engineering


Learnin' Good All This AI Stuff for Product Management

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I've invested a considerable amount of time taking numerous courses, so I dug into my emails to collect some of the suggestions I've doled out. First, it's worth addressing the extent to which a product manager even needs to understand how AI works in order to be effective. There is an endless stream of business articles about what AI is, what it does and how it is going to disrupt this and that, all of which is great, but I am talking about understanding how it works (e.g. As Marty Cagan pointed out in Inspired (a must-read), product managers can come from a variety of different vertical disciplines, including those that are not necessarily technical, such as marketing or sales. Can these individuals, or even product managers who come from engineering but don't necessarily have a background in AI, be successful managing AI products?


Artificial Intelligence School to Open in Fez

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With artificial intelligence expected to generate more than 2.3 million jobs by 2020, Morocco has begun to prepare its students for the future by opening a school dedicated to AI training. Rabat – As technology continues to be central in the world's vision for the future, the development of artificial intelligence (AI), the simulation of human intelligence by computers and machines, has become an increasingly important field in science. Meanwhile, Morocco, along with the rest of Africa, has largely failed to capitalize on this demand for AI research and development. However, all of this will change in the future, with the opening of a new school dedicated towards AI in Fez. In September, the Euromed University of Fez (UEMF) will open its doors to the Euromed School of Digital Engineering and Artificial Intelligence (EIDIA), a brand new center dedicated towards AI research, development, and education.


The Brutal Truth about Data Science and Data Scientists

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Most data scientists and the organizations that employ them don't seem to understand how data science is actually done, nor what it is exactly. They sort of jumped on the bandwagon -- without really understanding it, nor why it was important to them in a very visceral way. Science is not merely predictive -- at its heart, it is explanatory as well as diagnostic. Science leads to engineering -- a systematic mathematical approach to creating technology solutions based on the exploitation of some natural phenomenon. Winning Kaggle competitions is not data science; though, it is a reasonable start, I suppose – even though the best models in Kaggle are actually built by machines running genetic algorithms, where natural selection drives the outcome.


30 Data Science Punchlines - Towards Data Science

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For those who like brainfood on your vacation, here's a handy index of all my articles from 2018 boiled down to 30 (occasionally cheeky) punchlines to help you avoid/cause awkward silences at family events and holiday parties. Bonus: Videos, podcasts, foreign language translations for your non-English-speaking friends and family to enjoy, and an end-to-end deep learning tutorial for the Pythonistas among you. What on earth is data science? Data science is the discipline of making data useful. What Great Data Analysts Do -- and Why Every Organization Needs Them.


Government puts £12m into AI-powered vacuum cleaners and dolphin-protection tech

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The government is investing £12m in the development of new technologies including robots that can perform household tasks and products to protect dolphins from noise protection. The money is being invested by the Engineering and Physical Sciences Research Council (EPSRC) in four partnerships between universities and the private sector. Government funding is being supplemented by a further £17.5m in cash from commercial partners. The first project being funded involves work to develop materials that do not make noise underwater. This, the government said, will not only improve the life expectancy of dolphins, fish, and other marine creatures, but will also have a positive impact on human health.


How Product Managers Learn About AI Meeting Peak Effectiveness

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"What do I need to know about AI and what's the best way to learn it?" I've invested a considerable amount of time taking numerous courses, so I dug into my emails to collect some of the suggestions I've doled out. First, it's worth addressing the extent to which a product manager even needs to understand how AI works in order to be effective. There is an endless stream of business articles about what AI is, what it does and how it is going to disrupt this and that, all of which is great, but I am talking about understanding how it works (e.g. As Marty Cagan pointed out in Inspired (a must-read), product managers can come from a variety of different vertical disciplines, including those that are not necessarily technical, such as marketing or sales.


Vegebot robot applies machine learning to harvest lettuce

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Vegebot, a vegetable-picking robot, uses machine learning to identify and harvest a commonplace, but challenging, agricultural crop. A team at the University of Cambridge initially trained Vegebot to recognize and harvest iceberg lettuce in the laboratory. It has now been successfully tested in a variety of field conditions in cooperation with G's Growers, a local fruit and vegetable co-operative. Although the prototype is nowhere near as fast or efficient as a human worker, it demonstrates how the use of robotics in agriculture might be expanded, even for crops like iceberg lettuce which are particularly challenging to harvest mechanically. The researchers published their results in The Journal of Field Robotics.


New superomniphobic glass soars high on butterfly wings using machine learning: Engineers develop new superclear, supertransparent, stain-resistant, anti-fogging nanostructured glass based on butterfly wing

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The team recently published a paper detailing their findings: "Creating Glasswing-Butterfly Inspired Durable Antifogging Omniphobic Supertransmissive, Superclear Nanostructured Glass Through Bayesian Learning and Optimization" in Materials Horizons (doi:10.1039/C9MH00589G). They recently presented this work at the ICML conference in the "Climate Change: How Can AI Help?" workshop. The nanostructured glass has random nanostructures, like the glasswing butterfly wing, that are smaller than the wavelengths of visible light. This allows the glass to have a very high transparency of 99.5% when the random nanostructures are on both sides of the glass. This high transparency can reduce the brightness and power demands on displays that could, for example, extend battery life.


VA aims to expand artificial-intelligence research - VAntage Point

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The blog post below is adapted from a longer article in VA Research Currents. When Facebook suggests a new friend for you, or Gmail shows you ads based on your email content, or Alexa or Siri understands your verbal command to do some chore in the house, that's artificial intelligence at work. Or, for a more dramatic example, think of driverless cars that read traffic and make lightning-fast decisions to stay on course and avoid accidents. Basically, artificial intelligence (AI) means using computers to simulate human thinking. Computers will never be able to fully replicate the human mind in all its amazing nuance, speed, and complexity--at least most people hope not!--but scientists have made remarkable strides in teaching computers to handle tasks such as finding patterns in data, analyzing and weighing risk factors, choosing the best option from among many choices, predicting future events based on past ones, and solving problems.


Systers TechTalks: Get started with Machine Learning

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Brief introduction about what is Machine Learning and algorithms, theories, technologies used, applications, how to get started with, what programming language to learn etc. Yashashvi is freelance software developer and a final year student of Bachelors of Engineering in Computer Engineering. Yashashvi is an open source advocate and active contributor. Yashashvi has previously worked with Zulip(https://zulipchat.com/) and Indian Institute of Technology Bombay organizations. A technical woman is never alone when she's a Syster. Founded by Dr. Anita Borg, in 1987 together with 12 other women as a small electronic mailing list for women in systems.