11 Quotes About AI That'll Make You Think

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We hear a lot about AI and its transformative potential. What that means for the future of humanity, however, is not altogether clear. Some futurists believe life will be improved, while others think it is under serious threat. Here's a range of takes from 11 experts. Join nearly 200,000 subscribers who receive actionable tech insights from Techopedia.


How can attackers abuse artificial intelligence? - Help Net Security

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Artificial intelligence (AI) is rapidly finding applications in nearly every walk of life. Self-driving cars, social media networks, cybersecurity companies, and everything in between uses it. But a new report published by the SHERPA consortium – an EU project studying the impact of AI on ethics and human rights – finds that while human attackers have access to machine learning techniques, they currently focus most of their efforts on manipulating existing AI systems for malicious purposes instead of creating new attacks that would use machine learning. The study's primary focus is on how malicious actors can abuse AI, machine learning, and smart information systems. The researchers identify a variety of potentially malicious uses for AI that are well within reach of today's attackers, including the creation of sophisticated disinformation and social engineering campaigns.


Dealing with categorical features in machine learning

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Categorical data are commonplace in many Data Science and Machine Learning problems but are usually more challenging to deal with than numerical data. In particular, many machine learning algorithms require that their input is numerical and therefore categorical features must be transformed into numerical features before we can use any of these algorithms. One of the most common ways to make this transformation is to one-hot encode the categorical features, especially when there does not exist a natural ordering between the categories (e.g. a feature'City' with names of cities such as'London', 'Lisbon', 'Berlin', etc.). Even though this type of encoding is used very frequently, it can be frustrating to try to implement it using scikit-learn in Python, as there isn't currently a simple transformer to apply, especially if you want to use it as a step of your machine learning pipeline. In this post, I'm going to describe how you can still implement it using only scikit-learn and pandas (but with a bit of effort).


Researchers' deep learning algorithm solves Rubik's Cube faster than any human

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Since its invention by a Hungarian architect in 1974, the Rubik's Cube has furrowed the brows of many who have tried to solve it, but the 3-D logic puzzle is no match for an artificial intelligence system created by researchers at the University of California, Irvine. DeepCubeA, a deep reinforcement learning algorithm programmed by UCI computer scientists and mathematicians, can find the solution in a fraction of a second, without any specific domain knowledge or in-game coaching from humans. This is no simple task considering that the cube has completion paths numbering in the billions but only one goal state--each of six sides displaying a solid color--which apparently can't be found through random moves. For a study published today in Nature Machine Intelligence, the researchers demonstrated that DeepCubeA solved 100 percent of all test configurations, finding the shortest path to the goal state about 60 percent of the time. The algorithm also works on other combinatorial games such as the sliding tile puzzle, Lights Out and Sokoban.


Grant Thornton collaborates with Microsoft and Hitachi Solutions

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CHICAGO -- Grant Thornton LLP is collaborating with Microsoft and Hitachi Solutions to turn information into foresight. The collaboration uses artificial intelligence (AI) and machine learning (ML) to help Grant Thornton identify its clients' nascent business needs. Grant Thornton can then design solutions to address its clients' challenges before they balloon. As one of the nation's largest accounting, tax and consulting firms, Grant Thornton works with clients to overcome all manner of hurdles, from financial and operational to technological and risk-related. "We focus on staying ahead of our clients' needs," explains Nichole Jordan, Grant Thornton's national managing partner of Markets, Clients and Industry.


TTEC Recognized for Use of AI, Machine Learning and Digital Innovation in Learning and Development, Earns LearningElite Silver Award

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TTEC Holdings, Inc. (NASDAQ: TTEC), a leading digital global customer experience (CX) technology and services company focused on the design, implementation and delivery of transformative customer experience, engagement and growth solutions, has recently been recognized by Chief Learning Officer magazine as a 2019 LearningElite Silver Award winner. This robust, peer-reviewed ranking and benchmarking program recognizes those organizations that employ exemplary workforce development strategies that deliver significant business results. Special emphasis was placed this year on how these learning teams are helping their organizations adapt to and prepare for change. Winners were recently announced during the ninth annual LearningElite Awards program at the CLO Symposium conference. "TTEC is honored to be recognized as an elite learning organization and appreciates this award from Chief Learning Officer," said Steve Pollema, Executive Vice President, TTEC Digital.


Artificial Intelligence Market by Technology, Infrastructure, Components, Devices, Solutions, and Industry Verticals 2019 – 2024

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Artificial Intelligence (AI) represents a combination of various technologies including Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Speech Recognition, Context Aware Processing, Neural Network, and Predictive APIs. AI will be found in virtually everything, ranging from individual products and applications to wide spread systems and networks. Network infrastructure and computing equipment will rely upon AI algorithms for decision making while at the device level AI will be built into electronics at the chipset level. This report provides a multi-dimensional view into the AI market including analysis of embedded devices and components, embedded software, and AI platforms. This research also assesses the combined Artificial Intelligence (AI) marketplace including embedded IoT and non-IoT devices, embedded components (including AI chipsets), embedded software and AI platforms, and related services.


AI solves Rubik's Cube in fraction of a second - smashing human record

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The human record for solving a Rubik's Cube has been smashed by an artificial intelligence. The bot, called DeepCubeA, completed the popular puzzle in a fraction of a second - much faster than the quickest humans. While algorithms have previously been developed specifically to solve the Rubik's Cube, this is the first time it has done without any specific domain knowledge or in-game coaching from humans. It brings researchers a step closer to creating an advanced AI system that can think like a human. "The solution to the Rubik's Cube involves more symbolic, mathematical and abstract thinking," said senior author Professor Pierre Baldi, a computer scientist at the University of California, Irvine.


Machine Learning in Java - Programmer Books

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As the amount of data continues to grow at an almost incomprehensible rate, being able to understand and process data is becoming a key differentiator for competitive organizations. Machine learning applications are everywhere, from self-driving cars, spam detection, document search, and trading strategies, to speech recognition. This makes machine learning well-suited to the present-day era of Big Data and Data Science. The main challenge is how to transform data into actionable knowledge. Machine Learning in Java will provide you with the techniques and tools you need to quickly gain insight from complex data.


Elon Musk's Neuralink looks to begin outfitting human brains with faster input and output starting next year – TechCrunch

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Neuralink, the Elon Musk-led startup that the multi-entrepreneur founded in 2017, is working on technology that's based around'threads' which it says can be implanted in human brains with much less potential impact to the surrounding brain tissue vs. what's currently used for today's brain-computer interfaces. "Most people don't realize, we can solve that with a chip," Musk said to kick off Neuralink's event, talking about some of the brain disorders and issues the company hopes to solve. Musk also said that long-term Neuralink really is about figuring out a way to "achieve a sort of symbiosis with artificial intelligence." "This is not a mandatory thing," he added. "This is something you can choose to have if you want."