background preloader

Jeff Hawkins on how brain science will change computing

Jeff Hawkins on how brain science will change computing

http://www.ted.com/talks/jeff_hawkins_on_how_brain_science_will_change_computing.html

Related:  Artificial IntelligenceAI

Bionics Bionics (also known as bionical creativity engineering) is the application of biological methods and systems found in nature to the study and design of engineering systems and modern technology.[citation needed] The transfer of technology between lifeforms and manufactures is, according to proponents of bionic technology, desirable because evolutionary pressure typically forces living organisms, including fauna and flora, to become highly optimized and efficient. A classical example is the development of dirt- and water-repellent paint (coating) from the observation that the surface of the lotus flower plant is practically unsticky for anything (the lotus effect).[citation needed].

Non-Human Consciousness Exists Say Experts. Now What? Non-Human Consciousness Exists Say Experts. Now What? Phillip Low at Singularity University Have you ever considered the consciousness, or unconsciousness, of your dog? 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

Jeff Hawkins Hawkins also serves on the Advisory Board of the Secular Coalition for America and offers advice to the coalition on the acceptance and inclusion of nontheism in American life.[3] Early life and career[edit] Hawkins grew up with an inventive family on the north shore of Long Island. Hierarchical temporal memory Hierarchical temporal memory (HTM) is an online machine learning model developed by Jeff Hawkins and Dileep George of Numenta, Inc. that models some of the structural and algorithmic properties of the neocortex. HTM is a biomimetic model based on the memory-prediction theory of brain function described by Jeff Hawkins in his book On Intelligence. HTM is a method for discovering and inferring the high-level causes of observed input patterns and sequences, thus building an increasingly complex model of the world. Jeff Hawkins states that HTM does not present any new idea or theory, but combines existing ideas to mimic the neocortex with a simple design that provides a large range of capabilities.

Automated Grading Software In Development To Score Essays As Accurately As Humans Roboreaders that can score essays in standardized tests could also help teachers grade and students becomes better writers. April 30 marks the deadline for a contest challenging software developers to create an automated scorer of student essays, otherwise known as a roboreader, that performs as good as a human expert grader. In January, the Hewlett Foundation of Hewlett-Packard fame introduced the Automated Student Assessment Prize (ASAP…get it?) offering up $100,000 in awards to “data scientists and machine learning specialists” to develop the application. In sponsoring this contest, the Foundation has two goals in mind: improve the standardized testing industry and advance technology in public education.

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.

Hierarchical Temporal Memory We've completed a functional (and much better) version of our .NET-based Hierarchical Temporal Memory (HTM) engines (great job Rob). We're also still working on an HTM based robotic behavioral framework (and our 1st quarter goal -- yikes - we're late). Also, we are NOT using Numenta's recently released run-time and/or code... since we're professional .NET consultants/developers, we decided to author our own implementation from initial prototypes authored over the summer of 2006 during an infamous sabbatical -- please don't ask about the "Hammer" stories. I've been feeling that the team has not been in synch in terms of HTM concepts, theory and implementation. We decided to spend the last couple of meetings purely focused on discussions concerning HTMs.

Hugo de Garis Hugo de Garis (born 1947, Sydney, Australia) was a researcher in the sub-field of artificial intelligence (AI) known as evolvable hardware. He became known in the 1990s for his research on the use of genetic algorithms to evolve neural networks using three-dimensional cellular automata inside field programmable gate arrays. He claimed that this approach would enable the creation of what he terms "artificial brains" which would quickly surpass human levels of intelligence.[1] He has more recently been noted for his belief that a major war between the supporters and opponents of intelligent machines, resulting in billions of deaths, is almost inevitable before the end of the 21st century.[2]:234 He suggests AIs may simply eliminate the human race, and humans would be powerless to stop them because of technological singularity. De Garis originally studied theoretical physics, but he abandoned this field in favour of artificial intelligence.

Facial Recognition Software Distinguishes Between Real And Phony Smiles MIT researchers know when you're smiling for real (left) or out of frustration (right), but odds are you can't tell. Con-artists, deceivers, and fakers take note: feigning emotion to manipulate others is about to get a lot harder. Researchers at the MIT Media Lab have developed software that can differentiate between a genuinely delighted smile and one born from frustration. It turns out that the majority of people unknowingly smile to cope with frustration, and others may interpret those smiles as genuine.

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).

Evolvable hardware Evolvable hardware (EH) is a new field about the use of evolutionary algorithms (EA) to create specialized electronics without manual engineering. It brings together reconfigurable hardware, artificial intelligence, fault tolerance and autonomous systems. Evolvable hardware refers to hardware that can change its architecture and behavior dynamically and autonomously by interacting with its environment. Introduction[edit] Each candidate circuit can either be simulated or physically implemented in a reconfigurable device. Robotic Quintet Composes And Plays Its Own Music Sound Machines 2.0 is Festo's latest effort to create robotic musicians. The German engineering firm Festo has developed a self-playing robotic string quintet that will listen to a piece of music and generate new musical compositions in various musical styles effortlessly. Dubbed Sound Machines 2.0, the acoustic ensemble is made up of two violins, a viola, a cello, and a double bass, each consisting of a single string that is modulated by an electric actuator for pitch, a pneumatic cylinder that acts as a hammer to vibrate the string, and a 40 watt speaker. A new composition is generated in a two-stage process. First, a melody played on a keyboard or xylophone is broken down into the pitch, duration, and intensity of each note, and software with various algorithms and compositional rules derived from Conway’s “Game of Life” generates a new composition of a set length.

Related:  ...!?!...Computer Science