Results


These Trends Will Shape Embedded Technology in 2017

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Advances in processor technology will continue to push IoT applications, though all embedded applications will benefit from higher performance, lower power requirements, and increased connectivity. This year will see the delivery of the latest Cortex-M23 and Cortex-M33 platforms that incorporate advanced security support as a standard component (see "Cortex-M23 and M33 Incorporate Latest TrustZone Features"). These platforms offer interesting alternatives in the embedded space, where small-form-factor boards can take advantage of larger amounts of flash memory in compact packages. Complementary technologies like 3D imaging and Ultrahaptics' ultrasonic haptic response system (see "Ultrasonics Brings Haptics to Augmented and Virtual Reality") will make these reality systems much more usable.


Are You Ready for Artificial Intelligence Leadership? Centurysoft Blog

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With your human boss you always have to ensure that you are in the boss's good books. When you are working under the direction of artificial intelligence you could be working under an interactive conversational assistant who is most capable of providing all of the leadership you need to rely on to be a successful and valued employee. A truly good leader should be there to assist their staff and when artificial intelligence is integrated into the management role of a business it is an intelligent virtual assistant. Nick Gordon is a senior writer at Centurysoft Blog, where he covers topics such as Digital Media, Data Analytics, Chatbots, Artificial Intelligence and Business Intelligence.


10 Steps to Train an Effective Chatbot and its Machine Learning Models

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While the answer depends greatly on the problem being solved and the data powering the solution, in this blog we offer a common methodology for training the machine learning (ML) models powering your chat bot solution. For example, when training the Watson Business Coach application, we interviewed sellers, partners, and clients to collect questions and utterances like: "show me a Watson demo in Healthcare, "how can I use cognitive to improve customer service", "how is cognitive different from analytics", etc. Once training is complete, run the test set against the trained classifier and collect performance metrics such as accuracy, precision, and recall. For example, when training the Watson Business Coach application, we interviewed sellers, partners, and clients to collect questions and utterances like: "show me a Watson demo in Healthcare, "how can I use cognitive to improve customer service", "how is cognitive different from analytics", etc.


Robotics of things - the next big thing in embedded

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Whether they are smart, low energy, edge devices, intermediate gateways or compute nodes, all based on multicore system-on-chip (SoC) architectures requiring performance, reliability and security. As a result the embedded systems industry seems to be headed into two key areas: intelligence and autonomy. Sensor technology and image processing will continue to advance. Ultimately, the evolution of today's systems into highly intelligent and autonomous systems will have a huge positive impact to the global economy, and more importantly to the health, safety, and quality of our lives.


Artificial intelligence will make your sports wearables -- and you -- even better

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By bringing artificial intelligence to its wearable tech, PIQ is looking to improve on its design. Both the PIQ Robot and GAIA Intelligence give coaches and athletes the ability to analyze every movement during a game or match. To better understand and analyze sports movements, GAIA was developed. To give the artificial intelligence a head start, GAIA has been analyzing millions of movements from thousands of other athletes.


AI winter isn't coming, says Baidu's Andrew Ng

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Artificial intelligence researchers are now offered huge wages to perform fundamental research, as companies build research teams on the assumption that commercially important breakthroughs will follow. The advances seen in recent years have come thanks to the development of powerful "deep learning" systems (see "10 Breakthrough Technologies 2013: Deep Learning"). Richard Socher, chief scientist at Salesforce and a well-known expert on machine learning and language, says availability of huge amounts of data, combined with advances in machine-learning algorithms, will also keep progress going. Salesforce now also provides simple machine learning tools to companies, such as an image recognition system.


Context Levels in Data Science Solutioning in real-world

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Solution development: Using historical data, involves extensive experimentation, testing and validation; Solution deployment: Using the solution to get the insight and/or decision support; Solution assimilation: In the workflow enabling actions based on insight and/or prediction made by the solution; Solution maintenance and update: Periodic checking and validation of the solution performance and update to improve performance if required. Solution maintenance and update: Periodic checking and validation of the solution performance and update to improve performance if required. Solution maintenance and update: Periodic checking and validation of the solution performance and update to improve performance if required. An algorithm works with available data footprint of the process of interest; It discovers the relationships between the process characteristics and the outcomes; The above relationships are, more often than not, in form of complex patterns; Discovering these patterns require application of powerful learning algorithms on the historical data; Discovered patterns lead to learning the required model parameters; An analysis/model application algorithm use these parameters to create the model and apply it on the new data in order to compute the output.


AI winter isn't coming, says Baidu's Andrew Ng

@machinelearnbot

Artificial intelligence researchers are now offered huge wages to perform fundamental research, as companies build research teams on the assumption that commercially important breakthroughs will follow. The advances seen in recent years have come thanks to the development of powerful "deep learning" systems (see "10 Breakthrough Technologies 2013: Deep Learning"). Richard Socher, chief scientist at Salesforce and a well-known expert on machine learning and language, says availability of huge amounts of data, combined with advances in machine-learning algorithms, will also keep progress going. Salesforce now also provides simple machine learning tools to companies, such as an image recognition system.


Mega collection of data science books and terminology

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Adaptive Boosting (AdaBoost) - AdaBoost, short for "Adaptive Boosting", is a machine learning meta-algorithm formulated by Yoav Freund and Robert Schapire who won the prestigious "Gödel Prize" in 2003 for their work. When used with decision tree learning, information gathered at each stage of the AdaBoost algorithm about the relative'hardness' of each training sample is fed into the tree growing algorithm such that later trees tend to focus on harder to classify examples. Adaptive Boosting (AdaBoost) - AdaBoost, short for "Adaptive Boosting", is a machine learning meta-algorithm formulated by Yoav Freund and Robert Schapire who won the prestigious "Gödel Prize" in 2003 for their work. When used with decision tree learning, information gathered at each stage of the AdaBoost algorithm about the relative'hardness' of each training sample is fed into the tree growing algorithm such that later trees tend to focus on harder to classify examples.


MusicNet

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Automatic music transcription, inferring a musical score from a recording, is a long-standing open problem in the music information retrieval community. Music streaming services traditionally make recommendations based on collaborative filtering and metadata (e.g. Features learned from the MusicNet labels might be useful for recommendation. Can we learn to synthesize a performance given a score?