Artificial intelligence (AI) is an innovation powerhouse. It autonomously learns on its own and evolves to meet simple and complex needs, from product recommendations to business predictions. As more people and services produce data, more powerful AI is necessary to process it all. AI chipsets that use edge computing are the solution.
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This is the first post in a two-part series on Principal Component Analysis (PCA) and Independent Component Analysis (ICA). Although they have similarities (such as their names), they each achieve different tasks. In this post, I will give describe what PCA is, how it works, and as an example use it to define an S&P 500 index fund. Example code and other related resources can be found in the last section of this post.
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Within forecasting there’s an age old question, ‘is what I am looking at a trend?’ Within the realm of statistics there are many tools that, with various degrees of success, answer said question. Yet, no approach has been able to achieve that which started the field of data forecasting in the first place. Looking at a graph derived from the data and drawing conclusions from it. However, thanks to Deep Learning and Artificial Neural Networks that is about to change. Welcome Computer Vision!
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As I discuss in my article “Myths of Modelling: Data Speak”, Positivism — and, by association, its mythical beliefs — had been pretty thoroughly discredited by the 1960s. Unfortunately, as if often the case in the history of ideas, the counter-revolution over-compensated. Where the early revolutionaries would loosen the chains of narrow empiricism and open up for a more enlightened dialogue between hypotheses and the data that inspire and regulate them, the next generation would throw empiricism out all together. In the ensuing vacuity of common sense, practitioners had little choice but to crawl back to frameworks steeped in positivism.
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Google has picked a dozen companies for its first Google for Startups Accelerator: Voice AI. The 10-week program for voice AI startups in North America combines workshops and mentoring on technical and entrepreneurial topics.
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Who will benefit from advances in artificial intelligence? And should we be worried? Advances in artificial intelligence (AI) are likely to be of most benefit to three groups: the wealthy, those who have specialist skills in jobs that are not easily automated, and those who can work effectively with intelligent machines. These groups of people represent a minority that will have a marked advantage in the future over the rest of humanity. However, advances in AI could benefit everyone while still bolstering inequality.
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Splice, the New York-based, AI-infused, beat-making software service for music producers created by the founder of GroupMe, has managed to sample another $55 million in financing from investors for its wildly popular service.
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Both AppDynamics and Dynatrace offer a wide range of features and tools. This means while some tools are ideal for you, you might find many features redundant too. You can take advantage of the tree trial offered by both vendors to get a sense of how they work and see which tool works best for you.
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AIOps implementation makes life easier for the IT environment whereby it takes on the various challenges facing the existing system and provides us with all end-to-end report and visibility of our IT environment, and makes any IT team to be proactively respondent to any technical issue that arises.
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While applications such as electric mobility, stationary storage, drones and medical implants continue to take off, the global demand for sustainable rechargeable batteries is expected to increase drastically in the next decade. Europe alone would need a cell production capacity of at least 200 GWh up to the TWh range.
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Nanit’s nursery camera pairs computer vision with specially patterned clothing to help answer the question that most new parents ask themselves roughly every 90 seconds: “Is my baby still breathing?” This morning the company is announcing that it has raised an additional $25 million in a Series C round led by GV.
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Dell opens global Innovation Facility in Singapore, the First Outside US, , to focus on R&D for edge computing, data analytics and augmented reality. American tech giant Dell Technologies officially launched a US$50 million (S$66 million) research and development centre here on Monday (Feb 22) that will drive innovation in computing near where data is located.
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An artificial intelligence method can help combat emerging COVID-19 mutations by identifying the best potential vaccines to treat the virus, according to a study published in Scientific Reports.
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Psychiatric practice routinely uses semistructured and/or unstructured free text to record the behavior and mental state of patients. Many of these data are unstructured, lack standardization, and are difficult to use for analysis. Thus, it is difficult to quantitatively analyze a patient’s illness trajectory over time and his or her responsiveness to treatment, and it is also difficult to compare different patients quantitatively. In this article, experts in the field of psychiatry, along with machine learning models, have …
Read MoreUsing AutoML frameworks in the real world is becoming a regular thing for machine learning practitioners. People often ask: does automated machine learning (AutoML) replace data scientists? Not really. If you’re eager to find out what AutoML is and how it works, join me in this article. I’m going to show you auto-sklearn, a state-of-the-art and open-source AutoML framework.
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