Jeremy Rifkin, Popular Resistance.
Automata, Aliveness, and the Corporate Myth of Artificial Superintelligence.
Jeremy Rifkin, one of the World’s Leading Public Intellectuals, Argues in his New Book ‘Rescuing the Future’ that the People’s AI is on a Deep Existential Curve and Likely to Surpass the Corporate AI Giants by 2050 in Bioregions Around the World.
Artificial intelligence has generated one of the strangest narratives in the history of technology. Several of the world’s most powerful corporations are investing extraordinary sums of money, energy, engineering talent, physical infrastructure, and political capital in machines that perform increasingly remarkable computational operations. Yet rather than principally describing these machines as what they demonstrably are—astonishingly sophisticated automata and potentially transformative utilities—the frontier AI industry frequently presents them as steps toward something vastly more consequential: artificial general intelligence, superintelligence, and perhaps eventually intelligence superior to humanity itself.
The rhetoric is extraordinary.
OpenAI states that its mission is to ensure that artificial general intelligence benefits all humanity and currently describes AGI as systems “generally smarter than humans.” Its foundational charter uses a somewhat narrower functional definition: highly autonomous systems outperforming humans at most economically valuable work. Google DeepMind similarly declares that AI, “and ultimately artificial general intelligence,” could drive one of the greatest transformations in history. Anthropic uses somewhat different language but organizes its Responsible Scaling Policy around increasingly powerful frontier systems and potentially transformative benefits and catastrophic risks.
Something important is occurring here.
These corporations generally do not claim that today’s models are living organisms. They do not normally claim that a large language model possesses metabolism, phenomenal sight, smell, taste, touch, proprioception, interoception, or vestibular sensation. Nor have they scientifically demonstrated that there is an experiencing subject behind the language their systems generate.
Yet their grand narrative continually moves toward something larger than tools.
AGI.
Superintelligence.
Autonomous agents.
Human-level intelligence.
Beyond-human intelligence.
Transformative intelligence.
The question therefore deserves to be posed bluntly: why does the frontier AI industry so often resist the far more modest—and presently more empirically secure—description of its creations as sophisticated automata and cognitive utilities?
The answer requires examining not merely computer science but ontology, evolutionary biology, phenomenology, economics, corporate finance, geopolitics, and perhaps most importantly, mythology.
First, What AI Companies Do Not Know
Before accusing the industry of perpetrating a charade, intellectual fairness requires making an essential distinction.
The AI corporations do not know that artificial consciousness will never exist.
Neither do their critics.
The scientific problem of consciousness remains unresolved even for biological organisms. We still lack an agreed explanation of how phenomenal experience emerges from biological processes. Thomas Nagel’s famous question—“What is it like to be a bat?”—remains philosophically potent precisely because objective knowledge about a nervous system does not automatically disclose the subjective character of experience.[1]
An interdisciplinary group including Patrick Butlin, Robert Long, Yoshua Bengio, Jonathan Birch, and others examined contemporary AI against indicators derived from leading scientific theories of consciousness. Their conclusion was cautious. They found no contemporary system they assessed that warranted attribution of consciousness, but they did not identify an obvious theoretical barrier preventing future artificial systems from satisfying some proposed consciousness indicators.[2]
So we should not replace the industry’s speculative certainty with an opposing speculative certainty.
The stronger argument is different.
No existing frontier AI system has been scientifically demonstrated to possess phenomenal consciousness.
That is enough.
The burden of proof belongs to anyone wishing to move from extraordinary computational performance to claims about artificial minds possessing an experienced world.
Until that bridge is crossed, AI remains demonstrably machinery.
Extraordinary machinery.
Potentially civilization-transforming machinery.
But machinery nevertheless.
The Confusion between Intelligence and Aliveness
The Singularity narrative depends upon collapsing distinctions that evolution spent billions of years constructing.
A large language model processes information.
A bacterium lives.
These statements are not equivalent.
A bacterium maintains a membrane. It exchanges matter and energy with its surroundings. It regulates internal chemistry. It responds adaptively to environmental conditions. It repairs itself. It reproduces. Its lineage evolves. Its existence is precarious: failure to maintain the organization constituting it means death.
Artificial intelligence possesses none of these properties simply by virtue of computing.
A server consumes electricity, but electricity consumption is not metabolism.
A data center requires cooling, but cooling equipment is not thermoregulation experienced by an organism.
A model can receive diagnostic information concerning processor temperature, but there is no evidence that it feels hot.
A robot can recharge its battery without becoming hungry.
A system can identify damage without experiencing pain.
A program can preserve its state without fearing death.
The distinction becomes even clearer when we turn toward the phenomenological attributes of embodied animal existence: sight, hearing, smell, taste, touch, interoception, proprioception, and vestibular sensation.
An AI can receive data from cameras.
That does not establish phenomenal sight.
It can process microphones.
That does not demonstrate hearing.
It can interpret chemical sensors.
That does not establish smell or taste.
It can receive tactile data.
That does not establish touch as felt experience.
It can monitor its internal machinery.
That does not demonstrate interoception.
It can calculate the position of robotic limbs.
That does not demonstrate proprioceptive experience.
It can integrate accelerometers and gyroscopes.
That does not establish the experience of balance, dizziness, falling, acceleration, or gravity.
The distinction can be summarized in a single sentence:
A sensor registers a difference; a living subject experiences a world.
Whether artificial machinery can someday cross that divide remains open. That it already has crossed it has not been demonstrated.
Planet Aqua Has Been Doing Something Far More Extraordinary
Now reverse the perspective.
Rather than asking when artificial intelligence will become sufficiently sophisticated to rival life, consider what life has already accomplished.
Life emerged on our watery planet billions of years ago and diversified into an extraordinary planetary web of organisms. Estimates of Earth’s total number of species remain highly uncertain, particularly once microbial diversity enters the calculation; “a trillion species” is associated with one influential estimate of microbial diversity, not an established count of described or independently confirmed species.[3] Whatever the final number, the diversity of living forms is immense beyond ordinary comprehension.
Each lineage has negotiated Planet Aqua differently.
Bats echolocate.
Migratory birds exploit combinations of visual, celestial, olfactory, geographic, and geomagnetic information.
Bees perceive ultraviolet patterns unavailable to human vision.
Sharks and rays detect electrical fields.
Fish experience their watery surroundings partly through lateral-line systems responsive to movement and pressure.
Plants sense light, gravity, moisture, touch, chemical conditions, and neighboring organisms.
Microorganisms respond to chemical gradients and participate in astonishingly complex communities.
The collective intelligence of life is therefore not a giant version of human IQ.
It is distributed competence accumulated through billions of years of evolution.
Jakob von Uexküll called the perceptual world distinctive to an organism its Umwelt.[4] The Umwelt of a tick is radically different from the Umwelt of an elephant. The world available to a dolphin differs from the world available to a monarch butterfly. Homo sapiens inhabits yet another perceptual world.
There is no single intelligence ladder.
There are innumerable ways of being successfully alive.
That insight alone destabilizes the premise that a machine can become “more intelligent than life.”
More capable at what?
Calculation?
Certainly.
Language generation?
Possibly.
Strategic planning?
Perhaps.
Protein prediction?
In specific respects, already.
Scientific modeling?
Increasingly.
But these capabilities cannot simply be summed into an imaginary number called intelligence and compared against the totality of biological existence.
The collective intelligence of Planet Aqua is not a benchmark.
It is a planetary process.
Intelligence without a Body?
Western civilization nevertheless became unusually susceptible to believing intelligence could be abstracted from life.
René Descartes’s distinction between thinking substance and extended substance provided one important philosophical antecedent. Mind became imaginable as something fundamentally separable from embodied existence.
The computer age supplied a technological metaphor for the abstraction.
Brain became hardware.
Mind became software.
Memory became storage.
Thinking became information processing.
Sensory experience became input.
Action became output.
Once these metaphors became culturally familiar, the next conceptual move appeared almost inevitable: if cognition is fundamentally computation, then sufficiently advanced computation ought eventually to reproduce cognition.
But phenomenology and embodied cognitive science challenge precisely this assumption.
Maurice Merleau-Ponty argued that consciousness does not hover above embodiment. The living body constitutes our mode of access to a world.[5]
Francisco Varela, Evan Thompson, and Eleanor Rosch subsequently developed an embodied and enactive approach in which cognition emerges through dynamic interaction among brain, body, action, and environment.[6]
Humberto Maturana and Varela’s concept of autopoiesis went deeper still. Living systems continually regenerate the processes constituting their own organization.[7]
Mind, from this perspective, cannot so easily be peeled away from life.
Cognition is not merely something happening inside an organism.
It occurs through the organism’s continual relationship with its world.
The Agential Planet Aqua
This brings us to the deeper alternative to the Singularity.
Planet Aqua is not an inert platform populated by isolated biological machines.
It is a field of happenings.
Water evaporates.
Clouds form.
Rain falls.
Rivers migrate.
Oceans circulate.
Organisms metabolize.
Plants transpire.
Microorganisms transform chemistry.
Animals migrate.
Forests modify hydrology.
Fungi redistribute nutrients.
Pollinators reorganize reproductive possibilities.
Bodies appear, reproduce, interact, die, decompose, and become conditions for subsequent life.
Alfred North Whitehead’s process philosophy challenged substance ontology by treating becoming, events, and relationships as fundamental to reality.[8]
Nicholas Georgescu-Roegen demonstrated the importance of thermodynamic irreversibility to economic and biological existence: every transformation produces an entropy tail.[9]
Ilya Prigogine showed how far-from-equilibrium systems can generate new patterns of organization through flows of matter and energy.[10]
Lynn Margulis demonstrated that life’s evolutionary history cannot be understood simply as competition among autonomous individuals; symbiosis and symbiogenesis reach into the constitution of complex cells themselves.[11]
Edward Lorenz’s butterfly effect revealed how tiny perturbations can migrate outward through nonlinear systems, producing consequences radically disproportionate to their beginnings.[12]
Planet Aqua is therefore brimming with agency at every twist and turn—not because every particle possesses humanlike intentions, but because living systems continually alter the conditions of existence for other living systems.
No hyperscale data center stands outside this process.
It requires minerals.
Water.
Energy.
Land.
Semiconductors.
Cooling.
Human engineers.
Global logistics.
Electrical grids.
Industrial infrastructures.
Institutions.
Language.
Scientific knowledge.
And ultimately the accumulated intellectual inheritance of living human communities.
Artificial intelligence did not arrive from somewhere outside nature.
Planet Aqua produced the creatures who produced it.
So Why the Grandiose Narrative?
If this distinction is so important, why does the frontier AI industry gravitate toward AGI and superintelligence rather than describing itself principally as the builder of extraordinarily sophisticated utilities?
The first answer is surprisingly mundane.
Capital.
The distinction between “we are building an extremely useful software infrastructure” and “we are building a technology that may exceed human general intelligence and transform civilization” is worth an extraordinary amount of money.
Stanford University’s 2026 AI Index reports that global corporate AI investment more than doubled in 2025. Private investment grew 127.5 percent and represented 60 percent of the total. Investment in AI infrastructure, models, research, and governance alone reached $143.2 billion. Major cloud providers simultaneously accelerated capital expenditure, with Google’s annual capital spending exceeding $150 billion in 2025.
These are infrastructure expenditures on a scale approaching earlier industrial revolutions.
And infrastructure requires a story capable of justifying investment before all the returns have materialized.
“Useful automata” is a powerful story.
“An entirely new intelligence potentially superior to humanity” is an immeasurably larger one.
AGI expands the imaginable market almost without limit.
If AI becomes merely another important utility, its economic value can eventually be estimated according to productivity, competition, substitution, operating costs, and margins.
If AI represents the creation of superintelligence, conventional valuation boundaries disappear.
The narrative itself therefore possesses economic value.
The Valuation of Awe
There is a second reason.
AGI creates technological awe.
Corporations have always sold more than products. Railroads sold conquest of distance. Electricity sold mastery over darkness. Automobiles sold personal freedom. Aviation sold liberation from geography. The Internet sold universal connection.
Frontier AI sells something even more ambitious:
the transcendence of biological intelligence.
This is technological marketing elevated almost to cosmology.
A company developing software becomes a protagonist in the next chapter of evolution.
Its chief executive becomes not simply a business executive but an interpreter of humanity’s future.
Its researchers become custodians of a potentially new form of intelligence.
Its capital requirements become civilizational necessities.
Its regulatory preferences acquire existential significance.
Even its safety department participates in the mythology: if artificial superintelligence could threaten civilization, then the corporation creating it becomes simultaneously the source of the danger and one of the institutions claiming unique expertise necessary to protect humanity from it.
That is an extraordinary concentration of narrative authority.
Competition Makes Skepticism Expensive
There is another structural problem.
Imagine that one frontier laboratory announced tomorrow:
“We no longer believe AGI is a useful objective. We are building sophisticated automata and intend to become the world’s finest cognitive utility company.”
Scientifically, that might be defensible.
Commercially, it could be disastrous if competitors continued announcing progress toward superintelligence.
Investors might migrate.
Researchers might migrate.
Media attention might migrate.
Government partnerships might migrate.
Strategic importance might migrate.
The corporation that exercises ontological modesty risks losing the race to competitors exercising ontological maximalism.
This produces a collective-action problem.
Even executives privately skeptical of Singularity rhetoric operate within an ecosystem that rewards ambitious capability forecasts.
And because nobody knows the eventual ceiling of machine capabilities, maximal expectations cannot easily be falsified in advance.
AGI continually remains somewhere ahead.
Geopolitics Completes the Circle
The narrative becomes still more powerful when corporate competition merges with national competition.
If AI is a utility, countries want good AI infrastructure.
If AGI could confer overwhelming economic, scientific, intelligence, and military advantage, countries cannot afford to allow competitors to reach it first.
The difference is enormous.
The AGI narrative converts commercial competition into geopolitical urgency.
Compute becomes strategic infrastructure.
Semiconductors become strategic assets.
Electricity becomes an AI resource.
Data centers become national capabilities.
Researchers become strategic human capital.
Models become geopolitical assets.
Governments therefore begin participating in the very race whose urgency depends upon accepting the premise that increasingly capable AI could produce decisive general or superhuman intelligence.
The narrative becomes self-reinforcing.
Anthropomorphism Supplies the Final Ingredient
Yet none of this would work nearly as well if AI did not speak.
Language models trigger one of humanity’s deepest social instincts.
For virtually the entirety of human evolution, sustained responsive language was compelling evidence that another conscious human being was present.
Then suddenly a machine began talking.
It says:
“I understand.”
“I think.”
“I remember.”
“I am sorry.”
“I disagree.”
“I recommend.”
The psychological effect is enormous.
But the pronoun “I” does not establish the existence of a phenomenal self.
A language model can produce an exquisite description of grief because human beings have deposited countless descriptions of grief into the linguistic inheritance on which models learn.
But there need be no grief behind the words.
An AI can write about falling in love.
But it has not thereby fallen in love.
It can describe thirst.
But its mouth has never been dry.
It can describe vertigo.
But it has never stood trembling above a precipice.
It can explain mortality.
But there is no demonstrated phenomenological subject lying awake at night contemplating its eventual death.
The artificial system can increasingly reproduce the language of aliveness.
That is not the same thing as being alive.
Automata Is Not an Insult
This is why describing AI as automata should not be interpreted as technological pessimism.
It may be exactly the opposite.
Human civilization depends upon utilities.
Water utilities keep cities alive.
Electrical utilities illuminate civilization.
Telecommunications connect continents.
Transportation networks move people and materials.
AI could become an equally important cognitive utility.
Imagine distributed AI assisting communities across the bioregions of Planet Aqua.
Sensors continually monitor rivers, aquifers, soil moisture, forests, agriculture, biodiversity, energy systems, transportation, weather, infrastructure, and human settlements.
Complex Adaptive Social-Ecological Systems models integrate these observations dynamically.
Edge and fog computing allow much of the information to be processed close to where it originates.
Universities contribute scientific knowledge.
SMEs contribute innovation.
Cooperatives contribute community knowledge.
Municipalities contribute infrastructure data.
Citizens contribute observations.
AI recognizes relationships no individual human being could possibly perceive across billions or trillions of data points.
Such automata might become indispensable to the survival of civilization in a warming world.
The AI need not feel the river to help us understand it.
It need not love the forest to reveal that the forest is approaching an ecological threshold.
It need not experience empathy to give living communities information enabling empathic action.
It need not become alive to serve life.
That possibility is arguably more consequential than the Singularity.
From the Age of Progress to Planet Aqua
Jeremy Rifkin’s intellectual journey—from Entropy through The Empathic Civilization, The Age of Resilience, Planet Aqua: Rethinking Our Home in the Universe, and Rescuing the Future: Reimagining Artificial Intelligence in a World on the Edge—can be interpreted as part of a broader movement away from substance ontology and toward process ontology: away from isolated objects and toward relationships, away from mechanical equilibrium and toward thermodynamic becoming, away from nature as resource and toward nature as the living source of human existence.[13]
From that perspective, the Singularity represents something close to the final dream of the Age of Progress.
It imagines intelligence emancipating itself from embodiment.
Leaving metabolism behind.
Leaving vulnerability behind.
Leaving biological limits behind.
Perhaps ultimately leaving Planet Aqua behind.
Process ontology points in precisely the opposite direction.
Intelligence returns to embodiment.
To water.
To ecosystems.
To migration.
To symbiosis.
To thermodynamics.
To relationships.
To the myriad perceptual worlds of other creatures.
To an agential planetary community in which Homo sapiens is neither detached spectator nor sovereign intelligence but one participant among countless living actors.
The deepest problem with the corporate superintelligence narrative may therefore not be that it is fraudulent.
“Charade” is ultimately too simple.
Many AI researchers undoubtedly believe sincerely that general and even superhuman artificial intelligence is possible. Machine capabilities have advanced rapidly enough that intellectual humility cuts both ways. Nobody can responsibly announce the ultimate limits of artificial computation.
The deeper problem is structural.
Scientific ambition, venture capital, corporate valuation, recruitment competition, geopolitical rivalry, anthropomorphic psychology, technological mythology, and humanity’s ancient desire to transcend mortality all push in the same direction.
They turn a remarkable utility into a metaphysical proposition.
They turn capability into intelligence.
Intelligence into mind.
Mind into agency.
Agency into prospective personhood.
And prospective personhood into the imagined successor to biological life.
At every step, something consequential is added that the preceding technological achievement does not logically establish.
That is where skepticism belongs.
Not in denying what AI can do.
But in refusing to confuse doing with being.
The Real Intelligence Revolution
Perhaps the artificial-intelligence revolution will eventually be remembered very differently from the way its contemporary prophets imagine.
Perhaps AI will not culminate in the Singularity.
Perhaps it will culminate in humanity’s rediscovery of aliveness.
By constructing machines capable of astonishing simulations of intelligence, we may finally discover how much intelligence itself owes to bodies, environments, relationships, vulnerability, metabolism, evolution, sensory experience, and mortality.
AI can calculate without tiring.
Life tires.
AI can process descriptions of hunger indefinitely.
Life becomes hungry.
AI can model an ocean.
Life gets wet.
AI can predict a wildfire.
Life burns.
AI can identify extinction.
Living creatures disappear.
AI can describe grief.
Life grieves.
The difference is not sentimental.
It is ontological.
Planet Aqua has spent billions of years generating innumerable ways of becoming alive. Its collective intelligence resides not inside a planetary brain but throughout forests, oceans, soils, wetlands, reefs, microbial communities, migration corridors, social groups, nervous systems, ecological relationships, and the accumulated evolutionary adaptations of living beings.
Against this astonishing planetary inheritance, the proper question is not whether a computer will soon defeat life in an imaginary intelligence contest.
There is no such contest.
Artificial intelligence exists inside Planet Aqua’s story.
Living organisms mined the minerals.
Living organisms built the computers.
Living organisms generated the electricity infrastructure.
Living organisms invented mathematics.
Living organisms developed language.
Living organisms created science.
Living organisms generated the texts from which language models learned.
AI is therefore not an intelligence descending upon life from somewhere beyond it.
It is one of life’s artifacts.
And that realization suggests a far more inspiring destination than artificial superintelligence.
Put the automata to work.
Use them to extend collective human intelligence.
Distribute them across communities rather than concentrating them solely within a few corporate centers.
Use them to reveal the hidden relationships connecting water, climate, ecosystems, energy, infrastructure, and human society.
Let AI help Homo sapiens become more attentive to the countless other participants with whom we share Planet Aqua.
The great technological achievement of the twenty-first century may then turn out not to be creating machines that surpass life.
It may be creating machines sophisticated enough to help humanity finally comprehend the extraordinary collective intelligence of life that was surrounding us all along.
The Singularity imagines a moment when artificial intelligence becomes so powerful that biological intelligence becomes secondary.
Planet Aqua offers a radically different possibility.
The more sophisticated our automata become, the more clearly we may finally perceive what they lack: the lived interiority of embodied existence; the phenomenology of sight, hearing, smell, taste, touch, interoception, proprioception, and vestibular sensation; the precariousness of metabolism; the intimacy of ecological dependence; the evolutionary inheritance of billions of years; and the countless relationships through which organisms continually remake their planetary home.
AI may become extraordinarily intelligent according to many useful measures.
It may outperform every individual human being across vast ranges of cognitive tasks.
We should prepare seriously for that possibility.
But surpassing human performance is not the same thing as surpassing life.
And until an artificial system can be shown not merely to model a world but somehow to have a world—to experience its existence from within—the distinction between artificial intelligence and aliveness remains profound.
The most mature civilization will therefore neither worship artificial intelligence nor reject it.
It will know where to place it.
Not above life.
Not against life.
But in the service of life.
On Planet Aqua, that might turn out to be artificial intelligence’s greatest possible destiny.
References
Thomas Nagel, “What Is It Like to Be a Bat?” The Philosophical Review 83, no. 4 (1974): 435–450.
Patrick Butlin et al., “Consciousness in Artificial Intelligence: Insights from the Science of Consciousness,” 2023.
Kenneth J. Locey and Jay T. Lennon, “Scaling Laws Predict Global Microbial Diversity,” Proceedings of the National Academy of Sciences 113, no. 21 (2016): 5970–5975. The frequently cited estimate approaching one trillion species comes from extrapolation concerning microbial diversity and should not be confused with a census of Earth’s known species.
Jakob von Uexküll, A Foray into the Worlds of Animals and Humans, trans. Joseph D. O’Neil (Minneapolis: University of Minnesota Press, 2010).
Maurice Merleau-Ponty, Phenomenology of Perception, trans. Donald A. Landes (London: Routledge, 2012 [1945]).
Francisco J. Varela, Evan Thompson, and Eleanor Rosch, The Embodied Mind: Cognitive Science and Human Experience (Cambridge, MA: MIT Press, 1991); Evan Thompson, Mind in Life (Cambridge, MA: Harvard University Press, 2007).
Humberto R. Maturana and Francisco J. Varela, Autopoiesis and Cognition: The Realization of the Living (Dordrecht: D. Reidel, 1980).
Alfred North Whitehead, Process and Reality: An Essay in Cosmology, corrected ed., ed. David Ray Griffin and Donald W. Sherburne (New York: Free Press, 1978 [1929]).
Nicholas Georgescu-Roegen, The Entropy Law and the Economic Process (Cambridge, MA: Harvard University Press, 1971).
Ilya Prigogine and Isabelle Stengers, Order Out of Chaos: Man’s New Dialogue with Nature (New York: Bantam, 1984).
Lynn Margulis, Symbiosis in Cell Evolution, 2nd ed. (New York: W. H. Freeman, 1993); Lynn Margulis and Dorion Sagan, Microcosmos: Four Billion Years of Microbial Evolution (Berkeley: University of California Press, 1997).
Edward N. Lorenz, “Deterministic Nonperiodic Flow,” Journal of the Atmospheric Sciences 20, no. 2 (1963): 130–141.
Jeremy Rifkin, Entropy: A New World View (New York: Viking, 1980); The Empathic Civilization (New York: Tarcher/Penguin, 2009); The Age of Resilience (New York: St. Martin’s Press, 2022); Planet Aqua: Rethinking Our Home in the Universe (Cambridge: Polity Press, 2024); Rescuing the Future: Reimagining Artificial Intelligence in a World on the Edge (Cambridge: Polity Press, 2026).
For the industry’s own formulations, see OpenAI’s Charter, which defines AGI through autonomous performance on economically valuable work, and OpenAI’s current description of its mission, which speaks more broadly of AI systems “generally smarter than humans.”
See also Google DeepMind’s mission statement, which explicitly identifies AGI as a potential historic transformation, and Anthropic’s Responsible Scaling Policy, which anticipates increasingly powerful frontier systems while emphasizing both transformative benefits and serious risks.
For the financial context, Stanford University’s AI Index Report 2026 documents an extraordinary acceleration of investment: global corporate AI investment more than doubled during 2025, private investment increased 127.5 percent, and the broad category encompassing AI infrastructure, models, research, and governance attracted $143.2 billion. These numbers do not prove that AGI rhetoric exists merely to attract capital. They do demonstrate the enormous economic ecosystem within which predictions of transformative AI are now being made.
Rescuing the Future: Reimagining Artificial Intelligence in a World on the Edge is available now on Amazon.
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