The AI industry has always been the “futuristic view” for humans, whether in movies, cartoons, or real life. Computers work, think and act on behalf of futuristic humans – well, except in the Dune movies.
In the past half-decade, artificial intelligence has become the hottest topic in the world, second only to the Covid 19 pandemic, with most people fascinated by the industry’s massive growth and the extent they can use it. This growth is expected to continue at a rapid pace into the last years of the decade, with Statista predicting the $184 billion industry will grow to nearly $900 billion by 2030.
However, as the industry becomes a crucial part of our lives, which seems inevitable, it will shape how we think, interact with the world, and do the most basic and complex things in the future. We will be intertwined with it, probably more than we are today with the internet.
While still in its infancy stages, most powerful AI systems and models are controlled by mega-corporations such as OpenAI, IBM Watson, Google AI, and Amazon Machine Learning. These Big Tech firms own large data hubs, to train, build, and sell these models to users. This raises a very pertinent and justifiable fear amongst the common folk. Should we let this massive and dominant technological innovation be controlled by the billionaire de jour?
Satoshi was wary of the centralised financial institutions post-2008 global financial crisis and created Bitcoin to solve the centralisation conundrum. In a similar breath, AI needs similar solutions to remove the heavy hand of mega-corporations on what could be the “most important technological advancement in the past few decades”, as Microsoft’s co-founder Bill Gates called it in a blog post in 2023.
The problem with the current AI industry structure
As stated above, AI technology will be a way of life for ‘almost’ everybody on Earth, helping us complete very menial tasks to greater tasks. For instance, the growth of artificial general intelligence (AGI) can be used to create “AI secretaries”, or AI agents, that can help organise your calendar, pay your monthly bills, create a weekly diet schedule, or create your playlist. (“Hey AI agent X, can you create an R&B playlist including Beyonce, Ne-Yo, etc”)
While the data in the examples above may seem simplistic and elementary, such data is very important and personal for most people. Would you want to share such data with the Big Tech firms, who have time and again shown their willingness to use personal data only for profit?
Even more unsettling is that AI is being trained in more ‘human-related’ jobs that millions, and probably billions, of people need such as therapists and coaches. Millions of people will share their innermost thoughts, longings, fears, sexual desires, confessions, and embarrassments. Who would trust big tech with such information? It is already happening with ChatGPT, with more and more people using the AI tool to look for answers to their deepest personal questions.
This is the bottleneck of current AI systems and models – the centralisation of AI technology, monopolisation of data used to train the AI models, and privacy concerns by users. As such, several developers around the world are working on solutions that build sustainable AI models, without big tech firms’ prying eye on our personal data.
Blockchain, a decentralised and privacy-preserving technology, is being integrated with AI to ensure users enjoy the benefits of the technology without the toxicity of Big Tech.
A paradigm shift: The rise of decentralised AI services
Blockchain technology has been used extensively to correct the centralisation impact in the financial world and most industries, from supply chain to health care, etc.
Finally, the technology is extending its roots into artificial intelligence, helping democratise and decentralise the industry. The technology has enhanced data security and transparency through its immutable ledgers, transforming the global sharing of value and setting new standards for operational efficiency and transparency.
Integrating two of the most sought after technologies today, AI and blockchain, could be the key to having a free, open, and decentralised AI ecosystem. The primary goal of decentralised AI technologies is to democratise access to AI resources, including data, models, and compute power. This is crucial in minimising the oligopolised structures in AI, which limits the number of entities in the space due to the computational complexity and huge costs of data sets that are needed to train AI models.
For instance, NeurochainAI proposes an innovative solution to the challenges of centralised AI systems: a Decentralised AI Infrastructure As a Service (DeAIAS). Simply, NeurochainAI aims to break down the barriers of centralisation and monopolisation “by encouraging cooperation and coordination among various AI stakeholders,” its website reads.
Decentralised AI benefits developers and the general public in several ways:
- Decentralisation: Unlike the current AI models, a decentralised AI ecosystem allows a community of users to share resources such as computing power, data storage, algorithm processing, and model validation. These could be costly for any one company trying to build their models but by tapping into a global community of users the costs are reduced significantly.
- Ready-to-use infrastructure: NeurochainAI provides developers with a ready-to-use platform helping them develop their AI dApps faster and up to five times more cost-effectively compared to traditional methods. This promotes more innovation across the ecosystem, unlike depending on a few companies for all technological advancements.
- Incentivisation: One of the biggest benefits of a decentralised AI platform is rewarding the community for providing their resources. For instance, NeurochainAI rewards contributors with $NCN rewards, fostering a collaborative ecosystem where each participant plays a role in shaping the future of AI technology.
- Privacy and security of data: Decentralised AI also introduces an element of privacy of data. Given blockchain technology allows users to be the custodians of their data, only they choose what data to give to train the AI models.
- Active participation by the community: NeurochainAI is developed by the community and for the community. This involves community members actively participating in crucial AI training processes such as data curation and validation, algorithm processing, and model validation. This democratises AI development and enriches the models with diverse, real-world inputs.
The future of decentralised AI services
The rapid growth of artificial intelligence has ensured that many companies/individuals cannot create or train their AI models due to the phenomenal amounts of computing power needed. While centralised cloud computing was a ready solution for previous challenges of computing power, AI is different.
Decentralisation solves this problem by creating a network of nodes (computers) that harness the huge untapped computing power of CPUs across the world. This modular approach of decentralised physical infrastructure (DePIN) enhances scalability, provides a cheaper source of computing power than buying new servers, and increases community participation in training the AI models, allowing dApps to learn and share information with each other.
While decentralised AI is still at its infancy, the creation of platforms such as NeurochainAI will give Big Tech a run for its money – solving the monopolised nature of AI, computational complexity, and privacy of data for users.