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Bitcoin (BTC) mining company Bitdeer announced today that it had acquired a 101-MW gas-fired power plant near Fox Creek, Alberta, to build a "vertically integrated" BTC mining operation.
“We are really excited about planting roots in Alberta, our first site in Canada. This acquisition is the culmination of extensive collaboration with multiple government agencies and the Canadian Blockchain Consortium," Haris Basit, chief strategy officer at Bitdeer, said in a press release. "It marks a significant step in our strategy to become the first fully-vertically integrated Bitcoin miner, giving us unmatched control over costs, energy efficiency, and scalability."
Bitdeer says they plan to build out a 99 MW datacenter on the site. The site has the capacity to scale to 1 GW. Energy production costs for the facility will be between $20 to $25 per MW/h.
The plant is also licensed for a 99 MW interconnect to the local power grid, and Bitdeer said it plans to sell power back to the Alberta grid to stabilize prices during periods of high demand.
"By combining our own power generation, SEALMINER mining machines and opportunistic grid participation, we believe this site will set a new benchmark for industry unit economics," Basit added.
Bitdeer says it plans to commence site preparation and initial infrastructure development in Q2 2025 and have it fully operational in Q4 2026.
U.S. Commodity Futures Trading Commission (CFTC) Acting Chair Caroline Pham said Tuesday the regulatory agency has reorganized its enforcement division to “refocus” on fraud and “stop regulation by enforcement.”
Under former Chairman Rostin Behnam, the CFTC’s Division of Enforcement had a variety of task forces, including one focused on insider trading, another focused on cybersecurity and emerging technologies and a third aimed at combatting environmental fraud. The new reorganization slims the number of task forces down to just two.
The newly-created Complex Fraud Task Force is tasked with handling the enforcement, from preliminary inquiries to litigations, of complex fraud and manipulation across all asset classes. Paul Hayeck, deputy director of the enforcement division, will be the Complex Fraud Task Force’s acting chief. The Retail Fraud and General Enforcement Task Force will handle retail fraud and general enforcement, and will be led by Charles Marvine, also a deputy director of the agency’s enforcement division.
“This simplified structure will stop regulation by enforcement and is more efficient,” Pham said in a press statement. “These much-needed changes will maximize the CFTC’s resources to bring more actions to pursue fraudsters and other bad actors, and not punish good citizens.”
According to the CFTC’s announcement, the new structure will “more efficiently utilize the CFTC’s resources to prevent fraud, manipulation and abuse and ensure market integrity” as well as “provide enhanced governance and oversight of enforcement matters to prevent overreach and enhance consistency, fairness and due process.”
The CFTC’s rejection of the so-called regulation by enforcement strategy pursued under the Biden Administration echoes the ongoing about-face at the U.S. Securities and Exchange Commission, the CFTC's sister regulatory agency. Under current Acting Chair Mark Uyeda, the SEC has established a Crypto Task Force and disavowed the agency’s previous strategy of regulation by enforcement under former Chair Gary Gensler.
Read more: SEC Commissioner Hester Peirce Lays Out 10 Priorities for New Crypto Task Force
The rally in bitcoin (BTC) and crypto from the weekend's tariff-induced panic has proven to be a short-lived one.
Late in the U.S. trading day, bitcoin was down 4.8% over the past 24 hours to $96,900 after having climbed up to the $101,000 level just two hours earlier.
Much of the altcoin sector fared worse, with solana (SOL), (XRP), cardano (ADA) and chainlink (LINK) sporting declines of 6%-10%. Ether (ETH) was lower by 5.3%.
The start of today's late tumble appeared to coincide with a crypto-related press conference held by White House crypto and AI czar David Sacks alongside the heads of key committees in the Senate and House.
Hopes that the press conference would center on the chances of a strategic bitcoin reserve were dashed as the discussion centered almost exclusively on regulatory matters and platitudes.
Bitcoin did a get a mention at the end of the press conference, when — in response to a question — Sacks said that a White House working group on crypto is looking into the feasibility of a strategic bitcoin reserve. Asked if yesterday's executive order on creation of a sovereign wealth fund meant something for bitcoin, Sacks deferred, saying that's a question for Commerce Secretary nominee Howard Lutnick (who, along with Treasury Secretary Scott Bessent will be spearheading the SWF).
For now, it appears that bitcoin could be setting up for a retest of its Sunday evening low below the $92,000 level. Possibly bullish or bearish on the horizon will be Friday's U.S. January employment report. A soft number could have market participants pricing Federal Reserve rate cuts back into the outlook which may prove a boon to prices. Another strong print, though, might have investors pricing in a rate hike at some point this year — absent other forces, a headwind to prices.
The U.S. Securities and Exchange Commission’s (SEC) newly-created Crypto Task Force is working to create long-awaited regulatory clarity for the crypto industry, according to a Tuesday statement from Commissioner Hester Peirce.
Pierce, who was appointed by Acting Chair Mark Uyeda to spearhead the Crypto Task Force, laid out 10 of the group’s priorities, including resolving the question of what makes a cryptocurrency a security vs. a commodity, and creating a more “viable” path to registration by modifying the SEC’s existing paths.
Other priorities include “provid[ing] clarity about whether crypto-lending and staking programs are covered by the securities laws” and deciding which parts of the market fall outside the SEC’s jurisdiction.
The Crypto Task Force was established just two weeks ago, one day after former Chair Gary Gensler — who was known for his so-called regulation-by-enforcement approach to crypto — stepped down. Both Peirce and Uyeda have been vocal in their disapproval of Gensler’s strategy, and have indicated a massive shift in the agency’s approach to crypto regulation under the new Donald Trump administration. Just two days after the task force was created, the SEC rescinded its controversial Staff Accounting Bulletin 121, which Peirce heralded as a “milestone” for the Crypto Task Force in her Tuesday remarks.
Read more: SEC Forms New Crypto Task Force Spearheaded by Hester Peirce
Comparing the agency’s history of crypto regulation to a family road trip, Peirce said that the Crypto Task Force’s regulatory approach “should be more enjoyable and less risky than the crypto road trip the Commission has taken the industry on for the last decade.”
“On that last trip, the Commission refused to use regulatory tools at its disposal and incessantly slammed on the enforcement brakes as it lurched along a meandering route with a destination not discernible to anyone,” Peirce said.
Peirce acknowledged the “legal imprecision and commercial impracticality” of the SEC’s regulation of crypto under Gensler, and stressed that it will take time for the Crypto Task Force to decide what to do with the legacy of enforcement he left behind.
“Many cases remain in litigation, many rules remain in the proposal stage, and many market participants remain in limbo,” Peirce said. “Determining how best to disentangle all these strands, including ongoing litigation, will take time. It will involve work across the whole agency and cooperation with other regulators. Please be patient. The Task Force wants to get to a good place, but we need to do so in an orderly, practical, and legally defensible way.”
Though many parts of the agency’s approach to crypto regulation are changing, Peirce’s statement makes clear that the SEC’s primary objective – to protect investors – remains as important as ever.
“One of the reasons the U.S. capital markets are so robust, efficient, and effective is that we have rules designed to protect investors and the integrity of the marketplace, and we enforce those rules. We do not tolerate liars, cheaters, and scammers,” Peirce said. “As the Task Force works to help develop this regulatory framework, it will give careful consideration to antifraud protections. If the Commission spots fraud that lies outside our jurisdiction, it can refer the matter to a sister regulator. If it does not fall within any regulator’s jurisdiction, the Commission can bring that gap to Congress’s attention.”
Read more: Acting SEC Chair Uyeda Names 3 Appointees to Agency’s New Crypto Task Force
Taproot Wizards has raised $30 million with which it plans to build an ecosystem of applications using the OP_CAT Bitcoin improvement proposal (BIP).
OP_CAT is a feature that Bitcoin's pseudonymous founder Satoshi Nakamoto included in the software's original code but which he/she/they removed out of concerns that it exposed it to risks such as denial-of-service (DoS) attack.
Many developers have expressed a concern in bringing it back.
The proposal could bring Ethereum-like smart contract functionality to Bitcoin through introducing "covenants," or rules that determine how a specific transaction will function.
Taproot Wizards, whose vision is to "make Bitcoin magical again," sold a collection of 3,000 non-fungible token (NFT)-like pieces of digital art called "Quantum Cats" to drum up support for OP_CAT one year ago.
The Wizards have been attempting to "meme OP_CAT back into existence," according to an emailed announcement on Tuesday.
Co-founder Udi Werthimer describes OP_CAT as "the missing piece" to attaining "permissionless programmability for bitcoin, allowing lending, trading and smart contracts without giving up self custody," in Tuesday's announcement.
The $30 million funding round was led by Standard Crypto.
The U.S. Securities and Exchange Commission’s (SEC) Acting Chairman Mark Uyeda unveiled a list of the agency’s newly-appointed executive staff on Tuesday, including three members of the Crypto Task Force.
Two of the task force’s appointees come from within the SEC’s ranks. Richard Gabbert, who formerly served as a counsel to crypto-friendly task force head Commissioner Hester Pierce will be its chief of staff, as well as a senior advisor to Uyeda. Taylor Asher, who was previously a senior policy advisor to Uyeda, will be the task force’s chief policy advisor.
The other named appointee – Landon Zinda, who will be counsel to Uyeda and a senior advisor for the task force – previously served as policy director for crypto think tank Coin Center. Prior to his work for Coin Center, Zinda worked for two crypto-friendly congressmen, Sen. Pat Toomey (R-Pa.) and Rep. Tom Emmer (R-Minn.).
The SEC announced the formation of the new Crypto Task Force last month, just one day after former Chairman Gary Gensler stepped down. The task force will be focused on “developing a comprehensive and clear regulatory framework for crypto assets,” and will work closely with both Congress and the crypto industry, as well as sister regulatory agency the Commodity Futures Trading Commission (CFTC), according to the press release announcing its formation
The formation of the Crypto Task Force comes as the agency overhauls its approach to crypto regulation, moving away from the practice of so-called regulation by enforcement that became standard practice under former Chairman Gensler.
“To date, the SEC has relied primarily on enforcement actions to regulate crypto retroactively and reactively, often adopting novel and untested legal interpretations along the way,” the SEC said in a press statement. “Clarity regarding who must register, and practical solutions for those seeking to register, have been elusive. The result has been confusion about what is legal, which creates an environment hostile to innovation and conducive to fraud. The SEC can do better.”
Read more: SEC Commissioner Hester Peirce Lays Out 10 Priorities for New Crypto Task Force
WASHINGTON, D.C. — The U.S. House of Representatives and Senate are forming a joint working group to advance crypto legislation, and David Sacks, the crypto czar appointed by President Donald Trump, said his aim is "ensuring American dominance in digital assets” in an appearance Tuesday at a joint press conference in Washington.
Alongside the chiefs of the congressional committees that will work on digital assets legislation, Sacks laid out a broad pro-crypto agenda.
"I look forward to working with each of you in creating a golden age in digital assets," he said, calling crypto a "week-one priority for the administration."
A part of the plan was already revealed earlier on Tuesday, when details of a Senate stablecoin bill emerged. Senator Bill Hagerty, a Tennessee Republican, wrote a bill to set up U.S. oversight of stablecoin issuers, splitting regulation between state agencies and federal watchdogs — specifically the Federal Reserve and the Office of the Comptroller of the Currency.
Tim Scott, the South Carolina Republican who now chairs the Senate Banking Committee, said the panel would take up stablecoins first.
The lawmakers, which included House Financial Services Committee Chair French Hill, House Agriculture Committee Chair Glenn "GT" Thompson and Senate Agriculture Committee Chair John Boozman, also said market structure legislation would come up, referring back to last year's House passage of the Financial Innovation and Technology for the 21st Century Act (FIT21).
Hill said that a bill similar to FIT21 would move forward alongside a stablecoin bill in the House.
"We want to keep that innovation onshore in the U.S. Financial assets are destined to become digital, just like every analog industry has become digital, and we want that value creation to happen in the United States, rather than giving it away to other countries," Sacks said in the press conference, his first since taking the job of AI and crypto czar.
UPDATE (Feb. 4, 2025, 20:17 UTC): Adds additional detail.
The artificial intelligence (AI) world was taken by storm a few days ago with the release of DeepSeek-R1, an open-source reasoning model that matches the performance of top foundation models while claiming to have been built using a remarkably low training budget and novel post-training techniques. The release of DeepSeek-R1 not only challenged the conventional wisdom surrounding the scaling laws of foundation models – which traditionally favor massive training budgets – but did so in the most active area of research in the field: reasoning.
The open-weights (as opposed to open-source) nature of the release made the model readily accessible to the AI community, leading to a surge of clones within hours. Moreover, DeepSeek-R1 left its mark on the ongoing AI race between China and the United States, reinforcing what has been increasingly evident: Chinese models are of exceptionally high quality and fully capable of driving innovation with original ideas.
Unlike most advancements in generative AI, which seem to widen the gap between Web2 and Web3 in the realm of foundation models, the release of DeepSeek-R1 carries real implications and presents intriguing opportunities for Web3-AI. To assess these, we must first take a closer look at DeepSeek-R1’s key innovations and differentiators.
Inside DeepSeek-R1
DeepSeek-R1 was the result of introducing incremental innovations into a well-established pretraining framework for foundation models. In broad terms, DeepSeek-R1 follows the same training methodology as most high-profile foundation models. This approach consists of three key steps:
Pretraining: The model is initially pretrained to predict the next word using massive amounts of unlabeled data.
Supervised Fine-Tuning (SFT): This step optimizes the model in two critical areas: following instructions and answering questions.
Alignment with Human Preferences: A final fine-tuning phase is conducted to align the model’s responses with human preferences.
Most major foundation models – including those developed by OpenAI, Google, and Anthropic – adhere to this same general process. At a high level, DeepSeek-R1’s training procedure does not appear significantly different. ButHowever, rather than pretraining a base model from scratch, R1 leveraged the base model of its predecessor, DeepSeek-v3-base, which boasts an impressive 617 billion parameters.
In essence, DeepSeek-R1 is the result of applying SFT to DeepSeek-v3-base with a large-scale reasoning dataset. The real innovation lies in the construction of these reasoning datasets, which are notoriously difficult to build.
First Step: DeepSeek-R1-Zero
One of the most important aspects of DeepSeek-R1 is that the process did not produce just a single model but two. Perhaps the most significant innovation of DeepSeek-R1 was the creation of an intermediate model called R1-Zero, which is specialized in reasoning tasks. This model was trained almost entirely using reinforcement learning, with minimal reliance on labeled data.
Reinforcement learning is a technique in which a model is rewarded for generating correct answers, enabling it to generalize knowledge over time.
R1-Zero is quite impressive, as it was able to match GPT-o1 in reasoning tasks. However, the model struggled with more general tasks such as question-answering and readability. That said, the purpose of R1-Zero was never to create a generalist model but rather to demonstrate it is possible to achieve state-of-the-art reasoning capabilities using reinforcement learning alone – even if the model does not perform well in other areas.
Second-Step: DeepSeek-R1
DeepSeek-R1 was designed to be a general-purpose model that excels at reasoning, meaning it needed to outperform R1-Zero. To achieve this, DeepSeek started once again with its v3 model, but this time, it fine-tuned it on a small reasoning dataset.
As mentioned earlier, reasoning datasets are difficult to produce. This is where R1-Zero played a crucial role. The intermediate model was used to generate a synthetic reasoning dataset, which was then used to fine-tune DeepSeek v3. This process resulted in another intermediate reasoning model, which was subsequently put through an extensive reinforcement learning phase using a dataset of 600,000 samples, also generated by R1-Zero. The final outcome of this process was DeepSeek-R1.
While I have omitted several technical details of the R1 pretraining process, here are the two main takeaways:
R1-Zero demonstrated that it is possible to develop sophisticated reasoning capabilities using basic reinforcement learning. Although R1-Zero was not a strong generalist model, it successfully generated the reasoning data necessary for R1.
R1 expanded the traditional pretraining pipeline used by most foundation models by incorporating R1-Zero into the process. Additionally, it leveraged a significant amount of synthetic reasoning data generated by R1-Zero.
As a result, DeepSeek-R1 emerged as a model that matched the reasoning capabilities of GPT-o1 while being built using a simpler and likely significantly cheaper pretraining process.
Everyone agrees that R1 marks an important milestone in the history of generative AI, one that is likely to reshape the way foundation models are developed. When it comes to Web3, it will be interesting to explore how R1 influences the evolving landscape of Web3-AI.
DeepSeek-R1 and Web3-AI
Until now, Web3 has struggled to establish compelling use cases that clearly add value to the creation and utilization of foundation models. To some extent, the traditional workflow for pretraining foundation models appears to be the antithesis of Web3 architectures. However, despite being in its early stages, the release of DeepSeek-R1 has highlighted several opportunities that could naturally align with Web3-AI architectures.
1) Reinforcement Learning Fine-Tuning Networks
R1-Zero demonstrated that it is possible to develop reasoning models using pure reinforcement learning. From a computational standpoint, reinforcement learning is highly parallelizable, making it well-suited for decentralized networks. Imagine a Web3 network where nodes are compensated for fine-tuning a model on reinforcement learning tasks, each applying different strategies. This approach is far more feasible than other pretraining paradigms that require complex GPU topologies and centralized infrastructure.
2) Synthetic Reasoning Dataset Generation
Another key contribution of DeepSeek-R1 was showcasing the importance of synthetically generated reasoning datasets for cognitive tasks. This process is also well-suited for a decentralized network, where nodes execute dataset generation jobs and are compensated as these datasets are used for pretraining or fine-tuning foundation models. Since this data is synthetically generated, the entire network can be fully automated without human intervention, making it an ideal fit for Web3 architectures.
3) Decentralized Inference for Small Distilled Reasoning Models
DeepSeek-R1 is a massive model with 671 billion parameters. However, almost immediately after its release, a wave of distilled reasoning models emerged, ranging from 1.5 to 70 billion parameters. These smaller models are significantly more practical for inference in decentralized networks. For example, a 1.5B–2B distilled R1 model could be embedded in a DeFi protocol or deployed within nodes of a DePIN network. More simply, we are likely to see the rise of cost-effective reasoning inference endpoints powered by decentralized compute networks. Reasoning is one domain where the performance gap between small and large models is narrowing, creating a unique opportunity for Web3 to efficiently leverage these distilled models in decentralized inference settings.
4) Reasoning Data Provenance
One of the defining features of reasoning models is their ability to generate reasoning traces for a given task. DeepSeek-R1 makes these traces available as part of its inference output, reinforcing the importance of provenance and traceability for reasoning tasks. The internet today primarily operates on outputs, with little visibility into the intermediate steps that lead to those results. Web3 presents an opportunity to track and verify each reasoning step, potentially creating a "new internet of reasoning" where transparency and verifiability become the norm.
Web3-AI Has a Chance in the Post-R1 Reasoning Era
The release of DeepSeek-R1 has marked a turning point in the evolution of generative AI. By combining clever innovations with established pretraining paradigms, it has challenged traditional AI workflows and opened a new era in reasoning-focused AI. Unlike many previous foundation models, DeepSeek-R1 introduces elements that bring generative AI closer to Web3.
Key aspects of R1 – synthetic reasoning datasets, more parallelizable training and the growing need for traceability – align naturally with Web3 principles. While Web3-AI has struggled to gain meaningful traction, this new post-R1 reasoning era may present the best opportunity yet for Web3 to play a more significant role in the future of AI.
Solana-focused Canadian investment company Sol Strategies purchased 40,300 SOL between Jan. 19 and Jan. 31, for approximately $9.9 million at an average price of $246.53 per token.
The Toronto-based company, which runs three mainnet Solana validators, said that it now holds 189,968 SOL worth roughly $40.89 million purchased at an average price of C$256.21 per SOL, or around US$178.39 per token, according to a press release.
Last month the firm, which has submitted an application to list on the Nasdaq, sold $2.5 million of convertible debentures to add an additional 6,564.57 SOL at an average price of $265.65 per token. Solana price, at the time of writing, was trading at $215 after losing more than 8.5% of its value over the past week amid a wider cryptocurrency market downturn.
Sol Strategies, formerly known as Cypherpunk Holdings, is led by former Valkyrie Investments co-founder Leah Wald. It has acquired validators not only on Solana but also on Sui (SUI), Monad (MONAD), and ARCH (ARCH). Validators process transactions to help secure Proof-of-Stake blockchains by staking certain amounts of these networks’ cryptocurrencies.
According to its website, Sol Strategies also holds 3.168 BTC worth $315,800 at the time of writing as it shifted its investment strategy from accumulating BTC to SOL. Read more: ‘It’s So Early’: How Solana Is Competing With Ethereum for Institutional Interest
Ethereum is facing an identity crisis. Its native token, ether (ETH), is underperforming against competitors, and longtime builders are beginning to question whether the chain's technology is falling behind—and if its community is losing focus.
The Ethereum Foundation, the nonprofit that stewards Ethereum's development, has been blamed for many of the network's struggles. Co-founder Vitalik Buterin is spearheading a massive leadership shake-up at the organization, but his central influence over the process has sparked its own controversy.
Meanwhile, rival ecosystems like Solana are capitalizing on the uncertainty, attracting top talent and outpacing ETH in the market.
Amid this turbulence, a new project, Etherealize, is aiming to bring ETH to Wall Street. Founded by former banker Vivek Raman, Etherealize seeks to bridge the gap between traditional finance and Ethereum, positioning ETH as a serious asset class.
Raman, who spent a decade in banking before discovering crypto, believes his traditional finance background gives him a unique perspective. He has spent the past four years laying the groundwork for Etherealize, choosing to launch in January—a time of heightened market optimism driven by expectations of a crypto-friendly White House, even as Ethereum grapples with internal disputes and price stagnation.
In a recent interview with CoinDesk, Raman discussed his vision for ETH and the broader crypto landscape, including:
• His journey into Ethereum and the founding of Etherealize.
• How Etherealize is marketing ETH to Wall Street.
• The Ethereum Foundation’s role and banks’ views on layer-2 rollups.
This interview has been edited for brevity and clarity.
You've had all this experience in traditional finance, and you call yourself a newcomer to the Ethereum world. Walk me through how you got into crypto, what was that moment?
Raman: I was a trader at four banks, trading the most archaic, esoteric products—high-yield bonds, distressed bonds, leveraged loans and credit default swaps and stuff. These are all the backbone of the economy, but I saw how inefficient they are.
When you watch the movie Wall Street, and you see everything traded on the phone, you're like, “Oh, maybe the system's upgraded,” But it hasn't. It still trades like that.
I saw that for 10 years. I lived it. And I'm very lucky because I built a really good network, I have all these amazing mentors, all these people that ran banks and ran desks.
But after 10 years, the technological pace of Wall Street was not evolving at all, and I was like, "Let me find something else."
Right when I left Wall Street, I went to Austin, Texas, and I serendipitously met some of the Ethereum core developers on the research and development team. They were working on the Merge, and they taught me about Ethereum.
While I was on Wall Street, it was very anti-crypto because of the regulators. The "adoption moment" wasn't even close for the 10 years I was there. But when I found Ethereum, I realized that this was the answer for Wall Street.
There are different components to Etherealize, right? Where does the "marketing" part come in?
Raman: So it's three interrelated things.
The first thing is that everyone uses Ethereum; Ethereum is the most-adopted smart contract platform. Bitcoiners just talk about bitcoins—probably because there's not much utility, so all you can do is talk about it.
It's almost like with Ethereum, there's so much utility that no one actually talks about the ETH asset. But the asset is very important to the ecosystem; for better or worse, people use the asset as a proxy for ecosystem health. Part of the reason why I think Solana has so much of the limelight isn't because it's necessarily the best technology; it's because the token went up a lot.
So the first thing is to talk about ether as an asset — as a portfolio diversifier, as something that's complementary to bitcoin — and to provide that content, research and marketing to ETF issuers, to the broader public and to institutions.
The second is that Ethereum is obviously a utility platform. It's this new financial internet; they call it "the operating system for the financial economy." So we teach about Ethereum as a platform and what you can do with it: You can tokenize assets. You can build layer-2 ecosystems, where banks can actually have their own networksand can customize them to bring their customers on-chain.
And then, third, we actually try to give a call to action. The call to action is to tokenize assets on Ethereum or build a layer 2 on Ethereum, and we're building a product suite to actually facilitate Wall Street trading on the Ethereum blockchain.
Ethereum is experiencing an identity crisis. Its price is lagging far behind other cryptocurrencies, the Ethereum Foundation is undergoing a shake-up, and crypto community members are voicing their disagreements about Vitalik Buterin's central role in the ecosystem. Etherealize is coming to fruition at a moment when the ecosystem probably needs a marketing or advocacy arm. Is Wall Street the savior for Ethereum?
Raman: I don't think it's a silver bullet. The Ethereum Foundation shouldn't have to do everything, and Vitalik shouldn't have to do everything. Research and development — and the high-level, cutting-edge strategy and roadmap to future-proof Ethereum for the next 100 years — that's Vitalik's job.
Whose role is it to talk about these ecosystems? It's the application layer. It’s institutions like Etherealize.
The problem is that once the Overton window shifted from regulatory attacks to regulatory acceptance, the other layer-1 ecosystems, which have very centralized and centrally planned companies behind them, picked up mind share and marketing market share. But ultimately, the best of the best is Vitalik — the best of the best is the EF researchers.
I spent years developing this business plan, figuring out when the right time to strike was. I got a sign-off from Vitalik and the EF—they gave us a small grant to get us started last August. But I did a lot of due diligence. I surveyed many institutions and asked if this was the moment. And it was.
You've discussed the role of the Ethereum Foundation (EF). Some believe the foundation is in charge of running the ecosystem. How do you divide the roles between the EF and Etherealize?
Raman: The EF has great marketing people — there's just a lot to do.
We have this whole ecosystem of layer-2s that need coordination. One of the people in the Ethereum Foundation’s leadership always says, “Ethereum doesn't have one business development arm, it has thousands of business development arms," which are all the apps, the layer 2s, etc.
We're here to act as a conduit to all the different apps and layer twos. And we have access to people who actually want to use Ethereum: the Wall Street players and institutions.
We go back and forth [with the EF] all the time. We have the best relationship with them, but we are arm's length from them. I view all this as a very positive sum.
You bring up layer-2 networks. How does Wall Street view them? We know that Deutsche Bank is launching a layer-2 on ZKsync, and UBS has also expressed interest in using layer-2 technology. But what’s their view from what you’ve seen?
Raman: I think it's going to be very ironic when people look back at criticisms for layer twos as being value extractive and dilutive. I think Wall Street views the layer twos as an opportunity.
One of many reasons I think Ethereum will win over other layer-1s is because it doubled down on the layer-2 roadmap and realized that the whole world doesn't belong on one uniform chain.
There are different companies, different countries and different states. Everyone has their own culture. You can't stuff it all in one place with one set of rules.
Wall Street views this as an opportunity. Where's the place where you can make the most money deploying assets and applications? It's on layer 2. At the app layer, you can control your level of customization and privacy. On layer 2, you can have know-your-customer (KYC) features. All that stuff is going to be extremely critical.
Why has Wall Street been holding back — was it really purely just the regulatory clarity aspect, which has changed now that there’s a new administration in Washington?
Raman: I think regulatory clarity is the right answer, but maybe it's a little too simplistic.
I think the real issue is that there was no economic incentive for Wall Street institutions to actually use blockchains. Many of them viewed blockchains as competing or threatening. There was no way to make money using blockchains, especially with an oppressive regulatory regime.
With the shift in regulations and the expansion of technology like layer-2s, Wall Street can now make a lot of money using blockchains—specifically on Ethereum, by building layer-2s and running assets on them. They can make a lot of money now, and so they're all rushing in. It’s because they smell opportunity.
Read more: Ethereum's Vitalik Buterin Goes on Offense Amid Major Leadership Shake-up