Download Artificial Intelligence and Exponential Technologies: by Francesco Corea PDF

By Francesco Corea

Artificial Intelligence is a giant leap forward expertise that's altering our global. It calls for a few levels of technical talents to be constructed and understood, so during this e-book we will to begin with outline AI and categorize it with a non-technical language. we are going to clarify how we reached this section and what traditionally occurred to man made intelligence within the final century. contemporary developments in computing device studying, neuroscience, and synthetic intelligence expertise could be addressed, and new company versions brought for and by means of man made intelligence examine could be analyzed. eventually, we are going to describe the funding panorama, in the course of the relatively finished learn of just about 14,000 AI businesses and we are going to speak about very important beneficial properties and features of either AI traders in addition to investments. this can be the “Internet of Thinks” period. AI is revolutionizing the realm we are living in. it's augmenting the human reports, and it pursuits to enlarge human intelligence in a destiny now not so far away from this day. even though AI can switch our lives, it comes additionally with a few tasks. we have to get thinking about easy methods to accurately layout an AI engine for particular reasons, in addition to the right way to keep watch over it (and might be swap it off if needed). And notably, we have to commence trusting our expertise, and its skill to arrive an efficient and clever decision.

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Extra resources for Artificial Intelligence and Exponential Technologies: Business Models Evolution and New Investment Opportunities

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New types of learning methods are the key. The new incremental learning technique developed by DeepMind called Transfer Learning allows a standard reinforcement-learning system to build on top of knowledge previously acquired— something humans can do effortlessly. MetaMind instead is working toward Multitask Learning, where the same ANN is used to solve different classes of problems and where getting better at a task makes the neural network also better at another. The further advancement MetaMind is introducing is the concept of dynamic memory network (DMN), which can answer questions and deduce logical connections regarding series of statements.

Robotics is going mainstream. I believe that AI development is going to be constrained by advancements in robotics, and I also believe the two connected fields have to go pari passu in order to achieve a proper AGI/ASI. Looking at Fig. 1, it is clear how our research and even collective consciousness would not consider an AI as general or super without having a “physical body”. Other evidence that would confirm this trend are: (i) the recent spike in robotic patent application, which according to IFI Claims reached more than 3000 Fig.

I believe much more has to come, and that emerging markets such as India, Korea, or China will play a fundamental role in AI development. I am also a strong supporter of a centralized funding entity to invest into AI startups: there would be a trade-off between diversification and capital optimal allocation, but I consider the idea of the “AI mega fund” as more attractive and stable to foster and direct all the energies and funding in the right way. © The Author(s) 2017 F.

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