Quantified Self Uplevels to Quality of Life

The quantified self movement has barely gotten going in the last five years but contemporary shifts can already be seen such as the idea that the current activity is just an intermediary node on the way to the future exoself.

The quantified self refers to any individual engaged in the self-tracking of biological, physical, behavioral, or environmental information, often with a proactive stance towards action. At the center of the quantified self movement is, appropriately, the Quantified Self community with thousands of worldwide participants.

Quality of Life
A key contemporary shift is a push beyond the basic self-tracking of ‘steps walked’ and ‘hours slept’ to examine more complex qualitative phenomena like emotion, happiness, and productivity. The overall objective is to improve the quality of life.

CalmingTech
One example of improving the quality of life is by using ‘calming technologies’ to reduce stress. Whereas technology generally seems to speed things up, calming technologies do the opposite, helping to slow down and de-stress life.

The Calming Technology Lab at Stanford designs solutions to identify stressors, and respond to them by evoking a state of restful alertness in the individual. Calming technologies draw on the general principles of behavior design, where three aspects are required to produce a behavior change: sufficient motivation, sufficient ability, and a trigger. Calming technology is essentially a quantified personal stress management system.

Core Calming Principles
The CalmingTech lab has suggested ten core design principles to use in creating calming technologies, including reducing feelings of overwhelm, and having the ability to control interruptions. 

NewTech, ArtTech, CalmingTech…what could be next? HumorTech? SerendipityTech? 

Supercomputing: 16 petaflops, schmetaflops?

Supercomputing advances continue to exponentiate – the world’s best machine (IBM’s Sequoia - BlueGene/Q installed in the U.S. at LLNL) currently has 16 petaflops of raw compute capability.

Figure 1. Data Source: Top 500 Supercomputing Sites

As shown in Figure 1, the curve has been popping – up from 2 to 16 petaflops in just two years! However for all its massivity, supercomputing remains a linear endeavor. While the average contemporary supercomputer has much greater than human-level capability in raw compute power, it cannot think, which is to say pattern-match and respond in new situations, and solve general rather than special-purpose problems.

For the future of intelligence and cognitive computing, the three-way horse race continues between enhancing biological human cognition, reverse-engineering and simulating the human brain in software, and hybrids of these two.

The uncanny guest of post-nihilism

Nietzsche delivers the message that ‘god is dead’ with a parable where a madman goes into a 19th century European marketplace with a lantern at high noon asking ‘where has god gone?’ to the atheist-filled marketplace (in The Gay Science). Whereas previously the church had provided meaning to life and an endpoint to the story (e.g.; salvation), god was now dead and the marketplace was taking the church’s place in providing value and meaning to life, and there was no endpoint to the story, just nihilism (nothingness, e.g.; life is meaningless). Nietzsche presciently predicted the arrival of nihilism as ‘Europe’s uncanny guest.’ (from remarks by Robert Harrison at the Roundtable on the topic of "Nihilism" on February 29, 2011)

One could then ask, in the figurative marketplace for the new faith, what next uncanny guest might be lurking as the successor to nihilism? Post-nihilism could be the turning back to ‘something’ from ‘nothing,’ perhaps as many subjective virtual somethings as there are and will be ‘individual’ intelligences. The inward-turning path to individual liberty, choice, and subjectivism continues to prevail as opposed to a regression toward normative objective truths. Degreed objective truth (akin to degreed belief) is merely a transport layer for convenience and social lubrication but not a content layer. Early clues of the move towards greater subjectivism can be seen in the modern economy 2.0. The marketplace continues as a literal and figurative metaphor with an important mechanism for commuting meaning being the increasing value of the new currencies: reputation, status, attention, intention, etc. supplementing and perhaps eventually superceding money and labor. The need for stories and endpoints has as much relevance as ever.

Evolutionary adaptations and artificial intelligence

Art and religion are human evolutionary adaptations. Are there similar evolutionary adaptations that human-level and beyond artificial intelligence would be likely to make? Another way to ask this is whether art and religion were predictable? It seems that they were, maybe not the detailed outcomes, but that mechanisms would arise to allow for the achievement of human objectives such as status-garnering and mate selection.

Likewise, it seems quite possible that human-level and beyond artificial intelligence would be likely to make evolutionary adaptations. Utility functions could be edited in many ways. The primary area could be performance optimization, continuously improving cognition and other operations. A second area could be related to societal objectives to the extent that artificial intelligence is present in communities. Artificial intelligence might not have art and religion, but could have related mechanisms for achieving external and internal purposes.

Human body 2.0

The human body is a complex intricate composite of millions of years of evolution, but even the most cursory review immediately suggests the potential benefits of redesign. Without considering the deep possibilities and eventual exigencies of augmentation, it might be possible to replicate the full existing functionality of a human in a much smaller energy-conscious form factor, perhaps 1/10 the current size.

Waste: materials generation and energy expenditure
The biggest theme is waste due to untargeted processes. The main forms of waste are excess materials generated and energy used to move them around, all of which require a big overall system. Unlike the latest drugs, most natural molecules are untargeted; they travel around the body until they bump into a place to bind or are expelled unused. It is not just waste running through the blood stream and circulatory system, for example, steroid hormones diffuse into all cells, only binding to a small number.

Optimizing systems without sacrificing functionality
It could be argued that there are benefits to redundancy and waste could be better in some systems than others, for example, the value of having an extensive immune system on patrol 24/7 even though unused cell turnover is high. However, optimization could likely improve all system parameters.

Redesign phases: improved targeting and receptor enhancement
A potential human body redesign would certainly occur in phases, revising a few lower-impact operations first, targeting certain small classes of proteins to existing receptors for example. A second phase could include the generation or specificity-enhancement of receptors for a finer resolution of targeting.

Eventually, with robust targeting, it might be possible for the body to pump around 90% less ‘stuff.’

This would imply tremendous energy savings, and in turn decreased requirements for fluid, nourishment, vitamin, and mineral intake, and could even slow aging as processes do not wear out as fast.

Form factor hybrids
A smaller form factor may be undesirable for many reasons, but presumably it would be possible for streamlined wetware systems to merge into different kinds of hybrid form factors with ultralight ultrastrong hardware.

Phase transition in intelligence

There could be at least three approaches to the long-term future of intelligence: engineering life into technology, simulated intelligence, and artificial intelligence. Further, while the story of evolutionary history is the domination of one form of intelligence, the future could hold ecosystems with multiple kinds of intelligence, particular specialized by purpose/task.

There are significant technical hurdles in executing simulated intelligence and artificial intelligence, but the areas have been progressing in Moore’s Law fashion. The engineering of life into technology will need to proceed expediently to keep pace with technological advance, and tie a lot of wetware loose ends together.

At present, the mutation rate of genetic replication puts an upward bound on how complex biological organisms can be. The human cannot be more than about 10x as complex as Drosophila (the fruit fly), for example. However, if the error rate in the genetic replication machinery could be improved, maybe it would be possible to have organisms 10x more complex than humans, and so on, and so on…

Supercomputing and human intelligence

As of November 2009, the world’s fastest supercomputer was the Cray Jaguar located at the U.S. Department of Energy’s Oak Ridge National Laboratory, operating at 1.8 petaflops (1.8 x 10¹⁵ flops). Unlike human brain capacity, supercomputing capacity has been growing exponentially. In June 2005, the world’s fastest supercomputer was the IBM Blue Gene/L at Los Alamos National Laboratory, running at 0.1 petaflops. In less than five years, the Jaguar represents an order of magnitude increase, the latest culmination of capacity doublings each few years. (Figure 1)

Figure 1. Growth in supercomputer power

Source: Ray Kurzweil with modifications

The next supercomputing node, one more order of magnitude, at 10¹⁶ flops, is expected in 2011 with the Pleiades, Blue Waters, or Japanese RIKEN systems. 10¹⁶ flops would possibly allow the functional simulation of the human brain.

Clearly, there are many critical differences between the human brain and supercomputers. Supercomputers tend to be modular in architecture and address specific problems as opposed to having the general problem solving capabilities of the human brain. Having equal to or greater than human-level raw computing power in a machine does not necessarily confer the ability to compute as a human. Some estimates of the raw computational power of the human brain range between 10¹³ and 10¹⁶ operations per second. This would indicate that

supercomputing power is already on the order of estimated human brain capacity, but intelligent or human-simulating machines do not yet exist.

The digital comparison of raw computational capability may not be the right measure for understanding the complexity of the brain. Signal transmission is different in biological systems, with a variety of parameters such as context and continuum determining the quality and quantity of signals.

Heard from the future…

• I don’t feel like myself in this upload anymore
• I only got 98% fidelity in my revivification
• You must be a newbie, you never get full reload on a reviv
  
• I don’t want to be so present to my experience
• I don’t want to remember all my memories, I want to edit out x, y, z and enhance a, b, c and…
• I don’t want all my actions (and possibly thoughts) recorded by public cameras and sensor nodes
• Why did I reembody as a (man, dog, robot, hummingbird, bee, network node, airplane, etc.)?
• What is the construct "I"?
• Is this virtual world virtual? Where is the real virtual world?
• I think that AI over there is a few methods short of a class library