Ape-tizers:

• io.net is a Solana-based DePIN/AI project that decentralizes cloud computing
• IO Cloud and IO Intelligence make up the core of io.net
• io.net utilizes its features and blockchain technology to offer cheap AI to different categories of end users

If you’ve seen any of the videos coming out of Google’s VEO3, you probably have the same reaction I have: AI is moving way faster than most of us expect.

The pace of these updates is wild. And honestly, it does feel like AGI might be somewhere in Santa’s sack of gifts to the world, just before Christmas at this rate.

But with all this insane progress, it’s hard not to wonder about how much compute this is all taking.

Without io.net, AI is expensive. But why?

I mean, if massive projects like Sam Altman’s Stargate are still far from finished, how sure are we that AI acceleration across the board won’t be greeted by Everton’s low-block pretty soon, given the uneven gap between model sophistication and necessary compute power.

Just a few months ago, Ghibli-style images were enough to crash OpenAI’s servers. Now we’re talking about near-Hollywood-level video generation with VEO3 and other heavy-duty specialized agents that eat up way more processing power.

The more computational resources needed to power these elite models, the more the cost is pushed down to the end user, leading to expensive subscription fees.

Yeah! Good luck paying $2,400 per annum for a reasoning model.

The reality is, as long as computational resources remain expensive, access to significantly cheap AI will remain distant.

While centralized cloud infrastructure can help reduce cost overload, accelerate innovation, and improve efficient access to needed computing power, like all things centralized, it comes with significant security, privacy, and safety concerns.

As a matter of fact, these concerns are so important when you consider that recent AI updates are beginning to display worrisome characters like deception and blackmail.

io.net: The most efficient solution

To cut to the chase, the only real way to get cheap, safe, and reliable AI is by using a decentralized cloud setup. That means spreading the computing work across a bunch of idle GPUs that are actually good and can be trusted.

This kind of network helps in two big ways: it solves the supply issue and makes it easier for people to get access to affordable GPU power.

That leads to lower costs all around, so in the end, users can pay way less for AI tools and models.

This is where io.net comes in, as a decentralized network of GPUs on the Solana network, that provides for scalable and efficient compute power for AI applications and machine learning applications as well.

The way it works is that io.net aggregates underutilized GPUs across the world, leveraging a vast amount of unused hardware globally, such as gaming PCs and idle mining rigs.

But io.net doesn’t just do this, using a verification model called proof-of-work, io.net ensures that each GPU in the network meets a certain threshold for performance and reliability, thereby creating a foundation for a reliable decentralized network of efficient and cheap computing.

How does io.net deliver cheap AI to users?

In our previous articles about the subject, we’ve answered the question: How does io.net work? Today, we will look into io.net’s progress so far in ensuring that this all works out.

Delivering affordable AI to users means building the right decentralized infrastructure and products to support it, while making sure incentives are aligned to keep everything running smoothly.

io.net is heading in the right direction with a range of interconnected features, all designed to create a low-cost, accessible foundation for suppliers, consumers, and end users alike.

IO Cloud

Through the IO Cloud, clients can spin up a GPU cluster in minutes.

The IO Cloud is io.net’s base infrastructure for users to access on-demand, decentralized GPU clusters, reducing the technical and financial complexities associated with computing power for AI and ML applications.

IO Cloud functions as a permissionless marketplace, matching users with GPU clusters made up of nodes and IO workers that support a wide range of AI/ML tasks, such as batch inferencing, distributed training, hyperparameter tuning, and even reinforcement learning.

The IO Cloud marketplace allows users to select GPU clusters based on their geographic proximity and hardware preferences, ranging from NVIDIA A100 and H100 to consumer-grade GPUs.

You can also configure cluster parameters on the dashboard or via the API, choosing your preferred GPU type, the number of nodes needed in the cluster, memory, and runtime.  

The IO Cloud then uses a unique routing system to match these specified preferences with the available GPU suppliers.

Payments are made using $IO, io.net’s native token, allowing suppliers to earn from leasing their GPUs to clients.

The system further uses a staking mechanism to secure the network, thereby creating an additional layer of security for smooth interaction between all tiers of customers.

IO Intelligence

The next stack in io.net’s cheap AI infrastructure is IO Intelligence. With IO Intelligence, developers can access pre-trained AI models, APIs, and inference services on the go, without needing to manage GPUs.

Developers who want to introduce AI capabilities into their apps or builds can leverage this readily built service, circumventing the costs and technical hurdles associated with training their models or developing their agents.

The IO Intelligence service uses AI models trained on common tasks such as natural language processing, recommendation engines, speech recognition, and other non-intensive capabilities.

Additionally, IO Intelligence allows developers to access APIs that match their needs, allowing them to basically plug and play into their apps or builds, while leveraging the robust decentralized GPU network to handle and execute a wide range of inference streaming from these API integrations.

The real difference is in the cost disparity between IO Intelligence and traditional or centralized providers like AWS or Google.

Utilizing underused GPUs with verifiable quality across 140 countries allows io.net to provide cheaper and more efficient computing power to apps looking to integrate AI without having to empty their coffers.  

To ensure that GPU providers or suppliers don’t behave with malicious intent, IO Intelligence also utilizes proof-of-work verification to guarantee compute integrity and ensure that output can be trusted.  

Another important aspect of IO Intelligence is that it is flexible for users or developers, as they can fine-tune APIs or pre-trained models through IO Cloud’s GPU clusters, customizing these models to fit their use cases.

Quite like the IO Cloud, IO Intelligence is accessed through $IO, handling transactions and payments, while IO staking and IO ID ensures that system security is also taken care of.

IO Worker, Explorer, Token, Staking & ID

Beyond the IO Cloud and IO Intelligence, other working parts that come together to deliver cheaper AI to consumers are: IO Worker, Explorer, the IO token, staking, and ID.

The IO Worker functions as the interface between suppliers and clients, allowing the latter to borrow or lease their compute infrastructure to clients who need it.

Suppliers use the IO Worker platform to register their GPUs, specifying type, location, and availability.

The IO Explorer functions like a database and map of io.net’s decentralized GPUs, capturing availability, clusters, task completion tracking, and real-time data on performance, usage, and general network health.

The Explorer provides insights to clients and suppliers, thereby optimizing the entire network's general performance.

The $IO token is the native token of io.net. The token powers all transactions across the network, such as being able to incentivize GPU suppliers, while being a payment token through which clients and users can rent GPUs, and access IO Cloud and IO Intelligence.  

Network participants can stake the $IO token in order to participate in network operations such as validating compute tasks and actively engaging in governance decisions. Users who stake their $IO token earn rewards in $IO, creating a flywheel that streamlines network participation with incentives.

On the other hand, the IO ID serves as a form of identification for different levels of network participants. Users, stakers, and suppliers are authenticated to ensure that the network is secure from fraudulent participation.

All these moving parts work in tandem to create a robust, efficient, trustworthy, and reliable network of decentralized computing power that basically hands over cheap AI models and agents to the end user.  

Concluding thoughts on io.net  

Betting on AI also means betting on innovative infrastructure platforms like io.net.

Instead of relying on expensive, traditional solutions, io.net takes a decentralized approach, offering GPUs-as-a-service through smart innovation and cost-effective design, thereby delivering cheap AI to users.

The io.net solution also stands out as an outlier when you view it from the lens of the crypto industry. It remains one of the few projects that non-natives can easily access and utilize without feeling the need to be native.

Through its pre-trained models and APIs, io.net is accelerating global, retail, and commercial adoption of AI without the inherent security concerns.

Companies can use IO Intelligence to transform their businesses, whether large or small scale, without having to train models from scratch.

The io.net architecture supports decentralized inference, creating a safer environment for AI by reducing the risks of rogue behavior and malicious intent. This is made possible through proof-of-work mechanisms and the implementation of IO ID.

As AI continues to percolate every crevice, how each layer of infrastructure is built should concern us all.

io.net understands this inside and out. They know the stakes. And that’s why we’re paying attention.  
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Thanks to the io.net team for unlocking this article. All of our research and references are based on public information available in documents, etc., and are presented by blocmates for constructive discussion and analysis. To read more about our editorial policy and disclosures at blocmates, head here.