The International Conference on Machine Learning (ICML) 2018 will be held July 10–15 in Stockholm, Sweden. Yesterday, from more than 600 accepted papers, the prestigious conference announced its Best Paper Awards. Two papers shared top honours. Researchers Anish Athalye of MIT and Nicholas Carlini and David Wagner of UC Berkeley's Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples; and Delayed Impact of Fair Machine Learning, from a UC Berkeley research group led by Lydia T. Liu and Sarah Dean. The Best Paper Runner Up Awards go to Near Optimal Frequent Directions for Sketching Dense and Sparse Matrices, from Professor Zengfeng Huang of Fudan University; The Mechanics of n-Player Differentiable Games from DeepMind and University of Oxford's David Balduzzi and Sebastien Racaiere, James Martens, Jakob Foerster, Karl Tuyls and Thore Graepel; and Fairness Without Demographics in Repeated Loss Minimization, from a Stanford research group including Tatsunori B. Hashimoto, Megha Srivastava, Hongseok Namkoong, and Percy Liang.

Honor, a leading smartphone e-brand under the Huawei Group signed up to work with Central Saint Martins (CSM) students to explore the concept of colour and its emotional significance within the history of design, as well as the relationship between art, design and technological innovation. Collaborating to find beauty in Artificial Intelligence (AI), selected CSM students are to be awarded the Honor Art prize, which is an award given for a piece of final degree work that celebrates the innovative use of colour and technology in artistic practice. This year, the inaugural prize was awarded to MA Fine Art student Marco Pantaleoni for his series of works in 3D scanning, photography and painting. Receiving his award, Marco said: "I feel honoured to be awarded this prize. Technology is an essential part of my practice, so to be recognised by a technology brand like Honor, not only reinforces some of the concepts behind my work, it also really resonates with the way I create."

Psychology and neuroscience have played a key role in the history of AI and this is central to Starmind's activities. The new desktop app consolidates and improves upon Starmind's features, allowing ease of access without a web portal, pop-up notifications when an expert answers a question, and a more seamless UI. Starmind facilitates collaboration throughout large companies by using AI to learn who in a given company is an expert on a given topic, then matching employees with questions/problems to the relevant experts. To understand the basics of neuroscientific artificial intelligence and the Starmind application, Digital Journal caught up with Peter Wasser, the company's CEO. Digital Journal: How important is artificial intelligence to the modern company?

Sheng Wang is the chief technology officer at AutoGravity, a financial technology company in Irvine.AG AutoGravity is changing the way you purchase cars, and Sheng Wang is leading the way. As chief technology officer, Wang's aggressive use of data and focus on customer experience is allowing this startup to leave a mark on an industry that has left women out of the equation for far too long. In just four steps, Autogravity finds up to four options for financing before you go to the dealership. Wang spent a lot of her career in product management learning how to solve business problems and listening to customer needs, but her early years of coding made taking the position of CTO easy. "I think my dream is always to build a product that can change some part of a person's life," Wang said.

Boris Ladwig is a reporter with more than 20 years of experience and has won awards from multiple journalism organizations in Indiana and Kentucky for feature series, news, First Amendment/community affairs, nondeadline news, criminal justice, business and investigative reporting. As part of The (Columbus, Indiana) Republic's staff, he also won the Kent Cooper award, the top honor given by the Associated Press Managing Editors for the best overall news writing in the state. A graduate of Indiana State University, he is a soccer aficionado (Borussia Dortmund and 1. FC Köln), singer and travel enthusiast who has visited countries on five continents. He speaks fluent German, rudimentary French and bits of Spanish, Italian, Khmer and Mandarin.

Better Life Lab is a partnership of Slate and New America. In an age where every day brings more doomsday forecasts of massive technologicallybdriven unemployment, from driverless cars to A.I. robots as caregivers, journalist Annie Lowrey set out to answer a question: Is it possible to live in a world where we get what she calls "wages for breathing"? This week her findings come out in Give People Money: How a Universal Basic Income Would End Poverty, Revolutionize Work, and Remake the World. We spoke about what the idea of giving every American cash--no strings attached--would mean for work, gender inequality, and American identity, and whether it's actually a policy that could pass in the U.S. given the current climate of tying even the most basic benefits to paid work. This interview has been condensed and edited for clarity.

Humans use signs, e.g., sentences in a spoken language, for communication and thought. Hence, symbol systems like language are crucial for our communication with other agents and adaptation to our real-world environment. The symbol systems we use in our human society adaptively and dynamically change over time. In the context of artificial intelligence (AI) and cognitive systems, the symbol grounding problem has been regarded as one of the central problems related to {\it symbols}. However, the symbol grounding problem was originally posed to connect symbolic AI and sensorimotor information and did not consider many interdisciplinary phenomena in human communication and dynamic symbol systems in our society, which semiotics considered. In this paper, we focus on the symbol emergence problem, addressing not only cognitive dynamics but also the dynamics of symbol systems in society, rather than the symbol grounding problem. We first introduce the notion of a symbol in semiotics from the humanities, to leave the very narrow idea of symbols in symbolic AI. Furthermore, over the years, it became more and more clear that symbol emergence has to be regarded as a multifaceted problem. Therefore, secondly, we review the history of the symbol emergence problem in different fields, including both biological and artificial systems, showing their mutual relations. We summarize the discussion and provide an integrative viewpoint and comprehensive overview of symbol emergence in cognitive systems. Additionally, we describe the challenges facing the creation of cognitive systems that can be part of symbol emergence systems.

We're always impressed by the way David Zarrouk (a professor at Ben-Gurion University of the Negev by way of UC Berkeley's Biomimetic Millisystems Lab) manages to extract a ton of functionality from the absolute minimum of hardware in his robots. In the past, we've seen clever designs like a steerable robot that only uses a single motor, and a multi-jointed robot arm that uses a traveling motor to actuate all of its degrees of freedom. At the 2018 IEEE International Conference on Robotics and Automation (ICRA) in Brisbane, Zarrouk presented an update to STAR, the Sprawl-Tuned Autonomous Robot that we first wrote about in 2013. Called Rising STAR, or RSTAR, it takes the sprawling wheel-leg mobility and adds another degree of freedom that allows the body of the robot to move separately from the legs, changing its center of mass to help it climb over obstacles. RSTAR is the latest in Zarrouk's series of sprawling robots, designed to handle all kinds of terrain obstacles while minimizing cost of transport.

This is going to be an extensive article on my case on why CPC is a golden investment opportunity at the moment and why I think it is extremely undervalued. In my opinion, an increase of 50-100x by the end of the year, especially if you get in now, is not impossible. There are multiple factors to why CPC is going to be a golden investment, everything from its technology, its team, the market they are targeting and the fact that it is not yet known by many people - so if you are interested, spend a couple of minutes and delve into the case on why CPC will be one of the top gainers 2018. Cyber-Physical Chain (CPChain) connects blockchain with IOT to enhance the distributed systems in that realm. This technology has multiple advantages, firstly it will reduce the cost of interconnected systems, increase the value of data sharing, and enhance security and data sharing. The problem that CPC solves is the scalability issues along with the security and real-time issues of the current IOT. By combining the three technologies: blockchain, Internet of Things and distributed encryption storage and computing, it builds a new generation of Internet of Things, which can provide entire solutions for data acquisition, sharing and application in IoT industry. CPC also incorporates AI(Artificial intelligence) to establish data interconnection and solves many hard points in the industry.

Francois is not only the creator of the Keras deep learning library, but he's also a Google AI researcher. He will also be speaking at PyImageConf 2018 in August of this year. Please, join me in welcoming Francois to the PyImageSearch -- it is truthfully a privilege to have him here. I know you are very busy with your work at Google AI and on the Keras library -- I really appreciate you taking the time to do this interview. It's quite the honor to have you on the PyImageSearch blog! For people who don't know you, who are you and what do you do?