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Over the past three years, the cryptocurrency industry has experienced massive upheaval. In addition to the boost from the 2021 stimulus package, venture capital (VC) firms have invested $33 Billions in cryptocurrency and blockchain startups.
The following year, the Federal Reserve triggered a domino of crypto bankruptcies with a rate hike cycle that started with the collapse of Terra (LUNA) and culminated with the collapse of the FTX Ponzi scheme.
With over $3 billion lost in DeFi hacks in 2023, the promise of DeFi has lost its luster. The ongoing Bitcoin bull market shows a lack of trust in so-called altcoins. altcoin season It has not manifested yet.
In June 2023, Joseph Chalom, head of strategic partnerships at BlackRock, said: I got it. Institutional adoption of DeFi is “years and years away,” he said. However, there are arguments that a new AI narrative could merge with blockchain technology and its applications.
Given the lessons from the last cycle, what does the outlook for AI and cryptocurrencies look like?
Building an AI foundation with cryptographic composability
Looking back, it’s safe to say that “DeFi” has been subsumed by companies on top of the tokenized layer, such as Celsius Network and BlockFi, and DeFi has become CeFi. While these companies were successful in promoting the adoption of cryptocurrencies, they ultimately tarnished the term “cryptocurrency” itself.
An updated DeFi v2 should focus on a good user experience that does not stimulate the demand of centralized companies. Most importantly, DeFi security needs to be strengthened. The most promising solution in this direction is the Zero Knowledge Ethereum Virtual Machine (zkEVM).
zkEVM increases network throughput and reduces gas costs by abstracting on-chain transactions through zero-knowledge proofs (ZKPs). Additionally, zkEVM simplifies the user experience by facilitating alternative token payments for gas fees. In other words, solutions like zkEVM pave the way for the scalability needed for AI applications.
AI applications inherently involve large amounts of data, making them a potential bottleneck for blockchain networks. In front of this obstacle, Polygon zkEVM will be able to generate AI artwork through his Midjourney image generator.in this processthe results could be tokenized as low-fee NFTs.
Further developing other types of smart contracts, the crypto space has laid the foundation for AI with composability and permissionless access. Together, this creates an autonomous and efficient infrastructure for financial markets. Because every part of market activity can be decomposed into smart contracts, composability brings innovation across three composability layers:
- Morphological – Components that communicate between DeFi protocols and create new meta-functions.
- Atomic – The ability for each smart contract to function independently or in conjunction with smart contracts from other protocols.
- Syntax – The ability of protocols to communicate based on standardized protocols.
In reality, this is equivalent to Lego DeFi blocks. For example, Compound (COMP) allows users to provide liquidity to smart contract pools. This is one of the revolutionary pillars of DeFi, as users no longer need someone’s permission to lend or borrow. Borrowers can leverage smart contracts by providing collateral, as smart contracts act as liquidity pools.
Liquidity providers obtain cTokens in exchange for interest. If the provided token is her USDC, the generated token will be cUSDC. However, these tokens can be integrated across DeFi boards into all protocols compatible with the ERC-20 standard.
In other words, composability creates numerous revenue-generating opportunities so that smart contracts do not remain idle. The question is how to efficiently deal with this increased complexity. This is where AI comes into play.
Increase efficiency with AI
When we think of artificial intelligence (AI), what primarily comes to mind is superhuman processing. Financial markets have long since become too complex for humans to handle. Instead, humans have become dependent on predictive algorithms, automation, and personalization.
In TradFi, this typically means that the robo-advisor prompts the user about their needs and risk tolerance. The robo-advisor then generates a profile for managing the user’s portfolio. In the field of blockchain composability, such AI algorithms will gain much greater flexibility to siphon off revenue.
By reading market conditions on the fly while accessing transparent smart contracts, AI agents have the potential to reduce market inefficiencies, reduce human error, and enhance market coordination. The latter already exists in the form of automated market makers (AMMs) that provide asset price discovery.
By analyzing order flow, liquidity, and volatility in real-time, AI agents are ideal for optimizing liquidity provision and even stopping DeFi. Flash loan abuse By coordinating between DeFi platforms and limiting transaction sizes.
Inevitably, as AI agents improve market efficiency through real-time market monitoring and machine learning, new predictive markets may emerge as liquidity deepens. In that case, the human’s job would be to configure the bot to arbitrate against other bots.
in $42.5 billion Through 2,500 equity rounds in 2023, AI investments have already surpassed 2021’s crypto peak. But which AI crypto projects exhibit this trend?
Spotlight on AI crypto innovators
AI has been in the spotlight since ChatGPT was announced by OpenAI in November 2022. The attention that was previously focused on meme coins has now been focused on AI advances in inference, art generation, coding, and most recently text-to-video generation with Sora.
All of these areas of human interest rely on data center expansion. Unlike cryptographic tokens, which are smart contracts, AI tokens are basic blocks of text that an AI agent breaks down into relational units. Depending on the tuning of each AI model, these tokens represent a context window of relationships between concepts.
It is difficult to allow maximum processing power for each user prompt. When an AI model splits text into tokens, the output depends on the size of the tokens. Second, the token size determines the quality of whatever content is generated.
Obviously, the larger the token size, the more concepts the AI model is likely to consider when generating content. Given these inherent limitations, AI tokens are a natural fit for blockchain technology.
Just as Web3 games tokenize in-game assets for decentralized ownership, tradable currency, and reward incentives, AI can do the same. As a case in point, Fetch.AI (FET) is an open access protocol for connecting autonomous economic agents to his Fetch Smart Ledger via an open economy framework.
FET tokens are intended to monetize network transactions, pay for the deployment of AI models, earn rewards for network participants, and pay for other services. And just like people connect to DeFi services through wallets, you can use Fetch Wallet to connect to Fetch.AI’s agentverse and leverage deployed AI protocols.
For example, one of the many AI agents currently in beta agentverse PDF summary agent.
As a promising path to democratizing access and deployment of AI agents, the value of the FET token has increased 300% since the beginning of the year. According to Market Research Future, the AI agent market is predicted to grow as follows: $110.42 billion This corresponds to a compound annual growth rate (CAGR) of 43.80%.
Eventually, we may see an ecosystem of AI agents interacting with DeFi protocols and other services that benefit from automating real-time decision-making. This could extend to AI agents assisting self-driving EVs and performing delicate surgeries and patient care. pediatric surgeon “We’re excited to announce that this is the first time we’ve seen this,” said Dr. Daniel Walsh of the University of Kentucky School of Medicine in Lexington.
“A patient who wakes up at 1 a.m. two days after surgery can contact the chatbot and ask, ‘I’m having these symptoms, is this normal?'”
In the medical diagnostics space, Massachusetts-based Lantheus Holdings (LNTH) had already deployed its imaging agent PYLARIFY AI for early detection of prostate cancer. AI crypto projects like Fetch.AI have the potential to fully tokenize many such services.
The way forward: challenges and opportunities
Prior to AI integration, blockchain platforms face the same issue of institutional adoption. Is there a chance for smaller protocols to penetrate the mainstream, or is this limited to institutions only?
DeFi may have paved the way for tokenized financial markets, but large companies are more likely to instill public trust.
for example, canton network,In other words Supported by big banks and big tech, this service has the potential to replace smaller DeFi fish. After all, the convenience is Same day bank transfer Can be seamlessly integrated into blockchain networks. This is especially pertinent given that Microsoft is using the Azure cloud to power its Canton network while developing AI products.
At the same time, many users want to ride the rising value of AI crypto tokens and remain within the open access ecosystem. Furthermore, cryptographic protocols do not have to directly correspond to AI agent deployment. As a case in point, The Graph (GRT) can be used as a blockchain data indexing service for AI apps.
Based on this assumption, the “Google of blockchain” has gained 103% year-to-date. One of the most promising crypto projects to aid AI may be Injective Protocol (INJ). Injective aims to simplify and automate complex DeFi operations by “injecting” AI algorithms into the aforementioned DeFi market actions.
The base layer of the intersection of AI and crypto could include: alolan networkuse zero-knowledge machine learning (zkML) and federated learning to build AI apps that power your DeFi experience.
If the rollout of these open apps is successful, organizational networks such as Canton’s will become less attractive. This power relationship mainly depends on regulatory authorities, but regulations have not yet materialized in the virtual currency field as well.
conclusion
AI is poised to make data more understandable, actionable, and relevant to specific users. On the other hand, blockchain technology has formalized and decentralized the logic of human behavior into self-executing smart contracts.
When the two realms meet, an AI agent with a new purpose is born. A new generation of tokenized robo-advisors that takes full advantage of the composability of DeFi. And new markets will emerge as AI agents explore new possibilities.
From predictive analytics to injecting liquidity into on-chain markets, AI agents are poised to create a hyper-financialized future. Starting with Bitcoin As such, humanity will find plenty of building blocks to exploit.
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