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đŸ’„Wall Street Veteran Is the Face of Crypto in Ripple-SEC FightđŸ’„
December 07, 2022
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  • SEC lawsuit against Ripple nears two-year mark
  • Company says it spent $100 million on law firms

Stuart Alderoty is giving the US Securities and Exchange Commission its toughest fight against crypto regulation in one of the industry’s most important tests, even as the FTX debacle grips the world of digital assets.

Alderoty, a 63-year-old lawyer, has spent most of his career working for traditional financial players. As chief legal officer for the payments company Ripple Labs Inc., he’s now at the center of a scorched-earth litigation and public relations battle against the SEC and its chairman, Gary Gensler.

“They want to exert power that the law doesn’t otherwise give them,” Alderoty said in an interview in Washington prior to FTX’s bankruptcy.

The Ripple case is a keystone in the growing debate over regulating an industry that’s sometimes compared to the Wild West. It could soon enter a new phase: A federal judge is reviewing dueling motions from Ripple and the SEC, each asking the suit to be resolved in its favor.

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Stuart Alderoty
Photo: Ripple Labs, Inc.

Ripple claims it has already spent roughly $100 million to defend the case and, effectively, shield the entire crypto industry from what it calls overregulation by the SEC. Alderoty has turned to a roster of well-known outside lawyers, including the Obama administration’s SEC Chair Mary Jo White and her former deputy, Andrew Ceresney.

Meanwhile, the “crypto winter” descending on digital asset markets this year, and the high-profile meltdown of FTX, has the SEC touting its efforts to protect investors.

Crypto Cools

The closely watched SEC lawsuit against Ripple should provide the first “conclusive decision on whether a crypto asset is or is not a security,” said Tibor Nagy, a New York litigator who has represented crypto industry clients.

The SEC accuses Ripple, its CEO Bradley Garlinghouse, and the San Francisco-based company’s co-founder Christian Larsen of misleading investors by failing to register Ripple’s XRP—one of the world’s 10 largest crypto tokens—as a security.

Ripple raised more than $1.3 billion through an unregistered token offering, the agency said in its lawsuit, filed in December 2020.

The company argues that XRP isn’t an “investment contract,” and thus isn’t subject to the regulator’s authority. Allowing the SEC to regulate the token as a security would open the door to treating other assets—like cars, diamonds, and soybeans—as securities, Ripple said in court papers.

The SEC is feeling vindicated by its approach to crypto regulation. The agency announced Nov. 15, four days after FTX filed for bankruptcy, that it initiated 760 enforcement actions this year that led to a record $6.4 billion in fines and monetary recoveries for investors, up 64% from 2021.

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Gary Gensler, chair of the U.S. Securities and Exchange Commission.
Photo: Melissa Lyttle/Bloomberg

Regulators often look to show the public that they’re being tough on alleged bad actors after a financial disaster, said Gary DeWaal, a former chair of Katten Muchin Rosenman’s financial markets and regulation practice. Other crypto-related legal issues besides the demise of FTX have emboldened the SEC, he said.

DeWaal cited a November win by the SEC in a federal case in New Hampshire against blockchain payments network LBRY Inc. He said the ruling could expand the agency’s bid to classify digital tokens as securities under its purview.

A victory by the SEC against Ripple “would have a real chilling effect on the crypto space,” DeWaal said.

The SEC and Gensler, which have made no secret of their desire to be the top US crypto cop, declined to discuss the Ripple case. Gensler told Bloomberg News in an interview published Dec. 1 that crypto investors should embrace SEC regulation.

Allies and Adversaries

Alderoty, who grew up in Brooklyn and now lives on the Jersey Shore, joined Ripple as its top lawyer in 2019. He said he “gave up 30 years of networking” in more traditional Wall Street legal roles to try something new.

He put himself through college and law school—both at New Jersey’s Rutgers University—by taking a variety of jobs. He fought brush fires in California, drove a forklift in a light bulb factory, and memorized every US zipcode in the pre-digital era while working for United Parcel Service Inc.

Alderoty went on to serve as general counsel for CIT Group Inc.—a financial services outfit sold to First Citizens BancShares Inc.—and North American legal chief at HSBC Holdings PLC. He also was a litigator for American Express Co. and LeBoeuf, Lamb, Greene & MacRae, a precursor to a Manhattan law firm that famously flamed out.

In 2010, Alderoty was part of an advisory committee convened by the US Chamber of Commerce to vet future Supreme Court Justice Elena Kagan’s views on business issues after she was nominated for a seat on the high court.

Alderoty gave $10,000 to groups supporting Rep. Liz Cheney (R-Wyo.) in the last election cycle as the veteran lawmaker faced an onslaught from her own party over Cheney’s role on the Jan. 6 Committee. He also contributed $4,800 to a campaign for Senate Majority Leader Chuck Schumer (D.-NY), federal election records show.

Alderoty said he favors reasonable regulation of the crypto industry, but the SEC is playing politics instead of pursuing sound policy. He and Garlinghouse argue that Congress, not unelected agency leaders, should set the standards.

The two Ripple executives said the company has spent big money to make that happen. Garlinghouse said the $100 million figure includes legal bills, as well as discovery and expert witness costs incurred during the SEC litigation and year-long period before its enforcement action. Lobbying costs are separate, the CEO said.

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Mary Jo White appears at a 2014 hearing of the House Financial Services Committee.
Photo: Andrew Harrer/Bloomberg

White and Ceresney, a pair of Debevoise & Plimpton partners, are part of the legal team defending Ripple. So is Michael Kellogg, a founding partner of Kellogg, Hansen, Todd, Figel & Frederick, whose notable clients have included Saudi Arabia’s crown prince.

Alderoty declined to itemize hourly billables for Ripple’s prominent litigators.

Debevoise and King & Spalding have collectively handled more than 50% of Ripple’s litigation caseload in US federal courts in the last five years, according to Bloomberg Law data. More than 20 other firms have also represented Ripple during that time, including Boies Schiller Flexner; Cooley; K&L Gates; Quinn Emanuel Urquhart & Sullivan; and Skadden, Arps, Slate, and Meagher & Flom.

Ripple has spent $810,000 through the first three-quarters of this year on lobbyists, including those from Michael Best & Friedrich and Williams & Jensen, per Senate disclosures.

Garlinghouse, acknowledging the difficulty in forecasting legal proceedings, said he hopes for a resolution in Ripple’s dispute with the SEC by early 2023.

In the meantime, he said, the company is operating as though it has already lost the case by focusing on international markets. About 95% of Ripple’s business is abroad, said Garlinghouse, in places like Brazil, Dubai, Japan, Singapore, Switzerland, and the UK. Ripple recently sought to expand to the European Union by filing for a business license in Ireland.

“People thinking of starting a crypto or blockchain company shouldn’t do it in the US,” Garlinghouse said.

Cleary Gottlieb Steen & Hamilton partner Matthew Solomon and senior attorney Alexander Janghorbani—another pair of former SEC litigators—are representing Garlinghouse in the SEC case, while Larsen has retained a legal team led by Michael Gertzman and Martin Flumembaum of Paul, Weiss, Rifkind, Wharton & Garrison.

Flumenbaum has advised numerous high-profile clients, such as former junk bond trader Michael Milken and a late son of disgraced financier Bernard Madoff. Flumenbaum initially agreed to represent FTX founder Samuel Bankman-Fried, but last month backed out over what Paul Weiss called a “conflict.”

An ‘Already Confused Space’

The cross-border collapse of FTX and related implosion of BlockFi have created unwelcome waves for Ripple, which faces off against the SEC in a far different environment than that in which the lawsuit was filed two years ago.

Ripple said in a statement it has no “significant exposure” to the FTX and BlockFi bankruptcies. The company said it doesn’t foresee its business-to-business operations being affected.

Despite industry hopes for a decision that finally ends the uncertainty, the eventual court ruling in the Ripple-SEC case could add more “ambiguity to an already confused and ambiguous space,” said DeWaal, citing the conflicting ways regulators have approached crypto.

Nagy noted that while a “win for the SEC would be a harbinger of more regulatory action,” Ripple “appears to be playing the long game” and is likely to fight the case through appellate courts, if needed.

Ripple is working with legislators and regulators around the world to identify areas of common interest, Alderoty said. He also pledged that the company would remain aggressive in the SEC litigation.

Ripple recently prevailed in a months-long discovery fight over internal SEC communications related to a June 2018 speech by William Hinman, the SEC’s former head of corporation finance. Alderoty has called Hinman’s talk a seminal event that muddied the waters as to how the US classifies digital assets.

The “Hinman documents” remain confidential, but Alderoty has said that he feels more confident about Ripple’s legal arguments after receiving them.

Hinman, who returned last year to Simpson Thacher & Bartlett, declined a request for comment.

Alderoty in recent weeks has used the insolvencies of FTX and BlockFi to routinely take the SEC to task on Twitter. Ripple’s top lawyer intends to keep up the pressure on Gensler.

“His insistence on elevating the SEC’s quest for power over effective regulation in this country is doing deep financial damage,” Alderoty wrote last month.

The case is SEC v Ripple Labs Inc., S.D.N.Y., No. 1:20-cv-10832, 12/22/2020.

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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.
 
The latest generation of robots relies on enormous amounts of compute, simulation, training data, and foundation models. Many robotics startups today are built on infrastructure provided by large technology companies. NVIDIA's Omniverse is becoming a key simulation environment for robot training. Microsoft Azure is powering the training of robotics foundation models. Physical AI startups increasingly depend on hyperscale cloud infrastructure to train and deploy intelligent systems. Recent partnerships across the industry show just how central Big Tech has become to robotics development.
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Why Decentralized AI Exists
 
The idea behind decentralized AI is simple. Instead of a handful of companies owning the models, compute infrastructure, data pipelines, and intelligence networks, these resources are distributed across thousands of participants.
 
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.
 
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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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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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Beyond Bittensor: The Rise of Physical AI Networks
 
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Across the industry, researchers and builders are experimenting with decentralized approaches to physical AI.
 
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Run foundation models from OpenAI.
 
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It can't.
 
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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.

đŸ›ïž 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.

A 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.

A 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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