Are we there yet?
We are at yet another seemingly fundamental session of re-imagining the molds we use daily. Technology has continued forward rapidly with no signs of slowing. Bottlenecks thought insurmountable in the past have been smashed almost religiously with new applications of theory in niche industries that spread understandings to seemingly unrelated industries. This pace of constant progress feels like freefalling into the future and can be overwhelming for many that want to hold onto things for more than a few years. Generations condense and the work we are expecting to be done by a new finding before it is replaced is constantly shrinking. The modern ages have been broken up generally between:
Machine Age (1880-1945)
Jet Age (1940s)
Atomic Age (1945-present)
Nuclear Age (1950-present)
Digital Revolution (1950s-present)
Space Age (1957-present)
Information Age (1970-present)
Multimedia Age (1987-present)
Social Age (1996-present)
Big Data Age (2001-present)
There are 5 ages (high level ages in bold above) that started in largely different generations and decades that are still in process. There is more that bonds us in this time of constant general confusion than divides us. Specialization was the primary tenet carried forward throughout each age. This has been a constant in our societies for a long time, e.g. family names being a mark of trades as well as degrees for entry into a profession being so costly in money or time as to prohibit shifting careers too late. What comes from this is that we are less likely to clearly leave a prior age and more often expand the detail and complexity of prior ages seen. There is a revisiting that happens as we move forward as well that will continue to unfold, but clarity remains to be seen and felt in that social growth.
The Big Bit
The information age builds on and expands the abilities of its concurrent partners. If we were to generalize the evolution we would see the process becoming increasingly focused on passive engagement and overall ease of use while also increasing the number of functions possible. Many have wondered about the simulation question. As we have gotten to each new benchmark defining what we have collectively decided by majority decision what is considered the next step in reaching AI (Artificial Intelligence) we increase the expectation. We have seen Chinook (shared in 1994 for Checkers), Deep Blue (started in 1985 and seen in world victory in 1996 for Chess), and most recently AlphaGo (seen in first victory against a professional organic player in 2015 and against world renowned professional Lee Sedol in 2016 for Go). Each new age was made possible by technological advancements and breakthroughs that allowed the computational pieces necessary to be designed and built. These were all steps along the path of developing AI.
The reaction among many tech-fluent people once each stage was reached was a general shift in focus to what would have to come next to reach what humans feel is done naturally in daily life. Maybe the next game has yet to be developed. One direct idea we can imagine already, expanding the 19x19 board of a full-sized Go game would be going up in height to make up to 19 layers. The constraints and game forms seen at each layer addition likely changing how the games are played in general. Another might be combining Chess and Go to give teams of pieces different properties based on shape, color, weight, etc. A third would be bringing these first two ideas together. Additional features could be gaps in spaces available to move for all or specific pieces in layers or 3D regions of the board. These do not sound like games easily playable by a majority of people today. But we are seeing several questions arise such as when computers become more capable does society change to match? How does a more tech-fluent society change the definitions seen and paths explored as technology develops? More connected people become more empathetic (ie. the Social Age); how will this trend affect the path we take forward?
All of the systems described above are generally considered narrow A.I. because they are focused on one narrow task. The current expected steps forward in regards to intelligence are:
Narrow (focused on one specific task - where we find ourselves today)
General (able to transfer between tasks like people)
Super AI (wayyy smarter or more capable than people today)
We could explore these questions specifically around A.I. for a long time and many professionals have been doing just that. The question to explore now though is what are the differences we can see today between A.I. and yet to be seen S.I. (or Synthetic Intelligence).
A.I. and S.I.
The definitions of A.I. seen today vary in length and detail. The one shared on Wikipedia puts it simply as "AI is intelligence demonstrated by machines". Additionally, a machine is defined as "an apparatus using or applying mechanical power and having several parts, each with a definite function and together performing a particular task". With these two definitions we start to see a large part of the difference held today can be attributed to the distance between what we know about the machines we have created to play the games we actively play and what we actually understand about natural and organic systems. Systems we have built so far have been focused on specific goals. The ones that have reached broader acclaim have focused further on game goals. The movie WarGames is an example of earlier visions of this principle.
In a Synthetic Intelligence the focus is more on authenticity rather than victory. The how we get there part is still being explored and is not as readily defined in clear next steps. Steps could include the developments we have been seeing around neural networks and placing them in natural systems to allow them to evolve (largely) unsupervised. This principle focuses on representing our present understanding of organic systems as parameters for how their digital versions evolve. Thankfully and unfortunately, many of the problems seen today in understanding how organic systems evolve arise with these kinds of approaches. This seems to bring us closer to an authentic intelligence development process than force us to change course.
defined as "the opposite of artificial intelligence: it is all the systems of control that are not artifacts, but rather are present in biology. Normally when we think of NI we think about how animal or human brains function, but there is more to natural intelligence than neuroscience". There are questions that come up again. How do discrete and continuous systems differ? How long until the lines between the three blur at the high level and differ largely in style? What will these systems and their children look like in 50, 100, 500, and 1000 years? What comes next? Whether we re-enter the spiritual age is to be felt but the path we are on will be filled with many more twists and turns.The progression between the three seems to be specific designed, authentic grown, and broadly grown. Organic (or Natural) Intelligence is