Hello! There are two opportunities for anyone near Victoria, British Columbia, to take a continuing studies course from me in the New Year!
- Royal Roads: January 17, 9:00 – 4:30. Click here for more information and to register . This course is for business leaders or others with a stake in the future of an organization. There will be case studies and exercises tailored to futureproofing a business or other type of group.
- University of Victoria: Thursdays, January 16 – Feb 13, 6:30 – 8:30 .Click here for more information and to register . This course is for anyone with an interest in the short- and long-term future of humanity with respect to the effect of artificial intelligence and has a general focus.
Both courses will have practical definitions and explorations of the nature of artificial intelligence (AI). We will look at the effects of its disruption upon a variety of social institutions and sort out the hype from the science. They are essentially interactive, real-time applications of my book.
I’ve presented these courses before to rave reviews. Here are links to flyers for each event: Royal Roads and UVic.
I predicted that mass correlation of scientific papers by AI would happen much sooner than the 20 years that some in the field think it will take. Now read that in the course of a Watson project:
Machine learning software on a laptop can extract the critical information from scientific papers in seconds, enabling the creation of vast knowledge graphs across wide bodies of research in weeks rather than decades.
The world’s largest hedge fund is building a piece of software to automate the day-to-day management of the firm, including hiring, firing and other strategic decision-making.
Yes, it’s hard not to feel apprehension at statements like this:
The kinds of decisions PriOS could make include finding the right staff for particular job openings and ranking opposing perspectives from multiple team members when there’s a disagreement about how to proceed.
The machine will make the decisions, according to a set of principles laid out by Dalio about the company vision.
But the point is not whether or not we should do this. That boat has already sailed. This is happening whether we like it or not. Over a year ago, Gartner predicted that by 2018 25% of employees would report to a “robo-boss.” We are clearly on track for that. Here’s an optimistic take on robo-bosses.
MIT researchers have designed a new machine-learning system that can learn by itself to extract text information for statistical analysis when available data is scarce.
As KurzweilAI.net puts it, “And so it begins…” Here’s a system that can teach itself how to understand a topic by searching the Internet for more information. I know – what could possibly go wrong? Will this be a building block for all kinds of machine learning systems?
See this article about the proliferation of little brothers, corporations that closely monitor their workers as a matter of course, using a variety of new technologies.
If the expansion of corporate oversight continues — specifically in the United States — it will be due to a lack of real opposition. Workers expect to be compensated for producing product, not penalized for producing data, but that could change. There could be a resistance. But someone would have to lead it.
*45* companies are now focused on bringing AI to the retail channel.
Lex Luthor on intelligence: “Some people can read War and Peace and come away thinking it’s a simple adventure story. Others can read the ingredients on a chewing gum wrapper and unlock the secrets of the universe.” Is he on the right track? Is intelligence the ability to draw more conclusions from fewer data?
When I first saw “AI First World” I thought it was making some geographic analogy. Actually it is “AI-first”, as in, migrating from smartphones to AIs. I’m trying to figure out what that means.
I like these predictions from 1900 of life in 2000…not because they’re in the slightest bit accurate, but because they demonstrated the kind of creative thinking that you would need to exercise to conceive of life a hundred years hence. It could not be anything like what life then was like; it could not be predictable. Hence, it was as likely to contain winged firefighters, underwater croquet, and automated concert orchestras as anything else.
Source: CYA “The Web In A Blender”
This summer, a local kids’ art camp even jumped on the AI bandwagon.