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Is the artificial intelligence we see in science fiction movies at all realistic? Many tech industry experts believe the idea of a superintelligent or sentient AI is greatly exaggerated and many years away. But there's AI already in the works to help solve real-world problems that can improve people's lives.

The academic publisher Springer Nature published the book, which is titled "Lithium-Ion Batteries: A Machine-Generated Summary of Current Research." The document summarizes peer-reviewed papers on lithium-ion batteries, with quotations, hyperlinks, and automatically generated references. Below is the introduction of the book and link to download. 

Introduction
This is the first machine-generated scientific book in chemistry published by Springer Nature. Serving as an innovative prototype defining the current status of the technology, it also provides an overview about the latest trends of lithium-ion batteries research.

This book explores future ways of informing researchers and professionals. State-of-the-art computer algorithms were applied to: select relevant sources from Springer Nature publications, arrange these in a topical order, and provide succinct summaries of these articles. The result is a cross-corpora auto-summarization of current texts, organized by means of a similarity-based clustering routine in coherent chapters and sections.

This book summarizes more than 150 research articles published from 2016 to 2018 and provides an informative and concise overview of recent research into anode and cathode materials as well as further aspects such as separators, polymer electrolytes, thermal behavior and modelling.

With this prototype, Springer Nature has begun an innovative journey to explore the field of machine-generated content and to find answers to the manifold questions on this fascinating topic. Therefore it was intentionally decided not to manually polish or copy-edit any of the texts so as to highlight the current status and remaining boundaries of machine-generated content.

Our goal is to initiate a broad discussion, together with the research community and domain experts, about the future opportunities, challenges and limitations of this technology.

1. DeepMind: DeepMind has trained an artificial intelligence system how to predict the energy output of Google wind farms in the U.S. The variable nature of wind makes it difficult to accurately predict how much energy a wind farm could produce in any given time period. However, DeepMind’ AI system, a neural network trained on widely available weather forecasts and historical turbine data, can predict wind power output 36 hours ahead of the actual generation with a reasonable degree of accuracy.

2. Seimens: Autonomous smart grid: Smart grid that contains many adjustable components already play an essential role in the transition to renewable energy sources. Software from Seimens can operate these grids autonomously with maximum efficiency. Also, deep neural network based reinforcement learning methods are emerging and gain popularity for smart grid application.

3. SparkCognition: SparkCognition is an Austin AI startup. SparkCognition leverages excellent deep learning and machine learning techniques to provide predictive maintenance capabilities. SparkCognition’s AI platform learns from data to understand operational states and failure modes of assets and uses this intelligence to warn of impending asset failures.

4. Google Sunroof: Google Sunroof project uses deep learning and machine learning to calculate how much sunlight your rooftop receives and how many solar panels you can have on your rooftop. In this way, users can save lots of money.

5. Chevron: Chevron led an effort to employ deep neural networks and fuzzy kriging (a numerical method applied to imperfect data) to analyze the viability of a reservoir in California’s San Joaquin Valley in 2016. This site proved a good candidate for the experimental approach because of the complexity of the geological features.

This conference brings together the brightest and most experienced professionals in the field of AI for an immersive day of learning, discussion, and connection. This year’s agenda will focus on current and future impacts of AI applications and commercialization on enterprise, government, and society.   

We invite world class perspectives from research, entrepreneurship, investing, and business transformation, and the event aims to capture the deepest insights available within the AI ecosystem today. The 2019 speaker line up includes Danny Lange, VP of AI and ML at Unity Technologies, Oliver Brdiczka, AI Architect at Adobe, Kay Firth-Butterfield Head of AI and ML at World Economic Forum, and many more.  

Get access to practical wisdom on Applied AI methodologies and take advantage of AI’s powerful potential. Speakers and panelists will engage in thought-provoking discourse about how AI is reshaping life as we know it.  

For a limited time, get 50% off your registration using promo code “AAI1950Percent” when you visit https://www.eventbrite.com/e/bootstraplabs-applied-artificial-intelligence-conference-2019-tickets-50536289402.