If they haven't FUDed you, then you're not building anything worth FUDing.

Author: brody

Translation: DeepTechFlow

At first glance, "cryptocurrency and artificial intelligence" seems like a forced combination.

However, within these asymmetries, there are potential opportunities, and the risk-to-reward ratio seems heavily skewed towards the upside. This is why it's worth our time to delve into.

I'm often asked about my views on the integration of cryptocurrency and artificial intelligence, which prompted me to develop this simple framework:

• In what ways does blockchain introduce new advantages for the application of artificial intelligence?

• Which components of the AI technology stack are optimized through decentralized protocols?

• In what aspects do open-source decentralized AI applications achieve performance comparable to their closed-source competitors?

Overall, there are several key areas I'm focusing on to address these questions:

In what ways does blockchain unlock new advantages for the development of artificial intelligence?

Coordination Layer: These protocols aim to coordinate AI/ML developers to collectively create "intelligence" by offering their models and resources in exchange for rewards, typically based on the value generated by the intelligence.

This is why I'm so enthusiastic about Bittensor. It is massively achieving this goal (currently with 48 subnets and expanding), has a deep moat of talent, and a passionate token holder community that few ecosystems can emulate.

On the other hand, teams like Sentient, Allora, and Nous Research are also pursuing similar initiatives, albeit with different protocol designs and directions.

Incentive alignment is one of the core reasons why blockchain can effectively operate in the final stage, and this application's support for open-source AI development is fundamental.

People are gradually realizing this.

Which components of the AI technology stack are optimized through decentralized protocols?

Data: Accessing high-quality, validated, and robust datasets is crucial for artificial intelligence, but this is still a huge bottleneck. Optimizing the data collection process will help us break through the "data barrier."

Several teams we are closely monitoring are Grass and Vana, both of which are creating new efficient and optimized data collection mechanisms through incentives and ownership.

In short, Vana enables the realization of data DAO (decentralized autonomous organization), allowing users to contribute to unique datasets and receive corresponding rewards based on the specific data needs of AI developers.

In this field, several methodologies are being tested, all of which objectively outperform their Web 2 counterparts.

Data DAO Example

In what aspects do open-source decentralized AI applications achieve performance comparable to their closed-source counterparts?

Distributed Model Training: AI model training is a resource-intensive process involving training models to perform specific tasks by inputting large datasets through neural networks. Until a month ago, it was considered highly unlikely to carry out this process in a distributed manner.

Thanks to pioneers like Nous Research (DisTrO) and Prime Intellect (DiLoCo), breakthroughs in distributed model training for open-source and decentralized AI are accelerating, achieving performance parity with closed-source alternatives.

Seeing these foundational breakthroughs in the open-source decentralized AI field is exciting, as it fully demonstrates that viewing this field as solely reliant on hype is a mistake.

DisTrO was deployed on the Bittensor subnet in last week's Novelty Search event.

There's a saying: "If they haven't FUDed you (spread fear, uncertainty, and doubt), then you're not building anything worth FUDing." We believe this applies to this field.

After all, we acknowledge the existence of FUD (fear, uncertainty, and doubt). This prompts us to take a step back and build stronger frameworks and assessments to address these seemingly complex and difficult-to-interpret fields.

Thanks to all the builders who have put effort into these works! Your contributions are recognized by everyone.

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