Crypto World
AI will boost jobs; trillions in infrastructure
Artificial intelligence is being reframed as a fundamental utility rather than a purely productivity unlock, according to Jensen Huang, the founder of Nvidia. In a blog post this week, Huang portrays AI as essential infrastructure on par with electricity and the internet. He argues the facilities that design chips, operate data centers, and deploy AI applications represent the largest infrastructure buildout in human history. The sentiment is tempered by the recognition that the job of constructing and maintaining this ecosystem will be enormous, spanning a wide array of skilled trades. The analysis arrives as Nvidia (NVDA) continues to benefit from surging demand for AI hardware, a cycle that has propelled its stock higher in the past 18 months. (EXCHANGE: NVDA)
Huang’s “five-layer cake” concept frames AI infrastructure as a stacked, interdependent system. In his view, energy supplies the base; AI chips drive computation; the underlying infrastructure enables services and platforms; AI models provide reasoning and intelligence; and applications translate capabilities into real-world use cases. The blog argues that the architecture must be rebuilt almost from scratch to accommodate autonomous reasoning, real-time inference, and on-demand intelligence, rather than merely following stored instructions. This restructuring implies not only new factories and fabs but also a reimagining of operational workflows across industries. The five-layer framework has quickly become a touchstone for executives and policymakers contemplating how to allocate capital and talent in the AI era.
AI isn’t a single model. It’s a full stack.
Energy. Chips. Infrastructure. Models. Applications.
That’s the five-layer cake powering the largest industrial buildout in history — and the jobs, factories and AI applications rising with it. pic.twitter.com/rwxO6fdTnE — NVIDIA Newsroom
Huang notes that much of this infrastructure has yet to exist and requires a workforce that is still in short supply. The emerging demand for AI data centers—capable of housing powerful GPUs, high-speed networks, and robust cooling—will demand electricians, plumbers, steelworkers, network technicians, and operators. These are not entry-level roles; they require specialized training and experience, aligning with a broader push for skilled labor across advanced manufacturing and digital-enabled services. As the AI buildout accelerates, Huang argues, the scale of the opportunity will extend beyond any single country or sector, touching a wide spectrum of industries and geographies.
The AI boom’s corporate beneficiaries have become a focal point for investors. Nvidia, already a dominant supplier of AI accelerators, has emerged as one of the biggest winners in the current cycle. Its shares have surged more than 1,300% since 2023, a rally that followed the public release of ChatGPT and the ensuing AI race. The company’s role at the center of both the hardware ecosystem and the software-enabled AI pipeline has reinforced its status as a core proxy for AI demand, even as critics argue the cycle may be tempered by regulatory scrutiny, supply chain constraints, and macro headwinds. (EXCHANGE: NVDA)
Within this broader narrative, Huang’s comments echo a larger industry trend: the AI data-center expansion is reshaping employment patterns and wage prospects in specialized trades. A recent wave of corporate restructurings—at Block, Pinterest, and Dow—has highlighted how AI-enabled efficiency and automation are influencing staffing decisions. Block, Inc. announced a large-scale workforce reduction, a move its co-founder attributed in part to AI-enabled restructuring. Pinterest and Dow also cited AI as a driver for workforce reductions, underscoring a common theme: automation and AI adoption can compress roles while intensifying demand for high-skilled positions in AI hardware, data-center operations, and software engineering. Analysts at Goldman Sachs have characterized AI-driven layoffs as visible but modest, suggesting the macro impact on unemployment might be gradual even as the technology accelerates. (EXCHANGE: SQ)
The story also intersects with broader market dynamics. Nvidia’s ascent underscores the hardware supply chain’s centrality to AI-enabled growth, a trend that has implications for other technology equities and for sectors linked to data-center energy consumption. The AI infrastructure cycle is a reminder that the push into AI is not merely a software upgrade; it is a capital-intensive, global effort that requires policy alignment, capital allocation, and a capable workforce. As capital continues to flow into data centers, chip manufacturing, and related services, the demand for skilled labor, reliable power, and resilient networks is likely to remain a core feature of the investment landscape. (EXCHANGE: NVDA)
AI’s footprint in the economy is expanding rapidly, and Huang’s framework suggests a multi-decade horizon for the buildout. AI data centers will need not only hardware but also the operational expertise to install, maintain, and secure complex systems. The labor market for skilled trades—traditionally insulated from pure software cycles—could see persistent demand for technicians who can design, install, and upgrade AI-ready infrastructure. This reality may influence everything from wage dynamics to vocational training programs, and it could even shape incentives for crypto mining and other power-intensive activities that rely on cost-effective, scalable AI-capable hardware and energy platforms. The net effect is a gradual, rather than explosive, reallocation of resources toward AI-enabled capabilities across industries. (EXCHANGE: PINS; EXCHANGE: DOW)
As the AI narrative matures, investors and policymakers will be watching how the five-layer cake translates into real-world deployments and jobs. Huang’s estimate that “hundreds of billions” have already been invested, with trillions more to come, highlights the scale of the opportunity—and the risk of bottlenecks in supply chains, talent, and regulatory frameworks. In parallel, financial markets will assess whether the AI infrastructure cycle can sustain a broader earnings and growth trajectory for hardware suppliers, cloud providers, and software developers delivering AI-powered services. The cross-currents—tech capex, energy demand, labor shortages, and macro risk sentiment—will continue to shape how this AI era unfolds. (EXCHANGE: NVDA; EXCHANGE: SQ; EXCHANGE: PINS; EXCHANGE: DOW)
Why it matters
For investors, Huang’s framework reframes AI from a short-term optimization trend to a structural, capital-intensive expansion that will require a steady inflow of funding and a highly skilled workforce. The implied long horizon for infrastructure expenditure could sustain demand for AI accelerators, data-center gear, and software ecosystems for years, potentially supporting a more durable equity narrative for hardware-centric players and cloud providers. For builders and operators, the emphasis on a multi-layer stack underscores the importance of resilient, scalable energy, cooling, and networking capabilities. It also highlights the need for training pipelines that can deliver electricians, technicians, engineers, and operators who understand AI workloads from edge to core. For policy and macro participants, the discussion points to the macroeconomic implications of a large-scale industrial transition that could influence employment, wage dynamics, and regional competitiveness as nations compete to attract investment in AI-enabled infrastructure.
From a market-structure perspective, the AI infrastructure wave intersects with broader sectoral trends, including data-center consolidation, hyperscale capacity expansion, and the ongoing evolution of industrial tech. While the short-term price moves in any given stock or token can be volatile, the longer-term signal is one of sustained, capital-intensive growth in a space that sits at the convergence of compute, energy, and human capital. Crypto markets, which have historically been sensitive to energy pricing, risk sentiment, and technology cycles, may experience indirect effects as AI-driven optimization and automation influence energy demand, hardware pricing, and risk-off/ risk-on dynamics across tech-heavy equities. The net takeaway is a cycle that rewards suppliers of AI hardware, creators of AI software, and the labor ecosystem that will build and maintain the infrastructure of the AI era.
What to watch next
- Capital expenditure plans from Nvidia and peers to expand AI data-center capacity, with quarterly updates and guidance.
- Trends in skilled-labor supply for AI infrastructure, including training program developments and wage indicators for electricians, network technicians, and operators.
- Regulatory developments affecting AI deployment, energy efficiency standards, and data-center permitting in key markets.
- Announcements of new AI-enabled products or services from leading cloud providers and hardware suppliers, including integration of AI models into enterprise workflows.
Sources & verification
- Jensen Huang’s blog post outlining the “five-layer cake” framework: https://blogs.nvidia.com/blog/ai-5-layer-cake/
- Article discussing AI data centers and bitcoin mining considerations: https://cointelegraph.com/news/ai-data-centers-local-resistance-bitcoin-mining
- NVIDIA becomes a leading AI boom beneficiary (AI hardware dominance): https://cointelegraph.com/news/nvidia-becomes-first-4t-market-cap-company-on-ai-boom
- Block, Inc. layoffs attributed to AI-driven restructuring: https://cointelegraph.com/news/jack-dorsey-block-cuts-4000-jobs-ai-restructuring
- Pinterest and Dow announcements linking AI to workforce reductions: https://cointelegraph.com/news/ai-use-work-causing-brain-fry-say-researchers
- Goldman Sachs analysis on AI-driven layoffs and unemployment trends: https://finance.yahoo.com/news/goldman-sachs-warns-ai-fueled-layoffs-could-raise-the-unemployment-rate-this-year-chart-154251740.html
What the story means for the market
The trajectory Huang sketches positions AI infrastructure as a multiyear, capital-intensive cycle that could recalibrate how investors value hardware suppliers, cloud platforms, and enterprise software tied to AI workloads. As the industry navigates talent shortages, energy considerations, and macro uncertainties, the sector’s performance will hinge on the pace of data-center expansion, the efficiency of AI training and inference pipelines, and the alignment of policy with rapid technology adoption.
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Traders are pricing fewer Fed cuts in 2026 as U.S. unemployment dips to 4.3%, tempering the liquidity story for Bitcoin and Ethereum but not triggering a risk‑asset capitulation.
Summary
- Market pricing shows fewer bets on Federal Reserve rate cuts in 2026 as traders reassess the path of U.S. monetary easing.
- March U.S. unemployment came in at 4.3%, below the 4.4% consensus forecast and down from 4.4% in February, pointing to a still‑resilient labor market.
- For crypto markets, the mix of sticky employment and a shallower rate‑cut path argues for a slower liquidity tailwind, but not an outright macro shock.
Derivatives and rates markets have trimmed expectations for how aggressively the Federal Reserve will cut interest rates in 2026, according to Jinshi‑cited pricing data. That shift reflects growing skepticism that inflation will glide back to target quickly enough to justify deep easing, even as nominal policy rates sit at multi‑decade highs. Fewer cuts priced into 2026 effectively mean a higher “terminal” funding cost for leveraged players and a slower normalization of real yields — both headwinds to the kind of explosive liquidity conditions that fueled earlier crypto bull cycles.
At the same time, the U.S. labor market continues to look stubbornly robust. Jinshi reports that the March unemployment rate ticked down to 4.3%, beating expectations for 4.4% and edging lower from February’s 4.4%. That is hardly a recession print; if anything, it signals that job conditions remain tight enough to keep wage and service‑sector inflation from collapsing, giving the Fed political and analytical cover to hold rates elevated longer. For risk assets, including Bitcoin (BTC) and Ethereum (ETH), the combination of a still‑strong labor market and fewer rate cuts priced is a classic “higher for longer” setup: growth isn’t falling off a cliff, but the cheap‑money punch bowl stays out of reach.
Crypto traders react to US data news
For crypto traders, the implications are nuanced rather than outright bearish. A slower, shallower easing cycle tends to compress valuation multiples and cap speculative excess, making it harder for marginal capital to chase high‑beta altcoins with leverage. However, as long as unemployment hovers near 4–4.5% and the economy avoids a hard landing, on‑chain activity and real demand for digital assets can still grind higher, especially in narratives tied to stablecoins, tokenized treasuries and yield‑bearing infrastructure that directly intersect with rates markets. The immediate read‑through: expect less of a “melting‑up” liquidity rally in 2026 and more of a choppy, macro‑sensitive grind, where each shift in Fed‑cut odds and each monthly jobs print becomes a tradable event for both BTC and ETH volatility.
The White House no longer has a dedicated crypto policy lead, just days after President Donald Trump gave Vice President JD Vance a new enforcement mandate as “Fraud Czar.”
Trump announced the Vance appointment on Truth Social, directing the vice president to target what he called unprecedented taxpayer fraud in blue states. The move follows David Sacks’ quiet departure from the crypto czar position on March 26.
Sacks Out, No Replacement Coming
Sacks confirmed that he had used up his 130-day limit as a special government employee. The departure was not a resignation or termination. Federal law caps special government employee service at 130 days within a 12-month period.
The White House confirmed it will not appoint a replacement. Sacks transitioned to co-chair of the President’s Council of Advisors on Science and Technology (PCAST), an advisory body that produces recommendations but lacks operational policy authority.
He joins Mark Zuckerberg, Jensen Huang, and Marc Andreessen on the council.
His exit leaves the CLARITY Act stalled in the Senate and the broader crypto market structure bill unfinished.
Senator Bernie Moreno has warned that if the bill does not reach the Senate floor by May, it risks going dark until after the midterm elections.
Vance Turns to Fraud
Meanwhile, Trump’s “Fraud Czar” designation gives Vance a mandate focused on government spending enforcement.
Trump named California, Illinois, New York, Minnesota, and Maine as primary targets, claiming recovered funds could balance the federal budget.
Federal raids have already begun in Los Angeles, with arrests tied to $50 million in healthcare fraud.
The two czar roles are unrelated in scope. However, the contrast is notable.
The administration is deploying enforcement resources toward fiscal fraud while leaving the crypto policy seat empty at a critical legislative moment.
The post Trump’s Crypto Czar Role Sits Empty as White House Names Fraud Czar appeared first on BeInCrypto.
XRP is trading at $1.31, up by 0.9% in the last 24 hours, but price prediction still remains bearish for Ripple coin. Down nearly 30% year-to-date from a $1.88 open, the token is fighting to hold key support while the broader market registers extreme fear. What most traders haven’t priced in yet: a significant engineering overhaul quietly underway inside the XRP Ledger’s core repository.
Denis Angell, an XRPL core developer, outlined six active workstreams on April 2 that are reshaping the ledger’s foundational infrastructure, telemetry, nomenclature, type safety, refactoring, logging, and documentation.
“I’ve never been more excited for the XRP Ledger core development than I am now,” Angell posted, describing the effort as tedious but critical.
The work targets backend reliability and developer experience rather than user-facing features, a distinction that matters for long-term network competitiveness.
Whether these upgrades translate into price recovery depends entirely on market timing.
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XRP Price Prediction: $1.40 Before the Next Wave of Selling?
XRP’s current level of $1.31 places it uncomfortably below both major moving averages. The 50-day SMA sits at $1.40–$1.42, acting as immediate overhead resistance. The 200-day SMA at $2.04–$2.07 represents a full recovery target that feels distant given current momentum.
Support is clustered at $1.27–$1.29. That zone is thin. A clean break below it opens a more significant leg down with limited structural floors until the $1.10 range. The Fear and Greed Index reading Fear confirms capitulation sentiment, which historically precedes either a sharp reversal or a final flush.
Analyst consensus points to $2.04 as a potential recovery level by September 2026, achievable, but requiring sustained buying pressure that simply isn’t visible in current volume data.
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Bitcoin Hyper Targets Early-Mover Upside as XRP Tests Critical Support
XRP’s -29.6% year-to-date performance raises a legitimate question: at a $1.31 price point and a multi-billion-dollar market cap, how much asymmetric upside actually remains? For traders comfortable with the risk profile of early-stage assets, the calculus looks different at the infrastructure layer.
Bitcoin Hyper ($HYPER) is positioning itself as a genuinely novel infrastructure play, the first Bitcoin Layer 2 integrating the Solana Virtual Machine, delivering sub-second finality and low-cost smart contract execution while anchored to Bitcoin’s security model.
The presale has raised $32 million at a current price of just $0.013678, with healthy staking rewards available for early participants. The Decentralized Canonical Bridge enables native BTC transfers into the ecosystem, addressing Bitcoin’s longstanding programmability gap without sacrificing its trust layer.
More detail on Bitcoin Hyper is available here.
The post XRP Price Prediction: Can These 6 Ongoing Developments Save Ripple appeared first on Cryptonews.
TLDR
- Riot Platforms sold 3,778 Bitcoin for more than $250 million during the first quarter of 2025.
- The company reduced its total Bitcoin holdings to 15,680 BTC after the sale.
- Riot Platforms achieved an average selling price of over $76,000 per Bitcoin.
- The firm has now sold Bitcoin in consecutive quarters after raising nearly $200 million late last year.
- CEO Jason Les said earlier that sales were intended to fund ongoing growth and operations.
Riot Platforms sold more than $250 million in Bitcoin during the first quarter of 2025. The company confirmed it sold 3,778 BTC at an average price above $76,000. As a result, the firm reduced its total holdings to 15,680 BTC by the end of March.
Riot Platforms Cuts Bitcoin Holdings as Sales Extend Into Second Quarter
Riot Platforms reported that it sold 3,778 Bitcoin during the first quarter of 2025. The company achieved an average sale price above $76,000 per coin. Consequently, it reduced its Bitcoin reserves to 15,680 BTC at quarter’s end. The remaining holdings now carry a market value near $1.04 billion. Bitcoin traded at $66,844 at the time of valuation.
The Colorado-based miner has now sold Bitcoin in consecutive quarters. During November and December, it generated nearly $200 million from Bitcoin sales. The company has not yet disclosed detailed allocation plans for the recent proceeds. A company representative did not respond to a request for comment. However, earlier in 2025, CEO Jason Les addressed the purpose of prior sales.
Les stated that earlier Bitcoin sales aimed to “fund ongoing growth and operations.” He connected those operations to expanding infrastructure and computing capacity. The company outlined these objectives in its latest strategic business update. Riot Platforms has focused on increasing its data center capabilities. It also continues to adjust its capital structure through asset sales.
Riot Platforms Shifts Strategy Toward Data Center Development
Riot Platforms confirmed that it intends to expand beyond traditional Bitcoin mining. The firm stated that it plans to unlock its nearly two-gigawatt power portfolio. It aims to deploy that capacity for high-demand data center infrastructure. Les said, “2025 marked a watershed year for Riot.” He added that the company has transformed its future trajectory.
The company explained that it previously used most of its power portfolio for Bitcoin mining. Now, it seeks to reallocate that capacity toward data center development. Riot Platforms stated that its long-term goal is “to fully utilize our power portfolio for data center development.” This shift aligns with ongoing operational restructuring. The firm continues to balance mining output with infrastructure planning.
An activist investor, Starboard Value, urged the company to accelerate its transition strategy. Starboard Value stated that the opportunity could add as much as $21 billion to Riot’s valuation. The investor called for a “renewed sense of urgency” in pursuing this plan. Meanwhile, shares of RIOT closed up 2.47% on Thursday. The stock recently traded at $12.86.
Over the past six months, RIOT shares have fallen more than 33%. During the same period, Bitcoin has declined 47% from its all-time high of $126,080. The company continues to report updates through formal filings and public statements. Riot Platforms has not announced further Bitcoin sales beyond the first quarter.
Stephanie Cutter will join the prediction markets company as a policy adviser, having previously worked in Democratic lawmakers’ campaigns.
Predictions market platform Kalshi announced that a former staffer of US President Barack Obama had joined the company as a policy adviser.
In a Thursday notice, Kalshi said Stephanie Cutter would join the prediction markets company from Precision Strategies, a communications firm she co-founded in 2013. Kalshi said the addition of Cutter came as the company planned to “deepen its relationships in DC and across the country.”
According to Kalshi co-founder and CEO Tarek Mansour, Cutter’s experience allowed her to “get [the] message to the right people,” highlighting her background in government and politics. The predictions market already has staff with ties to the US government, including the appointment of the president’s son, Donald Trump Jr., as a strategic adviser in January 2025, the week before his father took office.
In the last year, Kalshi has come under scrutiny from many US state-level authorities, who have filed lawsuits against the platform and other companies offering event contracts on prediction markets for sports, alleging that they constituted illegal bets.
Under Trump nominee Michael Selig, the US Commodity Futures Trading Commission (CFTC) has claimed that the agency has the “exclusive jurisdiction” to oversee such markets, filing lawsuits against state gaming regulators.
Related: Polymarket expands into equities and commodities with Pyth price feeds
Lawsuits and proposed legislation
Many Democrats in US Congress have also called for scrutiny into prediction markets after what they called “suspicious trades” related to the country’s invasion of Iran. Although Kalshi and Polymarket announced plans in March to implement guardrails to prevent accounts from using insider information, some lawmakers introduced legislation that could ban politicians from engaging in such bets on prediction markets.
As of Friday, none of the bills proposed in Congress had been signed into law, and it was unclear what the outcome would be for many of the state-level lawsuits.
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XRP is grinding higher, but not breaking out. The token is sitting around $1.33 after a modest move up, with higher volume coming in — yet price still isn’t escaping its range. That usually means positioning is building, not conviction.
News Background
- XRP rose just over 1% to $1.33 with volume about 23% above its weekly average
- Price moved almost in lockstep with the broader crypto market, showing little independent strength
- No major XRP-specific catalyst drove the session
Price Action Summary
- XRP traded in a tight range, holding above $1.30 while struggling near $1.33
- Buyers stepped in on dips, creating higher lows
- Breakout attempts toward $1.33-$1.34 were repeatedly sold into
- Late-session price action stabilized without follow-through
Technical Analysis
- The key theme is correlation — XRP is moving with the market, not leading it
- Higher volume without a breakout suggests traders are positioning, not committing
- Structure is slightly constructive (higher lows), but capped by overhead supply
- This keeps XRP stuck in a compression phase, where range tightens before expansion
What traders should watch
- $1.34-$1.35 is the near-term ceiling — break that and momentum can build
- $1.30 remains the floor holding the structure together
- Until one of those levels breaks, XRP is likely to stay range-bound and reactive to broader crypto moves
Stablecoin monthly transaction volume reached $7.2 trillion in February 2026, overtaking the Automated Clearing House (ACH) network’s $6.8 trillion for the first time.
The ACH is an electronic payment network in the United States that enables transfers directly between bank accounts. It has become the most widely used infrastructure for handling electronic money movement across the country.
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It’s a symbolically significant milestone showing how massive crypto payment rails have become. The February crossover did not happen in isolation.
Artemis data shows that stablecoin volume climbed further in March, reaching $7.5 trillion. That figure matched ACH over the same period.
Meanwhile, the stablecoin market has continued to grow. DefiLlama data showed that the market capitalization surpassed $316.7 billion, setting a new all-time high.
Notably, a recent report revealed that stablecoins dominated crypto markets in Q1 2026. They made up 75% of total trading volume, the largest share on record.
Overall transaction volume exceeded $28 trillion during the quarter, marking another all-time high. However, according to CEX.IO, automated trading played a major role, with bots responsible for 76% of the volume, the highest proportion seen in the past two years.
“Q1 2026 made the 2022 comparison hard to ignore. Stablecoin dominance rising sharply, capital rotating defensively, USDT and USDC diverging, automation surging, and retail pulling back — these patterns appeared together in mid-2022, and they are reappearing now. If broader bearish conditions persist through the year, stablecoins could see further demand and dominance gains in the coming quarters,” the report read.
The rising volumes reflect more than speculative activity. It also highlights the expanding use of these assets in real-world applications, including business-to-business (B2B) payments, cross-border transactions, and other financial activities.
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The post Stablecoins Moved More Money Than the US Financial System’s Backbone appeared first on BeInCrypto.
The International Monetary Fund also warns that the distribution and speed of on-chain transactions bring new challenges and risks that require international coordination.
In a new staff research note published on Thursday, The International Monetary Fund (IMF) argues that tokenization represents a “structural shift in financial architecture,” not just an incremental efficiency gain.
Authored by Tobias Adrian — the IMF’s Financial Counsellor and Director of the Monetary and Capital Markets Department — the report focuses on the tokenization of real-world assets (RWAs) within the regulated financial system, namely banks, finance infrastructure, and asset managers, arguing that’s where “the most consequential transformation occurs.”
Settlement Speed Is a Double-Edged Sword
The IMF’s core thesis is that tokenization doesn’t just make existing finance faster, but represents a shift in how trust, settlement, and risk management work. In TradFi, trust is embedded in regulated intermediaries and time-delayed processes (end-of-day settlement, batch reconciliation). Those frictions, the report notes, actually serve a purpose: they give regulators and institutions time to intervene before a crisis cascades.
Tokenization, which the note defines broadly as “the representation of financial assets and liabilities on programmable digital ledgers,” collapses those frictions, bringing what is generally referred to as the primary benefits of blockchain: near instant settlement, 24/7 liquidity, etc. But, the report notes, that this reduction of barriers introduces new challenges and risks.
“Liquidity demands materialize instantaneously,” the note warns, creating conditions where a smart contract bug or oracle failure could trigger a chain reaction before anyone can respond. The IMF argues:
“When trading, settlement, custody, and compliance are embedded in code, supervision must extend beyond market participants to the design, governance, and resilience of market infrastructures themselves. Failures can
originate in smart contracts, data feeds, or consensus mechanisms, rather than firm balance sheets.”
Who Controls the Money?
A major focus of the report is on the quetion of settlement assets. The IMF identifies three competing models: tokenized commercial bank deposits, regulated stablecoins, and what the report refers to as wholesale central bank digital currencies (wCBDCs), with each carrying different risk profiles.
Cross-Border Gaps and the Fragmentation Risk
The report highlights that a major concern around the tokenization of RWAs in regulated financial markets is jurisdictional: tokenized transactions execute across borders at machine speed, while resolution and crisis management frameworks are still built around nationally domiciled institutions.
“Tokenization challenges crisis management and resolution frameworks that are built around nationally domiciled institutions, territorially bounded infrastructures, and jurisdiction-specific legal authority.“
In its research note, the IMF calls for international coordination and legal frameworks that can govern code itself, not just the institutions that deploy it.
“The key levers of control may lie in governance keys, consensus mechanisms, or smart contract logic operating across borders,” the note reads — a setup where no single regulator has a clear handle.
The report lands as the value of tokenized RWAs continue to surge, driven in part by tokenized funds from TradFi giants like BlackRock, Franklin Templeton, and Janus Henderson.
In 2025, tokenized RWA value tripled over the course of the year as a wave of financial institutions began tokenizing U.S. treasuries, private credit, and other RWAs.
Industry forecasts project the sector could hit $100 billion by end of 2026, with more than half of the world’s 20 largest asset managers expected to have launched RWA tokens by year-end.
Meanwhile, stablecoins have already begun functioning as mainstream financial infrastructure, with the GENIUS Act providing U.S. regulatory clarity in mid-2025.
This article was written with the assistance of AI workflows. All our stories are curated, edited and fact-checked by a human.
A solo Bitcoin miner secured a roughly $210,000 block reward on Thursday, proving that the so-called “mining lottery” is still paying out even if industrial operators dominate the network.
The miner, connected to CKPool’s solo service, found block 943,411 and earned 3.139 BTC in subsidy and transaction fees, according to data from block explorer mempool.space.
Solo mining remains rare. Statistics compiled by Bennet’s tracker show that solo mining pools have found just 20 Bitcoin (BTC) blocks over the last 12 months, paying out a total of 62.96 BTC, roughly one win every 18.7 days on average. The longest “drought” between blocks was 58 days, and the previous solo win came on Feb. 28.
The win comes as Bitcoin mining grows increasingly competitive. Network difficulty, the measure of how hard it is to find a block, recently recorded its steepest adjustment since February, falling about 7.7% before rebounding 3.87% in the past 24 hours, reflecting weaker hashrate and briefly improving miners’ odds.
Bitcoin difficulty relief is fleeting
Even so, current difficulty levels remain near historic highs, meaning the probability of any single solo miner discovering a block is still vanishingly small.
Related: Solo Bitcoin miner bags over $200K block reward using rented hashrate
Public trackers like CoinWarz show Bitcoin’s difficulty has climbed orders of magnitude over the past decade, with only brief downward adjustments when miners switch off unprofitable rigs or redirect machines to other workloads such as artificial intelligence.
As difficulty grinds higher and input costs rise, the economics of mining increasingly favor large, well-capitalized operators over hobbyists.
Major listed Bitcoin miners are responding by reshaping their balance sheets and fleet strategies rather than betting on luck. Riot Platforms sold 3,778 BTC during the first quarter of 2026, according to a Thursday release, adding to a number of crypto miners and firms that have sold Bitcoin recently, including MARA Holdings, Genius Group and Nakamoto Holdings.
Against that institutional backdrop, the CKPool win stands out as a reminder that individuals can still, on rare occasions, beat the odds.
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Ethereum layer-2 networks need “responsive pricing” to scale to billions of users and reduce the fee swings that still accompany congestion, Offchain Labs co-founder Edward Felten said during a keynote at EthCC 2026.
Ethereum’s EIP-1559 upgrade launched in August 2021, as part of the London hard fork. It reformed the Ethereum fee market by modifying the gas fee limit and introduced a feature that burns part of the transaction fees, removing them permanently from circulation.
Felten said gas-price swings are still the main mechanism for protecting networks from being overrun during periods of heavy demand, even though that produces the kind of fee volatility mainstream users tend to reject.
“[With responsive pricing], you can see more traffic at lower gas prices without overrunning the infrastructure.”
Volatile gas prices have long been a barrier to mass adoption, particularly for users accustomed to fixed or predictable transaction costs in traditional financial systems.
The issue matters because Ethereum’s scaling story is no longer just about adding more throughput. It is increasingly about whether layer-2 networks can make transaction costs predictable enough for mainstream-style apps while still pricing congestion honestly enough to protect infrastructure under heavy demand. Arbitrum’s dynamic pricing rollout is now one of the first live tests of that tradeoff.
Arbitrum One the first L2 to adopt responsive pricing
Arbitrum One adopted dynamic pricing in January. It described the model as an “Arbitrum platform direction to make fees more predictable under demand by aligning prices with real network bottlenecks.”
Related: Gavin Wood’s biggest hope: Free crypto transactions and Web3 tech worldwide
Felten shared multiple charts showing how Arbitrum gas fees remained lower during peak network volumes than fees on the Base network and other L2s that rely on EIP-1559.
Arbitrum One is the largest L2 with $15.2 billion in TVL, while Coinbase’s Base Chain is second with $10.9 billion, according to data from L2beat. L2s are securing over $39.7 billion in cumulative TVL, up 4.6% over the past year.
While responsive pricing may be more scalable and more transparent about underlying costs, its biggest downside is lower predictability than EIP-1559, according to Julian Kors, a senior developer and founder of execution workspace startup Pulsar Spaces.
The debate is not about one model being better, but whether networks optimise for “predictability and mechanism design purity or for efficiency and real-time cost alignment. EIP-1559 does the first very well. Responsive pricing leans into the second,” he told Cointelegraph.
Related: Ethereum Foundation accelerates 70,000 ETH staking plan after BitMine sale
Responsive pricing is a step forward, but the gas model needs replacing
Jerome de Tychey, president of Ethereum France and EthCC, told Cointelegraph that responsive pricing could improve user experience by making fees more closely reflect actual network demand.
Cyprien Grau, project lead at gasless Ethereum L2 Status Network, agreed, calling the new pricing model a “real improvement in fee accuracy.” However, the model still relies on a “fee market,” meaning that users may still face variable costs and gas spikes during congestion, he told Cointelegraph.
“It doesn’t solve the structural problem: L2 gas fees trend toward zero as scaling on L1 and L2s improves and competition intensifies. Responsive pricing makes the decline smoother, but you’re still building a revenue model on a depreciating asset.”
Grau added that responsive pricing is the “most advanced version of the gas model,” but said the gas model needs replacing. “L2s that scale to billions of users will be the ones where users never think about gas at all, and where networks’ economics don’t depend on charging them for it,” he added.
The fee model debate comes as parts of the Ethereum ecosystem are already rethinking the original rollup-centric scaling thesis. In February, Vitalik Buterin argued that some layer-2 assumptions no longer held and that future scaling should rely more heavily on the mainnet and native rollups.
L2 networks were created to scale Ethereum and offload part of the transaction load from the mainnet. However, Ethereum is now reconsidering its L2-centric approach, as these networks have siphoned significant economic value from the mainnet.
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