The BitTensor network has rapidly gained prominence in the decentralized AI space, expanding from 32 to over 50 subnets. Akash Network (AKT) is emerging as a key player in this ecosystem, especially as it explores collaborations with BitTensor without fully becoming a subnet. Let's dive deeper into both networks, and why Akash might benefit more from partnering rather than becoming a subnet under TAO.

What is BitTensor (TAO)?

BitTensor is a decentralized AI network that applies Bitcoin’s incentive model to attract top talent in creating high-quality AI models. Each subnet on TAO is designed to perform specific functions, managed by Subnet Operators. For instance, in a subnet focused on text-to-speech conversion, miners earn rewards in $TAO based on how well they complete tasks. Validators then evaluate the quality of these tasks according to standards set by the Subnet Owners.

In simpler terms, BitTensor can be imagined as a spaceship framework for AI—an empty vessel rewarding TAO tokens to subnet owners for contributing to the spaceship’s construction. The idea is that as more components of this spaceship are built by various subnet operators, it creates a robust AI structure that is accessible, trainable, and incentivized for everyone in a permissionless manner.

What is Akash Network (AKT)?

Akash Network provides decentralized infrastructure offering permissionless access to shared computational resources. This lack of gatekeeping creates a fair marketplace, where no central authority can favor certain users in terms of resource allocation. Anyone can use Akash at any time, provided they hold the $AKT token.

Akash’s Super Cloud occupies a critical intersection between AI and crypto, as it is the only decentralized network capable of hosting open-source AI applications ready for production. Akash’s CEO emphasizes that the network already powers around 80% of decentralized AI entities within Web 3, including organizations like PrimeIntellect, Venice.AI, and some TAO subnets!

Akash and BitTensor: A Perfect Pair

Subnet 27: Compute

Both Akash and BitTensor align in their commitment to open-source principles and transparent, permissionless systems. This has led to a natural synergy, with Akash playing a key role in some of BitTensor's subnets, including Subnet 27, where it provides the computational power needed for AI development.

In Subnet 27, computing power comes from a range of providers, including Runpod, Lambda, AWS, and Akash. With the rising costs of renting GPUs like H100 on centralized platforms, many enterprises struggle to secure resources, particularly when large financial contracts are required to access them. Akash Network steps in to bridge this gap, connecting Subnet 27 miners with certified GPU providers globally, ensuring that computational resources are both affordable and decentralized. This reduces reliance on centralized systems like AWS, which often experience outages and have fluctuating costs, making Akash an ideal partner in the TAO ecosystem.

Subnet 4: Targon

Subnet 4, or Targon, focuses on decentralized inference using deterministic validation mechanisms to incentivize miners to run OpenAI-compliant endpoints that serve both synthetic and organic queries. With the latest updates to Targon v4, this subnet can now rent GPU models, reflecting Akash’s unique ability to deploy AI models as a DePIN (Decentralized Physical Infrastructure Network), something other DePINs can’t achieve.

To become a Subnet 4 validator, miners require at least 8x A100 GPUs, and A100s or H100s are strongly recommended for optimal performance. These high-performance GPUs are rarely available for rent on centralized platforms, again positioning Akash Network as the solution to provide the necessary computational resources for Subnet 4 miners.

Subnet 6: Nous Research

Nous Research is training an open-source AI model known as Nous Hermes 2. Greg Osuri, the CEO of Akash, is an early investor in Nous Research. According to recent reports, Nous uses Akash to train their models. This marks a groundbreaking moment for decentralized AI training, where people can share their computing power to train a common AI model without centralizing all GPUs under one roof. Previously, such training models could only be developed in massive data centers, like Elon Musk’s Cortex.

With the rise of decentralized AI training, entities like Prime Intellect and Akash are now collaborating to train Intellect-1, the world’s first open-source decentralized AI model. This work is crucial as it opens new gateways for the future of decentralized AI.

Subnet 34: BitMindAI

BitMindAI addresses one of the most pressing challenges in today’s world amid the creative AI revolution: deepfake detection. Subnet 34 incentivizes the creation of deepfake detection models, where miners run binary classifiers that differentiate between real and AI-generated content. These miners can easily deploy on AWS or Akash at a cost 70% lower.

Since Akash is globally distributed, each Akash provider operates independently, making it more decentralized than centralized platforms like AWS. This further strengthens Akash’s appeal to Subnet 34 miners.

Subnet 46: Neural AI

GoNeuralAI produces 3D graphics models using Unreal Engine 5, based on user requests. They have launched a map builder to simplify world-building. Akash’s GPUs are critical to Neural AI’s current inference workloads, and while they are still launching their subnet, it's likely they will continue using Akash’s resources to run their operations.

The Bright Future of Akash

As BitTensor continues to expand its subnet capacity, the collaboration between Akash and various TAO subnets will only grow stronger. SN 44 ScorePredictHQ has already confirmed plans to use Akash in the near future, and there are undoubtedly many other subnets using Akash’s permissionless infrastructure without public acknowledgment.

Akash is becoming the go-to solution for decentralized computational resources, allowing it to thrive alongside TAO as a powerful DePIN.

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