Synchrotron light sources are powerful facilities that produce light in a variety of "colors," or wavelengths--from the infrared to X-rays--by accelerating electrons to emit light in controlled beams. Synchrotrons like the Advanced Light Source at the Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) allow scientists to explore samples in a variety of ways using this light, in fields ranging from materials science, biology, and chemistry to physics and environmental science. Researchers have found ways to upgrade these machines to produce more intense, focused, and consistent light beams that enable new, and more complex and detailed studies across a broad range of sample types. Many of these synchrotron facilities deliver different types of light for dozens of simultaneous experiments. And little tweaks to enhance light-beam properties at these individual beamlines can feed back into the overall light-beam performance across the entire facility.

A week ago today, hackers unleashed the first known attack using the vulnerability known as BlueKeep, a long-feared development that in practice turned out to be relatively benign. But don't worry, plenty of other things still went wrong. Like, say, the revelation that you can hack Alexa, Google Assistant, and Siri with lasers. Take the two former Twitter employees who allegedly used their insider access to spy on behalf of Saudi Arabia--a stark reminder of how ill prepared even the biggest companies are to protect consumer data from the people who work there. Or the spate of zombie text messages from February that hit people's phones Thursday with no explanation, the result of a third-party server that had failed on February 14 and was reactivated November 7. All the messages stranded in that queue finally got sent.

A week ago today, hackers unleashed the first known attack using the vulnerability known as BlueKeep, a long-feared development that in practice turned out to be relatively benign. But don't worry, plenty of other things still went wrong. Like, say, the revelation that you can hack Alexa, Google Assistant, and Siri with lasers. Take the two former Twitter employees who allegedly used their insider access to spy on behalf of Saudi Arabia--a stark reminder of how ill prepared even the biggest companies are to protect consumer data from the people who work there. Or the spate of zombie text messages from February that hit people's phones Thursday with no explanation, the result of a third-party server that had failed on February 14 and was reactivated November 7. All the messages stranded in that queue finally got sent.

This summer, the FaceApp debate exploded on social media, as people questioned the motives of the Russian engineers behind the technology that scanned millions of people's faces, with no indication of what happened to the data given to the app. Privacy is presumably top of mind for the general public, but people's urge to literally see the face of their own future selves seemed to outweigh that threat. FaceApp may serve no benefit beyond entertainment. But today, every company effectively becomes a tech company by leveraging advanced data analytics to fuel their business. With nearly every service, gadget, and add-on, we are constantly being asked to put our trust--in the form of our personal data--in brands, big and small.

In 2017 we put together a graph to showcase the must-haves, the should-haves and the nice-to-haves of different AI applications for marketing and growth. We call it the A.I. for Marketing & Growth Maturity Chart. A lot has changed since then though so it was time for an update. Let's dive right in! It's not new news that AI in Marketing can bring a return on investment for a company's capabilities. There are numerous spaces where A.I. is helping marketers.

BlackBerry and Baidu have announced a collaboration through which the Canadian and Chinese companies will team up for a number of connected and autonomous vehicle initiatives. The duo have signed a statement of intent to make BlackBerry's QNX operating system the basis for Baidu's previously announced Apollo autonomous driving platform. As part of the tie-up, Baidu said it plans to integrate a number of its own software products into BlackBerry's QNX Car infotaintment platform, including CarLife, which integrates connected cars with smartphones; Baidu's DuerOS voice interaction system; and high-definition maps. "We aim to provide automakers with a clear and fast path to fully autonomous vehicle production, with safety and security as top priorities," said Li Zhenyu, general manager of Baidu's intelligent driving group. "By integrating the BlackBerry QNX OS with the Apollo platform, we will enable carmakers to leap from prototype to production systems. Together, we will work toward a technological and commercial ecosystem for autonomous driving, intelligent connectivity, and intelligent traffic systems."

Researchers in Japan and at the University of Michigan recently said that they had figured out how to take control over Google Home, Amazon's Alexa or Apple's Siri devices from several feet away by shining laser pointers, and even flashlights, at the devices' mouthpieces. What brought this one was the ascent of the voice-controlled digital assistants, introduced a couple of years back and the security experts have expressed their worries that systems like Apple's Siri and Amazon's Alexa were a privacy danger and could be effectively and easily hacked. Kevin Fu, an associate professor of electrical engineering and computer science at the University of Michigan with respect to the usage of laser pointers said that "This opens up an entirely new class of vulnerabilities, it's difficult to know how many products are affected because this is so basic." The computer science and electrical engineering researchers -- Takeshi Sugawara at the College of Electro-Interchanges in Japan and Mr. Fu, Daniel Genkin, Sara Rampazzi, and Benjamin Cyr at the College of Michigan -- all of them released their findings regarding the same issue in a paper on the 4th of November. The researchers said they had informed Tesla, Portage, Amazon, Apple, and Google to the light vulnerability and the companies all responded saying that they were'studying' the conclusions in the paper that was released.

While buzzwords such as predictive maintenance, artificial intelligence, digital twin and augmented reality have promised to enable the fabled digital transformation of manufacturing, when it comes to Industry 4.0, most practical applications start and end with machine connectivity. And when it comes to driving value, look no further than answering these questions: "What's happening?" Simply put, most manufacturers are unable to see what's actually happening on the shop floor in real time because their machines are not connected to any sort of data collection or data visualization system. This inability to both see and use data to drive continuous improvement leads to massive inefficiencies that affect every component of a company's operations, from the shop floor all the way to the C-Suite. As the excitement around the opportunity presented by AI continues to grow, Lou Zhang, chief data scientist at MachineMetrics, offers his perspective on where AI lands within the Analytics Journey and its relationship to technologies such as machine monitoring and data collection.

While buzzwords such as predictive maintenance, artificial intelligence, digital twin and augmented reality have promised to enable the fabled digital transformation of manufacturing, when it comes to Industry 4.0, most practical applications start and end with machine connectivity. And when it comes to driving value, look no further than answering these questions: "What's happening?" Simply put, most manufacturers are unable to see what's actually happening on the shop floor in real time because their machines are not connected to any sort of data collection or data visualization system. This inability to both see and use data to drive continuous improvement leads to massive inefficiencies that affect every component of a company's operations, from the shop floor all the way to the C-Suite. As the excitement around the opportunity presented by AI continues to grow, Lou Zhang, chief data scientist at MachineMetrics, offers his perspective on where AI lands within the Analytics Journey and its relationship to technologies such as machine monitoring and data collection.

Bengaluru: Bengaluru Analytics Vidhya's third edition of DataHack Summit, India's Largest Conference on Applied Artificial Intelligence and Machine Learning will be held from 13 – 16 November 2019 at NIMHANS Convention Centre, Bengaluru. Global AI Leaders, Researchers, Machine Learning Experts, Data Scientists, Analysts and Engineers will be attending the summit to spark discussions on Machine Learning, Artificial Intelligence, Reinforcement Learning, Natural Language Processing, Generative Modeling, Computer Vision, Explainable AI, Cloud Computing, Deep Learning, Transfer Learning, Quantum Computing, and Speech Recognition. There will be a more than 1000 AI & ML professionals will be attending 8 workshops, 30 hack sessions and 70 talks. The conference will witness speakers including Dr. GeethaManjunath (Founder & CEO of NIRAMAI), SayanRanu (IIT Delhi), Dat Tran (Head of AI at Axel Springer Ideas Engineering), UjjyainiMitra (Head of Data, ZEE5), XanderSteenbrugge (Head of applied ML-research at ML6), Prateek Jain (Microsoft), Jayatu Sen Chaudhury (American Express), Nishant Agrawal (Intel), Dr. Vikas Agrawal (Oracle Analytics Cloud), Dr. HarshadKhadilkar (TCS) and 100 more experts sharing their views on the impact of Artificial Intelligence and Machine Learning. According to Kunal Jain, " Analytics Vidhya's mission is to build next-gen data science ecosystem and with DataHack Summit 2019 – we aim to bring together people, machines and their collaborative experience to make our world data-driven! After the immense success of the DataHack Summit 2018, the Summit has become bigger and will go deeper on the subject. With more than 70 sessions from experts across the globe spread across 4 days – there cannot be a better place to learn about Artificial Intelligence, Machine Learning and Deep Learning."