Tuesday, July 15, 2014

Will We Ever Emerge from Linear Thinking?

Will the Human Brain ever be able to Emerge from Linear Thinking?

Since civilization began, humans have excelled in linear thinking: understanding sequences or cause and effect. They rely and survive on remembering sequences, anticipating them, avoiding or benefiting from them, manipulating them and incorporating hosts of interfering linear variables, anticipating consequences and limits to those consequences.

Humans have condensed such thinking into symbols, numbers and more recently, into binary code, creating algorithms to detect and carry out every possible cause and effect they can think of: if a, then b. If ab, then c, if ab/c, then d and so on. Even quantum mechanical computation, is to date, linear, translating the elusive electron into a quantifiable, digitized vector: taking probability and quantifying that uncertainty into a qbit.

Sequential analysis, linear analysis, the grasp of cause and effect is to date, the only form of analysis humans seem to know. It is still the basis of artificial intelligence. But when we learn, if ever, to emerge from the world of sequence and sensitize ourselves to other forms of occurrences, other forms of cognition, artificial intelligence, computational mechanics, physics and science in general, might more closely mirror, explore and enjoy the undocumented quivering of nature.

SOURCE:
www.jeffreyepsteinscience.com

Saturday, May 10, 2014

Friday, May 9, 2014

Computational Biology: pattern prediction in biology.


Computational biology is the use of quantitative tools, data-analytics, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems.  Computational biology has been very effective when collecting large data sets and has helped sequence the human genome, create accurate models of the human brain, and assist in modeling biological systems.

Computational biomodeling, which builds computer models of biological systems, often uses visual simulations to assess the complexity of biological systems.  Biomodeling specifically uses specialized algorithms and visualization software, which help with the prediction of how bio systems will react under different environments.

Subsets of computational biology includes, computational genomics, neuroscience and pharmacology. Cancer computational biology aims to determine the future mutations in cancer through an algorithmic approach to analyzing data. Research in this field has led to the use of high-throughput measurement. High throughput measurement allows for the gathering of millions of data points using robotics and other sensing devices. This data is collected from DNA, RNA, and other biological structures. Areas of focus includes determining the characteristics of tumors, analyzing molecules that are deterministic in causing cancer, and understanding the how the human genome relates to the causation of tumors and cancer.

What all of these sub fields have in common is isolating key patterns in our biology. Pattern determination, the exceptions and derivatives, all stem from linear thinking, a type of analysis that relies on cause and effect, the only form of analysis that we know, an analysis that has helped humans survive and thrive. It is the basis of artificial intelligence. But when we learn, if ever, to emerge from the world of sequences and sensitize ourselves to other forms of occurrences, artificial intelligence and computational biology will more closely mirror the undocumented quivering of nature.

Jeffrey Epstein Ideas Forum: Jeffrey Epstein Ideas Forum: Computational Biology...

Jeffrey Epstein Ideas Forum: Jeffrey Epstein Ideas Forum: Computational Biology...: Jeffrey Epstein Ideas Forum: Computational Biology: pattern prediction in biolo... : C omputational biology is the use of quantitative tools...

Jeffrey Epstein Ideas Forum: Cancer Cells: Targeting the Dangerous Few

Jeffrey Epstein Ideas Forum: Cancer Cells: Targeting the Dangerous Few: It is generally assumed that all cancer cells within a tumor are the same and equally dangerous. That is not the case. Not only are there...

Friday, April 11, 2014

Is Human Intelligence Still Evolving?

Is Human Intelligence Still Evolving?


There is no doubt that human intelligence will continue to evolve. And not just an external evolution of building on acquired knowledge, but a physiological evolution of the brain and cells. How it will evolve is harder to predict.

It’s also difficult to define what we mean by human intelligence. But for the purpose of this article, we’ll define it as the ability to receive, interpret and deliver information.

It’s somewhat arrogant to assume that humans have reached a plateau in their physical evolution; particularly when one considers that we have been physically evolving for the last two and half million years. In fact, the evolution of hominid intelligence can be traced over its course for the past 10 million years, and attributed to specific environmental challenges.

We may no longer be so subjected to Darwin’s survival of the fittest, which is still alarmingly prevalent amongst, say, cockroaches and rats, but we are heading into an unchartered age of genetic manipulation, into an age of creation of the fittest.

We look forward to your thoughts on how you think human intelligence will evolve.

SOURCE: www.jeffreyepsteinscience.com

Merging Artificial and Organic Intelligence

The Merger of Artificial Intelligence and Organic Intelligence


Artificial Intelligence (AI) is any man-made machine that can process information and react to it in some productive way. John McCarthy, the brilliant computer and cognitive scientist, who coined the term in 1955, defined AI as "the science and engineering of making intelligent machines.”

There is of course, an increasingly blurred line between purely mechanical AI, and OI, organic intelligence. On one end of the spectrum, there is the computer, robot, cell phone, calculator, microwave and electronics and on the other, there is the human being, animal, plant or organic cell. But between the two spectrums, there is a growing fusion between the two, the development of implanted micro-machines for example, alleviating pain, vascular plaque, pacing the heart, regulating brainwaves, targeting cancer cells; a growing world of borgs, where both intelligences can serve each other, intertwining towards the great unknown.


SOURCE: www.jeffreyepsteinscience.com