What would a theory of artificial intelligence look like, and how might it be achieved? When designing a new engine or airplane wing, engineers can apply theories that have withstood years of scientific scrutiny, such as the Laws of Thermodynamics or Newton's Laws of Motion. To what theories --if any --can artificial intelligence (AI) researchers and technology pioneers turn when designing neural networks or algorithms? We asked experts from the fields of computer science, theoretical physics, and philosophy for their insights. The Encyclopedia Britannia defines a scientific theory as a "systematic ideational structure of broad scope, conceived by the human imagination, that encompasses a family of empirical (experiential) laws regarding regularities existing in objects and events, both observed and posited."

The advent of general adversarial networks (GANs) has led to increased popularity and adoption of artificial intelligence in the art world. It has been quite a few years since researchers have been trying to infuse the artistic skills into AI and there have been many interesting developments since then. Artists such as Mario Klingemann, Anna Ridler and many others have been at the forefront of this new-age GAN-powered art. Not only is AI creating breathtaking artwork but it is also being sold at auctions for hefty amounts. For instance, Canadian-Mexican artist Rafael Lozano-Hemmer has already made around $600,000 for an AI artwork.

China's rapidly growing tech economy is now facing some serious questions about the trade-offs involved in the widespread adoption of emerging technologies such as AI. In fact, China's Ministry of Science and Technology is now leading the debate over the relative benefits and drawbacks of artificial intelligence, with at least some recognition that certain AI applications – such as facial recognition technology – might have some very negative implications for personal privacy. At the same time, other regulatory authorities within China – including the Cyberspace Administration of China – are now taking a closer look at how popular consumer technologies (including mobile apps) might also be going too far when it comes to collecting, using and sharing user data. For now, the most high-profile emerging technology within China is artificial intelligence (AI), which is being embraced much more quickly and widely than in the West. For example, Chinese law enforcement authorities are using AI-powered facial recognition technologies to crack down on crime and terrorism, while urban planners and other policymakers are embracing AI as a way to come up with more efficient healthcare, education and transportation solutions.

Construction is one of the most challenging sectors for artificial intelligence and robotics. When it comes to manual skills and holistic thinking, no advanced technology can hold a candle to human labor. So far, we have seen a robot putting up a wall, the various uses of augmented and virtual reality (AR/VR) and AI systems performing repetitive tasks in the construction industry that people no longer want to do. While the concepts of work and tasks for people have changed with Industry 4.0, by 2050, it is estimated that two-thirds of the world's population will live in cities, which means new cities, more housing and more roads. To meet this demand, the construction sector needs to build around 13,000 homes every day worldwide.

Genpact's study, Commercial Banking: The Customer Experience Imperative, surveyed 500 senior commercial banking executives on the industry's changing landscape. The research reveals that while many banks understand the growing importance of CX and AI, questions remain regarding their ability to use AI for greater value and mine data effectively to embrace digital transformation and enhance service. The good news is most banks are optimistic about the future. Two-thirds of respondents say they expect to use AI across their organization in the next 12 to 18 months, compared with fewer than one in five today. Yet, some executives surveyed seem hesitant about whether AI will deliver on its promises to drive new personalized services to improve customer experience.

Buildings under construction are a maze of half-completed structures, gantries, stacked materials, and busy workers -- tracking what's going on can be a nightmare. Scaled Robotics has designed a robot that can navigate this chaos and produce 3D progress maps in minutes, precise enough to detect that a beam is just a centimeter or two off. Bottlenecks in construction aren't limited to manpower and materials. Understanding exactly what's been done and what needs doing is a critical part of completing a project in good time, but it's the kind of painstaking work that requires special training and equipment. Or, as Scaled Robotics showed today at TC Disrupt Berlin 2019, specially trained equipment.

GUWAHATI: Indian Institute of Technology (IIT) Guwahati launched the Samsung Digital Academy Programme by inaugurating the Samsung Digital Academy at the campus. The 14-week long course will be taught through classroom lectures, assignments and lab room sessions, self-study and mini-projects. Extensive tutorials and approach documents will also be provided to students to facilitate practical exercises. The curriculum at the Samsung Innovation Lab at IIT Guwahati will include Internet of Things (IoT), Embedded Systems (ES), Artificial Intelligence (AI) and Machine Learning (ML). The students will be trained on these industry-relevant skills in order to make them job-ready.

This is a 30 minute talk from GOTO Copenhagen 2019 by Feynman Liang - Creator of BachBot. I've dropped the full talk abstract below for a read before diving into the talk: Can musical creativity, something believed to be deeply human, be codified into an algorithm? While most music theorists are hesitant to claim a "correct" algorithm for composing music like Bach, recent advances in machine learning and computational musicology may help us reach an answer. In this talk, we describe BachBot: an artificial intelligence which uses deep learning and long short term memory (LSTM) to compose music in the style of Bach. We train BachBot on all known Bach chorale harmonisations and carry out the largest musical Turing test to date.

Computer vision models have learned to identify objects in photos so accurately that some can outperform humans on some datasets. But when those same object detectors are turned loose in the real world, their performance noticeably drops, creating reliability concerns for self-driving cars and other safety-critical systems that use machine vision. In an effort to close this performance gap, a team of MIT and IBM researchers set out to create a very different kind of object-recognition dataset. It's called ObjectNet, a play on ImageNet, the crowdsourced database of photos responsible for launching much of the modern boom in artificial intelligence. Unlike ImageNet, which features photos taken from Flickr and other social media sites, ObjectNet features photos taken by paid freelancers.

Whether it be on vacation, at work or at home, we humans in general live comfortable lives. Compared to only one century ago (in contrast to around 200,000 years of existence of homo sapiens) we have much less need for physical labour to sustain life. We have shelter, a soft bed, central heating and a shower. Our food is grown, distributed and cooked using lots of automation. We also have mobile phones.