Life 3.0 by Max Tegmark
The life defined as a process that can retain its complexity and replicate can develop through three stages: biological evolution, cultural evolution, and technological evolution.
Life 1.0 is unable to redesign either its hardware or its software during its lifetime.; both are determined by its DNA. and changes only through evolution over many generations.
Life 2.0 can redesign much of its software: the human can learn complex new skills - e.g. languages, sports, and profession - and can fundamentally update their worldview and goals.
Life 3.0 which doesn’t yet exist on earth, can dramatically redesign not only its software but it’s hardware as well, rather than having to wait for its to gradually evolve over generations.
The ability to change its design (software) enables life 2.9 to be not only smarter than life 1.0, but also flexible. If the environment changes, 1.0 can only adapt by evolving over many generations. Life 2.0 on the other hand, can adapt almost instantaneously via software update. For example, bacteria frequently encountering antibiotics may evolve drug resistance over many generations, but an individual bacterium won’t change its behavior at all.
You might argue that today’s human should be count as Life 2.1 as we can perform minor hardware upgrades such as implanting artificial teeth, knees, and pacemakers, but nothing as dramatic as getting ten times taller or acquiring thousand times bigger brain.
Artificial Intelligence (AI) may enable us to launch Life 3.0 this century and fascinating conversations have sprung up regarding what future we should aim for and how this can be accomplished.
Intelligence is the ability to accomplish complex goals cannot be measured by a single IQ.
A computation is a transformation of one memory state into another. In other words, a computation takes information and transmit it, implanting what mathematicians call a function. For example, 7 as an input to a square function will transform 7 into 49. How tangible physical stuff can give rise to something that feels as intangibles, abstract and ethereal as intelligence: it feels so non-physical because it’s substrate-independent, taking on a life of its own that doesn’t depend on or reflect the physical details. In short, computation is a pattern in the space-time arrangements of particles, and it’s not the particles but the pattern that really matters, Matters doesn’t matter.
In other words, the hardware is the matter and the software is the pattern. This substrate independence of computation implies that AI is possible: intelligence does not require flesh, blood or carbon atoms.
Memory, computation, learning, and intelligence have an abstract, intangible and ethereal feel to them because they are substrate independent: able to take on a life of their own that does not depend on or reflect the details of their underlying material substrate.
Any matter can be computronium, the substrate for computation as long as it contains certain universal building blocks that can be combined to implement any function. NAND gates and neurons are two important examples of such universal ‘computational atoms”. A neural network is a powerful substrate for computation as long as it contains certain universal building blocks that can be combined to implement any functions. Because of the striking simplicity of the laws of physics, we humans only care about a tiny fraction of all imaginable computational problems, and neural networks tend to be remarkably good for solving precisely this tiny fraction.
Moor’s law will of course end, meaning that there is a physical limit to how small transistors can be made. Whenever one technology stopped improving, we replaced it with an even better one. When we could no longer keep shrinking our vacuum tubes, we replaced them with transistors and then integrated circuits, where electrons move around in 2 dimensions. When this technology reaches its limits, there are many other alternatives we can try - for example, using 3-dimensional circuits and using other than electrons to our bidding.
Once the technology gets twice as powerful, it can often be used to design and build technology that’s twice as powerful in turn, triggering repeated capability doubling in the spirit of Moor’s law. The cost of information technology has now halved roughly every two years for about a century, enabling the information age. If AI progress continues, then long before AI reaches the human level for all skills, it will give us fascinating opportunities and challenges involving issues such as bugs, laws, weapons, and jobs.
Throughout human history, we have relied on the same tried and true approach, to keeping our technology beneficial: learning from mistakes. For example, when invented fire, repeatedly messed up and then invented the fire extinguisher, fire exit, fire alarm, and fire department.
Career advise for kids:
Recent forecasts for when various jobs will get taken over by machines identify several useful questions to ask about a career before deciding to educate oneself for it. For example:
Does it require interacting with people and using social intelligence
Does it involve creativity and coming up with clever solutions?
Does it require working in an unpredictable environment?
The more of these questions you can answer with a yes, the better your career choice is likely to be.
When the automobile came up, horse -owners thought there will be some new jobs that require horses, which never came and it will be the same with AI. Jobs can provide people with more than just money. Voltaire wrote in 1759 that “work keeps at bay three evils: boredom, vice, and need”. Conversely, providing people with income isn’t enough to guarantee their well-being. Romans emperors provided both bread and circuses to keep their underlings content and Jesus emphasized non-material needs in the Bible quote: “Man shall not live by bread alone”. So precisely what valuable things do jobs contribute beyond money and in what alternative ways can a jobless society provide them?
What is the natural state of life in our cosmos: unipolar or multipolar? Is power concentrated on distributed? After the first 13.8 billion years, the answer seems to be ‘both’: we find that the situation is distinctly multipolar but in an interestingly hierarchical fashion. When we consider all the information processing entities out there - cells, people, organization nations tec. - we find that they both collaborate and compete at a hierarchy of levels.
The branch of mathematics known as game theory elegantly explains that entities have an incentive to cooperate where cooperation is a so-called Nash equilibrium: a situation where any party would be worse off if they altered their strategy. To prevent cheaters from ruining the successful collaboration of a large group, it may be in everyone’s interest to relinquish some power to a higher level in the hierarchy that can punish cheaters. For example, people may collectively benefit from granting a government power to enforce laws, and cells in your body may collectively benefit from giving police force the power to kill any cell that acts too uncooperatively spewing out viruses or turning cancerous. Some hierarchies allow their lower parts to influence the higher-ups by democratic voting, while others allow upward influence only through persuasion or the passion of information.
Our experimentation over the millennia with different systems of governance shows how many things can go wrong, ranging from excessive rigidity to excessive goal drift, power grab, succession problems, and incompetency, There are at least four dimensions wherein the optimal balance must be struck:
Centralization - there is a trade-off between and stability: a single leader can be very efficient, but power corrupts and succession is risky.
Inner threats - one must guard both against growing power centralization (group collusion, perhaps even a single leader taking over) and against growing decentralization (into excessive bureaucracy and fragmentation)
Outer threats - if the leadership structure is too open, this enabled outside forces (including AI) to change its values, but if it’s too impervious, it will fail to learn and adapt to change
Goal stability - too much goal drift can transform utopia into dystopia, but too little goal drift can cause failure to adapt to the evolving technological environments.
Most organization fall apart after few years or decades. Only the RC church is the most successful organization in human history in the sense that it’s the only one to have survived 2 millennia.
If we had an abundant supply of antimatter (which we don’t), then a 100% efficient power plant would be easy to make: simply pouring a teaspoonful of anti-water into regular water would unleash the energy equivalent to 200,000 tons of TNT, the yield of typical hydrogen bomb - enough to power the world’s entire energy needs for about 7 minutes.
Our most common ways of generating energy today are woefully inefficient. Digesting a candy bar is merely 0.00000001% efficient, in the sense that it releases a mere ten-trillionth of the energy mc2 that it contains.
Compared to cosmic timescales of billions of years, an intelligence explosion is a sudden event where the technology rapidly plateaus at a level limited only by the laws of physics.
As per the author of What is life, Erwin Schrodinger that a hallmark of a living system is that it maintains or reduces its entropy by increasing the entropy around it. In other words, the second law of thermodynamics has a life loophole: although the total entropy must increase, it’s allowed to decrease in some places as long as it increases even more elsewhere. So, life maintains or increases its complexity by making its environment messier.
Not only can non-living matter have goals, at least in this weak sense, but increasingly does. If you’d been observing Earth’s atoms since our planet formed, you’d have noticed three stages of goal-oriented behavior:
- All matter seemed focused on dissipation (entropy increase)
- Some of the matter came alive and instead focuses on replication and sub-goals of that
- A rapidly growing fraction of matter was rearranged by living organisms to help accomplish their goals.
Some of the goal-oriented entities:
5 x 10e30 bacteria - 400 billions of tons
Plants - 400 billions of tons
7 x 10 e9 humans - 0.4 billion tons
10e 14 ants - 0.3 billion of tons
It is fascinating for me to hear and read the ethical views of many thinkers over many years and the way I see it, most of their preferences can be distilled into four principles:
Utilitarianism - positive conscious experience should be maximized and suffering should be minimized.
Diversity - a diverse set of positive experience is better than many repetitions of the same experience, even if th4e latter has been identified as the most positive experience possible
Autonomy - conscious entities/societies should have the freedom to pursue their own goals unless this conflicts with an overriding principle
Legacy - compatibility with scenarios that most humans today world view as happy, incompatibility with scenarios that essentially all human today would view as terrible.
The ultimate origin of goal-oriented behaviors lined in the laws of physics which involve optimization. Since humans don’t have the resources to figure out the truly optimal replication strategy, we have evolved useful rules of thumb that guide our decisions: feels such as hunger, thirst, pain, lust, and passion.
Consciousness = subjective experience
Books referred to in this book.
The day my butt went psycho / Andy Griffiths.’
Superintelligence by Nick Bostrom
The Organization of Behavior b: A neuropsychological theory by Donald Hebb
What is life by Erwin Schrodinger
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