Radar in Uber's self-driving vehicle detected pedestrian Elaine Herzberg more than five seconds before the SUV crashed into her, according to a new report from the National Safety Transportation Board. Unfortunately, a series of poor software design decisions prevented the software from taking any action until 0.2 seconds before the deadly crash in Tempe, Arizona. Herzberg's death occurred in March 2018, and the NTSB published its initial report on the case in May of that year. That report made clear that badly written software, not failing hardware, was responsible for the crash that killed Herzberg. But the new report, released Tuesday, marks the end of NTSB's 20-month investigation.

Lennar New Home Consultant Brittney Svach is selling "smart homes" at the Amazon Experience Center in Black Diamond, Washington, about an hour south of Seattle. Lennar New Home Consultant Brittney Svach is selling "smart homes" at the Amazon Experience Center in Black Diamond, Washington, about an hour south of Seattle. When the Ferguson family decided they wanted to live in the Seattle suburb of Black Diamond they weren't in the market for a smart home. But they wound up with one, a house packed with Internet-connected devices. "I just feel really fancy," she says about having Amazon's Alexa there to turn on the lights for her, or to remind her when to go to cheerleading practice.

Scientists from Intel, Amazon, Facebook and Google joined some of the leading academic minds on artificial intelligence (AI) to discuss the future of machine learning during the inaugural Responsible Machine Learning Summit hosted by UC Santa Barbara. With more than 120 students, faculty, business leaders and invited guests on hand, every speaker and panelist agreed on the importance of establishing an ethical foundation for machine learning, in which a computer uses algorithms and data to make predictions or decisions on its own. "We need to better understand the mutual influence between society and machine learning," said William Wang, a professor of computer science and organizer of the event. "Personally, I'm interested in improving the quality of life by learning the important societal factors and impacts that should be considered when building algorithms, such as fairness, transparency, privacy and accountability." The summit served as the opening for Wang's Center for Responsible Machine Learning.

When Indian Defense Minister Rajnath Singh said that blockchain and artificial intelligence would "revolutionize war," as Cointelegraph reported on Nov. 4, did he take things a bit too far? Jet engines have revolutionized warfare, and so have missiles and nuclear weapons -- but shared digital ledgers? Former NATO Secretary General Anders Fogh Rasmussen, for one, told Cointelegraph that he agrees with India's minister when he was asked about blockchain's possible military uses: Digital technologies have been transforming warfare since the 1990's so emerging technologies such as blockchain have the potential to define the war industry over the coming decades. Data and data sharing will be critical for warfare in the future, particularly with the development of artificial intelligence." "Sharing data is fundamentally about transactions.

In theory, marketing personalization should be a win-win proposition for both companies and customers. By delivering just the right mix of communications, recommendations, and promotions -- all tailored to each individual's particular tastes -- marketing technologies can result in uniquely satisfying consumer experiences. While ham-handed attempts at personalization can give the practice a bad rap, targeting technologies are becoming more sophisticated every day. New advancements in machine learning and big data are making personalization more relevant, less intrusive, and less annoying to consumers. However, along with these developments come a hidden risk: the ability of automated systems to perpetuate harmful biases.

Programmatic advertising is on a disruptive ride with new technologies such as artificial intelligence, machine learning, voice search and digital OOH attracting most advertisers. With 5G promising a push to programmatic on one hand and the implementation of GDPR posing new challenges, there's a lot more that marketers need to watch out for in the space. Here we track the top trends you need to follow in the programmatic Ad Tech space for 2020 and beyond. Programmatic advertising is by far the most crucial component of advertising technology - one that is keeping the entire adtech fraternity on a vigil for what's coming next. It is set to be the default media trading method in the coming years. According to Zenith's'Programmatic Marketing Forecasts' report, programmatic ad spend will reach $98 billion, amounting to 68% of the global digital media ad spend by 2020. Introduction of technologies such as artificial intelligence (AI), machine learning (ML) and 5G are going to make programmatic advertising more efficient, while the entry of newer advertising channels such as Digital Out Of Home (DOOH), podcast and audio programmatic advertising, voice-activated ads, smart devices, and AR/VR not only gives marketers more choices but also provides a more engaging, personalized experience for consumers.

It's That Time of Year Again--Fall Is Here and Packs of Robot Dogs Are Frolicking in the Leaves James Vincent The Verge "There's nothing I like more on bright and cold autumnal days than heading down to the park and watching the robot dogs playing in piles of leaves. To hear the scuttle of their little metal legs! To imagine the joy in their tiny silicon brains! The World's First Gattaca Baby Tests Are Finally Here Antonio Regalado MIT Technology Review "Anxious couples are approaching fertility doctors in the US with requests for a hotly debated new genetic test being called "23andMe, but on embryos." Elon Musk Says Building the First Sustainable City on Mars Will Take 1,000 Starships and 20 Years Darrell Etherington Tech Crunch "Addressing a question about comments he made earlier this week at the US Air Force startup pitch day event in California, Musk said that his stated launch cost of only around $2 million per Starship flight are essentially required, should the final goal be to set up a'self-sustaining city on Mars.'i"

Good day, The biggest AI bootcamp in Nigeria is here! Will you be part of the best of the best who will make it to the all-expense paid residential Artificial Intelligence Bootcamp?... This was a mail I received on September 24 from Data Science Nigeria. And below is a snippet of what I got on Data Science Nigeria's website today. I started my programming journey back in September, 2018 with the most highly rated course on Udemy courtesy of my mentor, Fakorede Abiola.

"By combining data from across our NASH clinical development program with artificial intelligence (AI)-based tools, we have the opportunity to better characterize this complex disease and understand how potential therapies can impact disease progression," said Mani Subramanian, MD, Senior Vice President, Liver Diseases, Gilead Sciences. "Applying PathAI's deep learning research platform for liver histology assessment will enable a more rigorous review of treatment response and has potential for the exploration of novel biology in patients with advanced fibrosis due to NASH." In a collaboration with PathAI, a leader in AI-powered research in pathology, Gilead is evaluating machine learning approaches to liver histology assessment for use in the diagnosis and staging of NASH and monitoring of treatment response in clinical trials. A study of images from liver biopsies from patients screened for the Phase 3 STELLAR program compared the staging and characterization of liver disease as assessed by experienced pathologists and by the PathAI research platform. The pathologists scored biopsies using the NASH Clinical Research Network (CRN) and Ishak fibrosis classifications, and the PathAI research platform, a convolutional neural network, evaluated these biopsies following training on more than 68,000 annotations from 75 board-certified pathologists.

The robots are coming – for jobs. This is the plain, cold, hard fact we now face as we head towards the third decade of the 21st Century. The technology-driven world in which we now live is one filled with promise – cars that drive themselves, algorithms that respond to customer service inquiries, automated business intelligence on tap. Yet, this brave new world is also filled with challenges. For even as AI and automation increase productivity and improve our lives, their widespread adoption means that many work activities humans currently perform will soon be displaced – if they haven't been already. What this doesn't mean, however, is that there will be a shortage of jobs in the future.