Altered State Machine wants to give NFTs an AI brain

Artificial intelligence is undoubtedly one of the most fascinating contributors to the development of the NFT space.

Image creation programs (such as DALL-E and Midjourney) that turn text-based messages into images) have become increasingly user-friendly and popular in recent months. NFT projects that use artificial intelligence to significantly contribute to the creation of their collections are also becoming more common.

But, depending on who you ask, the very concept of “AI art” is either a delight, an enigma, or an insult to artistic disciplines and the creatives who run them. However, the potential for AI to impact Web3 and NFTs goes far beyond the creation of digital art.

Altered State Machine, a platform and protocol that allows users to build, train, and trade AI “agents” like NFTs, is one company that aims to be at the forefront of AI in the metaverse. And this could usher in a new wave of significant changes.

Gives NFTs AI intelligence

Like many in Web3, ASM is excited about the future of these digital environments, and one of their goals is to help create metaverse spaces populated by AI agents that can compete with each other, interact and support human actors. But creating AI characters that result in a more versatile, living and breathing metaverse experience is just one of many potential uses for the ASM protocol.

ASM’s AI agents can adapt to a wide range of use cases. And the range of applications is wide, whether the agents are used for games, open-world metaverses like Decentraland or financial use cases.

How an AI NFT will actually look and behave depends on a few things. The agents of ASM’s protocol are composed of three elements: a “form,” a “brain,” and “memories.”

ASMs Artificial Intelligence Football Association, a metaverse game where AI teams compete against each other in soccer matches, is an excellent example of how the technology works. The game can be filled with forms, in this case NFT characters called AIFA All-Stars. The NFTs’ abilities are randomly determined by their internal AI ASM brains. In fact, the 40,000-character NFTs in the AIFA All-Stars collection were the first to receive what the company calls Non-Fungible Intelligence from ASM’s Brains during the company’s October 2021 origination.

So you have NFT character shapes powered by an AI brain. The final component is the AI ​​brain’s memories, which store behavioral strategies that the NFT character learns through model training.

The AI ​​brains perform this training both in the environments they play in (like a football stadium in a metaverse) and in “gyms” dedicated to improving the AI’s abilities. These training centers are web-based GPU cloud computing providers that run training algorithms for a specific ASM application. This spring AIFA example of game applications, this may look like improving the character’s shooting ability. If your AI is used for the DeFi markets, it might look like adjusting your risk tolerance for a trading fine.

Regardless of the use case, owners can pay for training time in these gyms using ASM’s native token, $ASTO. The company also provides opportunities for hardware owners to create and earn from GPU time given to gyms.

Each ASM-powered NFT is unique in its own way, from its visual characteristics to how it reacts to its surroundings. This takes things a step beyond what we currently see in the NFT ecosystem. While generative PFP projects randomly assemble character accessories and other visual attributes, ASM’s AI agents randomly assign behavioral tendencies in addition to their “physical” characteristics. These randomly assigned properties will appear in different ways depending on the context of use of the NFT.

Once trained, users can trade or sell enhancements. Commodifying these properties can help create an economy across different metaverses and in the gaming and financial markets. “Training depends on the use case,” explained David McDonald, CEO of Altered State Machine, in an interview with nft now. “[One of the things] that determines what they learn is how we build a specific environment.”

The AI ​​agents learn within the confines of their environment, like a metaverse football stadium. After this training, the same agents can exist and interact in different metaverse worlds as well, provided the environment in which they learned to play soccer is replicated in those worlds.

There are several other forms of composability these AI agents retain. Composability is a system design principle that relates to the ability of one system to interact with another. In this case, an AI can learn a new “skill” to adapt to a new environment.

McDonald added that one of the more advanced forms of composability in these AI brains could be something like motion.

“Learning how to create a unique way of moving around the world for an agent can be a composable element that you can insert into game or NPC (non-player character) experiences,” McDonald elaborated. “You can couple it with a natural language processor, for example, that allows for chat functionality. Or with a navigation AI that allows the AI ​​to learn to navigate the world. All these elements in the brain you can put together in interesting ways to create interactions and life in environments.”

So far, metaverse spaces rely on human actors to inhabit and animate them. But an essential feature of these worlds, McDonald believes, is what happens when you are not in these environments.

“Let’s say you set up a gaming store [in the metaverse] and you create a unique way to sell your digital goods in that space,” McDonald said. “When you’re not there, you kind of lose that ability. Being able to have your belongings take over when you go to the beach with your kids or whatever is a way [ASM] may have an impact as these metaverse spaces are expanded. The other way is that you can create experiences for many people that a single person cannot possibly do on their own. You can build commerce around digital interactions and scale them in a way that is not possible with a single person or even a large team of people.”

Muhammad Ali – The Next Legends metaverse boxing game

ASM’s most important upcoming project is Muhammad Ali – The Next Legendsa metaverse boxing game where characters use the company’s AI brains to hone their skills and fight against other AIs.

The project, which is slated for release sometime later this year, is a partnership between ASM and Authentic Brands Group, the company that owns Muhammed Ali Enterprises in partnership with Lonnie Ali, a trustee of the Muhammad Ali Family Trust. The game will feature character designs from Web3 creative factory Non-Fungible Labs.

As AIFA, The next legends will feature NFT characters featuring ASM’s AI brains. Players will train their characters, all of whom come with a random set of skills, to better develop the abilities (such as jabs, uppercuts, and stamina) needed to win these matches.

McDonald is particularly excited about the partnership and the project, saying he has looked up to Muhammad Ali all his life.

“It’s a great honor to help expand that history and his legacy into a brand new space. It’s an opportunity to create a really exciting and new game mechanic and a way to interact with stories that I think people are going to really enjoy. And sets us up to bring a whole new range of experiences in this space to Web3 and the metaverse.”

When asked how he feels about using the game to welcome people into the Web3 gaming community, McDonald emphasized that it’s critical to satisfy the needs and interests of both Web3 savvy and those new to the space.

“We need to make sure it’s user-friendly for anyone of all skill levels to participate in the game. I know people are already familiar with the current user experience of Web3, and those people are in the category I like to call power users,” McDonald said. “They’ve done the study and they probably understand the ASM protocol and they understand how gas works and how blockchains in general work. But the average user who might be interested in playing a Muhammad Ali AI boxing game probably doesn’t have that level of sophistication. So we must accommodate both of these entry points and ensure that the onboarding experience is not a barrier to entry.”

Putting AI back in the hands of the people

Overall, the implications of ASM’s technology frontier for Web3 are intriguing. In keeping with the Web3 ethos of ownership, collectors of these agents will have proof of ownership of an AI whose development and purpose they have control over. McDonald contrasts this with how AI in Web2 works, noting explicitly how algorithms in social media are completely out of the user’s control, which can have profound effects on a person’s psychology and mental health.

“One of the big problems with preference algorithms today, and we see this with things like TikTok, is that it will take you down a rabbit hole of what it knows from your behavior, but that might not be what you’re trying to target,” McDonald said. “That kind of algorithm has a lot of negative results when you look at things like showing depressed people content about depression. [It’s] send them down this rabbit hole they might not want because the algorithm knows that’s where they get the most engagement. Having self-sovereign control over preference AI I think is going to be an important thing for people.”