Active Learning

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Membership Query Synthesis: This is where the learner generates its own instance from an underlying natural distribution. For example, if the dataset are pictures of humans and animals, the learner could send a clipped image of a leg to the teacher and query if this appendage belongs to an animal or human. This is particularly useful if your dataset is small. Stream-Based Selective Sampling: Here, each unlabeled data point is examined one at a time with the machine evaluating the informativeness of each item against its query parameters. The learner decides for itself whether to assign a label or query the teacher for each datapoint.


5 Benefits of Sourcing CNC Machining Work Online

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Machining businesses mired in time-consuming traditional quoting might be surprised to learn that many of their counterparts are winning work with little more than a mouse click. Precisely how many is anyone's guess. Although these are top performers, other CNC machine shops constitute the majority of the 2,500-plus manufacturers bidding on this online platform (others include injection molders, additive manufacturing services and parts finishers). While many of the manufacturers are small, many of the parts purchasers are large. Some, like Bosch and BMW, have become investors, pouring more than $50 million into the company since May.


Azure Functions for ML ?

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Functional programming in pure form implies no state and no side effects when called (since there is no state). Azure Functions (much like AWS Lambda and Google Cloud Functions) is a neat concept where you don't need any explicit infra, you just deploy a function and reference it via an endpoint (URI). During my search for the ultimate (aka, ultimately cheap/free) deployment for my ML models, I thought I would try this out since the pricing docs state a high free # of executions. Setup is easy, go to Azure Portal and run thru the usual "Create" and search for "Functions" Not well documented is that you have to install both the node package (npm install -g azure-functions-core-tools) and the python package via pip (pip install azure-functions) if you are coding in Python on Visual Studio Code. Some languages have an online editor within Azure Portal which is kind of nice (though kind of dangerous).



The Future Of Artificial Intelligence In Retail

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Artificial intelligence (AI) is more than just cyborgs in movies trying to destroy humanity. It has actual real-world applications that can make our lives better and our businesses stronger and more profitable. In retail, artificial intelligence is being adopted rapidly - between 2016 and 2018 there was a 600% increase in adoption. Unfortunately the adoption rate is still relatively low, ranging from 26% for home improvement stores to 33% for apparel and footwear. If AI can make such a big difference, why isn't everyone adopting it?


AI and big data: driving enterprise using ethical principles SciTech Europa

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We spoke to Maria Axente, AI Programme Driver, PwC United Kingdom in the context of this event about how AI and big data can be used to drive enterprise using ethical principles. AI and big data are making big changes in enterprise. It is worth considering how we got to the stage we are at today, and the fact that AI as a discipline is around 56 years old but it has suddenly started to be implemented at a much larger scale. I think there are three main causes of this more recent widespread adoption of AI. One is the huge volume of data that is being collected via smart devices; mainly smartphones, but increasingly IoT devices.



Khadas VIM3 NPU ToolKit Release & Video Demo

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We've reviewed VIM3 with Android 9 shortly after launch, but until recently it was not possible to leverage the NPU since the software was not quite ready yet. The goods news is that Khadas has now released the NPU toolkit for both VIM3, and the cheaper VIM3L boards. The toolkit works in host PCs running Ubuntu 16.04 or 18.04 with Tensorflow framework, and inference can run on both Linux and Android OS in Khadas VIM3/3L board. It includes an Inception v3 sample with 299 299 sample photos, among other demos. You'll find documentation to get started with model conversion and inference in Linux on Khadas Wiki.


Western News - Western, RBC team up on data analytics, AI

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The next generation of leaders will be better armed against unprecedented technical transformation thanks to a new partnership between Western and Royal Bank of Canada (RBC) that will establish a program focused on the ethical and social aspects of data analytics and artificial intelligence (AI), university officials announced today. A $3-million investment by RBC has established The RBC Data Analytics and Artificial Intelligence Project at Western, an expansion of the university's ongoing cross-disciplinary work in data analytics and AI focused on answering big questions for the good of society. RBC's backing helps take that work to the next level, while training the next generation of experts, explained Western President Alan Shepard. "This investment is a catalyst to help Western provide tomorrow's leaders with the skillset they'll need to navigate a world full of data and find solutions to the challenges they will inevitably face during their careers," Shepard said Thursday. "We're excited to be partnering with RBC to help provide and promote training of 21st-century talent that's not only technically proficient, but also ethically and socially aware."


How to Make Your Chatbot Successful in the eCommerce Market

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I would like to start with the fact that the retail market today is developing by leaps and bounds, but traders by the way also do not standstill. On the contrary, they gradually seize the initiative by introducing Artificial Intelligence into their products. Note, when many things were simply impossible, but thanks to the arrival chatbots much have changed. Chatbots are one of the most effective tools in building relationships between customers. More and more retailers choose eCommerce chatbots as a primary method of communication with the visitors of their online stores.