Many of us have, by now, seen a new crop of images online that look not-quite-right, or not quite believable (in the sense of slightly wrong images of famous people doing strange things); and many of us know, or have heard about, the explosion in AI imaging through programs like DALL-E, Midjourney, and an ever-increasing number of others. Some of us have friends or online friends who are producing images that have us intrigued. I have such a friend in Jonathan Hoefler, and as a discussion of the ethics/dangers of AI ensued on one of his Facebook posts (and for the purposes of this article, unless noted otherwise, when I refer to "AI" I am referring specifically to the image-generating form of AI, not the text-generating or any other kind or use), I decided I'd better check it out for myself before arguing either for or against. I was a bit afraid of getting into it because I was worried it might "imagine" better than I do, leaving me feel useless as an artist. I'd also heard it's addictive, and I was worried about that too.

Just last week Rich Sutton published a very short blog post titled The Bitter Lesson. I'm going to try to keep this review shorter than his post. Sutton is well known for his long and sustained contributions to reinforcement learning. In his post he argues, using many good examples, that over the 70 year history of AI, more computation and less built in knowledge has always won out as the best way to build Artificial Intelligence systems. This resonates with a current mode of thinking among many of the newer entrants to AI that it is better to design learning networks and put in massive amounts of computer power, than to try to design a structure for computation that is specialized in any way for the task.

The Robust.AI Grace software combined with a Carter CMR simplifies mobile robot interactions. Robust.AI announced the release of a new autonomous mobile robot software suite called Grace. The software is named in honor of Grace Hopper, who was the first person to devise the theory of machine-independent programming languages, and managed the development of one of the first COBOL compilers, an early high-level programming language still in use today. Much like COBOL, the goal of Grace is to take a leap forward in the development of software for programming robotic solutions and reduce the complexity of robot programming. Grace is designed to be a no-code, modern software solution that runs partially in the cloud and partially on the actual robotic device, in this case an autonomous mobile robot (AMR).

Someday, perhaps, streets and highways will host only fully autonomous vehicles, wirelessly communicating and following algorithms that let them handle any situation they encounter. For now, though, city streets are filled with pedestrians, bicyclists, delivery trucks, double-parked cars, emergency vehicles, and construction crews, as well as human-operated cars with issues of their own. In this chaotic setting, self-driving cars face additional challenges beyond rapidly analyzing the complex environment and navigating through it. They also must keep their distracted occupants informed of issues potentially requiring attention. Equally important, they must continually coordinate their actions with humans, whether in other cars or on the street.

John Brockman: On the Promise and Peril of AI • Seth Lloyd: Wrong, but More Relevant Than Ever • Judea Pearl: The Limitations of Opaque Learning Machines • Stuart Russell: The Purpose Put Into the Machine • George Dyson: The Third Law • Daniel C. Dennett: What Can We Do? • Rodney Brooks: The Inhuman Mess Our Machines Have Gotten Us Into • Frank Wilczek: The Unity of Intelligence • Max Tegmark: Let's Aspire to More Than Making Ourselves Obsolete • Jaan Tallinn: Dissident Messages • Steven Pinker: Tech Prophecy and the Underappreciated Causal Power of Ideas • David Deutsch: Beyond Reward and Punishment • Tom Griffiths: The Artificial Use of Human Beings • Anca Dragan: Putting the Human into the AI Equation • Chris Anderson: Gradient Descent • David Kaiser: "Information" for Wiener, for Shannon, and for Us • Neil Gershenfeld: Scaling • W. Daniel Hillis: The First Machine Intelligences • Venki Ramakrishnan: Will Computers Become Our Overlords?

If you imagine the technologies that will define daily life in 50 years, it's tempting to think of Arthur C. Clarke's dictum that advanced technology is indistinguishable from magic. You might envision the world of 2069 bursting with things we would consider fantastical today. The problem with that is, technologies don't just magically appear. They come from the clever refinement and recombination of previously existing technologies. Even when powerful innovations do arise, it can take decades for them to replace old stuff that works well enough.

When we see some new technology, it's very surprising to us, and we immediately think of how it's going to be used; and we tend to think that it's going to be quite fantastic. But, in the long run, we sort of discount how much it is going to change the world. And I think computers are the prime example of that. If you go back to the late 1950s and early 1960s and look at movies that mention computers, they were all-powerful, going to do everything. So, there were these--built usually using vacuum tubes. They had the computing power of what you would find in a birthday card that plays a tune when you open it.

If you own a Roomba, you can thank Rodney Brooks, because he's the co-founder of iRobot. He launched the company almost three decades ago when he was a professor at MIT. He's trying to disrupt the world of industrial robotics with his new startup, Rethink Robotics. While I was in Boston a few weeks ago, I visited Rod at his home in Cambridge and captured some great stories. His extensive experiences over his career inspired the new company.

As robots become more ubiquitous, the interaction between humans and machines becomes more interesting. Understanding how we as people engage with robots or virtual characters is at the heart of Bruce Blumberg's passion and mission, shaping a career that starts in the earliest days of Apple and NeXT, Inc. and moves on to creating World of Zoo, a video game that ultimately informed the user interface on the earliest collaborative robots. I recently sat down with Bruce to talk about his ideas about the evolving nature of the relationship between human and machine. Q: What did the path you took from leading product marketing and development at Apple and Next, Inc. with Steve Jobs to working on human interaction with autonomous characters look like? Thinking about the work I've done on the whole, I've always been engaged in ways to make the user experience better.

Automatic speech transcription, Self-driving cars, a computer program beating the world champion GO player and computers learning to play video games and achieving better results than humans. Astonishing results that makes you wonder what Artificial Intelligence (AI) can achieve now and in the future. Futurist Ray Kurzweil predicts that by 2029 computers will have human level intelligence and by 2045 computers will be smarter than humans, the so called "Singularity". Some of us are looking forward to that, others think of it as their worst nightmare. In 2015 several top scientists and entrepreneurs called for caution over AI as it could be used to create something that cannot be controlled.