speech recognition


Petuum Launches Neurobots Product Line, Streamlining the Adoption of Powerful RPA with AI

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Petuum, an artificial intelligence platform company, announced Petuum Neurobots, a series of intelligent process automation (IPA) tools that provide cutting-edge AI capabilities to robotic process automation (RPA). This enables enterprise customers to quickly and cost-effectively deploy powerful RPA bots with the most advanced AI and machine learning (ML) technology. "We believe AI technology must be accessible to all companies of all sizes across different industries to achieve better business results. Neurobots are a critical part of Petuum's larger strategy to provide state-of-the-art AI that will transform RPA bots into intelligent agents that are cognitive, able to learn, think, and collaborate (with human and other bots), and therefore realize fully-operationalized business automation," said Dr. Eric Xing, founder and CEO of Petuum. The first Neurobots introduced include Kaibot for interactive conversational applications such as chatbots, Chimebot for automatic speech recognition, Chicbot for fashion applications and Pixbot for image understanding and enhancements.


Eta's Ultra Low-Power Machine Learning Platform

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Eta Compute has developed a high-efficiency ASIC and new artificial intelligence (AI) software based on neural networks to solve the problems of edge and mobile devices without the use of cloud resources. Future mobile devices, which are constantly active in the IoT ecosystem, require a disruptive solution that offers processing power to enable machine intelligence with low power consumption for applications such as speech recognition and imaging. These are the types of applications for which Eta Compute designed its ECM3531. The IC is based on the ARM Cortex-M3 and NXP Coolflux DSP processors. It uses a tightly integrated DSP processor and a microcontroller architecture for a significant reduction in power for the intelligence of embedded machines.


Learn to Build your First Speech-to-Text Model in Python

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This will sound familiar to anyone who has owned a smartphone in the last decade. I simply ask the question – and Google lays out the entire weather pattern for me. It saves me a ton of time and I can quickly glance at my screen and get back to work. But how does Google understand what I'm saying? And how does Google's system convert my query into text on my phone's screen?


ARTIFICIAL INTELLIGENCE

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Nagaraj is the Director of Emerging Technologies at V Group Inc. and a well-recognized name in Voice Analytics, Conversational AI and NLP domains. With over 20 years of experience in various technologies, Nagaraj plays a key role in advising and guiding the organizations on technology and go-to-market strategies. He spearheads V Group's efforts in developing revolutionary products and solutions by leveraging various technologies that transforms business and reach an unseen level of user-first engagement. He was instrumental in implementing the first ever speech recognition system for telecom and developing unique voice analytics solutions.


Amazon Is Building a Voice-Controlled Robot That's Like a 'Mobile Alexa'

TIME - Tech

Amazon is developing a higher quality version of the Echo speaker and ramping up work on its home robot. The company plans to release the new Echo by next year, according to people familiar with the product. Prototypes of the cylindrical speaker are wider than the current Echo to squeeze in additional components including at least four tweeters, said the people, who requested anonymity to discuss an internal matter. The robot, previously reported by Bloomberg, has wheels and can be controlled by Alexa voice commands, the people said. Both devices are being developed by Amazon Lab126, a research and development arm based in Sunnyvale, California.


Voice recognition

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A new health-focused startup called Notable today announced its first app for Apple Watch, which aims to automatically record and digitize visits to the doctor as well as "eliminate the vast majority clinical


Saykara Launches First Fully Ambient AI Healthcare Voice Assistant

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Saykara today announced the release of Kara 2.0, an AI-powered healthcare assistant that further simplifies the documentation process for physicians. Now featuring Ambient Mode, Kara 2.0 is a breakthrough AI-powered voice application for healthcare, allowing physicians and patients to interact as they normally do, all while Saykara listens, transcribes to text, parses text into structured data, and intelligently completes each form in a patient's electronic health record (EHR or chart). Saykara then automatically generates a clinic note including patient history, physical, assessment, plan, orders and referrals. With the release of Ambient Mode, Saykara is the only virtual healthcare assistant that can be used passively'in the room' during physician-patient appointments with no voice commands. Ambient Mode builds on Saykara's versatility and agnosticity, allowing it to better serve up to 18 disparate healthcare specialties, including primary care, pediatrics, internal medicine, orthopedics, urology and more.


Exploring Smarter Video Transcription to Support Universal Design for Learning and Cost Savings - Echo360

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Higher education institutions share a goal of making learning more accessible to all students. To meet this goal many colleges and universities, including UMass Amherst, have adopted the Universal Design for Learning (UDL) framework in an effort to design curriculum to serve all learners, regardless of ability, disability, age, gender or background. Modern technologies often play a supporting role in UDL, providing students with multiple modalities such as video, audio, and text. While these technologies can make implementing UDL easier, they can also be costly. Beginning with the Fall 2018 term, an interdisciplinary team of academic technologists, instructional designers, and instructors at UMass Amherst started exploring how classroom video and Echo360's new automated speech recognition (ASR) technology can create a pathway to cost-effective, scalable captioning that can improve accessibility and support universal design.


11 Tech Experts Predict The Next Big Developments In Home IoT

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The Internet of Things is taking on a larger role in the home. From voice assistants like Google Home and Amazon Echo to smart appliances, tech companies are on a mission to make everyday life easier through IoT devices. With technology, of course, there's always something new around the corner, and it's expected that artificial intelligence (AI) and machine learning (ML) will continue to expand the capabilities of IoT devices. To get an insider's perspective on what may be coming, we asked 11 Forbes Technology Council members to share what they think will be the next big thing in at-home IoT tech. IoT systems learning an individual's patterns, habits, preferences and autonomously operating are essential with the growing number of IoT devices at home.


10 European experts who have been paving the way to modern AI

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When asked why he robbed banks, Willie Sutton famously replied, "Because that's where the money is". And so much of artificial antelligence evolved in the United States – because that's where the computers were. However with Europe's strong educational institutions, the path to advanced AI technologies has been cleared by European computer scientists, neuroscientists, and engineers – many of whom were later poached by US universities and companies. From backpropagation to Google Translate, deep learning, and the development of more advanced GPUs permitting faster processing and rapid developments in AI over the past decade, some of the greatest contributions to AI have come from European minds. Modern AI can be traced back to the work of the English mathematician Alan Turing, who in early 1940 designed the bombe – an electromechanical precursor to the modern computer (itself based on previous work by Polish scientists) that broke the German military codes in World War II.