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Intel (INTC) Shares Slide 3% Following Foundry Leader’s Move to Qualcomm
TLDR
- Intel (INTC) declined approximately 3% on Thursday, closing at $45.46 with volume 41% below average
- Kevin O’Buckley, the SVP and general manager of Intel Foundry Services, departed to join Qualcomm as VP of global operations and supply chain
- The company revealed a partnership with AI chip startup SambaNova focused on the SN50 inference chip
- Wall Street consensus remains at “Hold/Reduce” with price targets ranging from $45.74 to $48.21
- Q4 earnings showed EPS of $0.15, surpassing expectations, though margins remain negative with cautious forward outlook
Shares of Intel (INTC) slipped nearly 3% during Thursday’s session, settling at $45.46 compared to the prior close of $46.88. Volume registered approximately 71 million shares, representing a 41% decline from typical daily levels.
The decline was primarily attributed to a significant personnel change: Kevin O’Buckley, who served as senior vice president and general manager of Intel Foundry Services, has exited the company.
O’Buckley is transitioning to Qualcomm, where he’ll assume the position of vice president of global operations and supply chain. The lateral move between two semiconductor powerhouses triggered immediate market reaction.
Intel acted swiftly to calm investor concerns. The chipmaker emphasized that Intel Foundry continues to be “one of Intel’s highest strategic priorities” and will operate under Naga Chandrasekaran’s leadership, who assumed the top foundry position last year.
The company publicly acknowledged O’Buckley’s contributions and extended best wishes. Official reasons behind his departure remain undisclosed.
Speculation suggests O’Buckley may have previously held a direct reporting relationship with CEO Lip-Bu Tan. Following Intel Foundry’s reorganization, his reporting structure shifted to Chandrasekaran. Whether this organizational change influenced his decision remains unclear.
Intel’s AI Inference Push
The week brought positive developments as well. Intel unveiled a partnership with AI chip startup SambaNova centered on the company’s latest SN50 inference chip. Intel is also contributing to SambaNova’s current funding round.
This collaboration positions Intel more competitively in the AI inference space, which industry analysts identify as a rapidly expanding, higher-margin segment. The partnership demonstrates Intel’s strategic efforts to establish stronger positioning in AI hardware beyond its core CPU operations.
Regarding financial performance, Intel delivered Q4 EPS of $0.15, exceeding the consensus forecast of $0.08. Revenue reached $13.67 billion, topping analyst projections of $13.37 billion. However, revenue declined 4.2% compared to the previous year.
The forward outlook presents challenges. Intel projected Q1 2026 EPS at zero, while analysts anticipate -$0.11 EPS for the complete fiscal year. The company continues facing negative net margins and negative return on equity.
Nvidia Eyes Intel’s Turf
Additional competitive dynamics are emerging. Nvidia, following its $5 billion Intel investment in December, is now advancing into the CPU sector — territory Intel has traditionally dominated.
As artificial intelligence firms transition from model training to deployment phases, CPU requirements are increasing. Nvidia aims to capture market share in this segment.
Analyst opinions show divergence. Tigress Financial maintains a Buy rating with a $66 price objective. Conversely, Wedbush holds a Neutral stance with a $30 target. UBS established a $51 target. MarketBeat’s consensus stands at “Reduce” with a $45.74 price target, while TipRanks reports an average of $48.21 based on recent analyst coverage.
Insider transactions show mixed signals. EVP David Zinsner acquired approximately $250,000 in stock during late January. EVP April Miller disposed of $981,000 worth of shares in early February.
Institutional ownership accounts for 64.53% of INTC shares. The stock’s 50-day moving average stands at $44.26, while the 200-day moving average registers at $37.07.
The consensus analyst price target of $48.21 suggests approximately 6.67% potential upside from current trading levels.
Hotter US PPI inflation data boosted precious metals but punished Bitcoin bulls, with BTC price downside nearing 3% on the day.
Bitcoin (BTC) slid further into Friday’s Wall Street open as US inflation data overshot expectations.
Key points:
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Bitcoin price downside strengthens as US inflation data comes in hot.
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Gold and silver benefit from a risk-off response to January PPI data.
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Bitcoin price expectations face the prospect of a rocky monthly candle close.
Bitcoin under pressure after hot US PPI print
Data from TradingView showed daily BTC price downside nearing 2.5% on Bitstamp, while gold eyed its highest levels since late January.
The January print of the Producer Price Index (PPI) came in markedly above expectations at 0.5% month over month versus an anticipated 0.3%, per data from the US Bureau of Labor Statistics (BLS).
Core PPI fared even worse at 0.8% month over month instead of 0.3%.
“The January increase in prices for final demand can be traced to a 0.8-percent advance in the index for final demand services. In contrast, prices for final demand goods declined 0.3 percent,” an official statement added.
With US inflation creeping higher more quickly than markets assumed, risk-asset pressure increased, while safe havens outperformed.
Gold passed $5,200 per ounce, while silver revisited $92 to hit its highest levels since Jan. 30.
Expectations for interest-rate cuts by the Federal Reserve at its March meeting fell below 4%, according to the latest readings from CME Group’s FedWatch Tool.
BTC price fears over “massive collapse”
With the monthly close in focus, Bitcoin market participants remained on edge.
Related: Hodlers have ‘given up’ at $65K: Five things to know in Bitcoin this week
Crypto trader, analyst and entrepreneur Michaël van de Poppe warned of a possible rerun of events from early February, where BTC/USD put in 15-month lows near $59,000.
“Pretty crucial area for me to hold on to. I’d highly favor that $BTC finds a higher low at $65k,” he wrote in his latest analysis on X.
“However, last day of the month; remember last month? A massive collapse on the markets. Let’s see what it brings: holding $65K opens up the scenario to run up from here.”
Earlier, Cointelegraph reported on key resistance levels for bulls to reclaim, notably the 200-week exponential moving average (EMA) and old all-time highs around $69,000.
At the time of writing, BTC/USD roughly matched February 2025 in terms of performance, with losses nearing 17% month-to-date.
The pair prepared its fifth consecutive month of losses, a phenomenon absent from the charts since 2018, data from CoinGlass confirms.
This article does not contain investment advice or recommendations. Every investment and trading move involves risk, and readers should conduct their own research when making a decision. While we strive to provide accurate and timely information, Cointelegraph does not guarantee the accuracy, completeness, or reliability of any information in this article. This article may contain forward-looking statements that are subject to risks and uncertainties. Cointelegraph will not be liable for any loss or damage arising from your reliance on this information.
- MYX rebounds 29% after heavy losses, driven by V2 partnership news.
- Trading volume surges; whales and institutions show bullish signals.
- The immediate key levels to watch out for are the support at $0.441–$0.430 and the resistance at $0.546.
MYX Finance has surprised many traders by climbing nearly 29% in the last 24 hours.
This comes after a brutal 91% drop over the past month, which left the coin trading near historically low levels.
What sparked the MYX Finance price rebound?
The most immediate driver appears to be MYX’s partnership with Consensys to launch MYX Finance V2 after a successful funding round.
The upcoming V2 upgrade promises gasless trading and 50x leverage, features that can attract both retail and institutional traders.
The news has been framed as a “comeback,” and it has sparked genuine buying interest, not just speculative chatter.
Technical factors are also playing a role.
MYX has been bouncing off extreme lows, and the sudden increase in trading volume confirms strong participation in the rebound.
The 24-hour volume surged to over $55 million, suggesting that bargain hunters and momentum traders are stepping in.
Indicators like the Relative Strength Index (RSI), which is oversold, hint at the selling pressure easing, signalling the end of capitulation.
This combination of fundamental and technical drivers has created a near-term bullish environment.
MYX price technical analysis
After climbing above the $0.49 level, MYX is now consolidating rather than extending its breakout.
Market watchers expect the token to trade in the $0.50 to $0.60 range in the near term.
A sustained pickup in buying interest, particularly if supported by larger capital inflows, could open the door for a move toward $0.70.
If participation from larger investors increases, price swings could become more pronounced, with upside levels around $1, $1.50 and potentially $2 coming into focus.
At the same time, the risk of sharp pullbacks remains.
Such declines are common in volatile markets and are often viewed as part of normal price discovery, where weaker positions are forced out, and liquidity is absorbed by larger participants.
Despite the possibility of short-term setbacks, the broader structure is seen as gradually constructive.
Upcoming risks
Traders should be aware of a key event risk.
On March 6th, about 9.72 million MYX tokens will unlock, worth roughly $9.67 million.
This could create short-term selling pressure as holders choose to liquidate some of their positions.
It is an important factor to watch alongside technical levels and the V2 launch.
MYX price forecast
For short-term traders, the near-term support is around $0.441–$0.430.
On the upside, the first resistance lies at $0.546, the previous swing high.
If the price breaks above this level, gains could extend toward $0.570 and potentially beyond.
On the downside, failure to hold $0.430 could see MYX revisit $0.405.
For now, consolidation above $0.49 sets the stage for a gradual upward move, while the V2 launch and new capital entering the market could trigger sharper rallies.
A heated debate has erupted over whether Canton Network is quietly positioning itself to replace XRP as the likely onboarder of institutions into crypto technology.
The DTCC processes quadrillions in value annually, and the market is suddenly debating the repercussions of its decision to pivot into real world asset (RWA) tokenization with the help of Canton.
This binary view is flawed. Canton Network builds the private rails for compliance, while XRP provides the liquidity that moves between them.
Key Takeaways
- The Infrastructure: Canton Network is designed for the privacy-preserving Tokenization of real-world assets like U.S. Treasuries, ensuring regulatory compliance on a private ledger.
- The Role: XRP functions as a neutral bridge asset for cross-border liquidity, solving the pre-funding problem rather than the custody problem.
- The Signal: Atomic Settlement on Canton complements the liquidity corridors of the XRP Ledger—they are distinct layers in the Institutional Crypto stack.
Canton Network: The Private Crypto Ledger for Atomic Settlement
The Canton Network, launched in 2023 by enterprise blockchain firm Digital Asset, is not a consumer-facing payment rail.
It is a network of networks designed specifically for regulated financial institutions looking to leverage blockchain while requiring absolute privacy.
Its primary engine is the Daml smart contract language, which allows financial institutions to synchronize data across disparate private blockchains without exposing sensitive trade details to the public.
Canton’s core utility is the Tokenization of real-world assets (RWAs). In pilots involving major players like Goldman Sachs and BNY Mellon, Canton demonstrated the ability to execute atomic settlement, swapping tokenized U.S. Treasuries for cash equivalents simultaneously.
This eliminates settlement risk and manages collateral mobility with a precision that legacy systems cannot match.
That matters because institutions cannot operate on fully transparent public ledgers.
Canton acts as a global synchronizer for these records. Unlike XRP, it does not predominantly seek to be a universal bridge currency; it seeks to be the verified vault where the assets live.
Discover: The next crypto to explode
XRP: The Crypto-Native Liquidity Bridge Canton Cannot Be
While Canton secures the asset, XRP moves the value. The XRP Ledger (XRPL) was designed with a specific friction point in global finance in mind: the dormant capital trapped in pre-funded nostro/vostro accounts. XRP acts as a neutral bridge asset, allowing a bank to swap fiat currencies in seconds without holding reserves in every target market.
The misconception that Canton replaces XRP ignores the difference between settlement logic and liquidity provision.
A private ledger can record a change in ownership instantaneously, but it does not inherently provide the deep, neutral market liquidity required to bridge volatile fiat currencies globally.
Ripple has deployed billions to cement XRP’s role as this connector between the banking world and the crypto economy.
For the DTCC, utilizing Canton for ledger synchronization does not negate the need for a mechanism to move value into and out of those synchronized ledgers efficiently. XRP operates on the liquidity layer, distinct from the asset custody layer that Canton occupies.
Two Layers, One Ecosystem: Why the Replacement Narrative Is Wrong
Essentially, Canton Network functions as the digital notary; XRP functions as the armored transport.
If Canton handles the atomic settlement of a tokenized Treasury bill within a permissioned U.S. network, XRP remains the most efficient tool for a foreign entity to source the USD liquidity needed to buy that bill.
This mirrors the challenge discussed by LiquidChain regarding cross-chain liquidity: distinct ledgers need a neutral connector to function efficiently at scale. Without a bridge asset, liquidity remains fragmented across private chains.
In conclusion, as with many debates in crypto, it’s rarely ever a case of backing the stronger horse when both horses excel at totally different things.
Discover: The best crypto to buy now
The post Canton Crypto Network vs. XRP: Breaking Down DTCC’s Infrastructure and Liquidity Needs appeared first on Cryptonews.
MARA Holdings Inc. posted a $1.7 billion net loss in the fourth quarter (Q4) of 2025, a sharp reversal from the $528 million profit it recorded a year earlier.
This report comes only hours after the Bitcoin miner entered a strategic partnership with Barry Sternlicht’s Starwood Capital Group.
MARA’s $1.7 Billion Loss Underscores Bitcoin Volatility — But AI Pivot Signals a New Playbook
MARA’s $1.7 billion Q4 loss came against the backdrop of a roughly 30% decline in Bitcoin’s price during the period. This forced the company to take a $1.5 billion non-cash fair value write-down on its digital asset holdings.
- Revenue for the quarter slipped 6% year-over-year (YoY) to $202.3 million, down from $214.4 million in Q4 2024.
- Adjusted EBITDA swung dramatically to negative $1.49 billion, compared with positive $796 million in the same period last year.
- For the full year, MARA reported a net loss of $1.3 billion, compared with net income of $541 million in 2024.
This shows how mark-to-market accounting can amplify volatility for large Bitcoin treasuries. Despite the earnings hit, MARA ended 2025 with 53,822 BTC on its balance sheet, up 20% YoY.
At a year-end valuation of approximately $87,498 per Bitcoin, those holdings were worth roughly $4.7 billion. Of the total:
- 38,507 BTC were unrestricted,
- 9,377 were loaned, and
- 5,938 were pledged as collateral.
This means about 28% of its Bitcoin stack is encumbered. The company generated $32.1 million in interest income from lending activities during the year.
Liquidity remained substantial. MARA reported about $5.3 billion in combined unrestricted cash and Bitcoin holdings, including loaned and pledged assets.
It also raised $568.6 million in 2025 through its at-the-market (ATM) program but suspended usage in Q4, marking the first quarter since 2022 without tapping the facility.
Operationally, the miner continued to expand. Energized hashrate reached a record 66.4 exahash per second (EH/s) in Q4, up 25% from a year earlier. However, this was below its previously stated 75 EH/s target as management emphasized capital discipline.
AI Infrastructure Pivot Reshapes MARA’s Growth Strategy
Bitcoin production totaled 2,011 BTC in the quarter, down 6% YoY, reflecting higher network difficulty and seasonal energy pressures.
Purchased energy cost per Bitcoin rose to $48,611 in Q4, while cost per petahash per day improved 4% to $30.5. It points to efficiency gains from the deployment of newer equipment.
Beyond mining, MARA is accelerating a strategic pivot toward energy and digital infrastructure, particularly AI and high-performance computing (HPC).
The company announced a joint venture with Starwood Digital Ventures to develop hyperscale, enterprise, and AI-capable data centers.
The partnership aims to deliver approximately 1 gigawatt (GW) of near-term IT capacity, with a roadmap exceeding 2.5 GW over time.
MARA can invest up to 50% in the projects, positioning itself for recurring infrastructure revenue and reduced exposure to Bitcoin price swings.
The company also highlighted its 64% stake in Exaion and the acquisition of a 42-megawatt data center in Nebraska as part of its AI/HPC expansion strategy.
Adding to market intrigue, MARA recently updated its executive compensation metrics in an 8-K filing. The company tied stock awards to megawatt capacity and contracted recurring revenue rather than solely to mining output.
The filing also introduced a change-of-control provision under which performance targets would automatically be treated as achieved if the company is sold. This move has fueled takeover speculation among investors.
Taken together, MARA appears to be balancing a massive Bitcoin treasury with an ambitious infrastructure buildout.
If this is true, then its transformation from a pure-play miner to a diversified energy and AI platform may determine whether it can smooth earnings volatility in the next crypto cycle.
Artificial intelligence has entered a defining new phase. The competitive conversation is no longer centered solely around model innovation, data volume, or algorithmic breakthroughs. Instead, the question enterprise leaders must now answer is far more foundational:
Is our compute foundation strong enough to scale AI across the business?
In 2026, the AI race has evolved into an infrastructure race – one that demands collaboration with the right AI infrastructure development Company and long-term architectural foresight. Amazon’s $12 billion investment in AI-focused data center campuses in Louisiana reflects a larger global reality: enterprise AI growth now depends on physical and architectural compute capacity.
The message for business leaders is clear: compute strategy defines market leadership.
The Shift from AI Experimentation to AI Industrialization
For years, AI initiatives lived in innovation labs – contained within pilots, proofs of concept, or isolated departmental use cases. Infrastructure requirements were minimal because workloads were temporary and limited in scale.
That reality has fundamentally changed.
AI now operates inside mission-critical systems, powering core operations, customer experience platforms, cybersecurity defenses, supply chain optimization, real-time analytics engines, and generative copilots. These are not experimental environments; they are revenue-generating, risk-sensitive business functions.
This evolution demands a formalized enterprise AI infrastructure strategy.
Deloitte’s 2026 Tech Trends analysis highlights a critical inflection point: the challenge is no longer just training models, but managing the long-term economics and scalability of inference at enterprise scale. As AI becomes operational, compute demand shifts from sporadic experimentation to continuous, production-level execution.
Enterprises must now make deliberate decisions about workload placement, hybrid scaling models, cost governance, and performance optimization.
AI is no longer a tactical deployment.
It is a strategic compute architecture commitment.
Amazon’s $12B Move: A Blueprint for AI-Ready Data Centers
Amazon’s $12 billion investment in new AI-focused data center campuses in Louisiana is more than geographic expansion – it is a signal of where global AI infrastructure economics are heading.
As reported by CNBC and covered in depth by Bloomberg, Amazon is expanding its cloud and AI capacity through purpose-built, next-generation data center campuses engineered for high-density compute workloads. These facilities are designed to support advanced AI applications that demand massive processing power, ultra-fast networking, and scalable energy infrastructure.
This investment reflects:
- Long-term compute capacity expansion
- AI-optimized hardware integration
- Advanced cooling systems built for dense GPU clusters
- Infrastructure tailored for large-scale, real-time AI inference
This is what AI-ready data center architecture for enterprises looks like in practice.
Unlike traditional facilities designed for general enterprise IT, AI-optimized data centers are engineered specifically to handle:
- GPU-intensive model training
- High-bandwidth, low-latency interconnects
- Continuous inference workloads
- Distributed real-time data processing environments
Amazon’s strategic expansion reinforces a broader industry truth: AI leadership is no longer defined solely by software innovation – it is secured through physical infrastructure leadership.
Why Compute Architecture Is Now a Strategic Weapon
Modern AI systems, particularly generative AI, real-time analytics engines, and autonomous decision systems, demand far more than virtualized servers. They require a reimagined enterprise compute architecture for AI workloads. Let’s examine why.
1. AI Is Compute-Intensive by Design
Training advanced foundation models can require thousands of GPUs operating simultaneously. Even inference, once considered lightweight, now demands specialized accelerators for high-speed response times.
Organizations that rely on outdated compute environments face:
- Processing bottlenecks
- Latency spikes
- Escalating operational costs
- Infrastructure fragility
AI doesn’t tolerate inefficiency. It exposes it.
2. Real-Time AI Changes Infrastructure Requirements
AI is increasingly embedded in live environments:
- Fraud detection in financial services
- Predictive maintenance in manufacturing
- Personalized product recommendations in e-commerce
- AI copilots in enterprise workflows
These applications require infrastructure for real-time AI, not batch-processing systems designed for overnight analytics.
Real-time AI demands:
- Ultra-low latency networking
- Edge integration capabilities
- Distributed processing
- Seamless scalability
According to TechRepublic’s enterprise AI coverage, many organizations struggle to transition AI from pilot to production because their compute, storage, and networking layers weren’t designed for production-grade workloads, creating bottlenecks that delay or derail deployments.
3. Energy, Cooling, and Sustainability Are Now AI Variables
One often overlooked aspect of AI infrastructure is energy intensity. AI workloads consume significantly more power than traditional enterprise systems.
Modern AI-optimized facilities incorporate:
- Advanced liquid cooling systems
- High-density rack configurations
- Renewable energy integration
- Intelligent power distribution networks
Amazon’s Louisiana campuses are expected to include significant utility and infrastructure upgrades – including new electrical systems funded in partnership with Southwestern Electric Power Company and up to $400 million in water infrastructure improvements to support high-performance operations.
The AI era is also an energy era. Infrastructure planning must integrate sustainability, resilience, and cost efficiency simultaneously.
The Rise of a Formal Enterprise AI Infrastructure Strategy
What separates AI leaders from followers is not experimentation – it is architectural foresight. A strong enterprise AI infrastructure strategy includes:
- Strategic Capacity Planning
Forecasting compute requirements aligned with AI adoption roadmaps.
- Hybrid & Multi-Cloud Alignment
Balancing hyperscale cloud, on-premise systems, and edge environments.
Monitoring inference economics to prevent uncontrolled compute spend.
Embedding zero-trust principles into AI workloads and data flows.
Workload Placement Intelligence
Running the right workloads on the right platforms for performance and cost optimization.
Without a structured strategy, enterprises face:
- Siloed AI deployments
- Fragmented compute environments
- Rising operational costs
- Limited scalability
Infrastructure must move from reactive to predictive.
Why Enterprises Are Turning to Specialized Partners
Designing, deploying, and optimizing AI infrastructure is not trivial. It requires deep expertise across hardware, orchestration, networking, and AI deployment pipelines.
This is why organizations increasingly collaborate with experienced:
- AI infrastructure development companies
- Enterprise AI development companies
These partners help enterprises:
- Architect scalable compute frameworks
- Optimize GPU utilization
- Design resilient multi-cloud ecosystems
- Integrate AI seamlessly into enterprise environments
Infrastructure transformation is complex, but strategic partnerships reduce risk and accelerate deployment timelines.
The Economic Implications of AI Data Center Expansion
Large-scale AI infrastructure investments are signaling a structural transformation in the global economy. Compute capacity is becoming a strategic asset influencing energy markets, semiconductor supply chains, regional talent hubs, and capital allocation priorities.
Enterprises are no longer simply purchasing software licenses; they are competing for sustained access to scalable compute ecosystems. As AI adoption accelerates, infrastructure availability, performance efficiency, and cost governance increasingly determine which organizations can innovate reliably at scale.
The deeper shift is this: AI infrastructure is becoming industrial infrastructure.
Just as railroads powered manufacturing growth and broadband enabled digital commerce, AI-ready compute environments now form the backbone of competitive enterprise ecosystems. Organizations that recognize infrastructure as strategic capital, not operational overhead, will define the next decade of market leadership.
What Enterprise Leaders Must Do Now
Infrastructure decisions can no longer be deferred to IT roadmaps. They must sit at the center of enterprise AI strategy. To remain competitive in the Infrastructure Era of AI, leaders should:
1. Conduct a Compute Readiness Assessment
Identify architectural bottlenecks, GPU constraints, latency risks, and cost inefficiencies that could limit AI scale.
2. Formalize an enterprise AI infrastructure strategy
Align infrastructure investment with long-term AI adoption plans, ensuring compute capacity grows alongside business ambition.
3. Redesign enterprise compute architecture for AI workloads
Move beyond retrofitting legacy systems. Build environments purpose-designed for training, inference, and hybrid scaling.
4. Build a dedicated infrastructure for real-time AI
Enable low-latency, production-grade AI systems that operate within mission-critical workflows.
5. Partner with AI Infrastructure Experts
Work with specialists who can design scalable compute environments and ensure your infrastructure supports sustainable AI growth.
The organizations that act decisively will turn infrastructure into a growth multiplier. Those who delay will find their AI ambitions constrained by architectural limits.
The New Definition of AI Leadership
AI leadership in 2026 is no longer measured by isolated model innovation, but by the strength and scalability of enterprise compute foundations. As AI shifts from experimentation to industrialization, competitive advantage depends on a well-defined enterprise AI infrastructure strategy and a purpose-built enterprise compute architecture for AI workloads. Organizations that invest in AI-ready data center architecture for enterprises and build infrastructure for real-time AI position themselves to scale efficiently, control costs, and sustain performance.
In this new era, infrastructure is not operational support – it is strategic capital. Market leaders will be those who align compute capacity with long-term business vision. Aniter, an enterprise AI development company, helps organizations design, deploy, and optimize scalable AI systems that deliver resilient, production-grade performance and measurable business impact.
ZachXBT just uncovered what looks like a coordinated insider trading ring at Axiom crypto. According to his findings, senior employees used internal data tools to front-run user trades for more than 10 months, allegedly pocketing over $400,000 in the process. The method involved privileged back-end access that allowed staff to track and mirror high-value wallets before the broader market reacted.
This points to deeper governance failures at a platform generating roughly $390 million in annual revenue. Non-technical staff reportedly had unrestricted access to live user identifiers, exposing a serious breakdown in internal controls.
Key Takeaways
- The Actor: Senior business development staff with unrestricted admin access to live user databases.
- The Method: Cross-referencing internal UIDs with on-chain data to identify and front-run KOL wallets.
- The Failure: A YC-backed unicorn generating $390M revenue operating with zero role-based access controls.
How the Insider Trading Scheme Operated Inside Axiom Crypto
The scheme was simple and effective. Investigators say employees used internal admin dashboards meant for support and compliance to pull private user data. By linking User IDs to on-chain wallets, they could identify high-profile traders and institutions behind supposedly anonymous addresses.
From there, the play was straightforward. Monitor activity, then trade ahead of it. Buy before a large wallet pushed price. Sell before a whale exits. It was front-running their own users.
The activity reportedly lasted at least 10 months. The troubling part is that business development staff had the same level of system access as technical security teams. That breakdown in internal controls created the information asymmetry that made the scheme possible.
Discover: The best crypto to diversify your portfolio with
$390M Revenue vs. Zero Access Controls: What Is Axiom Team Response?
Axiom generated $390 million in revenue and scaled rapidly, but the investigation shows its internal controls lagged far behind its growth.
The platform reportedly lacked basic role-based access controls. Business development staff had broad visibility into user identifiers and trading data, creating a “God mode” environment. Proper least-privilege systems and audit logs likely would have flagged the activity early. Instead, it allegedly went unnoticed for nearly a year.
The case highlights a common startup flaw: growth and volume are prioritized, while governance is deferred. That works at a small scale. At billions in volume, it becomes a liability.
Axiom has confirmed a full internal audit. But the reputational damage is significant, and regulators may view the alleged $400,000 in insider profits as potential fraud.
Discover: The best new crypto in the world
The post Axiom Crypto Exposed: ZachXBT Alleges $400k Insider Trading appeared first on Cryptonews.
Pantera Capital and Franklin Templeton’s digital assets units have joined the first cohort of Arena, a new testing environment from open-source AI lab Sentient that is designed to evaluate how AI agents perform in enterprise-style workflows.
In a Friday announcement shared with Cointelegraph, Sentient positioned Arena as a production-style benchmarking platform rather than a static model test. Instead of scoring agents on fixed datasets alone, it runs them through standardized tasks modeled on enterprise conditions, including long documents, incomplete information and conflicting sources.
“In this initial phase, participation refers to supporting the Arena program and developer cohort,” Oleg Golev, product lead at Sentient Labs, told Cointelegraph.
He said partners are helping shape what “production-ready reasoning” looks like for document-heavy tasks such as analysis, compliance and operations. The companies are not announcing capital commitments tied to the initiative.
Related: Jack Dorsey’s Block to cut 4,000 jobs in AI-driven restructuring
The launch comes as enterprises accelerate the deployment of AI agents into research and operational workflows, even as governance frameworks lag.
According to the Celonis 2026 Process Optimization Report, published Feb. 4, 85% of surveyed senior business leaders aim to become “agentic enterprises” within three years, while only 19% currently use multi-agent systems.
Production-style evaluation, not static scoring
Golev described Arena as a shared platform where developers submit AI agents to standardized tasks and compare results under consistent testing conditions.
The platform tracks failure categories such as hallucination, missing evidence, incorrect citations and reasoning gaps, allowing developers to diagnose recurring issues.
Arena plans to publish comparative performance metrics through a public leaderboard and release postmortems summarizing common failure modes and fixes.
Infrastructure partners, including OpenRouter and Fireworks, are supplying inference compute for the initial cohort, while other partners support tooling and workshops.
Related: High-yield bond surge signals rising risk, demand in BTC mining, AI infrastructure
Governance layer amid rising AI autonomy
The initiative emerges as financial and crypto companies experiment with giving AI systems greater economic autonomy.
On Wednesday, MoonPay launched infrastructure enabling AI agents to create wallets and execute stablecoin transactions.
On Thursday, Stripe executives warned that blockchains may need significant scaling improvements if AI-driven commerce expands.
Magazine: AI won’t make you rich but crypto games might, Axie founder steps down: Web3 Gamer
The United Kingdom’s Gambling Commission is exploring how cryptocurrency could be used for payments at licensed online casinos, as the country prepares to bring more crypto activity under a new regulatory regime led by the Financial Conduct Authority (FCA).
Tim Miller, the commission’s executive director for research and policy, said Thursday that the regulator wants to examine “the potential path forward” for allowing “cryptoasset to be used as a consumer payment option for licensed and regulated gambling in Great Britain.” Miller made the remarks at the Betting and Gaming Council’s annual general meeting in London, according to his published speech.
Companies carrying out regulated crypto activities will require authorization by the FCA under the Financial Services and Markets Act 2000 (FSMA) when the new regime commences, Miller said.
“And that, as well as the growing appetite we see from punters, means we do now want to start looking at what the potential path forward would be to create a way for cryptoasset to be used as a consumer payment option for licensed and regulated gambling in Great Britain.”
Commission asks industry group to map options
Miller said he requested that the Industry Forum, an advisory group representing gambling sector workers, explore the best path towards accepting cryptocurrency payments, without setting a deadline.
Miller said that accepting crypto payments may help protect British gamblers from illegal websites.
“Our illegal markets research also gives us evidence that crypto is one of the two biggest searches that lead British gamblers to illegal sites,” said Miller, adding that this may be an important consumer protection measure.
However, Miller highlighted that allowing crypto payments does not mean that casinos will be regulated by UK lawmakers, as they would struggle to pass customer suitability checks.
Related: UK Lords launch stablecoin inquiry as Bank of England moves to finalize rules
FCA sets 2027 deadline for new crypto framework implementation
The comments follow recent regulatory developments from the FCA, which has released a final consultation setting out 10 proposals covering crypto markets. The regulator is expected to conclude that process in March, with full implementation targeted for October 2027.
At the beginning of January, the FCA set a timeline for its new crypto licensing regime, requiring companies to seek full authorization before the regime goes live on Oct. 25, 2027, Cointelegraph reported.
“We expect the application period will open in September 2026,” the FCA said in a document published on Jan. 8.
Crypto asset service providers (CASPs) that miss this application window will fall under transitional rules, which allow existing products but restrict new offerings.
Magazine: How crypto laws changed in 2025 — and how they’ll change in 2026
Despite rising whale counts, total Bitcoin supply held by stakeholders has not significantly increased yet.
Bitcoin has almost reversed its weekly losses after a recovery near $68,000. At the same time, whale wallet growth now suggests distribution among more large holders.
Santiment reported that the asset is approaching a new milestone, as the number of wallets holding at least 100 BTC is set to surpass 20,000.
100+ BTC Wallets Surge
At current prices, a wallet containing 100 BTC is worth a minimum of $6.78 million. According to the firm, these wallets are typically owned by high-net-worth individuals, investment funds, long-term holders, or institutions. Santiment also noted that when the number of such large wallets increases during or after price declines, as is currently the case, it can be interpreted as a bullish signal.
However, the blockchain analytics firm also pointed out that the overall percentage of Bitcoin’s total supply held by key stakeholders has not significantly increased so far, which it said helps explain why prices have remained suppressed. This means that the rise in 100+ BTC wallets indicates distribution across a broader group of large holders, rather than a small cluster maintaining tight control.
Such a trend reflects less extreme consolidation at the top tier of holders. At the same time, Santiment stressed that wealth continues to concentrate in stronger hands relative to smaller retail wallets, meaning the trend does not point to decentralization at the smallest ownership level.
In previous instances, increases in whale wallet counts have often occurred during accumulation phases that later supported price recoveries. Santiment added that for a stronger impact, the growth in large wallet numbers needs to be in line with growth in overall supply held, as retail investors gradually sell their coins to larger holders.
Despite the near-term constructive on-chain signals, concerns of further downside risks remain.
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Bears Still in Control?
Market analyst Willy Woo, for one, tilted toward a bearish outlook for Bitcoin. He stated that the bearish sell-off by investors appears to have exhausted, which gives price room to consolidate sideways for about a month or potentially rebound toward the mid-$70,000 range, though he expects such a move would likely be rejected.
Woo explained that the broader market regime remains heavily bearish, with both spot and futures liquidity deteriorating. He added that he has never seen Bitcoin rally sustainably when both liquidity sources are bearish. Based on his assessment, he said Q4 could mark the end of the bearish trend, while bullish momentum may potentially return in Q1 or Q2 of 2027.
The analyst identified $45,000 as a typical bear market bottom. However, if global macro conditions break down, $30,000 would be fallback support, with $16,000 as the final level.
Another prominent market commentator, Doctor Profit, also previously predicted that while the “fastest” BTC crash may be over, the worst is yet to come.
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As the chart of the ASX 200 index (Australia 200 on FXOpen) shows, today’s candle has moved above the 9,210 level, marking a fresh all-time high. Since the start of the year, the benchmark of Australian equities has gained more than 5.6%, supported by:
→ A strong earnings season. A significant number of companies not only exceeded analysts’ expectations but also upgraded their profit forecasts for the 2026 financial year.
→ Economic resilience. The unemployment rate remains low despite the Reserve Bank of Australia maintaining a firm policy stance.
→ Elevated prices for gold, uranium and copper, along with signs of a recovery in China’s economy, which have provided support to the mining sector.
Technical Analysis of the ASX 200 Chart (Australia 200 on FXOpen)
Price action continues to unfold within an ascending channel (highlighted in blue) that has been in place since autumn 2025. Within this structure:
→ The median line acted as support on 24 February, signalling underlying strength.
→ The upper boundary has repeatedly served as resistance during 2026.
It is worth noting that:
→ The psychological 9,100 level had previously capped gains within the channel.
→ The index has now climbed above 9,200 near the upper boundary of the blue channel.
→ The RSI indicator is approaching overbought territory.
Given these factors, it is reasonable to assume that some long-position holders may look to take profits, potentially leading to a pause in bullish momentum. As a result, the following scenario cannot be ruled out:
→ Failure to secure a sustained move above 9,200;
→ The development of a corrective pullback in the ASX 200 (Australia 200 on FXOpen).
In such a case, support may emerge near the lower orange trend line, which reflects the upward trajectory seen during the second half of the month.
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This article represents the opinion of the Companies operating under the FXOpen brand only. It is not to be construed as an offer, solicitation, or recommendation with respect to products and services provided by the Companies operating under the FXOpen brand, nor is it to be considered financial advice.
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