Elon Musk urges the UN to limit AI weapons

Elon Musk has signed his name alongside more than 100 others to ask the UN to regulate the use of autonomous weapons systems. The group of concerned engineers, many of whom are respected in the field of AI, is asking the global body to “protect civilians” from “misuse” of AI-driven weapons. They believe that smart, self-guided kill bots would become the tool of choice for despots and tyrants.

Source: Elon Musk urges the UN to limit AI weapons

What Algorithms Want – Reflecting on (Human) Agency in an Age of Automation / @mitpress

‘How much should we let algorithms shape our lives?’ is the question at the heart of Ed Finn’s recent book “What Algorithms Want: Imagination in the Age of Computing”. Scanning Silicon Valley, computer science, and the cultural sphere alike it offers a smart and accessible reading of our current moment.

Source: What Algorithms Want – Reflecting on (Human) Agency in an Age of Automation / @mitpress

An Engineer’s Guide to the Artificial Intelligence Galaxy | The Fu Foundation School of Engineering & Applied Science – Columbia University

In 10 years, because AI will make so much money for humanity, we will enter the Age of Plenty, making strides to eradicate poverty and hunger, and giving all of us more spare time and freedom to do what we love.

In 10 years, because AI will replace half of human jobs, we will enter the Age of Confusion, and many people will become depressed as they lose the jobs and the corresponding self-actualization. And many of you will become parents concerned with how to improve education in order to prevent your children from being replaced by AI.

Source: An Engineer’s Guide to the Artificial Intelligence Galaxy | The Fu Foundation School of Engineering & Applied Science – Columbia University

Ways in Which Machines Learn – Hacker Noon

There are four major ways to train deep learning networks: supervised, unsupervised, semi-supervised, and reinforcement learning. We’ll explain the intuitions behind each of the these methods. Along the way, we’ll share terms you’ll read in the literature in parentheses and point to more resources for the mathematically inclined. By the way, these categories span both traditional machine learning algorithms and the newer, fancier deep learning algorithms.

Originally published in Andreessen Horowitz’s AI Playbook.

Source: Ways in Which Machines Learn – Hacker Noon

Smart Cities and Artificial Intelligence: Balancing Opportunity and Risk

Steven Hawking recently commented that artificial intelligence (AI) would be “either the best thing or the worst thing ever to happen to humanity”. He was referring to the opportunity that AI offers to improve mankind’s situation, set alongside the risks that it also presents. These same competing possibilities apply no less when AI is considered in the context of smart cities and the planet’s growing urbanization.  With smart cities, though, this is not just some abstract balance: there is a genuine choice of path to be made as smart cities and AI evolve together. This article explores the choice.

Source: Smart Cities and Artificial Intelligence: Balancing Opportunity and Risk