Huang


Microsoft's AI is getting crazily good at speech recognition

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Microsoft's speech recognition efforts have hit a significant milestone. It can now transcribe human speech with a 5.1% error rate, Microsoft technical fellow Xuedong Huang wrote in a blog post -- the same error rate as humans. Microsoft actually thought it hit this point last year, when it reached 5.9%, the word error rate it had measured for humans. "Reaching human parity with an accuracy on par with humans has been a research goal for the last 25 years," Xuedong Huang wrote.


Microsoft's AI is getting crazily good at speech recognition

#artificialintelligence

Microsoft's speech recognition efforts have hit a significant milestone. It can now transcribe human speech with a 5.1% error rate, Microsoft technical fellow Xuedong Huang wrote in a blog post -- the same error rate as humans. "Reaching human parity with an accuracy on par with humans has been a research goal for the last 25 years," Xuedong Huang wrote. "such as achieving human levels of recognition in noisy environments with distant microphones, in recognizing accented speech, or speaking styles and languages for which only limited training data is available."


No clicks required: Artificial-intelligence is changing how we shop, Boxed CEO says

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Similar to Amazon's Dash Button, Boxed is working on its own, easy reorder system. Amazon's Dash Button, with one click, will send Prime Members their favorite, most-used products -- ranging from Pampers diapers and Bounce detergent, to Gatorade and Cheez-Its. A pilot test called Boxed Concierge automatically fulfills shoppers' items in bulk, shipping them without even asking for approval on the receiving end. It's easier shipping items automatically in a business-to-business relationship, he said, but business-to-consumer becomes tricky and still requires a little bit of interaction.


A New Frontier for AI: Helping Scientists Develop Potential New Medicines

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But Austin Huang, Associate Director and the Biomedical Data Science lead in Pfizer's Genome Sciences and Technologies group in Kendall Square, Cambridge, Massachusetts, explains that "the methods that companies like Google and Facebook use to study large, complex datasets can also be used to help predict disease and possible treatment outcomes in human health data." If the ultimate goal of a self-driving car is to navigate a busy city street, in pharmaceutical research, the goal is to navigate the connections between a potential treatment and its effectiveness in treating a disease. Austin Huang, Associate Director and the Biomedical Data Science lead in Pfizer's Genome Sciences and Technologies group And if other fields of AI are any indication, he says, "when breakthroughs happen, change can follow very quickly," likening it to a "tipping point." To enable AI to reach those kinds of breakthroughs, it's important to teach computers how to "think" abstractly in discovering patterns in large datasets.


When AI Can Transcribe Everything

The Atlantic

Despite the recent emergence of browser-based transcription aids, transcription's an area of drudgery in the modern Western economy where machines can't quite squeeze human beings out of the equation. That is until last year, when Microsoft built one that could. Automatic speech recognition, or ASR, is an area that has gripped the firm's chief speech scientist, Xuedong Huang, since he entered a doctoral program at Scotland's Edinburgh University. Huang and his colleagues used their software to transcribe the NIST 2000 CTS test set, a bundle of recorded conversations that's served as the benchmark for speech recognition work for more than 20 years.


Exclusive: Singapore's plans for predictive transport GovInsider

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Below, he tells GovInsider how the island state is exploring plans to predict train disruptions; make every vehicle a traffic sensor; and ways to use artificial intelligence to secure all this infrastructure. As a solution, the government is looking to use drones and artificial intelligence to predict when trains and tracks will need repairs. Outside of public transport, Singapore is trialling autonomous trucks to transport containers at ports. This mentality has been shaken up by the Government Technology Agency's centralisation under the Prime Minister's Office, he believes.


GPUs to Run 1000 Times Faster by 2025 - Huang

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And although the pace may have slowed down, the number of transistors that could fit per square inch did continue to increase, doubling not every year but after every 18 months instead. Dennard scaling -- named after Robert H. Dennard who co-authored the concept -- states that even while transistors become smaller, power density remains constant such that power consumption remains proportional with its area. On NVIDIA's end, Huang assures that their venture into artificial intelligence and deep learning will keep them ahead even with the death of Moore's Law. That's not to say, though, that NVIDIA will stop making their GPUs more powerful.


Robots of the future will learn just like they would in Star Trek's Holodeck

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These simulators, most recently announced by Nvidia as a project called Isaac's Lab but also pioneered by Alphabet's DeepMind and Elon Musk's OpenAI, are 3D spaces that have physics just like reality, with virtual objects that act the same way as their physical counterparts. "We imagine that one of these days, we'll be able to go into the Holodeck, design a product, design the factory that's going to make the product, and design the robots that's going to make the factory that makes the products. Alphabet's DeepMind has had similar ideas: The AI research lab is most well-known for applying its AI to games, notably AlphaGo, which continues to beat human world-champions at Go, but also building AI that beats video games like Atari and Starcraft. While Nvidia's Isaac's Lab is meant to help build robots and products that do specific tasks in the real world, DeepMind's Lab is geared more towards research, or finding ways to build AI that can learn about its surroundings with little input.


China's Go masters and researchers are optimistic about the country's AI future

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The Chinese Association for Artificial Intelligence, meanwhile, is pushing for a higher academic status for AI courses such as machine learning and computer vision, which today are often nestled within computer science departments. For $131, anyone interested can take a class in deep learning--the AI approach that powers AlphaGo--offered by a Beijing-based company called ChinaHadoop. At Tsinghua University, a machine-learning course is capped at 60 students, but sometimes as many as 120 students show up, says Jie Tang, an associate professor there who studies machine learning and data mining. The summit will "trigger a new round of thinking and discussion regarding AI," in China, adds Minlie Huang, an associate professor at Tsinghua University who specializes in deep learning and natural-language processing.


How Nvidia is surfing the AI wave

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The other components of the strategy revolve around showcasing cutting-edge AI applications across sectors, building partnerships with other companies, nurturing technology start-ups and help build an AI ecosystem. TensorFlow is Google's deep learning framework while CUDA (Compute Unified Device Architecture) is a free software platform provided by Nvidia that enables users to program GPUs. Further, public cloud services providers such as Alibaba Group Holdings Ltd, Amazon Web Services, Baidu Inc., Facebook, Google, IBM, Microsoft and Tencent Holdings Ltd use Nvidia GPUs in their data centres, prompting Nvidia to launch its GPU Cloud platform, which integrates deep learning frameworks, software libraries, drivers and the operating system. Nvidia also worked with SAP SE to develop a product called Brand Impact--a fully automated and scalable video analytics service for brands, media agencies and media production companies.