Using Google Vision AI's Reverse Image Search To Richly Catalog Television News


Deep learning has revolutionized the machine understanding of imagery. Yet today's image recognition models are still limited by the availability of large annotated training datasets upon which to build their libraries of recognized objects and activities. To address this, Google's Vision AI API expands its native catalog of around 10,000 visually recognized objects and activities with the ability to perform the equivalent of a reverse Google Images search across the open Web and tally up the top topics used to caption the given image everywhere it has previously appeared, lending unprecedentedly rich context and understanding, even yielding unique labels for breaking news events. What might this process yield for a week of television news? Google's Vision AI API represents a unique hybrid between traditional deep learning-based image labeling based on a library of previously trained models and the ability to leverage the open Web to annotate images based on the most common topics visually similar images are captioned with.

Collaborative Filtering With User-Item Co-Autoregressive Models

AAAI Conferences

Deep neural networks have shown promise in collaborative filtering (CF). However, existing neural approaches are either user-based or item-based, which cannot leverage all the underlying information explicitly. We propose CF-UIcA, a neural co-autoregressive model for CF tasks, which exploits the structural correlation in the domains of both users and items. The co-autoregression allows extra desired properties to be incorporated for different tasks. Furthermore, we develop an efficient stochastic learning algorithm to handle large scale datasets. We evaluate CF-UIcA on two popular benchmarks: MovieLens 1M and Netflix, and achieve state-of-the-art performance in both rating prediction and top-N recommendation tasks, which demonstrates the effectiveness of CF-UIcA.

Top 5 Deep Learning and AI Stories- June 1, 2018


Fusing high performance computing and AI 2. Find your next binge-worthy show with AI 3. The connection between self-driving vehicles and radiology 4. Robots are learning new tasks by mimicking humans 5. How AI could spot a silent cancer in time to save lives 5. FUSING HIGH PERFORMANCE COMPUTING AND AI During GTC Taiwan 2018, NVIDIA CEO Jensen Huang announced HGX-2: a "building block" cloud-server platform that will let server manufacturers create more powerful systems around NVIDIA GPUs for high performance computing and AI. TechCrunch's Ron Miller sums it up best, saying that: "It's the stuff that geek dreams are made of. READ ARTICLE 6. FIND YOUR NEXT BINGE-WORTHY SHOW WITH AI While AI may play a leading role in the entertainment industry's depictions of the future on screen, it's already starring in entertainment behind the scenes, thanks to Netflix. Our latest AI Podcast features the company's research and engineering director, Justin Basilico. LISTEN HERE 7. CONNECTING SELF-DRIVING VEHICLES AND RADIOLOGY According to new commentary published in the Journal of American College of Radiology, AI implementation may not be as far as people believe, as seen in self- driving vehicles.

Google DeepMind gets closer to sounding human


Artificial intelligence researchers at DeepMind have created some of the most realistic sounding human-like speech, using neural networks. Dubbed WaveNet, the AI promises significant improvements to computer-generated speech, and could eventually be used in digital personal assistants such as Siri, Cortana and Amazon's Alexa. The technology generates voices by sampling real human speech from both English and Mandarin speakers. In tests, the WaveNet generated speech was found to be more realistic than other forms of text-to-speech programs but still falling short of being truly convincing. In 500 blind tests, respondents were asked to judge sample sentences on a scale of one to five (five being most realistic).

Altek License CEVA Imaging and Vision DSP for Deep Learning in Mobile Devices


"At Altek, we are constantly striving to enhance our digital image solutions and set the direction for the future of smarter imaging devices," said Jason Lin, General Manager and Corporate Senior Vice President of Altek. "CEVA's imaging and vision DSP provides the platform which allows us to further enhance the image quality of our solutions and push the boundaries of what a camera can do using artificial intelligence and advanced vision algorithms." "Altek is a proven leader in imaging, with a strong track record in the smartphone space and we are excited to work with them," said, Ilan Yona, vice president and general manager of CEVA's Vision Business Unit. "The combination of Altek's advanced imaging technologies along with our DSP-based vision and machine learning offering creates one of the most intelligent digital imaging solutions on the market today." CEVA's latest generation imaging and vision DSP platforms address the extreme processing requirements and low power constraints of the most sophisticated machine learning and machine vision applications used in smartphones, surveillance, augmented reality, sense and avoid drones and self-driving cars.