Jeff Hawkins on how brain science will change computing. 10 Important Differences Between Brains and Computers : Developing Intelligence. “A good metaphor is something even the police should keep an eye on.” – G.C. Lichtenberg Although the brain-computer metaphor has served cognitive psychology well, research in cognitive neuroscience has revealed many important differences between brains and computers. Appreciating these differences may be crucial to understanding the mechanisms of neural information processing, and ultimately for the creation of artificial intelligence. Below, I review the most important of these differences (and the consequences to cognitive psychology of failing to recognize them): similar ground is covered in this excellent (though lengthy) lecture.
Difference # 1: Brains are analogue; computers are digital It’s easy to think that neurons are essentially binary, given that they fire an action potential if they reach a certain threshold, and otherwise do not fire. Difference # 2: The brain uses content-addressable memory Difference # 4: Processing speed is not fixed in the brain; there is no system clock. Human Brain's Processing Speed Established. In a new scientific study, which analyzed human reaction times to various events, it was established that the connections inside the human brain only transported about 60 bits of information per second.
The investigation relied on century-old knowledge, which held that the brain's processing speed was intimately related to the amount of time it took for it to complete a task. This duration also reflects the time it takes for the cognitive processes involved in solving a problem to act, Technology Review reports. Reaction times have been a window into the human brain for many years, experts say.One test for reaction times is called a visual lexical decision task. A participant watches a screen, where numerous letters appear. The term entropy is used here to describe the amount of information that is needed so that the state of the entire system can be established. The French expert's method also seems to contradict Hick's Law.
Economists See More Jobs for Machines, Not People. Singularity Hub | The Future Is Here Today…Robotics, Genetics, AI, Longevity, The Brain… Winning the Race With Ever-Smarter Machines. Blog. I’ve been working to draw a graph that compares employment trends since the end of the Great Recession with other important trends in the economy, and also with earlier periods.
Here’s what I’ve come up with (click on the graph for a bigger pdf version, and click here for a spreadsheet with the graph and all its data): Using data from the invaluable online resource FRED (and with the help of an equally critical real-world resource, my RA Noam Bernstein), I’ve plotted the trends since 1995 in US GPD, total corporate investment in equipment, and total corporate profits from non-financial companies (and also for all companies, including financial ones). I set the January 1995 value for each of these equal to 100 to allow comparisons across them over the years.
I also plotted the US employment-population ratio, or percentage of working-age people who have jobs (the axis for this line is on the right-hand side of the graph). Do you agree? Don't Look Now — the Robots Are Gaining. Five Innovations that Could Change the Way We Live, Work and Play To some extent, coverage of robotics is outside the parameters of the mobility beat. But robotics is becoming more real, and traditional mobile devices - cameras, sound equipment and portable computers - are part of the equation. These perambulating devices need to have a way to "see" where they are and report those views - along in most cases with other information - to a central source that most likely still is manned by a human.
The other reason for covering this area is that it is very cool. Check out the videos at The Huffington Post. The top video shows a Defense Advanced Research Project Agency (DARPA) robot that can climb stairs. This is only the latest feat for PETMAN, which has already mastered walking. Last week, Public Radio International (PRI) reported on something of a twist: Robots that are designed to keep humans safe. The robotic work going on now simply is stunning. The Rise of the Artifical-Intelligence Economy - Megan McArdle - Business. Adam Ozimek -- blogger at Modeled Behavior and associate at Econsult Corporation As a child I used to read my grandfather's Popular Science and Popular Mechanics magazines. The constant promise and inevitable disappointment of amazing technologies that mostly never materialized (a problem likely exacerbated by my focus on the amazing and outlandish ones) made me skeptical of futurist predictions.
It is somewhat strange then, that I now commonly find myself a proponent of futurist visions equally as grand as those that once made me a cynic. But I'm not alone in seeing the near future as a quickly changing technological landscape. They present two convincing cases of technology changing quicker than we would have thought. The... truck driver is processing a constant stream of [visual, aural, and tactile] information from his environment. ... Yet despite how difficult this challenge seemed just a few years ago, Google has made astounding headway in building a functioning driverless car.
The Surprising Path Of Artificial Intelligence. Editor’s note: This is Part I of a three-part guest post written by legendary Silicon Valley investor Vinod Khosla, the founder of Khosla Ventures. In Part II, he will describe how software and mobile technologies can augment and even replace doctors. In Part III, he will talk about how technology will sweep through education. Forty years ago this December, President Nixon declared a war on cancer, pledging a “total national commitment” to conquering the disease. Fifty years ago this spring, President Kennedy declared a space race, promising to land a man safely on the moon before the end of the decade.
Though we made it to the moon the efforts in cancer and artificial intelligence have failed in their larger ambitions but have made progress. Rather than the brute force logic-based development that was envisioned with Commander Data, successful systems have been built from examples rather than logical rules. Where will these advances in computing lead us in the next decade? Intro to AI - Accessible Content.
AI Publications. Software agent. In computer science, a software agent is a computer program that acts for a user or other program in a relationship of agency, which derives from the Latin agere (to do): an agreement to act on one's behalf. Such "action on behalf of" implies the authority to decide which, if any, action is appropriate.[1][2] Related and derived concepts include intelligent agents (in particular exhibiting some aspect of artificial intelligence, such as learning and reasoning), autonomous agents (capable of modifying the way in which they achieve their objectives), distributed agents (being executed on physically distinct computers), multi-agent systems (distributed agents that do not have the capabilities to achieve an objective alone and thus must communicate), and mobile agents (agents that can relocate their execution onto different processors).
Concepts[edit] The basic attributes of a software agent are that agents Nwana's Category of Software Agent Distinguishing agents from programs[edit] Intelligent Software Agents: Definitions and Applications. David Wallace Croft Senior Intelligent Systems Engineer Special Projects Division, Information TechnologyAnalytic Services, Inc. (ANSER)croftd@nexos.anser.org Definition: Agent Agent: One that is authorized to act for another. Agents possess the characteristics of delegacy, competency, and amenability. Delegacy: Discretionary authority to autonomously act on behalf of the client.
Actions include making decisions, committing resources, and performing tasks. Competency: The capability to effectively manipulate the problem domain environment to accomplish the prerequisite tasks. Amenability: The ability to adapt behavior to optimize performance in an often non-stationary environment in responsive pursuit of the goals of the client. Examples of human agents include booking agents, sales agents, and politicians. Definition: Software Agent Software Agent: An artificial agent which operates in a software environment. Delegacy for software agents centers on persistence.
Agent Variants Applications Back. ConceptNet 5. Amazon Mechanical Turk - Welcome. Artificial Intelligence. UMBC Agent Web -- news and information on software agent technology. Media Lab: Software Agents.