills, oil and gas companies can tap into BHGE’s applied AI capabilities, services and expertise and the power of NVIDIA GPU-accelerated computing and AI to build a more secure future.
BHGE and NVIDIA will showcase AI-infused oil and gas demos in the solutions fair at the BHGE Annual Meeting this week in Florence, Italy.
See how deep learning can be used to predict failures and identify rock formations, as well as to mine 3D models to create efficient environment scans, which can aid procurement of drilling permits. Also see how massive-scale visualization of production data on a GIS map can provide insights into relative production efficiencies of wells spread over several regions.
For live updates from the event, follow @BHGECO and #BHGEAM18.
The post NVIDIA and Baker Hughes, a GE Company, Pump AI into Oil & Gas Industry appeared first on The Official NVIDIA Blog.