Microsoft has added to the slowly growing pile of technologies aimed at spotting synthetic media (aka deepfakes) with the launch of a tool for analyzing videos and still photos to generate a manipulation score. The tool, called Video Authenticator, provides what Microsoft calls "a percentage chance, or confidence score" that the media has been artificially manipulated. "In the case of a video, it can provide this percentage in real-time on each frame as the video plays," it writes in a blog post announcing the tech. "It works by detecting the blending boundary of the deepfake and subtle fading or greyscale elements that might not be detectable by the human eye." If a piece of online content looks real but'smells' wrong chances are it's a high tech manipulation trying to pass as real -- perhaps with a malicious intent to misinform people.

The Artificial Intelligence in Fashion market in Asia Pacific is expected to grow from US$ 3,718.6

As AI continues to advance, so will the power to make use of it to enhance digital advertising and marketing methods and supply priceless buyer insights for corporations With the power to gather knowledge, analyze it, apply it after which study from it, AI is reworking digital methods. As it continues to advance, so will the power to make use of it to enhance digital advertising and marketing methods and supply priceless buyer insights for corporations. It is indicated that artificial intelligence is indispensable in future digital merchandise, particularly within the digital advertising and marketing area. From the film "The Matrix" to the Google AI, from the humorous and sensible Siri to Tesla's self-driving automotive, there are increasingly more enterprises which might be implementing AI in digital advertising and marketing for his or her companies. Artificial intelligence is altering the way forward for digital advertising and marketing.

To capture the communications gain of the massive radiating elements with low power cost, the conventional reconfigurable intelligent surface (RIS) usually works in passive mode. However, due to the cascaded channel structure and the lack of signal processing ability, it is difficult for RIS to obtain the individual channel state information and optimize the beamforming vector. In this paper, we add signal processing units for a few antennas at RIS to partially acquire the channels. To solve the crucial active antenna selection problem, we construct an active antenna selection network that utilizes the probabilistic sampling theory to select the optimal locations of these active antennas. With this active antenna selection network, we further design two deep learning (DL) based schemes, i.e., the channel extrapolation scheme and the beam searching scheme, to enable the RIS communication system. The former utilizes the selection network and a convolutional neural network to extrapolate the full channels from the partial channels received by the active RIS antennas, while the latter adopts a fully-connected neural network to achieve the direct mapping between the partial channels and the optimal beamforming vector with maximal transmission rate. Simulation results are provided to demonstrate the effectiveness of the designed DL-based schemes.

In late April 2020, a company named OpenAI uploaded dozens of new tracks to SoundCloud, all of them matter-of-factly titled like "Hip-hop, in the style of Nas" or "Pop, in the style of Katy Perry." You'd be forgiven for initially thinking the songs were average YouTube covers. A few seconds spent listening to the gargled production, bizarre lyrics, and eerie vocals would definitely change your mind. The songs were all made using an artificial intelligence software called Jukebox, designed by OpenAI, a billion dollar research organization leading the field in AI research. Jukebox isn't your standard Elvis impersonator: After being trained on 1.2 million songs and other data about genres and artists, the neural net has learned to produce original music in the uncannily recognizable style of famous artists like Elton John and Rihanna.

Pune: Sixty percent of Indian enterprises believe that Artificial Intelligence (AI) will disrupt their business in the next two-three years, according to a study by industry body Nasscom and consultancy EY. The study, 'Can enterprise intelligence be created artificially? A survey of Indian enterprises,' is based on a survey of over 500 CXOs across sectors like retail, BFSI, healthcare and agriculture on the maturity of AI adoption along with the key challenges faced on their AI enterprise journey. Seventy percent of Indian enterprises that deployed AI have achieved measurable results. Implementing AI will not only catalyse the innovation to stay competitive but also generate long-term value for enterprises," said Debjani Ghosh, President, Nasscom. Operational efficiency, customer experience and revenue growth are the main reasons why enterprises are turning to AI, with BFSI firms (36%) leading the way, followed by retail (25%), healthcare (20%) and agriculture (8%). "Some of the biggest impediments to the adoption of AI include the quality of data available, the level of digitisation at the enterprise and the maturity of the partner network," said Nitin Bhatt, Partner and Technology Sector Leader, EY India. Ensuring trust through explainability, accountability and ethical use are also major concerns for wider AI adoption. People and cultural issues were other big challenges, with 40% citing workforce displacement and 32% citing cultural impediments to AI adoption. However, among the firms that had gone ahead with AI adoption, 19% said workforce displacement was a challenge while 55% cited cultural factors. "Explainability is an important factor.

In this post, I interview my former UMBC lab mate, Dr. Huguens Jean, who was just hired to work at Google's Video AI Group as an artificial intelligence researcher. Huguens shares his inspirational story, starting from Port-au-Prince, Haiti where he was born and raised, to his schooling at UMBC, and now to his latest position at Google. He also shares details on his humanitarian efforts where he's successfully applied computer vision and deep learning to rural Rwanda to help count footfall traffic. The data him and his team gathered through footfall traffic analysis was used to help the non-profit organization, Bridges to Prosperity, to construct infrastructure such as bridges and roads, to better connect Rwanda villages. Let's give a warm welcome to Dr. Huguens Jean as he shares his story. Thank you for doing this interview. It's such a wonderful pleasure to have you here on the PyImageSearch blog.

While news podcasts are increasingly popular, most focus on national and global news. It tends to be harder to find local news, especially in an on-demand, audio format. Google wants to change this. Today, it announced plans to bring Your News Update to Google Podcasts and to make it easier to listen to local news via Google Assistant. If you subscribe to Your News Update in the Google Podcasts app, Google will offer a mix of short news stories based on your interests, location, user history and preferences.

Hey guys, I have written my first blog post on how to plot decision boundaries for classification models. Plotting decision boundaries can help immensely in the model selection and hyperparameter tuning process, as it can help detect overfitting or underfitting. I noticed that many online explanations and tutorials explaining overfitting rely on 2D datasets (i.e. Such boundaries can be easily plotted on a 2D plane, but what if your data contains six input features? One can use dimensionality reduction to plot the actual points, but what about the decision boundaries themselves?

Most of us know how delightful it is to hear a computer-generated song playlist that feels entirely personal. Now, Google wants to create a similar type of bespoke audio experience--not with music, but with news. The company is adding some new features to its existing news aggregation service called Your News Update, which gathers news clips from different outlets and plays them in one continuous audio feed. Think of it like a Feedly or Flipboard-type service for spoken stories from your preferred news publications. Google has updated the service to create a more fluid listening experience, so that sitting through an entire session doesn't feel like you're just working your way through a hodgepodge of disparate stories.