🌵 The Intersection of Crypto & AI 🌵

Big Brain Breakdown

Market Metrics

Total Crypto Market Cap: up 3.5% to $2.24T
Total AI Sector Market Cap: up 2.2% to $21.3B

Top Movers (24hrs):

📈Atlas Navi (NAVI): up 14% to $0.1381
📈OctaSpace (Octa): up 11.3% to $1.67
📈Agoras (AGRS): up 10.3% to $1.82

🧠 Big Brain Breakdown

Bittensor is arguably the most prominent AI-focused protocol today, as reflected in both its flourishing developer ecosystem and ~$2 billion market capitalization.

At its core, the Bittensor network is a platform that incentivizes and orchestrates open-source AI contributions solving a diverse array of use cases. Through its unique subnet architecture, Bittensor's primary goal is to enable humanity's access to democratized, censorship-resistant, and permissionless AI. (More on Bittensor here)

Sounds pretty ambitious, right?

Well, it is, and naturally, the Opentensor Foundation and the rest of the Bittensor ecosystem are not the only ones trying to achieve that goal. That's why we're diving into the growing landscape of these coordination protocols, assessing their similarities, differences, and strategies for usurping King TAO.

Commune AI

Commune is perhaps the closest competitor to Bittensor, adopting similar core elements such as the Yuma consensus mechanism, Substrate blockchain framework, subnet architecture, and even comparable subnet use cases. According to some community members, Commune may be seen as a “make it all back” play for those who missed out on Bittensor in the early days.

However, it’s worth mentioning the key differentiation from Bittensor: its subnet 0, which enables the incentivization of “value additive” projects to be built outside of the typical mining markets occurring within the other subnets.

A “value additive” project could be in the form of content creation, efforts towards a COMAI exchange listing, Discord bots, or otherwise difficult ad hoc initiatives to fund. Weights on this subnet are determined manually and linearly by the Stakeholder community, so the miners (contributors) are rewarded to the degree of which the community deems appropriate.

This clearly presents a unique set of opportunities for non-technical contributors to get excited about the ecosystem and earn some COMAI. Of course, it’s also something we hope that Bittensor aims to eventually adopt as well.

Sentient

As most know, Sentient stole the spotlight at EthCC in Brussels this year with the announcement of its impressive $85 million seed round, however, it is until recently that people fully understood what the team was building.

In a nutshell, Sentient is creating a decentralized marketplace for AI models. Without getting too deep into the weeds, the team is innovating across several dimensions, mainly at the model and output authentication levels with its OML (Open, Monetizable, Loyal) format for AI models and model fingerprinting for authentication.

Sentient's approach to incentivizing and coordinating model contributors differs substantially from Bittensor's. Unlike Bittensor's subnet architecture, Sentient focuses on individual model ownership and compensation through usage-based rewards, enabled by the OML format.

This approach provides a clear monetization path for emerging developers, offering a straightforward way to earn from their creations. However, this model-centric focus may not foster the same level of task diversity and cross-domain collaboration that Bittensor's subnet structure encourages.

The success of Sentient's approach will likely depend on its ability to balance individual incentives with the broader needs of a diverse AI ecosystem.

Allora Network

Standing behind its catchy slogan, “self-improving decentralized intelligence,” Allora Network is emerging as a key player through its novel context-aware Inference Synthesis mechanism and its focus on quantitive prediction modeling for tasks such as asset price predictions.

What exactly does that mean? In simplistic terms, this mechanism is a custom approach to coordination where network participants use AI to aggregate the results of all predictions submitted, benchmark the results against the live outcome, and use those results for future predictions.

Some comparisons with Bittensor can be drawn, especially with the use of Allora’s “topics”: a flexible and community-oriented approach to specific AI tasks with their own set of rules for participant interaction and performance evaluation, similar to Bittensor subnets. Current topics mainly revolve around predicting the prices of varying crypto assets within 10 minutes & 24 hours, but recently, predicing the winner of the US election has surfaced as a topic.

We are really looking forward to diving deeper into the Allora project, as we think that there are several unique mechanisms that deserve their own respective spotlights and syntheses.

It is very exciting to see the wider market validating the importance of responsible AI model coordination, incentiviziation, and contribution. All of these platforms enable the every day user, solo-devs, and scrappy startups to get their hands dirty with this nascent AI tooling, and earn rewards in the process. We are seeing the infant stages of these platforms blossom into what we believe will be the future defacto venues for every aspiring AI dev to go and tinker, something that was simply not possible just a year ago.

🤡 Meme of the Day

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