I am quite enamored by scientific
breakthroughs and understanding, as also interesting applications through
technologies. Mindboggling AI development in the last few years, and even
months, is happening realtime. This ‘general-purpose technology’ has the
potential to quantitatively change world, and unlike previous general purpose
technologies that impacted human society (for instance printing press, steam
engine, electricity, telephone, automobile, transistors, internet etc.) AI is
tremendous in its scale and speed. With deep learning neural network and geometrically progressed transistor intense computational power (scaling
through GPUs) churning on internet created stupendously large data AI has
suddenly come alive. Transistor architecture worked LLMs into generative AI. With
multimodal inputs AI has started to experience the world, and moving from 2D
language inputs to 3D awareness with ever refining sense data that is expected
to move from one domain to another effortlessly. Recent history of technology
was about manipulating atoms -from tools to machines, hydrocarbons to electricity,
materials to medicine, the primary driver of new technologies was material
-manipulation of atomic elements. In the last few decades technology moved
towards sophistication and abstraction. “Information as core property of
universe. It can be encoded in a binary format and is, in the form of DNA, at
the core of life operates” (The Coming Wave, Mustafa Suleyman). So, bits
(increasingly genes and soon qubits) has replaced atoms as force of innovations
and inventions. Breathtaking speed at which other equally significant
technologies like synthetic biology, quantum computing, robotics,
nanotechnology, fusion energy etc. are evolving parallelly creates an exciting
though extremely unpredictable ecosystem.
AI i.e. Artificial Intelligence
is already moving into robotics -Physical Intelligence, to be more effective it
will have to organically learn, indeed evolve, with complex reality. It is
futile to discuss AGI -indeed without even base definition agreement, or
consciousness -the computation created binary mode matching human consciousness
-which is a byproduct of billions of years of evolution. Artificial Capable
Intelligence (ACI) is suitable benchmark wherein AI can achieve complex goals
with minimum oversight. This cuts the hype and help to realistically work the
challenges humanity face. In this dynamically developing scene it is difficult
to keep track, indeed arduous to filter out chaff from substance. Even among
the experts, inside voices, there are polarized views on AI. On the one side we
have Geoffrey Hinton (AlexNet 2012 deep learning used neural network
backpropagation that essentially triggered the present AI revolution) who is
deeply worried and then on the other extreme we have Yann LeCun (now with Meta,
also forbearer of neural network) who is sceptic of the hype (indeed he even
downplayed AlphaGo before it made the breakthrough, so clearly people at helm aren’t
sure). You have many significant voices (I have read books, articles, watched
videos/talks so on to get the nuances of where the AI is moving) and find likes
of Demis Hassabis (heads DeepMind) quite grounded and value at the right place.
Hassabis and his team understood the potential of deep generative neural
network and used it to solve challenging problems humanity face. Protein
folding has been one of science’s grand challenges for half a century. AlphaFold
was able to predict how proteins might fold based on their DNA by training on
the set of known proteins and extrapolating from them. In just about two years
DeepMind uploaded some 200million structures of protein in one go, representing
almost all known protein! AlphaFold’s contribution to biological science,
medical research, pharmacy and ofcourse insight into process of life is
pathbreaking, indeed a paradigm shift. It must be duly recognized.
So, the question here is how
creative AI is? LLM through chat models like GPT, Claude so on is able to do
some amazing stuff and converse that may sound almost human. It can even write
excellent poems. But then it is only spitting out from the patterns of what it
is fed. However, one cannot be dismissive despite narrow frame of language
learning. Language makes much of human world. True all other species are
intelligent enough to negotiate the world, indeed thrive, without the use of
language. But I dare argue surviving is not wholeness of living, and human life
epitomizes the meaningfulness of life. Language is an indelible part of human
progress, and much of human emotions, awareness, expressions, knowledge and
complex thoughts and ideas are embedded in language. So, if AI is ingesting all
these literature and writings that was ever written it is but expected that it
will have some emergent understanding of what it is to be human. It may not
understand much about senses, as a blind person may not about sight, but may have
a fair idea of what it means to see by abstracting from knowledge of seeing. You
really cannot say there is nothing there except language. If it is able to see
patterns that humans are not even capable to then that means it is not merely
spitting out or regurgitating. The patterns we don’t decipher or are even aware
may crisscross, entangle, interact to create meaning that could be insightful. It
is not mere language. It is coded human lives, the collective experiences and
understanding of humanity. So, since it is not mere language even hallucination
is limited, or else we don’t understand the pattern that it has spotted (except
where things are factual because in bigger schemes of things facts are
contextual and subjective therefore LLM falters -not in the intent but
execution). It clearly is emergent, and is able to connect patterns we are incapable
to decipher is by definition creative. DeepMind Co-founder Suleyman sometime
back mentioned an interesting take on hallucination as mutation. Information of
life coded through genes is in constant interaction with reality hence evolve in
a gradual process, but sometimes with epigenetic awareness, a sudden change can
creep in, life can take a leap, this response may resonate or falter. AI
hallucination i.e. giving out wrong information is a problem in limited context
of wrong and right but in a bigger context it is creative emergence.
Even in the limited non LLM
context, whether it is AlphaGo or AlphaZero, it is clear that AI is able to see
patterns that is way beyond human understanding. Feeding framework rules was
enough for it to creatively work the context to bring out patterns that humans
playing the game for centuries couldn’t fathom (just watch AlphaZero with
Stockfish, you will be mindblown by pawn attack strategy. Not into Go game but move 37 is
in the annals of AI wonder). So much so that it was able see relation between
molecules to create new antibiotic (halicin), meaning, our science may not be knowing
certain aspects of molecular relations that pattern was able to decipher. Soon
AI should be able to decipher its own pattern and open up the black box and
help us reverse engineer the knowledge in these deep patterns. With multimodal
input, studying human actions and perceiving world in more dimensions (3D to
start with, god knows how many dimensions are there, and what AI could bring
out!) AI will become more capable and discerning with merging of other equally
compelling technologies like advancement in precision gene modification through
CRIPSRcas9 and DNA printing, and yes quantum computing (everytime it is “within
ten years”! but yes Chinese have made massive advancement -being an
authoritarian country a cause of concern) the shift from digital to quantum is
change of narration from binaries to probables, fusion energy will definitely
add to the mix limited by power source as also advances in synthetic data that
will create perpetual high quality data source. What is of concern is AI in the
hand of bad player, as also channel for deep fakes, disinformation and
misinformation. There need to be regulation on AI in limited context ie dealing
with right and wrong, binary of facts. Bigger context AI -that is beyond right
or wrong, in the realm of subjective, where the probabilities converge to reveal
something new, must be kept open.
Unlike science technology is
incentivized by profit hence the path of technological progress is narrow.
There is a loss that is unnoticed when BigTech clamor over how to monetize AI.
What possibilities are there for that part that is left out, unmonetized AI,
and how that could change the world we know is a pertinent thought. In the
faster and bigger computation what is also left out is slow thinking, the
pause, the still. Will AI ever be able to decipher patternless world of
silence? AI is creative alright but is
limited within the framework, as for LLM -within the framework of known human
experience (from which it can extrapolate). An entirely new thought, new idea,
a Einstein or a Chekov or Dickinson level insight is impossible (new herein
can only emerge from entangling of deep patterns, within the frame of known).
Human mind is astounding and can see patterns that is based on no known
understanding. But AI has its own place, and surely cannot be negated, and is
equally astounding in its own way. This comparison is futile. There is an
iteration of billions of years with all the senses, critical thinking faculties
and intuitions.
Recently there is a development
through liquid neural network that is controllable, adaptable, energy efficient,
and contrary to the stampede to scale up the network, it focuses on scaling
down with few but richer nodes. They studied simple organism (in this case a
worm called c elegans) and how they take decisions to face complexities of life
and strategies of survival, and built neural system based on the math of few
hundred neurons. Liquid neural network used 19 odd neurons for self-driving
cars instead of mess of hundreds and thousands used. The next step for sustainable
elegant solutions for technological challenges will have to come nature. Each specie
is millions of years of R&D to face the complexities of life. They have
survived and thrived means these are successful. Human brain is complex but
uses very less energy unlike GPUs that run AI. It is estimated that by 2030
they will consume a quarter of total global energy produced. The recent advancement
in Biotech through CRISPRcas9 is using billions of years of survival strategy of
bacteria against virus. Technology has been capitalizing on algorithm from
nature like evolutionary algorithm, swarm algorithm, or even algorithm from
foraging strategy of slime mold that optimizes resources and dynamically
interact with changing scenarios (when I first time read about these single
cell slime molds -that even lacks neurons, I got goosebumps). There is an
organic intelligence at work that is smart, solves problems and survives
without as much as a neuron. Next time take a close look at wonderfully
arranged hexagonal cells of beehive, it optimizes space, resources and
material. Or know about fire beetles that can sense fire from 130km away. The more
you know more you will be astounded (I also have a youtube channel that you can
search). As technology advances and look for solutions take a closer look at
nature. Understand how nature works, the physics, chemistry and maths that life
has aligned with, and what Einstein called Spinoza’s god. Extropic.ai intents
to revolutionize computation by making a bold move of reimagining the idea of
computer. A computer without suppressing natural entropy of world, and leverage
it as an asset, in harmony with entropy rather than against it. Nature’s
elegant solutions iterates simple into complex.