Scientists are recruiting members of the public to help clean up the shores of Great Britain. Plastic waste is scattered across the beaches of the UK and a computer programme is being developed to help spot the litter. The charity campaign needs human volunteers to help train an artificial intelligence algorithm that will automatically spot plastic in pictures taken by drones. Plastic Tide, the charity behind the project, hopes to harness cutting edge drone and algorithm technology to create an open source map of the plastic pollution problem. Peter Kohler, founder and director of The Plastic Tide, said: 'Marine creatures die each year through starvation due to eating plastic that stays in their stomach, making them feel full.

A few weeks back, I wrote about the need for machine learning at the edge and what big chip firms are doing to address the challenge. Even as Intel, ARM, and others invest in new architectures, startups are also attempting to innovate with new platforms. GreenWaves Technologies, based in France, is one such company. It has built a machine learning chip that offers multiple cores and low-power machine learning at the edge. The chip is called the GAP8 application processor.

Terrible traffic, prayer-inducing merges, road signs that are all but impossible to read, dangerous road conditions, and drivers who hazard sudden, scream-worthy maneuvers, all add to Moscow's commuting woes. Sadly, this is what 98% of the world's roads are like, and why one Russian company, Cognitive Technologies Group, may come out ahead in the race to birth the self-driving car. President and founder of the group Olga Uskova, is skeptical of Silicon Valley's sunny projections of when autonomous vehicles will go mainstream. The reason, she told The Guardian was that there are too many variables in most places to look out for. In Moscow for instance, "The environment is ever-changing: the snow has covered traffic signs; it's raining on your windshield, the sun is blocking you. Our people train using these kinds of data."

Recently, IndustryWeek hosted a PTC-sponsored webinar called Pragmatic Paths to Accelerate Manufacturing Performance with Industrie 4.0. The presenters, Kent Eriksson, a Senior Advisor in PTC's IoT Transformation Advisory Practice, and Stephen Laaper, a Digital Supply Networks leader in Deloitte Consulting's Strategy & Operations practice, had too much information about the best, most practical ways to adopt the Industrial Internet of Things (IIoT) didn't have time to answer every listeners' questions. It's such a vital component to the future of manufacturing success, one that there is much to learn about, that we all felt these questions could not linger. So here they are, and even if you couldn't attend, there is much to glean from these experts' responses. Q: Where should we draw distinctions between Industrie 4.0 and IoT, and Big Data and its connectors?

Hedge funds are increasingly turning their attention towards artificial intelligence technology to get an edge on the competition when it comes to trading strategies. Quantitative trading - a subset of what hedge funds do which focuses on algorithms and computers to trade clients' assets - is a natural testbed for machine learning technology, which is good at spotting trends in big data sets and executing at high speed. For example, at Man Group - a London-based hedge fund - "by 2015 artificial intelligence was contributing roughly half the profits in one of Man's biggest funds, the AHL Dimension Programme that now manages $5.1 billion, even though AI had control over only a small proportion of overall assets," as reported by Bloomberg. For what it's worth, European Union lawmakers have attempted to legislate against algorithm-centric funds disrupting the market with the Markets in Financial Instruments Directive (MiFID II) regulation. Britain's Financial Conduct Authority (FCA) meanwhile is charged with maintaining order in UK markets, but these efforts can be difficult when the algorithms are by their nature difficult to investigate - also known as black box algorithms.

Angelina Jolie and Senator John McCain recently penned a joint op-ed piece for the New York Times. In their lengthy article, Jolie and McCain asked Americans, as well as the U.S. government, to help save the Rohingya Muslims. "Around the world, there is profound concern that America is giving up the mantle of global leadership. Our steady retreat over the past decade has contributed to a wide array of complex global challenges – a dangerous erosion of the rule of law, gross human rights violations and the decline of the rules-based international order that was designed in the aftermath of two world wars to prevent conflict and deter mass atrocities," they wrote. Jolie and McCain also cited a lack of diplomacy in Myanmar, which has led to the fleeing of approximately 680,000 Rohingya Muslims.

Tech companies are rushing to infuse everything with artificial intelligence, driven by big leaps in the power of machine learning software. But the deep-neural-network software fueling the excitement has a troubling weakness: Making subtle changes to images, text, or audio can fool these systems into perceiving things that aren't there. That could be a big problem for products dependent on machine learning, particularly for vision, such as self-driving cars. Leading researchers are trying to develop defenses against such attacks--but that's proving to be a challenge. Case in point: In January, a leading machine-learning conference announced that it had selected 11 new papers to be presented in April that propose ways to defend or detect such adversarial attacks.

Does it ever seem like your dog is in tune with your emotions? You may be on to something. In new experiments, dogs showed signs of understanding whether a human or a dog was happy or mad based on facial expressions and vocalizations. The research, published in the journal Biology Letters, set out to explore the emotional connection between man and his best friend. "We still didn't know if the dogs ... can somehow understand that, say, a happy facial expression is positive and a negative facial expression is negative," says study leader Natalia de Souza Albuquerque, a Ph.D. student in experimental psychology at the University of São Paulo in Brazil.

We've compiled a list of the hottest events and conferences from the world of Data Science, Machine Learning and Artificial Intelligence happening in 2018. Below are all the links you need to get yourself to these great events! Please get in touch if there are any great events or conferences you think should be added!

These very different inventions share one thing in common: they were created by women. Despite their significant contributions, many of these female inventors have gone unrecognized. In honor of International Women's Day, take a moment to appreciate these six inventions we wouldn't have without women. Thanks to Melitta Bentz from Germany, you don't have to worry about grounds in your cup of joe. In 1908, Bentz was in search of a better coffee-drinking experience.