Axie Infinity price

We can’t tell you where babies come from… …but we CAN tell you how to breed axies 👇 Step 1: Select the axie you want to breed and click Manage axie. Step 2: In the axie management page, click Breed. Step 3: Click Let’s Breed and sign the transaction. After breeding, you’ll receive an egg which takes 7 days to become a fully mature axie. Note: Breeding requires a varying amount of SLP (depending on the axies’ breed count) and a flat AXS breeding fee.

While I cannot disclose specific names, I am pleased to share that a market structure has been established where the subsidiary of Story Protocol can supply data to the robot division of the most well-known electric vehicle company globally, a company creating top-tier audio generation AI models, and the leading firms in the AI semiconductor field. It has been a while since I last shared news. Fortunately, just as our subsidiary was launching, Meta acquired Scale AI for approximately 41 trillion won in enterprise value, significantly shaking up the market, and as a result, substantial opportunities are opening up much faster than expected. The structure we are creating is entirely different from existing data distribution methods. Here is the future we envision. Anyone, anywhere in the world, can contribute their POV videos, bio-based audio, multilingual speech, and sensor-based log data, and this data will be collected, cleansed, labeled, and curated according to AI workflows, and immediately rewarded with stablecoins or cryptocurrencies. All data will be recorded on the Story blockchain, an immutable global ledger, and each dataset will be converted into on-chain IP assets. Just as users in the Philippines earned cryptocurrency through the game Axie Infinity, a time will come when countless people worldwide will earn direct income by contributing real-world data. On one side, individuals will autonomously provide data, while on the other, companies like Tesla will pay stablecoins for this data and legally acquire licenses. I once mentioned in a Bloomberg interview with a smile that if companies like Scale AI are akin to low-wage data exploitation factories, where numerous people in developing countries are seated in cramped rooms earning a few dollars per hour to click and draw boxes, then the structure we envision is a much fairer and better alternative. It allows anyone to contribute autonomously, with their contributions registered as IP on-chain, and transparently rewarded. We aim to create a new system that guarantees ownership and participation in the data itself, along with economic upside, rather than merely assigning labeling labor. In fact, I have been quite inactive in sharing my news over the past year. In February, the $IP token of Story Protocol was listed on major exchanges, including Coinbase, and it recorded a market capitalization of approximately 6 to 7 trillion won based on Fully Diluted metrics, but the weight of such numbers was beyond imagination. Unlike stocks, tokens are traded 24/7, which meant facing the market and community's reactions in real-time, making it a form of ecosystem management and real-time strategic operation for my team and me. Amidst the chaos of adapting, I reduced my social interactions and focused most of my time on work. Over the past year, Story has started with the concept of "tokenizing intellectual property (IP)" and has created a new IP-based infrastructure where creators can directly own rights and profits. Numerous contents across various fields such as music, fiction, art, and fashion have been tokenized through our platform, and experiments are being realized where brands like Blackpink and Justin Bieber, as well as Crocs and Smiley, create secondary creations with fans through AI remixing. However, while we were building a content-based IP infrastructure, a strong signal began to emerge from a completely new direction. The question was, "Could real-world data also be IP?" In fact, in recent months, many AI teams have started reaching out to us, looking for "structured datasets with clear usage permissions, traceability, and royalty distribution." Through these conversations, one thing became clear. The real bottleneck in AI is not GPUs or models, but high-quality real-world data organized as IP. Text and image-based models have already reached a certain level of standardization, and the next wave is moving towards 'AI operating in the physical world,' such as robotics, autonomous driving, healthcare, and smart devices. These models can no longer learn from data scraped from the internet. Instead, they require unique, irreplaceable data collected from specific sensor logs, POV camera footage, bio audio, multilingual speech, and other real-world environments. Meta's CTO Andrew Bosworth left this remark: "No matter how much media content is learned from the internet, AI cannot understand the friction and material intuition a person feels when picking up a coffee cup." Such data cannot be found on the web, nor can it be fabricated. And this is precisely the point where Story sees the expansion of IP. We are now expanding the infrastructure we have built over the past few years for art, music, and fiction to encompass real-world data. And the first project in this direction is Poseidon AI. Poseidon is a new protocol incubated by Story Protocol, which has received $15 million in initial investment from a16z. It is a full-stack data infrastructure that collects, refines, labels, and registers real-world data as IP on-chain, ultimately enabling commercial licensing. Once AI teams clearly define what data they want, anyone, anywhere in the world can contribute data through their smartphones, wearables, dash cams, hospitals, and IoT devices. This data will be automatically labeled and anonymized, registered on the Story blockchain, and distributed like NFTs or automatically licensed through smart contracts. Contributors will be rewarded immediately, and users will have access to datasets with legal and technical stability. The person who designed all of this is Sandeep Chinchali @SPChinchali, co-founder and Chief Scientist of Poseidon, and Chief AI Officer of Story. He earned his Ph.D. in distributed AI systems from Stanford, has worked as a researcher at NASA, and was an early engineer at a startup acquired by VMware, and is now a professor at UT Austin. Most importantly, he has spent the last decade researching a structure that collects data from the real world and fairly compensates people for it, known as Data Dividend. Sandeep says: "The next leap for AI comes not from more GPUs, but from better data." In the future, the most important IP will not be Model Architecture or AI chip design. The most valuable IP will be data. Poseidon is the first data IP infrastructure to realize this. And all of this is only possible on the programmable, traceable, monetizable IP infrastructure that Story has built over the past few years. Following content IP, we are now preparing to define and utilize real-world data as IP on-chain. I will share such updates more frequently in the future.

In crypto you can make a multi billion + token project even if your product is only temporarily useful. $PUMP fits this bill exactly. Other interesting cases include the myriad of L2s on ETH, such as $ARB which are barely used today. Last cycle of course you had Axie ($AXS), NFTs with $BLUR etc. All multibillion dollar projects / all with a similar fate. It’s not the fault of the team that crypto investors poorly project out how sustainable the underlying economic activity is (which is extrinsic to the team’s ability to execute) and by extension earnings/cash flow..

In times like these, when everything moves quickly, encountering a vision designed to be slower resonates even more deeply. After a long time, I read a post by @storysylee, the founder of Story (@StoryProtocol), and I found myself deeply agreeing with his insights on the essential bottlenecks in the AI industry and the specific structures to address them. In particular, the direction that 'data is IP' and the way to define and settle it on-chain made me nod in agreement. If the center of the AI industry was GPUs and models, I am now convinced that the next chapter will definitely be 'real-world data.'