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Crypto and banking: tokenization of the global financial system is yet to come | Opinion
May 18, 2024
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This is Part Two of a three-part series interview with William Quigley, a cryptocurrency and blockchain investor and co-founder of WAX and Tether, conducted by Selva Ozelli exclusively for crypto.news. Part One is about Sam Bankman-Fried’s and Changpeng Zhao’s prison sentences. Part Two is about cryptocurrency and banking. Part Three is about the future of NFTs.

1) In Part One of our interview, you indicated that you began your career at Andersen as a bank auditor. Coincub recently issued a crypto banking report that ranks the most crypto-friendly banks in the world. What are your thoughts on tokenizing the banking system?

I could write a book on this topic, but I will summarize my thoughts briefly.

Money and payments have been evolving for as long as they have existed. The methods society has used to store and transfer value during my lifetime have changed, first by digitizing and now by tokenizing.  Each major upgrade to the global monetary architecture has introduced both new benefits and new risks over the past several decades. With digitization, the vast majority of what people generally think of as “money” is, in reality, ledger balances sitting on databases maintained by commercial banks. As a general rule, banks use relational databases primarily, but not exclusively, running on Unix and Unix-like operating systems, which were first developed in the 1960s

The tokenization of the global financial system is still in the early stages. Still, it may have a transformative impact on how ownership of commercial bank deposits, payments, government, and corporate bonds, money market fund shares, gold and other commodities, real estate, and other assets and liabilities are recorded on blockchains and other distributed ledgers,  enabling far-reaching new functions. 

As detailed in Coincub’s Crypto Banking Report, several financial institutions around the world have been actively exploring the possibility of tokenizing assets to improve the way we transfer value using blockchain technology to facilitate fast, secure, low-cost international payment processing services (and other transactions) through the use of encrypted distributed ledgers that provide trusted real-time verification of transactions without the need for intermediaries such as correspondent banks and clearing houses.  Notwithstanding recent advancements in digitization, our banking payment and settlement systems remain slow and inefficient for many users, with delayed settlements for large classes of transactions and numerous intermediaries, each adding layers and layers of costs. 

Tokenization and distributed ledgers have the potential to overcome many of these obstacles by globally operating around the clock and introducing settlement finality in real time. Because tokenization offers:

  • Programmability—which may make it easier for the bank and bank customers to automatically remove funds, respond to liquidity stresses immediately and automatically, and move liquidity when and where it is needed.
  • Instant settlement—which may provide the ability to hard-wire future transfers of value on the ledger that automatically self-execute based on the occurrence of future conditions, thereby increasing the speed and intensity of bank settlements. 
  • Atomic settlement—which may reduce the risk of loss in the time between payment and delivery or the simultaneous exchange and settlement of payment and delivery, including among multiple parties.
  • Immutability of the shared ledger—which may serve as a transaction record and reliable audit trail. Blockchain-based IT infrastructure can significantly reduce payment errors and cut down on account reconciliation time. The transparency and immutability of the ledger can help regulators and law enforcement agencies obtain accurate and verifiable data on token transactions and seize assets from criminals.

While tokenization of the global financial system will face challenges and risks as financial institutions, developers, regulators, and other stakeholders continue developing the technology, we already see examples of how tokenization is beginning to deliver tangible benefits in the global banking industry.  For instance, in China, the digital yuan, which was rolled out in 2020, could put China ahead of Europe and the United States in the global race to develop a state-backed digital currency, which is also known as central bank digital currency (CBDC) that is used throughout their banking system.  Digital yaun has so far been used mainly for domestic retail and public sector payments in the amount of 100 billion yuan ($14.5 billion), according to data released by the People’s Bank of China.

2) What challenges and risks will tokenization introduce to the banking industry? The fall of cryptocurrency exchange FTX, which we talked about during the first part of our interview, was a watershed moment whose knock-on effects—included a market slump, a crypto banking crisis in 2023 with five bank failures, regulatory backlash, and further bankruptcies. On April 26, U.S. regulators closed Philadelphia-based Republic First Bank, marking the nation’s first banking failure of 2024 due to “material weaknesses in internal control over financial reporting.” However, this may only be the beginning of more bank failures, as consulting firm Klaros Group analyzed about 4,000 U.S. banks and identified 282 smaller banks that face potential losses tied to higher interest rates. 

On the technological and operational side, many open questions remain concerning the tokenization of the global banking system. If tokenization plays a central role in our future financial system, with small banks being taken over by larger banks as they fail, many questions remain unanswered:

  • Will there only be a small handful of unified, interoperable ledgers of banks on which all tokenized transactions occur globally?  
  • Or will many banks maintain their own blockchains? 
  • To what extent will these banking blockchain platforms be interoperable so that customers using different blockchains can transact globally and seamlessly with each other in a safe and secure manner?
  • How will cyber security and other financial risks be handled among banks? For example, when Silicon Valley Bank failed last year, stablecoin USDC broke its dollar peg after Circle, the United States firm behind the coin, revealed that $3.3 billion of its $40 billion of USDC reserves backing it were held at Silicon Valley Bank. In contrast, at Tether (USDT)—the world’s first-ever and most traded stablecoin, which I co-established—reserve deposits transparently reported to the public daily were better managed against the risk of bank failures. 

Then, there is the legal, regulatory, and tax perspective, with countries introducing different legal regulatory and taxation regimes governing digital assets and blockchains.  Additional work is needed to clarify the extent to which ownership and other rights associated with a given asset attach to and move cross-border with a token.

Eventually, these and many other critical questions will be answered—one way or another—as financial institutions, developers, regulators, and other stakeholders continue developing blockchain technology around the world. Meanwhile, with leadership from the Financial Action Task Force (FAFT) and the Organization for Economic Co-operation and Development (OECD), some global standards are being established in money laundering and tax laws.

3) In Part One of our interview, you indicated that you co-founded the first ever fiat-backed stablecoin Tether, the world’s most traded digital asset, taking the lead in the industry with fierce competition from Meta, BRICS countries, and others. Tell us about Tether stablecoin.

Tether is a fiat-backed stablecoin launched by Tether Limited Inc. in 2014. Tether Limited is owned by the British Virgin Islands-based company iFinex Inc., which also owns Bitfinex, a Hong Kong-based cryptocurrency exchange that offers digital asset investing and trading to users outside the United States.

As of May 2024, Tether has been minted on 14 protocols and blockchains. Tether stablecoins avoid the extreme volatility of digital assets, most commonly by tying their values to the price of a traditional currency/fiat currency like the US dollar, euro, or Chinese Yuan. Meta attempted to issue a stablecoin called Libra, which was then renamed Diem, which shut down in 2022.  BRICS countries have been eager to issue a stablecoin based on a basket of fiat currencies since 2017. Tether launched #BRICST last year at the BRICs Summit, a BRICS stablecoin to be an alternative to the USD and USDT, and pegged to the Chinese Yuan, offering 10% per annum returns to meet this demand.

Tether is the largest cryptocurrency in terms of trading volume, commanding 64% of the market share among stablecoins. Having surpassed Bitcoin in 2019, USDT became the most traded digital asset in the world. As of May 4, 2024, Tether had over $110 billion, €36 million, ¥20 million, Mex $19 million, and AUDT 246,000 in circulation, leading to concerns about it being a systemic risk for digital asset markets and threatening the stability of wider financial markets.

Tether is generally considered safe for investment, primarily as a means to hedge against the volatility of other digital assets. However, like any investment, it comes with risks, and it’s essential for investors to consider Tether’s efforts to maintain a fully transparent company, by publishing a record of the current reserve assets on a daily basis and heightened regulatory compliance in cooperation with international regulators.

4) As the most traded digital asset, Tether is unavoidably used in illicit transactions. According to TRM Labs, USDT was linked to $19.3 billion of illicit transactions in 2023 and was the most used stablecoin for criminal activity in crypto last year. Do you have any comments concerning the illicit use of Tether?

Since December 1, 2023, Tether has been cooperating with law enforcement and regulatory agencies by introducing a voluntary wallet-freezing policy. Tether offers secondary market controls to freeze transactions associated with individuals listed on the United States Office of Foreign Assets Control (OFAC) Specially Designated Nationals (SDN) List. This list includes companies and individuals controlled or owned by sanctioned countries. 


Recently, Tether also announced its partnership with blockchain surveillance company Chainalysis to monitor transactions with its tokens on secondary markets. The monitoring system will help Tether identify risky crypto addresses/wallets that could be used to bypass sanctions or engage in illicit activities like terrorist financing and illicit transfers.

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🤖Can Decentralized AI Stop Big Tech from Owning the Future of Robotics?🤖
The race to build the future of robotics is no longer just about robots. It's about who controls the intelligence behind them.
 
Over the last three years, a small group of companies has emerged as the backbone of the AI revolution. Microsoft provides cloud infrastructure. NVIDIA supplies the chips. Google, OpenAI, Anthropic, Meta, and others develop the models. Together, they control much of the compute, data, and software stack powering modern AI.
 
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Will these same companies end up controlling robotics too?
 
It's a valid concern.
 
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This means anyone can contribute compute, contribute models, validate outputs and can participate.
The most visible example today is the decentralized AI network known as Bittensor (@bittensor). The network has evolved into a large ecosystem of specialized AI markets called subnets, where participants compete to provide useful machine intelligence and are rewarded based on performance. Rather than relying on a single company, intelligence is generated and validated by a distributed network of miners and validators.
 
Think of it as an attempt to build an open marketplace for AI instead of a world where intelligence is rented from a few centralized providers.
 
Why This Matters for Robotics
 
Robotics has a unique problem. Unlike chatbots, robots operate in the physical world. They need to perceive environments, make decisions, move safely and they need to learn continuously.
 
The challenge is that collecting and training on real-world robotic data is incredibly expensive. That's one reason large companies have such an advantage. They can afford the compute, simulation environments, and data infrastructure needed to train robotics models at scale.
 
This is where decentralized systems become interesting.
 
Instead of one company collecting all the data and training all the models, decentralized networks could allow thousands of contributors to participate in building robotic intelligence.
 
Imagine a future where:
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  • Delivery robots contribute navigation data.
  • Factory robots contribute manipulation data.
  • Developers contribute models.
  • Validators evaluate performance.
The resulting intelligence becomes a shared network rather than a proprietary asset.
 
That vision is beginning to emerge.
 
Bittensor's Move Toward Physical AI
 
While many people associate Bittensor (@bittensor) with language models and AI services, parts of the ecosystem are increasingly exploring embodied intelligence and robotics.
 
One example is Kinitro, a subnet focused on incentivizing the training and evaluation of embodied AI systems. The goal is to create competitive environments where developers build robotic intelligence and are rewarded based on performance.
 
The broader Bittensor ecosystem has also expanded into compute marketplaces, distributed inference systems, bandwidth infrastructure, and AI coordination layers that could eventually support robotics workloads. Several subnets now focus on decentralized compute, confidential inference, data transfer, and model training, critical components for future robotic systems.
 
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Not a decentralized robot network yet.
 
But the infrastructure that could support one.
 
Beyond Bittensor: The Rise of Physical AI Networks
 
Bittensor isn't alone.
 
Across the industry, researchers and builders are experimenting with decentralized approaches to physical AI.
 
New research published in 2026 introduced the concept of DAO-enabled decentralized physical AI, or DePAI. The idea combines robotics, decentralized infrastructure, AI models, governance systems, and human oversight into a single framework. Instead of centralized control, robots and physical infrastructure could be coordinated through transparent rules and distributed ownership models.
 
At the same time, developers are exploring decentralized operating systems for robots that allow machines to communicate directly with each other and with distributed compute resources. These architectures are designed to make robotic systems more resilient and less dependent on a single cloud provider.
 
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The goal is resilience.
 
If one server fails, the system continues.
 
If one company disappears, the network survives.
 
If one participant leaves, innovation continues.
 
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Big Tech has resources. A lot of resources.
 
Training advanced robotics models requires enormous compute budgets, sophisticated simulation environments, access to specialized hardware, and vast amounts of real-world data.
 
That's why many robotics startups still partner with major cloud providers and AI companies. It's often the fastest path to deployment.
 
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The challenge isn't just decentralizing intelligence.
 
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The Most Likely Outcome
 
The future probably won't be fully centralized. And it probably won't be fully decentralized either. Instead, we're likely heading toward a hybrid model.
 
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Train on Azure.
 
Run foundation models from OpenAI.
 
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The real question isn't whether decentralized AI can eliminate Big Tech.
 
It can't.
 
At least not anytime soon.
 
The real question is whether decentralized AI can prevent a future where a handful of companies control every robot, every model, every dataset, and every decision made by the machines operating around us.
 
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Navigating the world of blockchain 🧭
Navigating the world of blockchain can feel like learning a completely foreign language. Between technical jargon and fast-moving Web3 terminology, getting started can be overwhelming.

Whether you are exploring digital assets, building on-chain, or simply trying to understand decentralized technology, here is your foundational glossary of essential blockchain terms every beginner should know.

🏛️ 1. Core Architecture: The Base Layer

  • Blockchain: A distributed, immutable digital ledger that records transactions across a peer-to-peer network of computers. Once data is written to a block and added to the chain, it cannot be altered without altering all subsequent blocks.
  • Block: A collection of verified transactions grouped together. Once filled, the block is cryptographically linked to the previous one, forming a chronological "chain."
  • Node: An individual computer connected to a blockchain network that helps validate transactions, store ledger data, and maintain network consensus.
  • Consensus Mechanism: The set of rules and algorithms that network nodes use to agree on the validity of transactions.

    • Proof of Work (PoW): Requires miners to solve complex mathematical puzzles using computational power (e.g., Bitcoin).
    • Proof of Stake (PoS): Requires validators to lock up ("stake") native tokens as collateral to participate in block validation (e.g., Ethereum).

🔑 2. Ownership & Security: Wallets and Keys

  • Public Key (Address): An alphanumeric string that acts like your bank account number or email address. It is safe to share publicly so others can send you digital assets.
  • Private Key: A secret cryptographic passphrase or key that grants full access and control over your wallet assets. Never share your private key or seed phrase with anyone.
  • Seed Phrase (Recovery Phrase): A sequence of 12 to 24 random words generated when you set up a wallet. It acts as the master backup key to restore your wallet and access your funds on any device.
  • Hot Wallet vs. Cold Wallet:

    • Hot Wallet: A software-based crypto wallet connected to the internet (e.g., browser extensions, mobile apps), making it convenient for frequent transactions but higher risk.
    • Cold Wallet: An offline hardware device (e.g., Ledger, Coldcard) designed to isolate private keys from internet-connected threats.

⚙️ 3. Execution & Functionality: Smart Contracts and Apps

  • Smart Contract: Self-executing code stored on a blockchain that automatically enforces agreement terms once predetermined conditions are met—eliminating the need for intermediaries.
  • dApp (Decentralized Application): Applications built on top of a blockchain network that run via smart contracts rather than centralized cloud servers.
  • Gas Fees: Network transaction fees paid to validators or miners to cover the computational energy required to process actions on a blockchain.
  • Layer 1 vs. Layer 2:

    • Layer 1 (L1): The underlying primary blockchain network (e.g., Bitcoin, Ethereum, Solana) that handles base security and finality.
    • Layer 2 (L2): Secondary frameworks or companion networks built on top of an L1 to increase transaction speeds and lower gas fees (e.g., Arbitrum, Optimism, Base).

💰 4. Financial & Market Concepts

  • Tokenomics: The economic design, supply dynamics, utility, and distribution model of a cryptocurrency or token project.
  • DeFi (Decentralized Finance): Financial services—such as lending, borrowing, trading, and earning interest—built on smart contracts without traditional banks or financial intermediaries.
  • Liquidity: The ease with which an asset can be bought or sold in a market without significantly impacting its price.
  • DYOR (Do Your Own Research): A foundational golden rule in the Web3 space reminding users to independently verify technical code, whitepapers, and team backgrounds before making any capital commitments.

💡 Quick Cheat Sheet

"Not your keys, not your coins."

If you do not hold the private keys or seed phrase to your digital wallet, you do not truly own the assets inside it—a centralized entity or exchange does. Always prioritize security first as you explore the space.

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AI Is Coming for Your Job Title

Artificial intelligence may or may not take your job, but it has already broken into the human resources department and vandalized the org chart.

The evidence is all over LinkedIn, where perfectly serviceable occupations now arrive wearing titles such as “forward-deployed and agentic AI architect.” That person may be building sophisticated software. They may also be helping a chatbot remember what happened three prompts ago. Either way, somebody approved the business cards.

The expanding AI lexicon offers a useful counterpoint to the darker debate about technology and employment. Most discussion centers on how many jobs AI will eliminate. Hiring data presents a more complicated picture that includes a weak overall labor market containing a small but rapidly growing neighborhood of AI-related work.

Indeed Hiring Lab found that the number of postings on Indeed mentioning AI surged 134% from its February 2020 level by the end of 2025, even as total postings stood only 6% above that benchmark. AI appeared in a record 4.2% of Indeed postings in December.

AI, in other words, is not merely changing work. It is adding syllables to it.

The Titles Employers Actually Want

The undisputed champion is AI engineer, which ranked No. 1 on LinkedIn’s 2026 Jobs on the Rise list. The ranking, based on growth during the previous three years, also highlighted AI consultants and strategists, AI and machine-learning researchers and data annotators.

The title is popular partly because it is wonderfully accommodating. An AI engineer might build applications around large language models, connect corporate data to an AI system, improve model performance or spend Thursday afternoon persuading a customer service bot not to offer refunds for products the company doesn’t sell.

Indeed’s data showed the terminology spreading beyond Silicon Valley. Nearly 45% of data and analytics postings contained an AI-related term at the end of 2025, along with roughly 15% of marketing postings and 9% of human resources listings. A more recent Indeed analysis reported by Business Insider found that the number of frequently advertised job titles explicitly referencing AI rose from 264 in 2022 to 822 in the first quarter of 2026. Nearly two-thirds were outside traditional technology fields.

That produces titles such as AI marketing manager, AI learning specialist, responsible AI counsel and AI transformation lead. These are not always new occupations. Frequently, they are familiar jobs that have discovered a highly effective résumé keyword.

LinkedIn data cited by the World Economic Forum estimated that AI investment has supported 1.3 million positions, including AI engineers, data annotators and forward-deployed engineers, plus more than 600,000 AI-enabled data center jobs. The server racks, unlike the chatbots, still need electricians.

The Jobs With the Science-Fiction Salaries

At the upper end, AI has created a compensation market that resembles professional sports, except the competitors wear hoodies and discuss inference latency.

Syracuse University review put chief AI officer compensation between $200,000 and more than $500,000, while specialized roles can exceed $400,000 after bonuses and equity. Frontier research engineers, AI infrastructure specialists and engineers who can train or deploy advanced models command some of the largest packages.

Then there is the forward-deployed engineer, an old Palantir title that the AI boom has placed on a rocket sled. These engineers embed with customers, translating an executive’s desire to “do something with AI” into software that works. The Next Web reported that Indeed postings for the role were about 19 times higher in January than a year earlier.

CTO guide from the blog Signal Through the Noise placed forward-deployed engineer compensation between $238,000 and $700,000, research-engineering packages as high as $1.4 million and chief AI officer compensation above $1 million in some cases. It also made a less flattering observation: Many lavishly differentiated titles describe the same three basic functions. People build AI products, train models or keep the infrastructure from catching fire.

The Department of Unnecessary Titles

AI has created some genuinely new work. Evals engineers design tests to determine whether models perform reliably. AI red teamers try to make systems fail before customers do. Model behavior engineers study why an AI system responds as it does. AI governance leaders manage risks involving data, bias, security and regulation.

Other titles seem to have escaped from a brainstorming retreat.

There is the Claude Evangelist, whose mission apparently combines product education with the traditional duties of an apostle. There are vibe coders, who build software by describing what they want and accepting AI-generated code with varying degrees of supervision. “Vibe engineer” is the more respectable version, roughly equivalent to putting on a blazer before asking the machine to fix the login page.

“Context engineer” is a real discipline involving the data, instructions, memory and tools supplied to AI models. “Prompt engineer,” once advertised as a possible six-figure profession for gifted chatbot whisperers, is increasingly treated as one skill inside a broader AI role.

The CTO guide also identified “builder,” “AI-native developer,” “RAG engineer,” “agentic AI engineer” and “principal agentic GenAI forward-deployed context architect,” the last of which appears to require both technical proficiency and exceptional lung capacity.

Has AI created entirely new jobs? Absolutely. Some occupations, including AI safety, evaluation and model governance, exist because modern generative systems introduced new technical and business problems. However, many job titles are old jobs with fresh vocabulary, higher salary bands and a sudden aversion to the words “software developer.”

That may be the safest prediction about AI and employment. The machines will automate some tasks, generate others and force companies to rethink the division of labor. Before any of that is settled, however, corporate America will form a steering committee, appoint a chief agentic transformation evangelist and schedule a meeting to determine what that person does.

Source

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