Things You Need To Know About Bitcoin Inscription

The controversial basalt stone tablet is inscribed with an ancient Hebrew inscription attributed to … [+] the biblical Jewish King Jehoash who ruled Jerusalem in the ninth century BC. (Photo by David Silverman/Getty Images)

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In 2023, bitcoin inscription has garnered immense attention in the crypto space, sparking widespread debate over whether it’s another technology hype or a valuable innovation. In this article, I will present some facts to deepen your understanding of this emerging concept.

Embedding Of Unique Data Into Blockchain

In early 2022, the blockchain realm witnessed a groundbreaking development: Bitcoin
BTC ordinals. This innovation transformed Bitcoin’s blockchain, introducing a method for creating non-fungible tokens (NFTs) by directly inscribing data like text, images, and videos onto the chain. Think of it as etching treasured texts into limited number of timeless bronzes – that’s the essence and allure of blockchain inscriptions.

This concept quickly spread to Ethereum
ETH and other Ethereum Virtual Machine (EVM)-based chains, where users, attracted by low costs, began inscribing data within transactions. This technique, mirroring the success of Ethereum Request for Comment 20 (ERC-20) tokens, is gaining traction on various chains, including Solana
SOL and Avalanche
AVAX , heralding a new era of digital asset creation and management.

Individual’s Access To Low-Cap Crypto Assets

The discussion about Bitcoin inscriptions centers on the fairness and transparency of how these assets are issued. While not perfectly equitable, they offer a more transparent alternative compared to other methods in the digital asset ecosystem, thus drawing substantial individual participation. Different from Initial Coin Offerings (ICOs) now heavily regulated and often exclusive to VCs and accredited investors, inscriptions have emerged as a beacon for individual investors seeking access to low-cap crypto assets.

This open-access distribution mechanism contrasts the conventional routes dominated by VCs and institutions, who find themselves at a crossroads in this rapidly evolving inscription landscape. Their hesitation, torn between the risk of overpaying now and the fear of missing out, underscores a significant shift in the crypto world: leveling the playing field, where individuals can now stand toe-to-toe with institutional players. This paradigm shift epitomizes one of the crypto world’s most defining characteristics – its ability to empower individuals.

Performance Testing on Blockchain Networks

The blockchain industry currently lacks real ‘killer’ applications. Such applications are necessary for testing the performance of many public chains for their massive adoption. Without superior performance, these chains are speculative for developers and users aiming to deploy widely adopted applications. However, inscription speculation is a good test, providing reference data for potential future applications. Let’s see two examples as follows:

– Celestia’s modular blockchain launched its first inscription project, CIAS. Within an hour of its launch, it received over a million visits from more than 120,000 people, with over 50% of Celestia’s transactions related to CIAS. The team later announced a remote procedure call (RPC) fault, leading to a pause in minting.

– On December 15, the Arbitrum
ARB network stopped at 10:29 AM Eastern Time due to a user surge from inscription protocols, causing network downtime for 78 minutes. Arbiscan data shows that on December 15, transactions on the Arbitrum chain spiked to 4.39 million, a new record.

Inscription minting is typically uncomplicated and often a zero-fee transaction. As shown in the above examples, chains may face congestion and outages during user surges. This indicates significant room for improvement in mainstream public chains’ performance. This improvement is crucial for handling an influx of massive Web2 users effectively in the future.

Top AI Chatbots In 2024: Choosing The Ideal Bot For Your Business

Top Generative AI chatbots in 2024

Sherren Shanequa

Integrating artificial intelligence (AI) in the business sector is no longer a luxury but a necessity. This article comprehensively analyzes various generative AI chatbots – including ChatGPT, Google
Bard, Claude AI, Bing Chat, and OORT AI – and their potential impact on business operations. It delivers an in-depth comparison, providing business leaders with essential insights to determine the AI chatbot most aligned with their unique organizational requirements.

ChatGPT: A Creative Conversationalist

OpenAI’s ChatGPT – GPT-4 stands at the forefront of natural language processing (NLP) technology and is renowned for generating human-like responses. This capability has rendered it an invaluable tool for applications across industries.

Advantages for Businesses:

  • It serves as a potent tool for creative content generation.
  • The platform offers powerful integration capabilities, allowing for seamless incorporation into existing business frameworks and offering substantial customization potential.
  • It has significantly reduced costs while enhancing efficiency.

Challenges for Businesses:

  • The model may occasionally grapple with inaccuracies and inherent biases, necessitating vigilant oversight.
  • Its limited contextual awareness poses challenges in handling sophisticated customer interactions.
  • GPT-4’s knowledge base, current as of April 2023, lacks real-time updates. This limitation can significantly hinder dynamic business environments where up-to-the-minute information is essential.
  • There is a risk of the system responding to inappropriate queries, potentially jeopardizing sensitive data.

In summary, while GPT-4 is a trailblazer in the realm of generative AI, offering tailored solutions for businesses, its challenges with accuracy and the absence of real-time updates present notable obstacles to widespread business adoption.

Google Bard: A Google Ecosystem Assistant

Seamlessly integrated into Google’s vast ecosystem, Google Bard emerges as a multifaceted digital assistant adept at streamlining various tasks. Its capabilities extend to efficiently managing schedules by interfacing with Gmail, retrieving up-to-the-minute flight and hotel information, offering navigational assistance via Google Maps, and suggesting activities through YouTube video recommendations.

Advantages for Businesses:

  • Offers seamless integration with Google’s suite of services, providing comprehensive and efficient assistance.
  • Ensures access to timely and accurate information, leveraging Google’s expansive search index.
  • Features translation capabilities for over 100 languages, significantly enhancing global communication.
  • Boasts advanced reasoning abilities, powered by Gemini Pro, an inherently multimodal AI model, for superior reasoning and decision-making.

Challenges for Businesses:

  • As it is still in the trial phase, there are prevailing uncertainties regarding its performance and reliability.
  • Exhibits limited integration potential with non-Google services, restricting its utility for some businesses.
  • The risk of occasional inaccuracies and biases is present, demanding additional oversight.

In summary, while Google Bard is a promising entrant in the realm of digital assistants, its current trial status indicates a need for further development, particularly in terms of integration with diverse business systems. As it evolves, Google Bard holds the potential to become an increasingly valuable tool for the business community.

Claude AI: A Safety-conscious AI Solution

Claude AI distinguishes itself in the AI landscape with its strong commitment to safety and ethics. This AI model ensures that its interactions are precise and ethically responsible.

Advantages for Businesses:

  • Excels in coding and mathematical tasks, offering specialized expertise.
  • Demonstrates versatility in integration across various businesses.
  • Emphasizes ethical considerations and user safety, consciously avoiding potentially harmful or unethical responses and openly acknowledging its limits rather than providing inaccurate information.

Challenges for Businesses:

  • Possesses potential limitations in conversational abilities and scope, which might restrict its utility for diverse business needs.
  • Its dedication to safety and avoidance of misinformation might limit its capacity for engaging in creative or hypothetical discussions.

In its current form, Claude AI presents an appealing option for businesses seeking to incorporate an AI chatbot into their operations, particularly due to its safety-centric approach. While its strong focus on safety is laudable, it may come at the expense of reduced creative freedom. Overall, Claude AI represents a solid choice for businesses prioritizing the integration of a safe and reliable AI chatbot into their ecosystem.

Bing Chat: A Web Search Based Assistant

Bing Chat, leveraging the capabilities of GPT-4 and integrated with Bing’s search functionalities, excels in providing swift and precise web-based contextual responses. Its unique selling point lies in its access to a vast array of current online data. This feature sets it apart from ChatGPT, with information available up to April 2023.

Advantages for Businesses:

  • Offers seamless integration with Bing’s search results, delivering timely and updated information.
  • Employs the GPT-4 model, enhanced with Bing’s web-crawling capabilities for greater accuracy.

Challenges for Businesses:

  • Despite utilizing GPT-4, it inherits certain limitations from ChatGPT, such as generating hallucinated facts, which could be misleading in critical business contexts.
  • Exhibits limited integration capabilities with non-Microsoft services, potentially restricting its versatility.
  • While effective for quick facts, its dependence on search snippets may fall short in managing complex or detailed customer interactions.
  • Bing Chat’s limited personality and conversational depth might only partially meet a diverse clientele’s varied needs and expectations.

In summary, while Bing Chat offers the latest information through its integration with Bing Search, its accuracy and integration challenges present hurdles for comprehensive business adoption. Nonetheless, its real-time data access represents a significant advantage over many AI chatbots.

OORT AI: A Privacy-Centric and Customizable AI

OORT AI distinguishes itself in the AI arena with a strong emphasis on privacy and customization. This innovative solution enables businesses to integrate a factually accurate, versatile, and secure AI system into their operations swiftly and effortlessly without requiring specialized coding skills or AI expertise. A standout feature of OORT AI is its utilization of a decentralized storage network, which ensures the utmost privacy of customer data.

Advantages for Businesses:

  • Delivers highly customized responses using a personalized knowledge base, with advanced features such as integration of images and videos.
  • Adopts a privacy-first approach with its decentralized storage network, offering enhanced data security.
  • Provides a comprehensive analytics dashboard, offering critical insights into user behavior. This feature is pivotal for refining marketing strategies, elevating customer service, and improving product offerings.
  • Ensures significant cost reductions in frontline support and operational tasks, an attractive proposition for businesses seeking to optimize budgets while maintaining high-quality AI interactions.

Challenges for Businesses:

  • Relies heavily on a well-structured dataset for optimal functioning.
  • Currently offers limited integration capabilities.

In conclusion, OORT AI is an optimal solution for businesses prioritizing privacy and response accuracy. Its unique advantage lies in its decentralized data storage, providing an additional layer of security. However, the platform’s effectiveness is contingent on the quality of the uploaded data, and it does not offer real-time updates, which may pose limitations for some business applications.

Generative AI chatbot comparison

Sherren Shanequa


In the dynamic realm of AI chatbots for businesses in 2024, ChatGPT, Google Bard, Claude AI, Bing Chat, and OORT AI have emerged as robust options, each boasting distinct strengths and considerations. Whether prioritizing advanced language processing, ethical considerations, cautious responses, or privacy and customization, the key for businesses lies in making an informed choice that aligns with their unique priorities. As technology continues to evolve, companies must leverage these AI chatbots’ strengths to elevate their operations, enhance customer interactions, and stay ahead in the ever-evolving landscape of 2024.

Top Decentralized Cloud Projects For AI Business

A visitor takes a picture of humanoid AI robot “Ameca” at International Telecommunication Union … [+] (ITU) AI for Good Global Summit in Geneva, on July 5, 2023. (Photo by FABRICE COFFRINI/AFP via Getty Images)

AFP via Getty Images

The demand for affordable computing power exponentially increases in burgeoning fields such as AIGC, Web3, and the Metaverse. Computing power, often called the “oil” of future human society, is essential. Yet, numerous independent data centers around the world are underutilized. For example, the US’s average utilization rate hovers around 12% to 18%. This underutilization leads to bottlenecks, which has a cascading effect of escalating prices for GPU computing. Consequently, several projects are underway, aiming to construct a decentralized cloud network to maximize these untapped compute resources, with a focus on AI business applications. This article highlights some of the most reputable of these projects.

Understanding AI Model Training and Inference

Compute power is predominantly utilized in AI model training and inference. AI model training is the process of employing a machine learning algorithm to build a model using a training dataset. Meanwhile, AI inference involves applying the trained model to a new dataset, generating outputs or “predictions” based on the intelligence acquired during the training phase. This allows for understanding new data and making real-time decisions. We reviewed each project in this article, specifying whether it focuses on model training, inference, or both.

Akash Network (Founded in 2017 – Training, Inference)

Akash Network, an innovative open-source supercloud network, provides a decentralized marketplace for cloud computing. It enables users to buy and sell computing resources securely and efficiently, offering a “reverse auction” system where customers can submit their desired price, with providers vying for their business. This results in competitive pricing. The network, leveraging technologies such as Kubernetes and Cosmos, employs the Akash Token (AKT) for transactions and governance. It boasts features like limitless storage, dedicated IP addresses, and high levels of privacy and security.

Cortex Labs (Founded in 2017 – Inference)

Cortex is an open-source, peer-to-peer, decentralized blockchain platform that seamlessly integrates AI models. AI developers can upload their models onto the blockchain and incorporate them into smart contracts. Cortex has accomplished significant milestones, such as launching the world’s first AI on the blockchain and enabling AI inference on-chain. It is recognized as an innovative blockchain for its AI integration and machine-learning capabilities. It empowers decentralized applications to utilize on-chain inference and fulfill smart contracts’ objectives.

Bittensor (Founded in 2019 – Inference)

Bittensor, an open-source protocol, powers a decentralized blockchain-based machine-learning network. Reminiscent of Bitcoin’s mining network, it provides censorship-resistant access to a decentralized network of machine learning models. Bittensor’s vision is to establish a pure market for AI models, creating an incentivized environment for the transparent exchange between consumers and producers of these valuable models. Its focus on encouraging AI model participation and fostering markets that create value sets it apart within the industry.

Gensyn (Founded in 2020 – Training)

Gensyn is a machine learning computing network aiming to unite the world’s computational resources into a global supercluster accessible to everyone. It enables developers to train deep learning models over a network of interconnected devices, utilizing idle computing power in a verifiable way. The network employs blockchain technology to validate the completion of deep learning tasks, initiating token-based payments. Gensyn aims to democratize compute power with decentralized technology, providing AI developers with a cost-effective, scalable, and environmentally conscious solution.

OORT (Founded in 2021 – Training, Inference)

OORT is a pioneering decentralized data cloud designed to optimize privacy and cost-efficiency by integrating global computing and storage resources. It offers enterprise-grade decentralized cloud-based solutions tailored for generative AI and data-driven businesses. With a substantial network of over 29,000 nodes across more than 100 countries, it boasts prestigious clients and partnerships, including DELL, Lenovo Image, BNB Chain, Tencent Cloud, and Cardano. OORT’s ‘Talk to Data’ (TDS) service has dramatically enhanced Lenovo Image’s customer support, boosting customer satisfaction rates from 30% to over 90%. OORT is at the forefront of transitioning traditional non-crypto users to blockchain-based decentralized cloud solutions. (Founded in 2022 – Training, Inference) has established a decentralized physical infrastructure network to source GPU computing power for AI and machine learning applications. It streamlines infrastructure deployment by leveraging an open-source library used by OpenAI to distribute ChatGPT training across over 300,000 CPUs and GPUs. Furthermore, it utilizes Solana’s blockchain for transactions, rewarding machine learning engineers and miners for contributing computing power. Unlike centralized services like AWS, offers a more adaptable approach, analogous to Kayak in the airline industry, by facilitating the booking of compute resources.

Insights From OpenAI DevDay And GPT’s Impact On Crypto Projects

SAN FRANCISCO, CALIFORNIA – NOVEMBER 06: OpenAI CEO Sam Altman speaks during the OpenAI DevDay event … [+] on November 06, 2023 in San Francisco, California. Altman delivered the keynote address at the first ever Open AI DevDay conference. (Photo by Justin Sullivan/Getty Images)

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On November 6, OpenAI marked a milestone in AI development by hosting its inaugural developer conference (“DevDay”) in San Francisco. This event showcased unveiling five groundbreaking products and features, including 1. GPT-4 Turbo, an enhanced model with more cost-effective pricing than its predecessor; 2. Assistants API; 3. Custom GPTs and the GPT Store; 4. Custom GPT Models; and 5. Copyright Shield. These introductions are poised to significantly reshape the AI landscape, setting the stage for future advancements in the field. This article delves into the insights from the conference and examines its impact on cryptocurrency projects.

Transforming GPT Into A Barrier-free Tool

In his conference speech, Sam Altman emphasized OpenAI’s goal to establish GPT as a foundational tool for AI product development. Central to this vision is the belief that a tool must be user-friendly and cost-effective for widespread adoption. The conference revealed OpenAI’s dedication to these principles. Innovations like GPT Turbo, Assistant API, and Custom GPTs are all designed to streamline GPT usage for developers and the general public. On the other hand, the GPT-3.5 Turbo 4K model now offers input tokens at a reduced cost of $0.003 (down by 4x) and output tokens at $0.006 (2.7x cheaper), reflecting a commitment to affordability.

This approach mirrors the early 1990s internet era when a concerted focus was on enhancing user experience and reducing internet costs. As the internet underwent transformative changes, investments surged in infrastructure improvements. This led to today’s scenario where bandwidth and cost are seldom concerns. Drawing a parallel, it’s anticipated that GPT’s AI-driven wave will follow a similar trajectory. AI’s usage barriers and costs are expected to diminish significantly in the foreseeable future, making GPT a go-to tool for innovation and creative endeavors. This shift is poised to democratize AI access, encouraging broader engagement and exploration in this field.

Effortlessly Creating Crypto Projects with GPT

The potential of GPT in the crypto world is immense. With Custom GPTs, even individuals with no technical knowledge can now easily create crypto-related projects. Imagine developing an airdrop search platform in minutes to direct users to the latest crypto airdrop information. The process is straightforward: navigate to “My GPTs” to tailor ChatGPT for your specific needs, define your project goals to the GPT builder, enable web browsing capabilities in your custom GPT, and then deploy it. This platform allows users to receive concise summaries from the web in response to queries like, “What are the top five airdrops in November 2023?” However, it’s crucial to remain vigilant about GPT’s tendency for ‘hallucinations’ or inaccuracies. This issue is why GPT interfaces typically include disclaimers about potential errors, underscoring the ongoing research in academia and industry to mitigate these issues.

Yet, MyGPT is still relatively basic. Building a GPT-centric application is challenging. For large-scale applications, additional functionalities beyond GPT’s capabilities are always necessary. Consider a scenario where user analytics are crucial — tracking user location distribution, average time spent on the platform, and satisfaction with the platform’s responses. Such insights necessitate further technical development beyond what GPT offers. As a result, integrating GPT into an existing crypto project becomes a more viable option in this context. For example, consider a SocialFi project enhanced with GPT APIs. This integration allows users to create distinct avatars endowed with unique speech and emotional traits, facilitating dynamic interactions within the platform. This approach not only enriches user experience but also leverages the capabilities of GPT more comprehensively and effectively.

Embracing the AI Revolution in the Crypto World

OpenAI’s DevDay has set the stage for a new era in the intersection of AI and decentralized applications. As AI tools like GPT become more sophisticated and accessible, their integration into the crypto world is poised to bring unprecedented innovation and growth. On one hand, GPT is evolving into an accessible and cost-efficient tool, poised to break down usage and financial barriers. On the other hand, leveraging GPT to create or integrate into crypto projects has become significantly more accessible, paving the way for a boost in innovative projects within the crypto ecosystem, all driven by GPT’s capabilities.

Why Verifiable Computing Matters In The Decentralized Cloud Era

A world map showing the locations where Ethereum programming is being worked on.

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The push for data privacy combined with the allure of cost savings has propelled the decentralized cloud to the forefront of technological evolution. Such projects include Dfinity, OORT, Akash, and more. Unlike a mere spin-off of traditional centralized cloud services like AWS and Google Cloud, the decentralized cloud now lays the groundwork for decentralized applications (dApps), the sprawling Web3 ecosystem, and the ever-evolving metaverse. Yet, as we venture into this new era, technical challenges, like verifiable computing, emerge prominently.

Verifiable Computing: The Quest For Authenticity

In our world dominated by vast computational needs, outsourcing complex tasks to cloud servers has become routine. But herein lies the challenge: once we receive the results, how can we be confident of their accuracy? Consider this – you assign an AI training task to a platform like AWS. A week later, you receive millions of neural network parameters from this AI training task. But how can you ensure that these parameters genuinely reflect a week’s worth of training and not just a day’s?

The most straightforward solution is to send the identical task to another cloud platform, Google Cloud, and juxtapose the results. However, this method is not only redundant but also doubles the costs. So, what’s the alternative? It is the topic of verifiable computing – a domain focused on validating outsourced computational outcomes without re-executing the entire process.

Trust Issue In A Decentralized Cloud

In a centralized setup, the issue of verifiable computing still needs to be solved. Yet, consumers rarely question the authenticity of results from platforms like AWS. This trust, whether born out of brand loyalty or sheer lack of alternatives, becomes the de-facto solution to the verification problem in centralized clouds.

However, the decentralized cloud universe operates on an entirely different premise – inherent distrust. In this setup, servers from around the globe can link up. Owners of these servers, driven by their motivations, can enter or exit this network freely. This fluidity poses a significant challenge: if you dispatch an AI training task to servers scattered across India, the US, and France without formal contracts or knowledge about their operators, how can you vouch for the results’ authenticity?

Solutions To The Verifiable Computing

The issue of verifiable computing in a decentralized cloud is a challenging problem researchers are actively trying to solve over the past 40 years. Emerging from these debates are innovative blockchain-based solutions inspired by the Proof-of-Stake mechanism. In essence, these frameworks demand service providers to ‘stake’ or lock up a certain amount of cryptocurrency when they enter the network. If the network detects any foul play or if a task issuer raises an alarm, penalties ensue, effectively slashing the malicious party’s staked assets. The EntrapNet protocol, which borrows the idea from entrapment in criminal law, serves as a beacon in this context. The key to making such a system work is ensuring it remains decentralized and autonomous. By removing the reins from any single entity, Entrapnet fosters an environment where trust can be re-established in the decentralized realm. In achieving this, we inch closer to solving the complex puzzle of verifiable computing.

In conclusion, as the decentralized cloud continues to reshape our digital landscapes, it’s imperative to address its inherent challenges head-on. Among these challenges, verifiable computing is a long-standing academic problem, which is the key to building the foundation of a decentralized cloud. Some solutions have been proposed, such as EntrapNet in the OORT data cloud. Still, researchers are studying more efficient and straightforward answers.

Absolute Privacy In Web3 Is An Illusion

Blockchain is a foundational technology for web3 applications

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Web3, often referred to interchangeably as Web 3.0, represents the next evolution of the World Wide Web. It encompasses principles such as decentralization, blockchain technologies, and token-based economics. Since blockchain is a foundational technology for web3 applications, many assume that web3 is synonymous with anonymity and privacy. However, this assumption is challenged when one understands that the blockchain protocol operates on a traditional Internet Protocol (IP)-based Peer-to-Peer (P2P) network, which raises questions about its complete anonymity.

IP-Based P2P Networks and Their Role in Web3

An IP-based P2P network represents a form of decentralized network architecture. These networks rely on the IP for data routing. Individual nodes within the network communicate directly with each other, bypassing the need for a centralized server or hub. In such a network, every participating node enjoys equal status. It can directly communicate with others without the intermediary of a central server. IP-based P2P networks find their applications in Web3. A notable example of this type of network is the browser-based P2P network crafted in Rust, employing WebRTC, WebAssembly (Wasm), and the Chord Distributed Hash Table (DHT) algorithm.

Now, we can conceptually divide blockchain transactions into two layers: the application layer and the network layer. The application layer handles transaction management, blockchain processing, and mining. In this layer, we distinguish nodes by their public keys. Meanwhile, the network layer facilitates communication between nodes. This communication transpires over an IP-based P2P network, specifically through inter-node transmission control protocol (TCP) connections. In the network layer, nodes are recognized by their IP addresses.

Bitcoin’s Transparency Dilemma: An Anonymity Paradox

We now use Bitcoin as an example to illustrate why a blockchain operating over an IP-based P2P network cannot guarantee anonymity. In the Bitcoin network, each user is distinguished by a public cryptographic key (Anonymity). Yet, if someone manages to associate this key with the real-world identity of its owner, the entire financial history of that owner can be gleaned from the public blockchain, given its inherent transparency. Since the Bitcoin blockchain operates on an IP-based P2P network, it’s feasible to correlate public keys with personal identities via various channels, including the networking protocols upon which Bitcoin is constructed. Merging transaction graph data with IP analysis poses a significant threat to privacy. It can be perilous for users who are deanonymized.

For instance, consider a transaction graph where a Bitcoin account consistently receives a majority of small transactions between 11 a.m.-2 p.m. and 5 p.m.-9 p.m. daily. This account probably belongs to a restaurant. If we associate a single transaction ID (the public key) from this graph to a real-world identity (say, a diner at the restaurant), then the establishment’s location and the identities of everyone involved in those Bitcoin transactions can be pinpointed using IP-tracking tools. Furthermore, the complete transaction histories of these diners would be exposed. It’s crucial to understand that this challenge isn’t exclusive to Bitcoin. Web3 platforms execute crypto transactions on the blockchain and, as a result, grapple with similar anonymity concerns within their IP-based P2P networks.

Methods to prevent Web3 de-anonymization

In recent years, academia has churned out commendable solutions to tackle this challenge. One avenue is overhauling the existing network protocols. For instance, shifting from IP-based to content-based networks (CBN) offers promise. A content-based network represents a new kind of communication infrastructure. In this system, the flow of messages across the network is determined by the content within the messages, not by specific addresses provided by senders and attached to those messages. The primary distinction between content-based and IP-based networks lies in their driving forces: content-based networks rely on the actual message content, whereas IP-based networks depend on explicit addresses given by senders and linked to the messages. This approach better safeguards users’ identities, reducing concerns about potential IP address breaches. Another promising strategy is revamping the IP-based P2P network to offer robust anonymity guarantees, as seen with Dandelion. Dandelion fundamentally reshapes the Bitcoin networking architecture to thwart network-induced deanonymization.

In conclusion, achieving unadulterated anonymity in web3 is an arduous task. The journey ahead mandates continued exploration and innovation to transform web3 into a sanctuary of privacy.

Why Blockchain Is Necessary In Decentralized Clouds

Employee checking a server rack at the new data center in Biere, Germany.

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In an era dominated by centralized entities, decentralized infrastructures (or clouds) emerge as the bedrock for a new wave of decentralized applications. Decentralized clouds such as Dfinity‘s Internet Computer, Filecoin‘s decentralized storage, and OORT‘s decentralized data cloud drive technological innovations. The building blocks of this decentralization technology are diverse, involving blockchain, networking science, coding theory, and scheduling optimization, to name a few. However, the role of blockchain still needs to be discovered to many. This article seeks to demystify blockchain’s pivotal role in decentralized clouds for those less acquainted with decentralization technologies.

Decentralization Is Beyond Geographical Distribution

Decentralization is often perceived merely as data being processed and stored in geographically distributed servers. This is a misconception that only captures part of the essence of decentralization. The other pivotal aspect is “decentralized governance.” It means that the network’s servers are managed and operated by many independent and diverse entities from different regions, an element arguably more essential than mere geographical distribution. To illustrate, imagine if a singular organization possessed control over every Bitcoin
mining machine worldwide; it could manipulate the Bitcoin ledger at will, potentially annihilating its value instantaneously. This scenario underscores the deficiencies and risks of relying solely on geographical decentralization, emphasizing the imperative need for decentralized governance to safeguard the integrity and balance of the system. This also highlights why tech giants like Amazon
or Google
, despite their own capability to create decentralized cloud networks, cannot supersede existing decentralized infrastructure projects—their governance remains centralized.

Blockchain Provides The Foundation For Decentralized Governance

As long as we comprehend that decentralized governance is pivotal for constructing a decentralized infrastructure, we require a mechanism to facilitate this form of governance. Blockchain is the technology that fulfills this need. The blockchain network interlinks all geo-distributed data servers globally and offers two main advantages. On the one hand, blockchain builds trust in trustless environments. For instance, a data center owner in India may neither trust nor know a data center owner in France. However, both parties need assurance that the resources contributed by the other are authentic and the rewards received are fair concerning the contributed resources. The blockchain serves as a public ledger, recording all actions of every participant in the network, like the transaction recording of every user in the Bitcoin network. The transparency and immutability of blockchain foster trust among all parties. On the other hand, Blockchain facilitates incentives to each participant via cryptocurrency. Cross-border microtransactions are crucial for incentivizing each entity in the decentralized network, a feature not supported by the current financial systems. For instance, should we need to send a few dollars to each of thousands of parties from 100+ countries, cryptocurrency is the best solution. By doing so, blockchain is the underlying necessary technology. Beyond these, blockchain avails numerous other benefits in decentralized infrastructures. We may discuss these benefits in future articles.

Decentralized Infrastructures Paves The Way For Privacy And Affordability

The ascent of decentralized infrastructures is fueled by the increasing demand for data privacy and cost-effectiveness—areas where centralized infrastructures are losing ground. While current decentralized solutions may not match the enterprise-grade performance of services like AWS or Google, the continuous evolution of technology promises a future where decentralization is the norm, pushing centralized entities to realign their strategies with this unfolding reality. While the journey of decentralized infrastructures is laden with challenges, the marriage of technologies like blockchain heralds a future of possibilities, empowering a world where decentralization is not an alternative but a standard. The nuanced understanding of blockchain’s role is crucial for embracing the future of decentralization.

Key Takeaways From 2023 Asian TOKEN2049 Event

Japanese tattoo artist Ichi Hatano posing with a “hannya” mask digital image on an digital display, … [+] selling his designs as non-fungible tokens (NFTs).

AFP via Getty Images

The crypto community gathered in Singapore last week for TOKEN2049, one of the premier blockchain events in Asia. While 2022’s brutal bear market dampened past years’ extravagant parties and hype, the 10,000+ attendees were largely optimistic about the industry bouncing back. According to one of the event organizers, the enthusiasm and energy at TOKEN2049 showed the crypto community is resilient and still believes blockchain will revolutionize finance and beyond. Here are some of the main themes and insights that emerged from over 100+ speakers across stages, countless panel discussions, and nonstop networking:

Eyes On 2024 For The Next Bull Run

Most industry veterans believe the bear market has bottomed out, and the next bull cycle will kick off in 2024. Several potential catalysts were cited, including the Bitcoin
halving in spring 2024, reducing new supply by 50%, and U.S. approval of a spot Bitcoin ETF. According to the co-founder of a quantitative crypto trading firm, the Bitcoin Spot ETF is inevitable. He said that with the halving, 2024 is when we’ll enter the next cycle. The sentiment was similar among venture investors. According to one crypto wallet startup founder, we’ll have a bull market next year, and they expect Bitcoin’s price to increase significantly in 2024. Some warned that severe down cycles are a feature of the crypto market as it matures. As one founding partner at a VC firm stated, bear markets are like a forest fire that clears away underbrush so more substantial new growth can emerge.

AI And Blockchain: A Power Duo

Integrating artificial intelligence (AI) and blockchain technology has been a hot topic of discussion. Crypto projects increasingly seek to incorporate AI for use cases like transaction monitoring, trading algorithms, and data analytics. The crypto industry needs new technologies like AI to reach the next level. On the other hand, AI researchers see blockchains as valuable for decentralized computing, storage, and securely transmitting sensitive data. For instance, blockchain is one of the core technologies to establish a decentralized cloud infrastructure which can significantly reduce cost and enhance data privacy. OORT and Gensyn are the projects along this line. Consequently, this symbiotic relationship could supercharge development and mainstream adoption on both fronts.

Asia Ascending

Asia, especially Southeast Asia (SEA), is rapidly becoming the epicenter of crypto innovation and adoption. Western projects are increasingly looking east for funding, development talent, and users. The U.S. regulatory climate has stifled projects there, while Asia is more forward-thinking. SEA also has demographics ripe for web3 engagement. Younger generations in SEA are diving into crypto gaming and metaverses in a big way. Meanwhile, Asian crypto whales have emerged and are actively deploying capital. One VC partner said they see tremendous regional startup activity and deal flow.

Old Money Goes New School

The most significant shift compared to past TOKEN2049 events was the growing presence of traditional financial institutions. An executive from a central Asian bank said they’re opening crypto trading desks and preparing various ETF products. The bitcoin halving is going to be a huge deal, he said. Others shared plans to participate in digital asset markets via research, trading, custody, and client services. Major financial institutions like Fidelity are ramping up digital asset offerings.

While the crypto winter has been long and harsh, freezing out speculators and scammers, the attendees of TOKEN2049 were largely optimistic about spring returning. The seeds of the next bull run are being planted as adoption spreads, regulation evolves, and financial incumbents recognize blockchain’s revolutionary potential. By accelerating collaboration between critical sectors like finance, technology, and research, TOKEN2049 is helping position Asia at the forefront of that blockchain future.

The Crypto Fintech Redefines Latin America’s Financial Landscape

A woman buys in a store that accepts bitcoins in El Zonte, La Libertad, El Salvador on September 4, … [+] 2021.

AFP via Getty Images

As Latin America stands on the brink of a crypto fintech renaissance, countries such as Brazil, Argentina, and Mexico are leading a transformation reverberating across the region. With a backdrop of high inflation, political challenges, and an alarmingly high unbanked populace, many crypto startups emerge to reshape the future of Latin American finance. This article dives deep into the factors propelling this wave and how Agente BTC
, a crypto startup in Peru, is catalyzing change in a region ripe for financial evolution.

Leading Countries in Latin America’s Crypto Fintech Space

Latin America is poised for a crypto fintech revolution, with countries like Brazil, Argentina, Chile, Colombia, Mexico, and Peru leading the change. This trend is expected to expand to the Caribbean and Central American nations, including Honduras and Guatemala. The commonalities among these countries are the impact of high inflation, a significant percentage of unbanked individuals, and political challenges. For instance, Argentina’s annual inflation was 104% in March 2023. These factors have led to inappropriate monetary policies and a lack of financial education, creating a need for alternative solutions.

The highest penetration of crypto users is in Argentina. The ownership of digital currencies in Argentina is about 23.5% of its population, but this is still not even 1% of the total number of users in India. Brazil is also gaining traction, attracting investments from notable groups like Softbank that have recognized the potential of the region’s crypto market.

Education plays a crucial role in driving change. It emphasizes the significance of large-scale educational events in Argentina and Brazil and initiatives like Devcon in Colombia. Currently, education and research groups are emerging in this region. Moreover, crypto companies contribute to education with free events and partnerships with universities.

Regulators in Latin America are engaging with crypto institutions to foster development and establish regulations supporting these technologies’ growth. Success stories include Ukraine’s crypto donations during wartime and El Salvador’s increased tourism after legalizing crypto, as examples of the potential benefits for the region.

AgenteBTC Democratizes Financial Inclusion

AgenteBTC, a crypto startup founded in 2019 in Peru, provides access to crypto assets, higher returns, lower remittance rates, and 14,000+ physical cash-in points in Latin America. In an interview with Victor Egoavil, CEO of Agente BTC, the company unveils its vision of democratizing financial inclusion and enhancing accessibility across Latin America. Recognizing the challenges faced in the region, Agente BTC emphasizes its disruptive approach, tailored to address the population’s unique needs.

Victor highlights the urgent need for financial inclusion: “In Latin America, a staggering 70% of the population remains unbanked or underbanked, and an overwhelming 58% of point-of-sale transactions are still settled in cash.” To address this, Agente BTC has launched an ambitious initiative called KasNet, aiming to establish 15,000 centers across Peru. This initiative can potentially reach as many as 32 million previously underserved customers.

What sets Agente BTC apart is its meticulous attention to the specific requirements of the Latin American landscape. The company firmly believes that engaging with local communities and immersing in their culture is essential to making a lasting impact. Victor remarks, “By strategically positioning ourselves at the heart of communities and actively engaging with local culture, we aim to redefine the boundaries of financial accessibility.”

Crypto Fintech Opportunities Surge in Latin America

Latin America’s crypto fintech space is experiencing significant growth, led by countries like Brazil, Argentina, Chile, Colombia, Mexico, and Peru. With the Caribbean and Central American nations soon to follow suit, the region is poised for a transformative financial evolution. Agente BTC’s vision of democratizing financial inclusion and its tailored strategies position it as a key player in reshaping the future of finance across Latin America.

What Businesses Need To Consider For Generative AI Adoption

Generative AI powered chatbot for online customer service.


Recently, there has been a notable trend in adopting Artificial Intelligence Generated Content (AIGC) across diverse industries. Some well-known implementations of this transformative technology include products like Notion AI, Microsoft Copilot, and Adobe Photoshop. However, integrating AIGC into one’s business has its challenges. Let’s explore the pivotal technical considerations one should be aware of:

Ensuring Factual Accuracy

Large Language Models (LLMs) are typically trained on vast and varied datasets, equipping them with an extensive breadth of knowledge. This enables them to answer a broad spectrum of questions. Often, companies need to customize an AI agent using their proprietary data, tasking it with providing answers grounded in this specialized knowledge base. However, the custom AI agent sometimes gives an answer not generated from this specific knowledge base. A prevalent challenge arises when the AI agent, unable to retrieve a response from its particular knowledge base, reverts to its broader general knowledge. While this is a testament to its adaptability and creativity, it can be a double-edged sword. For instance, an AI-driven customer service assistant must deliver precise responses to address user concerns. Misleading customers with general or incorrect information is counterproductive and potentially detrimental. Thus, the solution for businesses is to augment LLMs with robust algorithms and safeguards, ensuring the unwavering accuracy of the information provided.

Elevating Intelligence for Human-like User Experience

At the heart of successful AIGC integration is an exceptional user experience. AI agents that fall short in their intelligence quotient risk being abandoned. A case in point is the website chatbot or voice bots in customer service. However, AIGC offers the potential for a paradigm shift by upping the AI agent intelligence. Consider its application in customer service: An AI agent enabled with AIGC could present users with multimodal responses, ranging from text and voice to visuals like images and videos. As illustrated in the Figure (an example from OORT TDS), this multimodal approach enhances customer satisfaction considerably. Yet, it’s vital to understand that LLMs, in their native state, might not meet this desired level of intelligence. Pushing the boundaries requires the integration of advanced algorithms—like those that can process multimodal inputs, enabling the AI to comprehend diverse data types, from Excel spreadsheets to photographs.

Multimodal response in customer service powered by OORT TDS

Max Li

Prioritizing Information Security

As AI agents become so capable in data processing, questions surrounding the safety of user data surge to the forefront. Where is the data stored? How does the AI access and utilize it? Such concerns underscore the ever-growing importance of data privacy and security in the age of AI. On the other hand, AIGC might produce detrimental or censored information. Current measures to filter and block unsuitable content on the internet, often reliant on keyword-based algorithms, may seem adequate. However, LLM-empowered AI agents bring a nuanced understanding—they can glean user intent, often reading between the lines rather than just processing direct keyword inputs. Therefore, ensuring the privacy and security of user datasets and guaranteeing the appropriateness of the AI’s outputs must be addressed by businesses before full-scale AIGC adoption.

AIGC is on the Brink of Widespread Adoption

The evident success of AIGC, shown by popular applications like Notion, suggests it will soon be common in many industries. It’s not a question of ‘if’ but ‘when.’ However, as we approach this significant change, three main points remain very important: factual accuracy, human-like intelligence, and data security. Building on the foundation of Large Language Models (LLMs), it’s up to innovators to create advanced algorithms that tackle and overcome these challenges, ensuring a smooth and safe integration of AIGC into our daily tech landscape.

How To Use AI To Gain Ethereum Market Insights

AI becomes a powerful tool to gain Ethereum insights

AFP via Getty Images

In this article, we explore the vast potential of Large Language Model (LLM)-based AI systems in their application to the dynamic Ethereum market analysis. For easy understanding, we use the AI analysis on Ethereum Non-Fungible Token (NFT) marketplace as an example. Overall, applying AI to gain Ethereum insights needs three steps. Firstly, one must gather vital on-chain Ethereum data and associated off-chain metadata. Following this, one needs to construct a specialized database designed for the LLM. The final step is to apply the LLM-based retrieval augmented generation (RAG) approach to analyze data and gain insights.

Collect On-chain And Off-chain NFT Data

In the context of NFTs, the data collection necessitates diving into both the on-chain and off-chain dimensions. OpenSea, a premier NFT marketplace, presents a fertile ground for extracting on-chain data, such as NFT transaction details and metadata. One can conduct the data collection process via OpenSea’s API documentation, a simple approach to accessing on-chain data. Concurrently, the off-chain data, such as NFT images or videos, are always stored in InterPlanetary File System (IPFS), a decentralized storage network. The initial step involves identifying the content-addressed IPFS hash, a unique identifier signifying the NFT image within IPFS. This hash is typically in the NFT metadata or forms part of the transaction details. The next move involves constructing the HTTP gateway URL. Equipped with the IPFS hash, one can build the URL, which subsequently enables the sending of an HTTP request. Tools such as Axios or the inherent fetch function serve as ideal aids to send an HTTP GET request to the constructed URL, thereby retrieving the NFT image data.

Build An LLM Knowledge Database

Equipped with the LLM with appropriate data for efficient operation, it is essential to construct a comprehensive knowledge database. This knowledge database would serve as a reliable resource for semantic search, enabling the identification and retrieval of the most relevant data. Consequently, the LLM is provided with the correct context, thereby facilitating the generation of precise outputs to your request. Upon the on-chain and off-chain data is acquired, a systematic cleaning and organization of the amassed data is necessary. This process includes identifying relevant properties and attributes integral to NFT analysis, such as categories, design studios, intellectual property holders, and sales history. Many approaches exist to extract these properties from images, such as through the NFT metadata or free image recognition software. Following successfully extracting and encoding the data features, we can quickly build a personalized LLM database.

Use An LLM-based AI Model To Gain NFT Insights

Relying exclusively on an LLM for generating factual text or even fine-tuning the model with your database may not necessarily yield a factually accurate response. Thus, we suggest a RAG approach for NFT data analysis. RAG represents a methodology that segregates the knowledge database from the language model. This methodology entails posing a question or submitting a request to the AI agent, such as inquiries related to emergent NFT trends, distinct properties, or correlations and relationships between property attributes and NFT market performance. Subsequently, a search algorithm, for instance, Azure Cognitive Search, probes the most pertinent text within the knowledge database, likely to contain the required answer. As a final step, a succinct prompt, in the form of instructions to the LLM along with relevant document text, is directed to the LLM. The model then utilizes this input to formulate a response that aligns with the original request, ensuring a fact-based, contextually relevant output.

AI Will Become A Powerful Tool In The Blockchain Industry

This article utilizes Ethereum NFT analysis as a representative case to demonstrate the efficacy of employing an LLM-based AI methodology for obtaining blockchain insights. In its versatility, this method holds potential for widespread application within the blockchain domain. We anticipate that the future will witness an influx of LLM tools to enhance and facilitate various aspects of blockchain operation and analysis.

How Decentralized Networks Reduce The AI Costs

Google introduces its new Compute Engine infrastructure service at USA-Technology-Google I/O … [+] Developer Conference.

Corbis via Getty Images

The emergence of Artificial Intelligence Generate Content (AIGC) has disrupted multiple industries, revolutionizing sectors including customer service, consulting, finance analysis, and design. Its conversational interface and true intelligence have brought significant refinement to these businesses. Yet, the high costs associated with AI training and inference impede the widespread adoption of AIGC among individuals and small to medium-sized enterprises. For instance, the cost of a single training session for GPT-3 is estimated to be around $1.4 million, and the training cost can be up to $12 million for some larger models. To tackle this challenge, decentralized computing networks, serving as the backbone of the next-generation internet, hold promise in reducing costs. By leveraging decentralized resources, AIGC can overcome financial barriers, enabling broader access and utilization of its transformative capabilities.

Decentralized Network Connects Global Underutilized Computing Resources

In the realm of decentralized computing, a network is formed by harnessing the collective power of underutilized computing resources across the globe, ranging from data centers and servers to high-end personal computers. For instance, up to 85% of total GPU capacity sits idle. This untapped potential provides a remarkable opportunity for AIGC. As an illustration, an AI startup based in New York could dispatch its training tasks to servers located in the Middle East. By doing so, the aggregated costs, encompassing server expenses, electricity consumption, and maintenance, would be significantly lower than utilizing services from a centralized provider like AWS in West Virginia. Such decentralization opens doors to cost-efficient and geographically distributed AI processing, facilitating innovation on a global scale.

AI Computing Can Be Conducted In Geo-distributed Computing Servers

The leverage of global under-utilized computing resources can be implemented through two distinct methods: model parallelism and data parallelism.

Model parallelism involves fragmenting the model into a set of interconnected smaller models. Each of these smaller models is then assigned to a server, with training taking place simultaneously across all servers using the same dataset. During the training process, these smaller models exchange information among themselves, ultimately converging towards a globally optimized training outcome. This approach allows for efficient utilization of distributed resources, optimizing both computational and memory requirements.

Data parallelism, on the other hand, revolves around employing the same model across multiple servers while each server operates on a different subset of the dataset. Rather than transferring all the data to a centralized server, the model is distributed among the servers, each utilizing its local dataset for training. Subsequently, model fusion takes place, where the trained models from each server are combined to create a unified model, enriched by the diversity of the various datasets.

By harnessing the power of model parallelism and data parallelism, organizations can achieve cost savings in AI training while capitalizing on distributed resources.

Blockchain Builds A Trustable Decentralized Network

One of the primary obstacles in utilizing servers contributed by unknown parties worldwide is establishing trust and ensuring their honest and accurate performance. Addressing this challenge necessitates the implementation of a well-designed incentive mechanism based on blockchain technology. By leveraging blockchain, honest and high-quality servers can be incentivized, while those failing to meet the required standards can face penalties.

The integration of blockchain is crucial due to its ability to facilitate cross-border microtransactions, which are inadequately supported by the current financial system. Consider that the customer needs to pay small paychecks of $50 each to a couple of servers located in Kenya, South Korea, and India. Furthermore, the transparency inherent in blockchain technology ensures fairness among servers, promoting sustainable contributions and fostering a trustworthy ecosystem.

Decentralized Network Is Necessary For AIGC’s Adoption

In the ever-expanding realm of artificial intelligence, the development and utilization of AIGC should not remain confined to tech giants like Google
and Microsoft
. The continuous release of open-source large language models (LLMs) presents a golden opportunity for individuals and smaller players to harness the power of AI. Empowering them to train and customize their own models to fit their unique business needs is the key to unlocking their potential. However, to realize this vision, a crucial element must be addressed: ensuring easy access to substantial and cost-effective computing power. As one solution to this vital ingredient, a decentralized network paves the way for a more inclusive and dynamic AI landscape, where innovation knows no boundaries.

Top Startups And Crypto Tools To Watch For Blockchain’s Next Billion Users – Part II

Bitcoin ATMs have soared in recent years.

AFP via Getty Images

In this article, we continue the topic with discussions on account abstraction, blockchain scalability, and decentralized infrastructure.

Account Abstraction

The crypto wallet serves as the entry point for many individuals entering the blockchain space, but it often poses challenges for newcomers. Simplifying the interaction with crypto wallets is crucial, including streamlining processes such as handling gas fees, seed phrases, and approvals.

Account abstraction has long been desired within the developer community, as it unlocks programmable authorizations and encourages a wider range of wallet and protocol designs. This feature has numerous practical applications, such as enhancing the user experience of storing and recovering private keys, facilitating easier payment of gas fees, allowing accounts to change public and private keys, supporting diverse signature verification systems (including post-quantum safe signature algorithms), and more.

By incorporating account abstraction, the blockchain ecosystem can significantly improve the accessibility, usability, and security of crypto wallets. It ultimately makes blockchain technology more user-friendly and inclusive.

Projects using account abstraction or its variations include zkSync and Alchemy Bundler.

Blockchain Scalability

Scalability refers to a computer system’s capacity to handle increasing workloads, such as large databases or search engines. Blockchain networks often struggle with effective scalability when dealing with significant amounts of transactions. People have made insufficient efforts to adapt blockchain systems to cope with growing workloads, data, and resource demands (e.g., computing power, servers, or bandwidth). To address these limitations, Layer 2 solutions have emerged as protocols built on top of Layer 1 blockchains like Bitcoin
or Ethereum
. It aims to enhance scalability, privacy, and other characteristics of the underlying blockchain.

Various Layer 2 solutions exist, including state channels, sidechains, optimistic rollups, and zero-knowledge roll-ups. Rollups, in particular, offer a scaling solution that can lower transaction costs and increase throughput on blockchain protocols. Among these solutions, zkEVM stands out by leveraging the power of zero-knowledge proofs and maintaining full compatibility with the Ethereum virtual machine. This approach positions zkEVM favorably in terms of privacy, security, and scalability for the foreseeable future.

By embracing Layer 2 solutions like zkEVM, blockchain networks can alleviate scalability issues, enabling them to handle larger workloads, accommodate the growing demands of data-intensive applications, offer improved performance, and expand the range of possible use cases across various industries.

Projects to watch include zkSync, Scroll, Arbitrum
, and Taiko.

Decentralized Infrastructure

Decentralized infrastructure has indeed posed challenges for the blockchain industry, particularly in terms of deployment and management. Currently, many decentralized applications rely on centralized infrastructure providers like AWS for their hosting needs. However, to achieve widespread adoption, it is crucial to ensure easy access and enterprise-grade performance for decentralized infrastructure. This entails organizing blockchain data for effortless accessibility and deploying applications on a global network of geo-distributed servers to guarantee data ownership, eliminate single-node failure, and mitigate censorship risks.

Noteworthy examples of decentralized infrastructure services include decentralized website hosting, decentralized storage and compute, as well as decentralized database. By addressing these challenges and promoting user-friendly decentralized infrastructure, the blockchain industry can unlock the potential for mass adoption. It enables increased privacy, security, and reliability in the digital ecosystem.

Projects to watch include The Graph, Alchemy, Oort, Storj, and Gensyn.

Billions Of Users Embrace Decentralization

As the awareness and importance of data privacy and ownership continue to rise, the demand for robust solutions will intensify in the coming years. To cater to this growing need, blockchain-based decentralized technologies and products must advance swiftly. The rapid maturation of decentralized solutions, coupled with enhanced scalability and seamless user experiences, will be vital in capturing the attention and adoption of the next billion users. By addressing these challenges, blockchain-based decentralized technologies can pave the way for a data-centric future that respects individual privacy and ownership.

Top Startups And Crypto Tools To Watch For Blockchain’s Next Billion Users

Blockchain and cryptocurrencies gain popularity worldwide.

Getty Images

Although blockchain technology has been developing fast since the birth of Bitcoin
, the adoption of blockchain and crypto remains low due to the immaturity of the technology, products, and regulations in the blockchain space. As of 2023, the estimated global crypto ownership rate averages 4.2%, with over 420 million crypto users worldwide, according to the Singapore-based fintech company Triple A. However, these statistics signify a potentially huge market. In what follows, we aim to identify blockchain projects and tools that seek to onboard the next billion users. The best discussion for this topic falls into three categories: decentralized applications, protocols, and infrastructure. We present the detailed discussions in Part I and Part II articles. Part I article presents evolving decentralized finance (Defi) and evolving non-fungible tokens (NFTs). Part II article presents account abstraction, blockchain scalability, and decentralized infrastructure.

Evolving DeFi

DeFi is an umbrella term for peer-to-peer financial services using blockchain. With DeFi, users can perform most banking functions such as earning interest, borrowing, lending, buying insurance, trading derivatives and assets, and more. The process is faster and doesn’t require paperwork or intermediaries.

As DeFi continues to grow and enhance liquidity, capital efficiency, and other aspects, more users will shift from centralized financial systems to decentralized solutions. Decentralized exchanges (DEX) are a cornerstone of DeFi. Due to compliance issues with centralized crypto exchanges and the decentralized nature of blockchain, people are increasingly inclined towards DEX for trading. Of course, the compliance of DEX will also mature over time.

Furthermore, DeFi derivatives, which include cryptocurrencies and other assets on the blockchain, are gaining significant interest and are becoming equally important in the world of crypto finance. In traditional finance, a derivative is a contract whose value derives from the performance of an underlying entity, such as an asset, commodity, index, interest rate, or another derivative. Given the importance of derivative contracts in mature traditional financial systems, it’s no surprise that derivatives are emerging in crypto finance markets.

Projects to watch include, dYdX
, Curve Finance, Trader Joe, and Maverick Protocol.

Evolving NFTs

NFTs are distinct cryptographic tokens that exist on a blockchain and cannot be duplicated. These tokens can represent both digital and real-world items, such as artwork and real estate. While the NFT market has experienced a downturn in the past year, it cannot be denied that NFTs have significantly contributed to raising awareness and attracting the general public to the blockchain industry. The advancements in the following two NFT technologies will play a significant role in the future adoption of NFTs by billions of users. On the one hand, ERC-6551 is the new token standard for the Ethereum
network, elevating the capabilities of ERC-721 NFTs to a new level, and unlocking new use cases for NFTs.

Currently, NFTs are primarily static assets with limited functionality beyond ownership transfer. They lack transaction history, signature control, and linked ownership of all benefits received, such as airdropped tokens. By utilizing ERC-6551, all relevant benefits associated with an NFT, including airdropped tokens, will be recorded within the NFT itself. When selling an NFT, buyers will also see these records, and all associated tokens will be transferred to the buyer. With ERC-6551, we can seamlessly add new layers of ownership to all existing and new NFTs, opening up use cases that project creators have long desired but have yet to find simple solutions for.

On the other hand, dynamic NFTs, called dNFTs are NFTs with encoded smart contract logic that automatically change their metadata based on external conditions. They enable the creation of digital items that can evolve and change over time, offering a more engaging experience for buyers and fans in various domains such as gaming, music, art, and more. For instance, imagine a digital weapon in a game that gains new abilities or attributes as the player progresses. With dNFTs, these advancements can be seamlessly reflected in the corresponding NFT, creating an immersive and dynamic gaming experience. This innovative use of blockchain technology adds a new layer of depth and customization to gaming, enhancing player engagement and opening up exciting possibilities for interactive storytelling within virtual worlds.

Projects to watch include Rarible and Art Blocks.

We will continue the discussion in the Part II article.