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How the Enlightenment Ends

Heretofore confined to specific fields of activity, AI research now seeks to bring about a “generally intelligent” AI capable of executing tasks in multiple fields. A growing percentage of human activity will, within a measurable time period, be driven by AI algorithms. But these algorithms, being mathematical interpretations of observed data, do not explain the underlying reality that produces them. Paradoxically, as the world becomes more transparent, it will also become increasingly mysterious. What will distinguish that new world from the one we have known? How will we live in it? Artificial intelligence will in time bring extraordinary benefits to medical science, clean-energy provision, environmental issues, and many other areas. First, that AI may achieve unintended results. Second, that in achieving intended goals, AI may change human thought processes and human values. First, that AI may achieve unintended results.

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Personal Robots Group “The Huggable”: Static Display of V2 Huggable Prototype. Star Wars Where Science Meets Imagination. International Touring Exhibit, 2008. “The Huggable”: Interactive Demonstration of Third Generation Prototype at the San Raffaele Del Monte Tabor Foundation (HSR), Milan, Italy, May 6-7, 2008. Machine Learning Part 5: Underfitting and Overfitting Problems - Chun’s Machine Learning Page Here we are again, in the fifth post of Machine Learning tutorial series. Today I will talk about two common problems you may face in Machine Learning: Underfitting and Overfitting. Wait! There is something wrong, isn’t it? - You may wonder…

Low-cost USB Rubber Ducky pen-test tool for $3 using Digispark and Duck2Spark It’s a story as old as time: some hacker sees nice hardware pen-testing tool, hacker recoils in horror at the price of said tool, hacker builds their own version for a fraction of the price. An example of this is Rubber Ducky, an excellent Hak5 hacking tool that thanks to the work of several developers we can emulate using a small and cheap Digispark. An advantage of cheap hardware from generic off the shelf parts is that it is disposable and almost impossible to trace. The USB Rubber Ducky is a keystroke injection tool disguised as a generic flash drive. Computers recognize it as a regular keyboard and automatically accept its pre-programmed keystroke payloads at over 1000 words per minute.

Overfitting in Machine Learning: What It Is and How to Prevent It Did you know that there’s one mistake… …that thousands of data science beginners unknowingly commit? And that this mistake can single-handedly ruin your machine learning model? Free: Data Science Career Guide Learn how to land a high-paying job in data science and future-proof your career with the most efficient roadmap to learning DS & ML for busy professionals. No, that’s not an exaggeration.

Interactive drama, art and artificial intelligence Artificial intelligence methods open up new possibilities in art and entertainment, enabling rich and deeply interactive experiences. At the same time as AI opens up new fields of artistic expression, AI-based art itself becomes a fundamental research agenda, posing and answering novel research questions that would not be raised unless doing AI research in the context of art and entertainment. I call this agenda, in which AI research and art mutually inform each other, . Expressive AI takes seriously the problem of building intelligences that robustly function outside of the lab, engaging human participants in intellectually and aesthetically satisfying interactions, which, hopefully, teach us something about ourselves. This thesis describes a specific AI-based art piece, an interactive drama called , and describes the practice of Expressive AI, using , as well as additional AI-based artwork described in the appendices, as case studies.

Python Machine Learning Tutorial, Scikit-Learn: Wine Snob Edition In this end-to-end Python machine learning tutorial, you’ll learn how to use Scikit-Learn to build and tune a supervised learning model! We’ll be training and tuning a random forest for wine quality (as judged by wine snobs experts) based on traits like acidity, residual sugar, and alcohol concentration. Before we start, we should state that this guide is meant for beginners who are interested in applied machine learning. Can we ever build a robot with empathy? At this year’s International Consumer Electronics Show, we started to see consumer-grade robots – machines that can fly up to take your picture, clean your floor and even wink or hold a conversation. Japanese company SoftBank is unveiling a robot that can tell a joke and converse in four languages. By now we are all used to talking to our smartphones; the message of the electronics show seemed to be that the market is finally ready for intelligent machines. Then came ominous warnings from two famous thinkers. Stephen Hawking warned that “the development of full artificial intelligence could spell the end of the human race”, while AI investor Elon Musk proclaimed: “Artificial intelligence is our biggest existential threat.”

Preparing Your Dataset for Machine Learning: 8 Steps Reading time: 10 minutes There’s a good story about bad data told by Martin Goodson, a data science consultant. A healthcare project was aimed to cut costs in the treatment of patients with pneumonia. What human emotions do we really want of artificial intelligence? Forget the Turing and Lovelace tests on artificial intelligence: I want to see a robot pass the Frampton Test. Let me explain why rock legend Peter Frampton enters the debate on AI. For many centuries, much thought was given to what distinguishes humans from animals. These days thoughts turn to what distinguishes humans from machines.

5 common mistakes to avoid when de-duping your data Data is power and with that power comes great responsibility. One of the biggest obstacles in data is identifying duplicates and de-duping. The aim of data-deduplication is to eliminate any redundant data in your business. Duplicates are created in all areas of your business such as the sales rep inputting a new record without checking the database first, a marketer uploading a list of potential buyers without checking if the record exists and a customer who inputs their information again as they forgot they have an account with you already. Data deduplication ensures proper data management of such records, reduced data storage, more effective marketing communications, and better predictive analysis. Duplicate records can actually can a huge impact on machine learning and data science records by theoretically giving customers two times the predictive power and therefore create a bias in the outputs.