Interview with Footprint Analytics CEO

Footprint Analytics is devoted to making a structured information platform that bridges the hole between Web2 and Web3 information.

We specialise in structuring information. Regardless of the relative benefit of Web3 over Web2 in clear on-chain information, sure challenges stay. These embody the nascent standing of the business, an absence of standardized practices, and an absence of organized information. In consequence, information utility turns into problematic.

For instance, think about the situation the place you wish to entry transaction information on Opensea from a number of chains resembling Ethereum, Solana, and Polygon. This course of entails understanding OpenSea’s enterprise mannequin, learning sensible contract code, and sequentially extracting transaction information from every chain.

This course of is difficult. At the start, it’s difficult and liable to errors all through the information assortment course of. Second, it’s technically advanced, given the variations in ledger design and information constructions throughout chains. Lastly, it results in a waste of assets. In a situation the place 1,000 folks want this information, they’d must undergo a equally advanced course of 1,000 instances. This important repetition considerably hinders information assortment effectivity and wastes computing assets.

This brings us to the aim of Footprint Analytics: to summary information from disparate sectors resembling GameFi, NFTs, and DeFi and set up standardized information practices for the Web3 business. This, in flip, will allow builders and business contributors to entry and analyze information effectively and precisely.

Up to now, we’ve launched platforms on greater than 20 blockchains, organized into three core segments:

Footprint Development Analytics as an Trade Answer: Tailor-made options for Web3 tasks in advertising progress and operational analytics, much like a Web3 model of Google Analytics, driving tasks in direction of data-driven progress.Zero-Code Knowledge Evaluation Instruments: Offering an expertise much like ChatGPT, this software permits customers to acquire information evaluation stories by easy queries and responses. Within the foreseeable future, the usage of on-chain information will probably be enormously simplified – no difficult understanding of Web3 enterprise logic or superior programming expertise will probably be required, streamlining the transition from Web2 to Web3.Free Unified API: By means of a unified multi-chain and cross-chain API, this function facilitates cross-chain information entry throughout a number of chains, offering customers with a seamless expertise to retrieve information from a number of chains for free of charge.

As a knowledge platform, Footprint is a pure match with AI. AI encompasses three key sides: computing energy, information, and algorithms. Amongst these, computing energy is the inspiration that underpins AI mannequin coaching and execution. On the similar time, information is the essence of AI, and algorithms dictate AI efficiency, together with mannequin accuracy and utility effectiveness.

Of those, information is undoubtedly an important and indispensable. Knowledge is the lifeblood of industries and tasks, and its significance extends to key areas resembling privateness and compliance, the place its worth is immeasurable. Knowledge could also be past buy, given its involvement in privateness and compliance points. AI acts as each a shopper and a producer of knowledge.

Presently, Footprint’s utility of the convergence of knowledge and AI encompasses a number of major facets:

Throughout the information content material era section, the contribution of AI inside our platform is essential. Initially, we use AI to generate information processing code, offering customers with a extra streamlined information evaluation expertise.

Extra particularly, we’re driving innovation in two particular instructions.

First, we’re curating and categorizing reference information. Taking lately deployed contracts on the blockchain for example, our AI can autonomously decide the protocol to which a contract belongs, the kind of contract, and even whether or not the contract falls below classes resembling LP or Swap on Dex platforms. This clever structuring and classification enormously improves information accessibility.

Second, we are able to generate higher-level area information based mostly on our reference information. For instance, we use AI to create information inside domains resembling GameFi, NFT, and many others., offering customers with richer information assets. This strategy enhances the standard of knowledge content material and allows customers to raised perceive information throughout completely different industries.

To enhance the front-end person expertise, now we have launched an AI-based clever evaluation perform. As talked about above, when customers have interaction Footprint for information evaluation, they encounter an expertise much like a dialog with ChatGPT. Customers can ask questions and instantly obtain corresponding information evaluation stories. The underlying logic entails translating textual content into SQL queries, dramatically decreasing the entry barrier for information evaluation.

Lastly, relating to person help, we’ve developed an AI-powered customer support bot. We feed AI with information from Footprint, which spans GameFi, NFT, DeFi, and different areas, to construct a customized AI customer support bot for Footprint. This AI bot gives speedy help to customers by answering questions associated to the usage of Footprint, together with information varieties, information definitions, API utilization, and many others. This enormously will increase the effectivity of buyer help whereas decreasing the quantity of handbook work.

Nevertheless, it’s value noting that whereas AI functions can enhance productiveness and assist clear up most challenges, they will not be omniscient. Based mostly on our information processing expertise, AI can help in fixing roughly 70% to 80% of challenges.

From a broader perspective, whatever the area wherein AI is utilized, a essential consideration is the extent of acceptance of AI’s fault tolerance. Completely different utility situations have completely different fault tolerance necessities. There’s a have to stability the accuracy and reliability of AI in opposition to folks’s tolerance for error.

For example, in healthcare, the choice to belief both AI or a doctor might contain trust-related challenges. Within the funding area, AI can present components that affect the path of BTC costs, however folks should have doubts when making precise purchase or promote choices.

Nevertheless, exact accuracy will not be paramount in advertising and operational analytics, resembling person profiling and tiering, as a result of minor errors gained’t considerably influence. In consequence, error tolerance is extra readily accepted in these contexts.

Presently, Footprint is primarily targeted on information in its efforts to combine AI with Web3, which presents its personal set of challenges:

First, the primary problem is information era, particularly offering high-quality information for AI to attain extra environment friendly and correct information era capabilities. This relationship between AI and information could be in comparison with the engine and gasoline of a automotive, the place AI is the engine and information is the gasoline. Regardless of how superior the engine, an absence of high quality gasoline will forestall optimum efficiency.

This raises the query of the right way to generate high-quality information, for instance, the right way to rapidly and robotically generate information in areas resembling GameFi, NFTs, DeFi, and others. This consists of robotically organizing the information connections, primarily creating a knowledge graph. Extra particularly, it entails figuring out components such because the protocols to which contracts are related, the sorts of contracts, the suppliers, and different pertinent particulars. The principle purpose of this course of is to constantly present the AI with high-quality information to enhance its effectivity and accuracy in information manufacturing, thus making a virtuous cycle.

The second problem is information privateness. Whereas Web3 is essentially dedicated to decentralization and transparency, the necessity for privateness might change into paramount because the business evolves. This consists of defending customers’ identities, belongings, and transaction data. This example presents a dilemma: the transparency of knowledge on the blockchain progressively decreases, limiting the quantity of knowledge accessible to AI. Nevertheless, this challenge will probably be addressed because the business progresses, and homomorphic cryptography is a attainable resolution.

In conclusion, the convergence of AI and Web3 is inherently intertwined with a core downside: information accessibility. In essence, the final word problem for AI lies in its entry to high-quality information.

I consider reaching important integration and adoption of Web3 and AI will depend on addressing two basic challenges. First, there’s a necessity to offer enhanced companies to Web3 builders and builders, particularly in areas resembling GameFi, NFTs, and social platforms. Second, it’s crucial to scale back the boundaries on the appliance entrance to make sure a smoother person entry into the Web3 panorama.

Let’s begin with serving the developer group. On this space, two major sorts of functions stand out.

One class is AI-powered growth platforms. These platforms use AI expertise to automate the creation of code templates. Whether or not for constructing DEX platforms or NFT marketplaces, these platforms can intelligently generate code templates tailor-made to the precise wants of builders, considerably rising growth effectivity.

In video games, AI can pace up the creation of recreation fashions and the era of pictures, thus accelerating the sport growth and launch course of. These platforms have allowed builders to focus extra on creativity and innovation quite than extreme time on repetitive, primary duties.

The opposite class revolves round AI-powered information platforms. These platforms use AI to autonomously generate domain-specific information in numerous industries resembling GameFi, NFTs, SocialFi, and DeFi. The purpose is to decrease the edge for builders to make use of and apply information, and simplify information evaluation and use.

By means of AI, these platforms can robotically generate numerous information units, enriching builders with wealthy information assets and enhancing their understanding of market traits, person conduct, and extra. By offering builders with complete information help, these information platforms take away information utilization boundaries and catalyze creative functions’ emergence.

Mass adoption has at all times been a key problem within the Web3 area. For instance, the market has lately seen the emergence of blockchain options with just about negligible charges geared toward rising transactions per second (TPS). As well as, options such because the MPC pockets successfully handle the first barrier to migration from Web2 to Web3 by overcoming migration challenges.

The answer to those challenges doesn’t rely solely on AI expertise however is intertwined with the holistic evolution and growth of the Web3 ecosystem. Whereas AI performs a key position in enhancing effectivity and decreasing boundaries, the underlying infrastructure and progress of Web3 stay key components in fixing the mass adoption downside.