Navigating the Digital Frontier as Blockchain and AI Collide
As history has unfolded, distinct innovations have invariably marked the dawn of new epochs — resulting in the dispersion of value and information.
Introduction
The printing press and double-entry bookkeeping broke aggregation in information and value, paving the way for intellectual and economic advancement.
Early inventors crafted calculators, looms, and difference engines — automating manual labours one cog at a time. Today, in the intricate fabric of the digital realm, two titans rise as providers of automation: Artificial Intelligence (AI) and Blockchain technology. A new epoch awaits us once more — the question is, how do we arrive there?
AI is mastering not just routine tasks but higher faculties like strategy, language and creativity. These systems ingest vast swaths of data as they strive for omniscience and prescience, portending an imminent age of unbound knowledge and infinite creation.
AI symbolises a world of endless possibilities. In juxtaposition, blockchain is anchored to digital scarcity. Bitcoin’s fixed cap of 21 million coins sparked a movement rooted in cryptography and restraint. Blockchain public ledgers encode trust through transparency, engraving immutable records of value exchange across decentralised networks.
Embracing open-source, this tech grows — meticulously, deliberately.
Public discourse swirls over the nature of AI’s essence; will it be open for all or protected behind proprietary walls? This draws parallels to ancient debates between the sovereign and the subservient. The Middle Ages’ reluctant transition to the Renaissance witnessed a pendulum swing in power dynamics. Aggregated sources shifted to more distributed ones.
This piece posits that today’s society and economy will mirror those undulations. This reshaping is inexorably linked to AI, a synthesiser of information, and Blockchain, a conductor of value. AI looks to a future unbounded by human constraints. Blockchain reconsiders how to engineer systems resilient to human excesses. Their intersection seems improbable, but therein lies the magic…
At the intersection of AI and Blockchain, a symbiotic relationship is beginning to emerge. AI’s ever-adaptive algorithms will bolster Blockchain’s utility and security. Reciprocally, Blockchain can provide an unassailable chronicle of AI’s journey and choices.
Open vs. Closed Source Explored
Historically, secretive orders have guarded the arcane logics that animate the minds of those that hold power. Complex sigils scrawled on concealed parchment, hidden away in remote monasteries and elite campuses were only accessible to the privileged few.
Centuries later, our era is similarly marked by the concentration of power, secretive orders having been replaced by nation-states and colossal corporations.
Nations? They centralise administrative functions, mould national identity, and grip economies tightly.
Corporations? They sway governments, mould minds through media, co-opting nascent technologies to dominate globally.
With regards to value, the information age has heralding unprecedented productivity, but paradoxically its benefits accrue to a few digital overlords. The vast majority of contributors and the broader community have been left in the shadows.
Regarding information, while access has broadened, the control has tightened, leading to an age of surveillance, censorship, and subtle manipulations.
Thankfully the spirit of openness struggles against these walled fortresses, and it has the power to uplift AI and enlighten the masses. Just as the printing press did, open source AI can liberate knowledge like a manifesto nailed on the fortress gates.
Exploring this dichotomy, we see that open and closed models of AI development mirror their different philosophies. Open source AI liberates knowledge into the collaborative commons, aiming for radical transparency. Its very core is accessible to all, allowing a multitude of minds to mould, refine, and propagate it. It promotes universal access and continuous improvement by the collective genius of the hive mind.
Yet such unfettered freedom requires diligent administration to prevent misuse — governance and quality control become thorny in radically transparent systems.
In contrast, closed models allow for commercial control and tighter oversight that prevents misuse. Here, Big Tech incumbents exert dominion over their prized innovations, ensuring both proprietary advantage and an unblemished standard of quality and security. But these fortified walls, while safeguarding treasures, may occasionally stifle collective innovation. And opacity leads to distrust, and progress inevitably bottlenecks.
While microchip performance has increased a hundredfold in recent decades, closed sourced software’s inability to scale at even linear rates is not only recognised, but dissected by scholars[¹]:
In contrast open source programs (e.g. Linux) exhibit geometric growth rates[2], breaking the inverse squared barrier constraining most traditionally built computer programs. In other words, open source software is less constrained, evolves faster and can better address markets.
Alongside technology, it is these markets and the open sharing of ideas that leads to prosperity for people and increases in standards of living as argued by Matt Ridley in The Rational Optimist[3]. The cross-pollination of ideas is crucial for innovation. When people from different cultures interact, their unique perspectives combine for novel solutions to problems.
As Charlie Edwards argued for the metaverse, I posit here that both paradigms have their rightful place in the digital pantheon. Open source AI catalyses innovation to paint a horizon of shared dreams; closed source AI carves out niches for unique masterpieces. But the former? It promises a brighter tomorrow, ushering in a new “Age of Enlightenment”
The Confluence of Blockchain and AI
As a new digital epoch unfurls, blockchains stand tall, casting luminous trails for AI to tread. With their hallmarks of transparency, immutability, and decentralisation, blockchains transform from a mere ledger to a lighthouse of trust for AI.
Every move? Clear. Every operation? Counted. Blockchain pulls AI from the shadows — it transforms from an enigmatic force to a transparent and verifiable entity.
Yet, hurdles exist across computing, lawmaking, and design. Transitioning from opaque institutions to clear communities challenges society. Standards emerge gradually through trial and error. And certain industries and interests will resist losing control over their data and algorithms. This presently manifests as calls for regulation; but it’s a calculated move by the incumbents, aiming for regulatory capture from the inside out[4].
Quoting George Stigler, the 1982 Nobel Prize winner in economics: “…as a rule, regulation is acquired by the industry and is designed and operated primarily for its benefit…”
Or said another way, regulation favours the incumbent. Special interests are prioritised over the general interests of the public.
If this substantial challenge can be overcome, open and decentralised AI promises major shifts:
First, AI transparency: Instead of proprietary models restricted to Big Tech, there will be open publication of AI models. Boosting innovation through collaboration and shared knowledge.
Second, assured provenance with on-chain records: Blockchains ensure traceability. With transparent training data, we tackle biases, build public trust, and make AI outcomes auditable. As AI informs high-stakes decisions across healthcare, justice, and finance, data and compute verifiability becomes imperative.
Third, AI democratisation: AI models, stored and traded on-chain, become accessible. Crypto networks open data markets where individuals control and benefit from their data.
Fourth, fair and algorithmic incentives: Remunerate people for contribution and keep systems stable and secure. Users get paid for feedback, fixing AI biases. Decentralised networks reward for the provision of distributed compute and data storage.
Fifth, community-driven evolution: Instead of a central power the community oversees, using on-chain tools like token voting. Collective consensus, not top-down decisions. Oversight by fork rather than fiat.
Finally, ubiquitous automation: The emergence of protocols to enable autonomous AI agents and provide services in prediction markets, capital management, and more.
Decentralised and transparent systems self regulate. It’s the “triple” aspect of the notion of “triple entry bookkeeping” — everyone can see what you’re doing.
Decentralised Data and Compute Substrate
Computations and data are the lifeblood of AI. By wrapping these services on-chain, provenance is assured, trust imbued, privacy provided, access controlled, rewards dispersed, and monetisation possible. The path is paved for innovations like decentralised machine learning and expansive data analytics.
The amount of compute required in this future world cannot be underestimated — a scarce resource that is already stretched.
Ethereum can compute, but it can’t compute that much, and neither can rollups, even five layers deep. Instead this stuff requires its own chain to manage, monitor, secure and authorise its resources. Decentralised compute networks will leverage idle GPUs dispersed around the globe. They herald the construction of a deep, asynchronous pipeline where parallel tasks can overlap.
By eliminating the majority of costs within centralised data centres (servers, rent, AC and people) and allowing individuals to capitalise on already purchased hardware — it makes AI training more scalable and affordable. According to recent research from UCLA, decentralised computing can offer up to 2.75x more performance-per-dollar than traditional GPU servers.
DeComp allows interconnected systems, geographically dispersed, to work together to solve a problem. Over very large datasets where you can’t afford a system to fail halfway through. But most importantly private data (clinical or genetic) that can’t be piped into data centres. Instead, a swarm of compute must come to it.
Data is the biggest rate-limiter to AI advancement — the focus should be on making data sets more accessible, providing an outlet for a wide range of use cases. Data NFTs provide sovereignty. Tokenised protocols for lineage. Smart contracts for revenue splits.
Envisioning a Decentralised Renaissance
The collision of these two technologies has the potential to decentralise power, moving from giants to the people, redefining our interaction with authority.
The convergence of AI and blockchain could unlock new possibilities and drive innovation in various domains.
This synergy unfurls on the horizon, stirring up sectors from decentralised finance to supply chain logistics, healthcare paradigms such as decentralised science, the metaverse, social entertainment, and educational frameworks. But like all journeys into the uncharted, it’s marked with caution tape. We must thoughtfully understand challenges such as job displacement, centralisation of power, and alignment risks.
Yet, the implications are profound. Industries could witness a surge in efficiency, transparency, and customer empowerment. Society stands at the cusp of deeper privacy, inclusive economics, and democratised resources. To shepherd this evolution, robust laws, symbiotic alliances, and global engagement are essential.
Here at ID Theory, we make principled investments into decentralised networks through four themes. This essay has described how decentralised infrastructure can power an AI revolution, but we also have been thinking deeply about the impacts on our other core investment areas.
Within decentralised finance, operations are streamlined. Security is enhanced. AI driving smart contracts will bring them to life. Automated execution. Algorithmic risk management. Optimal pricing strategies. Everything gets a revamp. And fresh, innovative solutions will emerge such as DeFiGPT that you can ask, in plain language, to optimise your yields.
Pharma is ripe for disruption. Decentralised science, as a movement, eliminates both institutional and geographic barriers, thereby catalysing innovation and scientific advancement. Moreover, open-source AI is fuelling this innovative surge. Tools such as AlphaFold and ProteinMPNN play pivotal roles in enabling and speeding up breakthroughs, and blockchain technology has the potential to further enhance their prowess.
And in the metaverse, Autonomous Worlds will emerge, persistent in form and offering new forms of entertainment. These have been addressed extensively in our other essays.
However, the most exciting implementations are Autonomous AI Agents, completely free to transmit value and information in any way they want.
Rise, Autonomous Agents
In describing the several shifts that blockchain will drive in decentralised AI, the final point described autonomous AI agents as a benefactor of such integrations. They don’t merely follow orders; they perceive, they think, they act (assert agency) within their environment to achieve predefined objectives.
They can duplicate, collaborate, and streamline workflows. They will engineer constructs that transcend human limitations — crafting complex clockwork, code and circuits to augment our own ingenuity. Akin to grandmasters of chess, they assimilate information, strategise, and execute actions autonomously, perpetually contemplating myriad possibilities and refining their approach based on their unfolding comprehension of reality.
The emergence of autonomous AI agents will catalyse immense transformations and totally reshape work and society. Blockchain allows multi-agent systems to be co-owned and aligned by global communities. Developers are incentivised to constantly improve codebases. Evolution by competition in a 24/7 economic pvp battleground. As these agents march forward into the unknown, we stand on the cusp of novel paradigms and vocations.
Escaping from the confines of top-down cathedral designs, these agents will be the drivers of the bottom-up bazaars and shape our future economy. And that? Well, that’s a tale for another time.
Conclusion
The promise of this convergence, coupled with the emergence of autonomous AI agents, provides a tantalising prospect for crypto investments. With institutions scared off by regulators and retail burned by frauds, it may herald a fresh influx of capital and activity, as discussed in my next essay, invigorating the crypto ecosystem from its very core.
Blockchain and AI belong together. Transparency. Accessibility. Antifragility. The repercussions on industry are widespread, ushering in transformative business models and democratising access to knowledge.
In front of us lay the tools to unlock an automated awakening — we can push away inequities, and shun fragmentation — transforming AI into a public good that serves all of humanity. But, as with any transition, prudence is vital.
Every renaissance has its maelstroms and our voyage is not without its tempests — technical amalgamations, the fickle nature of crypto markets, regulatory quagmires, and ethical quandaries loom large. Economic arenas where agents tussle and toil over digital commodities will inevitably be open to attack and exploitation. And so, navigating these intricacies becomes paramount for the sustained evolution of this revolution.
Standing at this juncture, it truly appears that we sit upon the precipice of a renaissance, with AI and blockchain poised to orchestrate a symphony of change, the echoes of which resonate with boundless possibilities.
References:
[1] https://www.salon.com/2002/04/08/lehman_2/
[2] W. Godfrey, Michael & Tu, Qiang. (2000). Evolution in Open Source Software: A Case Study. Proceedings of the International Conference on Software Maintenance (ICSM 2000). 131–142.
[3] Ridley, M. (2010) The Rational Optimist. HarperCollins Publishers.
[4] https://www.youtube.com/watch?v=F9cO3-MLHOM
[5] Generative Agents: Interactive Simulacra of Human Behavior, Joon Sung Park, Joseph C. O’Brien, Carrie J. Cai, Meredith Ringel Morris, Percy Liang, Michael S. Bernstein
[6] https://www.science.org/doi/10.1126/scirobotics.abm4636
[7] https://pixelink.substack.com/p/where-humanism-meets-the-metaverse
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