Artificial Learning (AI) has been defined as the single biggest disruptor of the information technology industry, changing the world as we know it and contributing to the forward march of human endeavors.
AI- a game changing technology is everywhere and all the big tech players want a piece of this cake while it is still being served hot off the plate.
From game theory to military strategies, newsletters to video games, urban planning to digital finance- AI tools are redefining how we perceive real life problems and approach their solutions.
AI, indeed, is the future and we are in the middle of a massive shift.
Therefore, it is no surprise that AI related cryptocurrencies have seen price increase exponentially over an extremely short period of time.
Blockchain technology- an open source movement, is poised as a natural partner of AI. It has provided solutions against problems of cost efficiency, bias, clutter, and extreme dependence on data in the AI world.
Therefore, it is imperative to say that the future will belong to a collaboration of AI and Blockchain technology and will create massive ripples.
Blockchain x AI
We are already witnessing numerous instances of companies combining blockchain and AI technologies.
0G claims to be the first modular AI chain as it just announced a $35 million funding round to continue building a data availability solution that specifically caters to generative AI.
This makes it easier to build on-chain AI integrations.
Similarly, HyperCycle is building an AI-to-AI communication network. It is often referred to as the “AirBNB for AI compute”. It is a peer-to-peer network designed to offer cheaper and more accessible compute. At the end of February 2024, it was reported that they had more than 347,000 nodes in their compute network. They’re making a globally accessible platform for AI collaboration.
Consensus Learning (CL)- the future of decentralized Machine Learning
Recently, the Flare research team released a paper introducing Consensus Learning (CL). This innovative approach aims to make decentralized machine learning more efficient and secure. Let’s take a look at what Consensus Learning (CL) is and why it matters.
What Is Consensus Learning (CL)?
In essence, CL uses blockchain technology to create decentralized AI models. Blockchains rely on nodes or participants in a network to come to consensus.
For CL, the consensus happens in two stages.
Stage One is the individual learning phase. At this stage, each participant in the network builds their own model, which can either be trained from scratch or fine-tuned with new data. Once the model is ready, it is used to create predictions on a set of test data.
Stage Two is where the network reaches a consensus. We may call this phase the communication phase where participants in the network submit their initial predictions. A consensus/gossip protocol coordinates this and during this process, participants continuously update their predictions. The process not only allows the participants to reflect their assessments but also reveal their confidence in their own predictions.
When the nodes in the network agree on the best output or decision, a consensus is reached.
Why Use Consensus Learning?
Data privacy is the most important feature of CL framework as the underlying model of each node or participant in the network remains private and by extension, none of the underlying data is shared. Such a structure allows users to implement sensitive data for machine learning.
CL also facilitates and encourages many different participants which results in creation of a pool of diverse data which is then combined to create the final output. This increases performance and makes the output from this process more reliable. It reduces bias and enhances models’ ability to generalize on unseen data. CL makes it harder to introduce unreliable data to the model.
Also Read: Crypto Marketing Strategies with AI for 2024 Growth
The Road ahead
Consensus learning is an amalgamation of blockchain and AI technologies- a natural match made to solve upcoming challenges in the industry. In the near future, we are bound to witness an increase in the collaboration between the two technologies.