Blockchain has been one of the most impactful technologies over the past two decades, now supporting a $2.1 trillion crypto market. This technology has also been integrated across other vital industries, including supply chain management, finance, and healthcare.
That’s just the scratch of it; blockchain’s capabilities are proving to be a game-changer in the Artificial Intelligence (AI) space, which at the moment is the coolest kid in the block. Almost every big tech company is currently expanding its AI footprint and generative AI tools such as GPT, DALL-E, and Midjourney have become everyday applications for most people.
So, where does blockchain fit in this futuristic world where machines are edging closer and closer to human intelligence? Before diving into the details, it is worth noting that both technologies actually complement each other, but for this piece we will specifically focus on blockchain’s value proposition in the advancement of AI models and ecosystems.
Transparency in AI Operations
By design, blockchain infrastructures are built on the basis of transparency; for example, Bitcoin’s blockchain is a distributed and public ledger which can be audited by anyone. This aspect is also what makes it secure given that it is almost impossible to forge transactions or incorporate corrupted data on the blockchain.
As it stands, most AI projects are nowhere close to achieving transparency, an issue that has attracted criticism and questions on the data being used to train AI models. However, with blockchain technology, such challenges can be addressed. How exactly? Building AI models on auditable blockchain infrastructures, be it permissionless or hybrid ecosystems, would allow all the stakeholders to authenticate the legitimacy of any input.
IBM’s Watson’s is a good example of an AI product that has leveraged blockchain’s key properties in healthcare and logistics. In the former, blockchain helps to secure patients’ data and the maintenance of transparent medical records while in the latter, it enhances the tracking of goods as Watson AI handles logistics optimization.
Sourcing of Affordable Computational Resources
One of the biggest challenges facing AI at the moment is the competition for limited computational resources. A recent publication by the World Economic Forum estimates that the demand for AI computing resources is currently accelerating at an annual rate of between 26% and 36%. To make matters worse, big tech are edging out smaller players as a result of the rising computational costs associated with the demand-supply dynamics.
Instead of every AI builder or innovator relying on hardware resources produced by a handful of entities like Nvidia, it would be more economical to tap into the idle GPU space by billions of users across the world. Computational blockchain ecosystems such as Qubic can easily make this a reality. This Layer 1 blockchain has adopted an advanced mining model dubbed the Useful Proof-of-Work (uPoW) mechanism.
Unlike Bitcoin’s typical PoW, which consumes a lot of energy solely for network security and operational purposes, Qubic’s uPoW directs its additional computational power towards AI productivity. This includes tasks such as training artificial neural networks (ANNs) that power Qubic’s blockchain-based, open-source AI software, Aigarth.
More importantly, Qubic’s uPoW mining network has the capacity to scale into the thousands, allowing its decentralized computational power to be used for training billions of ANNs.
Decentralized & Automated Marketplaces for AI Services
While the AI industry has scaled significantly within the past two years, it is still operating in siloed ecosystems. The big tech who are currently the frontrunners are in competition mode on who will capture the market share. But at a cost to the consumer – some of the products being pushed out are clearly not fine tuned or could do better if they borrowed or integrated some aspects from their counterparts.
In other words, the current rush on who will be the best does not support a collaborative market environment that innovators can seamlessly tap into.
On the brighter side, decentralized AI service markets powered by blockchain technology are popping up to fill this gap. One of such ecosystems is SingularityNET; this permissionless AI marketplace uses automated smart contracts to enable interested service buyers to deal with AI agents. In doing so, SingularityNET is not only making it possible for innovators to access the latest AI algorithms and applications, but for the owners of these services to monetize them on a global scale.
Data Privacy
By now, it is not a secret that AI programs require a lot of input data for them to be able to match human intelligence or achieve singularity (self-improvement) in the future. However, there are serious concerns on the violation of data privacy rights; for instance, OpenAI, the company behind ChatGPT was sued last year on claims of having used stolen data from millions of personal profiles to train its AI model. Unfortunately, this is not a unique case.
So, how can blockchain introduce a comfortable degree of privacy in AI development? There are some decentralized infrastructures such as the Ocean Protocol which are designed to support the AI market with privacy in mind. At the core, this open-source protocol facilitates the exchange of data and data-based services.
However, unlike big tech who are prone to violating consumer data, Ocean Protocol has built a feature to prevent this type of shortcoming; Compute-to-Data. Users can therefore share valuable data or services for AI training without necessarily revealing some parts of the information that they would like to keep private.
Conclusion
We’re living in the 21st century, an era where technological innovations currently dictate the trends. AI and blockchain are at the intersection of this futuristic world, and while they have yet to match the adoption levels of the internet, it is only a matter of time before the synergy between these two technologies unlocks a whole new dimension of utilities. It will be intriguing to watch how it unfolds; the future is interesting!
