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This Research Startup Raises $13.1M in Funding to Give Doctors Access to An Unprecedented Amount of Medical Knowledge

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The advent of machine learning has provided the healthcare industry with an unprecedented increase in knowledge. Data-driven databases now enable doctors to give patients accurate diagnosis earlier on that ever before. OWKIN is a machine learning platform for medical research. The company hopes that its predictive analysis platform will enable doctors to effectively understand patient and tumor heterogeneity. AlleyWatch spoke with Cofounder and CEO Thomas Clozel to learn about the company's latest technological advancements in medical research and its latest round of funding, which brings the total funding raised to $18M over two funding rounds for the startup founded in the fall of 2016.


Afghanistan president says U.S. drone killed Taliban chief Maulana Fazlullah, wanted over 2012 Malala Yousafzai shooting attack

The Japan Times

KABUL – President Ashraf Ghani confirmed Friday that Pakistani Taliban chief Maulana Fazlullah has been killed in a U.S. drone strike. Fazlullah is believed to have ordered the failed 2012 assassination of Malala Yousafzai, who became a global symbol of the fight for girls' rights to schooling, and who later won the Nobel Peace Prize. U.S. forces targeted Fazlullah in a counterterrorism strike Thursday in eastern Kunar province, close to the border between Afghanistan and Pakistan, U.S. officials said, without confirming his death. "I spoke with Prime Minister of #Pakistan Nasir ul Mulk and Chief of Army Staff General Qamar Javed Bajwa and confirmed the death of Mullah Fazlullah," Ghani tweeted, adding: "His death is the result of tireless human intel led by #Afghan security agencies." Ghani added the Pakistani leaders had assured him the strike was "a great step toward building trust between the two nations," while urging them to "bring (the) Afghan Taliban residing in Pakistan to the negotiation table."


Top 10 Machine Learning Researchers In India

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Much of his work is directed toward understanding interactions and learning from them. Ravindran is also a co-organiser of several noted data science and AI-focused conferences, seminars and workshops in India. Bidyut Baran Chaudhuri is the founding head of Computer Vision and Pattern Recognition Unit at ISI, Calcutta.


Playing with dimensions: from Clustering, PCA, t-SNE... to Carl Sagan!

#artificialintelligence

This post is an experiment combining the result of t-SNE with two well known clustering techniques: k-means and hierarchical. This will be the practical section, in R. But also, this post will explore the intersection point of concepts like dimension reduction, clustering analysis, data preparation, PCA, HDBSCAN, k-NN, SOM, deep learning...and Carl Sagan! For those who don't know t-SNE technique (official site), it's a projection technique -or dimension reduction- similar in some aspects to Principal Component Analysis (PCA), used to visualize N variables into 2 (for example). When the t-SNE output is poor Laurens van der Maaten (t-SNE's author) says: As a sanity check, try running PCA on your data to reduce it to two dimensions.


SAPVoice: Your Mercedes-Benz Dream Car Is One Machine Learning Algorithm Away

Forbes - Tech

There's a supremely easy way to find the Mercedes-Benz of your dreams on the horizon, and I watched its premiere at the SAPPHIRE NOW 2018 event. Called the car detection app, this working prototype was a pitch perfect reflection of Daimler's evolution of the iconic Mercedes-Benz brand for a digital-first customer experience. I caught up with Robert Kriehs, Senior Solution Architect at Daimler, who shared the entire back story. "Whether someone is a first-time or long-time Mercedes-Benz customer, we want to provide them with a completely digital sales experience," said Kriehs. "We've already connected our customers with Mercedes me services using social media and mobile. Machine learning is the next innovation, meeting a new generation of drivers where they live, work and play with personalized, immediate services."


US drone strike kills Pakistani Taliban leader who ordered Malala Yousafzai assassination, Afghanistan says

FOX News

Nov. 7, 2013: Pakistani Taliban leader Mullah Fazlullah is seen on television at a coffee shop in Islamabad. The Pakistani Taliban leader known for beheading police officers and even ordering the assassination of Nobel Peace Prize winner Malala Yousafzai has been killed by a U.S. drone strike, Afghanistan's Defense Ministry says. Mohammad Radmanish told the Associated Press on Friday that Mullah Fazlullah, the ruthless insurgent leader, died along with two other terrorists a day earlier in the Marawara district along the Afghanistan-Pakistan border. A statement attributed to U.S. Forces-Afghanistan spokesman Lt. Col Martin O'Donnell said an American "counterterrorism strike" was carried out in the region targeting "a senior leader of a designated terrorist organization," but did not say whether it had killed anyone. Fazlullah previously ordered the bombing and beheadings of dozens of opponents when his band of insurgents controlled Pakistan's picturesque Swat Valley from 2007 until a massive military operation routed them in 2009.


Four Reasons Why Machines Will Always Need A Human

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Elizabeth Holm, a professor of materials science and engineering at the College of Engineering at Carnegie Mellon University and a computational materials scientist at Sandia National Laboratories says we're in the midst of an artificial intelligence (AI) culture shift. She also says that machines won't replace human experts. "Machines are great at handling things, like large amounts of data, but machines still need an expert, a human, to analyze the data, set parameters and guide decisions," said Holm. "Engineering and science decisions are based on understanding how things work. How does a bridge support its load? How does an engine convert fuel into motion? In contrast, AI transforms data into decisions without understanding any underlying principles," said Holm. "Applying AI to engineering and science will require a culture shift: either we will learn to trust decisions that we do not understand, or AIs will evolve to base their decisions on principles that humans can interpret and control."


AI: The 'Antidote' For What's Ailing Marketing?

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Iskender Dirik, CEO of Microsoft ScaleUp in Berlin, is tasked with nurturing continental Europe's best startups. He is also a venture partner at EQT Ventures, one of the largest venture capital funds in Europe. In addition, this tech trailblazer and AI enthusiast has founded several startups, built up big data and machine-learning technologies for large corporations, and advised Germany's DAX companies in the field of online marketing. In this interview with CMO.com, Dirik discusses some business issues he expects AI to solve, how AI will be a job creator, and a trio of other emerging technologies he's watching closely. CMO.com: Iskender, you published an infographic entitled "The Future of AI Transformed Marketing" (PDF).


Eight ways the Internet of Things will change the way we live and work

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IBM's Almaden lab is sacred ground for techies. Set in the middle of 700 grassy acres on a hill south of San Jose, its scientists have filed thousands of patents. They've won Turing and Nobel prizes. And almost 60 years ago, they pioneered the first bulky disk drive. Since then, they've been involved in successive pushes to miniaturize it and miniaturize it again, so that now even the tiniest of devices can gather and store data.


DRE-Bot: A Hierarchical First Person Shooter Bot Using Multiple Sarsa({\lambda}) Reinforcement Learners

arXiv.org Artificial Intelligence

This paper describes an architecture for controlling non-player characters (NPC) in the First Person Shooter (FPS) game Unreal Tournament 2004. Specifically, the DRE-Bot architecture is made up of three reinforcement learners, Danger, Replenish and Explore, which use the tabular Sarsa({\lambda}) algorithm. This algorithm enables the NPC to learn through trial and error building up experience over time in an approach inspired by human learning. Experimentation is carried to measure the performance of DRE-Bot when competing against fixed strategy bots that ship with the game. The discount parameter, {\gamma}, and the trace parameter, {\lambda}, are also varied to see if their values have an effect on the performance.