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Gemini Restructuring and Laying Off 25% of its Global Workforce 

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Gemini, the cryptocurrency exchange founded by Tyler and Cameron Winklevoss (often referred to as Gemini Space Station in some contexts, ticker: GEMI), has undergone a significant restructuring in February 2026.

This includes laying off approximately 25% of its global workforce up to around 200 employees and exiting operations in the UK, EU including other European jurisdictions, and Australia. The moves come amid a sharp downturn in the crypto market, with Bitcoin experiencing notable declines, leading to lower trading volumes, tighter liquidity, and rising regulatory pressures.

Gemini, which went public via IPO in September 2025, has seen its stock plummet more than 80% from post-IPO highs, with its market value dropping sharply. The restructuring aims to reduce operating expenses, streamline toward a leaner model partly enabled by increased use of AI in engineering and other roles, and refocus primarily on the US and Singapore.

The company is shifting emphasis toward custody services and its newly launched prediction markets platform, as revenue growth has lagged behind expenses.
Expected pre-tax restructuring costs are around $11 million, with most changes to be completed in the first half of 2026.

In mid-February, Gemini also parted ways with three C-suite executives: COO Marshall Beard, CFO Dan Chen, and CLO Tyler Meade (effective immediately), with interim replacements appointed internally. Cameron Winklevoss is absorbing some COO responsibilities. Additional quiet US staff cuts have occurred beyond the initial announcement.

This isn’t related to Google’s Gemini AI model. The news pertains specifically to the crypto platform. The crypto industry continues facing challenges post-2025 market cycle, with firms adjusting through cost-cutting and strategic pivots. Gemini’s changes reflect broader pressures in the sector.

The 25% staff layoffs (affecting up to ~200 employees globally) and related restructuring at Gemini (the crypto exchange founded by the Winklevoss twins, NASDAQ: GEMI) in early February 2026 carry several significant implications, both for the company and the broader crypto sector. This comes amid a sharp crypto market downturn, with Bitcoin down over 40% from its late-2025 highs, reduced trading volumes, and persistent profitability challenges.

The moves are explicitly designed to slash operating expenses, align costs with lower revenue, and accelerate breakeven. The company cited revenue growth lagging behind expenses, with prior quarters showing substantial losses, ~$159.5M in one reported period, and estimates of up to ~$600M net loss for 2025.

Restructuring costs are estimated at ~$11M pre-tax, mostly in Q1 2026, but the long-term goal is meaningful cost reduction through workforce cuts, AI integration in operations, and exiting high-complexity/low-return international markets (UK, EU, Australia). This refocuses Gemini on core strengths in the US and Singapore.

Emphasis shifts toward custody services (a more stable, fee-based revenue stream less tied to volatile trading) and the newly launched prediction markets platform. This bets on emerging niches amid declining traditional exchange activity, but success is uncertain in a bearish environment.

The abrupt departures of three C-suite executives (COO Marshall Beard, CFO Dan Chen, CLO Tyler Meade) —shortly after the initial announcement—signal deeper internal turmoil. Cameron Winklevoss is absorbing some COO duties without a replacement, suggesting recentralization of power but raising concerns about governance and execution risk.

GEMI shares have plummeted >80% from post-IPO highs peaking near $45-46 in late 2025, with market cap dropping from ~$4B to under $700M (recent trading around $5.8–$6.6). Additional quiet US staff cuts and executive exits triggered further declines. Analysts from  Truist Securities highlight solvency worries and question the original IPO prospectus’s optimism about international growth.

International users face account wind-downs potentially driving them to competitors. This shrinks Gemini’s global footprint but simplifies operations. The crypto “winter” is hitting infrastructure players hard. Gemini’s aggressive post-IPO expansion bet on continued bull conditions through 2027 backfired with the rapid price crash, highlighting overexpansion risks in bull markets.

It echoes patterns seen in prior cycles where exchanges over-hire and over-extend during highs. As a US-focused, compliance-heavy exchange, Gemini faces higher costs from regulations, while offshore/DEX competitors capture volume with lower overhead. The retreat from regulated but complex markets (EU/UK) underscores difficulties in global scaling under tightening rules.

This reinforces that even well-known, publicly traded players aren’t immune. It could pressure peers to accelerate cost controls, pivot to non-trading revenue (custody, derivatives, prediction markets), or face similar scrutiny. Investor confidence in crypto IPOs/post-IPO stability may wane further.

If Gemini stabilizes via its US pivot and new products, it could emerge leaner. However, ongoing market weakness risks further cuts or distress. This reflects a classic crypto cycle correction: hype-driven growth unraveling under reality. Gemini is in survival mode, prioritizing US dominance and profitability over global ambition.

The crypto sector continues its Darwinian phase, where adaptability and cash runway determines who endures. The situation remains fluid with no major positive reversals reported.

Anthropic Alleges Massive Distillation Campaign by Chinese AI Labs, Escalating Fight Over Chips and Safeguards

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Anthropic’s claim that 16 million Claude interactions were siphoned through 24,000 fake accounts reframes the AI race as a battle over inference access, safeguards, and chip supply — not just model training.


U.S. artificial intelligence firm Anthropic has accused three Chinese AI developers, DeepSeek, Moonshot AI, and MiniMax, of orchestrating what it describes as a coordinated, large-scale “distillation” campaign to extract capabilities from its Claude AI system.

Anthropic said the three labs created more than 24,000 fraudulent accounts that generated over 16 million interactions with Claude. The queries, it alleged, were designed to systematically replicate some of Claude’s most advanced features, including agentic reasoning, tool use, and coding — areas considered differentiators among frontier AI systems.

The accusations land amid heightened geopolitical tension over artificial intelligence, particularly as Washington reassesses export controls on advanced semiconductors to China and as Chinese AI labs close the performance gap with U.S. counterparts.

Distillation as a competitive shortcut

Distillation is a common technique in machine learning in which a large, high-performing model acts as a “teacher” to train a smaller “student” model. Within a single company, it is used to compress models for lower-cost deployment while retaining much of their capability.

Across companies, however, the method becomes controversial. By querying a rival’s model at scale and using the responses as training data, a competitor can approximate performance without replicating the comprehensive research, compute expenditure, or alignment work that went into the original system.

Anthropic said the alleged campaigns varied in focus and scale. It tracked more than 150,000 exchanges linked to DeepSeek that appeared aimed at strengthening foundational reasoning and alignment, including workarounds for policy-sensitive prompts. Moonshot AI allegedly generated more than 3.4 million exchanges focused on agentic reasoning, tool integration, coding, data analysis, and computer vision. MiniMax accounted for roughly 13 million exchanges targeting agentic coding and orchestration, with Anthropic claiming it observed traffic being redirected toward the latest Claude release shortly after launch.

The scale matters since sixteen million interactions represent not casual usage but what Anthropic characterizes as industrialized extraction.

DeepSeek, in particular, has drawn scrutiny since releasing its open-source R1 reasoning model last year, which analysts said approached the performance of leading U.S. frontier labs at a fraction of the cost. The company is reportedly preparing DeepSeek V4, a new model said to outperform both Claude and OpenAI’s ChatGPT in certain coding benchmarks. Earlier this month, OpenAI also accused DeepSeek in a memo to U.S. lawmakers of using distillation techniques to mimic its systems.

Export controls and compute leverage

The dispute is unfolding alongside debate over access to high-end chips. Last month, the Trump administration allowed U.S. firms, including Nvidia, to export advanced AI processors such as the H200 to China, loosening earlier restrictions.

Anthropic linked the alleged distillation campaigns to computing power. “The scale of extraction… requires access to advanced chips,” the company said in a blog post.

It argued that export controls serve a dual function: limiting direct model training and constraining the compute needed for high-volume distillation.

This framing shifts the chip debate. Historically, export controls focused on preventing Chinese firms from training large frontier models from scratch. Anthropic’s claim suggests that even if direct training is restricted, access to sufficient inference compute could enable large-scale replication via API querying.

Policy analysts say this complicates enforcement. Distillation occurs through legitimate product interfaces — paid or public APIs — rather than through overt hacking. That creates a grey zone between normal usage and systematic extraction.

National security dimension

Anthropic also framed the issue as one of security. The company said U.S. developers build safeguards into frontier systems to prevent misuse in areas such as bioweapons design or malicious cyber operations.

“Models built through illicit distillation are unlikely to retain those safeguards,” Anthropic wrote, warning that dangerous capabilities could proliferate if protections are stripped out during replication.

It pointed to the possibility of authoritarian governments deploying advanced AI for offensive cyber operations, disinformation campaigns, and mass surveillance — risks that increase if such systems are open-sourced without embedded safety layers.

Dmitri Alperovitch, chairman of the Silverado Policy Accelerator and co-founder of CrowdStrike, told TechCrunch the allegations were unsurprising.

“It’s been clear for a while now that part of the reason for the rapid progress of Chinese AI models has been theft via distillation of U.S. frontier models. Now we know this for a fact,” he said. “This should give us even more compelling reasons to refuse to sell any AI chips to any of these [companies], which would only advantage them further.”

Anthropic said it will continue investing in defensive measures to make distillation harder to execute and easier to detect, while calling for “a coordinated response across the AI industry, cloud providers, and policymakers.”

Such coordination could include tighter API rate limits, improved anomaly detection, contractual enforcement mechanisms, and shared threat intelligence among AI labs. Cloud providers — which host the infrastructure underpinning both U.S. and Chinese AI workloads — may also face pressure to monitor and flag high-volume extraction patterns.

The broader stakes extend beyond one company. If frontier AI capabilities can be replicated rapidly through sustained querying, the competitive moat built on research expenditure and chip access narrows. In that scenario, advantage may hinge less on breakthrough architecture and more on distribution control, access management, and compute governance.

At the same time, aggressive restrictions carry trade-offs. Limiting chip exports could affect U.S. semiconductor revenues and accelerate domestic Chinese chip development. Restricting API access could constrain legitimate global customers and developers.

Anthropic’s allegations therefore crystallize a central tension in the global AI race: openness versus control. The tools that make AI widely usable, APIs, cloud access, and scalable inference, also create vectors for replication. As Chinese labs close the performance gap with U.S. peers, the contest increasingly revolves not just around building the most advanced model, but protecting it.

Dangote Refinery Set for Public Listing in Four Months as Retail Investors Promised Dollar Dividend Option

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Aliko Dangote says ordinary Nigerians will be able to buy shares in the $20 billion Dangote Refinery within five months, with the option to receive dividends in either naira or U.S. dollars.


Chairman of Dangote Group, Aliko Dangote, has confirmed that ordinary Nigerians will be able to acquire shares in the Dangote Refinery within the next four to five months, marking a significant step toward opening up ownership of one of Africa’s largest industrial projects.

Dangote made the disclosure on Saturday, February 21, 2026, during a media tour of the refinery alongside the Group Chief Executive Officer of Nigerian National Petroleum Company Limited (NNPC), Bayo Ojulari, and other senior executives of the state-owned oil firm.

He described the visit as symbolic, emphasizing that NNPC is not merely a collaborator but an equity participant in the refinery.

“Today is really our best day ever. At least he (Ojulari) is not just a guest, he is a shareholder and you know NNPC invested in us when we ourselves were not even sure that the refinery will be successful,” Dangote said.

According to him, NNPC holds a 7.25% equity stake in the refinery on behalf of Nigerians. “They are holding 7.25% of the shares that we have here, which is more than the shares that Elon Musk has in Tesla, and they are holding that on behalf of Nigerians,” he said, adding that individual Nigerians will soon have the opportunity to directly participate in ownership.

“But individually Nigerians too will have an opportunity in the next maximum four or five months they will actually be able to buy their shares.”

Structure of the Planned Offer

The refinery, valued at about $20 billion, is expected to list roughly 10% of its equity on the Nigerian Exchange Limited (NGX) in 2026. Dangote had earlier disclosed that discussions were ongoing with the Securities and Exchange Commission of Nigeria and the NGX to finalize the framework for the initial public offering (IPO).

A distinctive feature of the proposed listing is the dual-currency dividend structure. Dangote said investors would be allowed to receive dividends either in naira or in U.S. dollars, citing the refinery’s foreign currency earnings profile.

“People will have a choice either to get their dividends in naira or to get their dividends in dollars because we earn in dollars,” he stated.

Projected export earnings of about $6.4 billion, largely from petrochemical products such as polypropylene and fertilizer, are expected to underpin this dollar dividend model. That revenue stream provides the refinery with a steady flow of hard currency, which in turn supports the feasibility of foreign currency payouts to shareholders.

Capital Market and Currency Implications

If executed within the stated timeline, the IPO would rank among the most consequential listings in Nigeria’s capital market history. A company of this scale entering the exchange is likely to boost market capitalization on the NGX and attract renewed domestic and international investor interest.

The structure also introduces a new dynamic into Nigeria’s equity market. Dollar-denominated dividends are uncommon on the local exchange, and the option could appeal to investors seeking protection against exchange rate fluctuations. For retail investors who typically have limited access to dollar-based assets, such a structure may represent a rare opportunity to hold an instrument tied to foreign currency earnings.

Beyond liquidity gains, the listing could deepen retail participation in equities at a time when household savings are often concentrated in fixed-income instruments. By offering exposure to an asset with a strong export orientation and integrated value chains, the refinery may broaden the investment landscape for individual Nigerians.

The Dangote Refinery occupies a central position in Nigeria’s downstream petroleum industry. Designed to reduce reliance on imported refined products, it has implications for fuel supply stability, trade balances, and industrial feedstock availability.

Its petrochemical outputs, including polypropylene, are critical inputs for manufacturing sectors such as plastics, packaging, and consumer goods. Fertilizer production also links directly to agricultural productivity, which has wider food security and export implications. The project seeks to capture more value domestically rather than exporting crude and importing finished products by combining refining and petrochemicals in a single integrated complex.

Opening up ownership to the public embeds this industrial infrastructure more directly into Nigeria’s financial system. It creates a bridge between capital markets and large-scale manufacturing, potentially setting a precedent for how future infrastructure and industrial projects are financed.

Relationship with NNPC

Dangote expressed optimism about collaboration with the new NNPC leadership under Ojulari, describing the relationship as forward-looking.

“I think the sky is the limit and we would cooperate and also make sure we work together to make Nigerians proud,” he said.

NNPC’s 7.25% stake positions the state oil company as both a shareholder and a strategic partner. That arrangement may facilitate alignment on crude supply agreements, product distribution channels, and broader policy coordination within the energy sector.

Following the announcement of the listing, Nigerians have excitement and readiness to bet on the refinery. Dangote indicated that priority would be given to Nigerian retail investors to ensure broad-based participation.

Amazon Unveils $12bn Louisiana Data Center Expansion Amid Intensifying AI Infrastructure Race

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Amazon plans to invest $12 billion in new AI-focused data center campuses in Louisiana as part of a broader $200 billion capital expenditure push.


Amazon on Monday announced plans to invest $12 billion in new data center campuses in Louisiana, reinforcing its aggressive expansion of artificial intelligence and cloud infrastructure even as investors weigh the financial implications of surging capital expenditures.

The facilities will be located in Caddo and Bossier Parishes in northwestern Louisiana. Amazon said it expects to create 540 full-time roles tied directly to the data centers and support approximately 1,700 additional jobs connected to the campuses, including electricians, HVAC technicians, construction workers, and security specialists. Beyond direct employment, such projects often generate secondary economic effects through local suppliers, logistics providers, and service industries.

The investment forms part of Amazon’s broader capital spending strategy. Earlier this month, the company projected roughly $200 billion in capital expenditures for the year — a figure that outpaces other hyperscale cloud operators and underscores the scale of infrastructure required to support next-generation AI workloads. Combined, major technology firms have forecast nearly $700 billion in 2026 expenditures as the race to build AI capacity accelerates.

Amazon’s announcement follows a volatile period for its stock. Shares declined for nine consecutive trading sessions after the company’s Feb. 5 earnings report, wiping out more than $450 billion in market value during that stretch. Investors have questioned whether the pace of capital deployment may weigh on near-term profitability, particularly as AI monetization models are still evolving.

A substantial portion of Amazon’s spending is directed toward AI-related assets, including advanced data centers, proprietary chips, networking equipment, and specialized computing clusters. These investments are largely channeled through Amazon Web Services (AWS), the company’s cloud division and primary profit engine. AI services, including model training and inference, are increasingly becoming core growth drivers for AWS, but they require enormous upfront infrastructure commitments.

Amazon’s expansion mirrors similar moves by competitors such as Microsoft and Google, both of which have committed hundreds of billions of dollars to expanding their global data center footprints. Meta has also selected Louisiana for a major project — the $27 billion Hyperion data center joint venture with Blue Owl Capital.

The clustering of hyperscale facilities in Louisiana signals the state’s growing appeal as an infrastructure hub. Factors likely include land availability, grid capacity, regulatory conditions, and economic development incentives. For technology firms, site selection balances proximity to energy sources, transmission infrastructure, fiber connectivity, and tax considerations.

AI models require vast computational power not only for initial training but also for ongoing inference — the process of generating responses or predictions in real time. As enterprises integrate AI into customer service, analytics, healthcare diagnostics, and industrial automation, demand for high-performance computing continues to rise. Hyperscalers are effectively building the backbone for this digital transformation.

Energy, Water, and Community Considerations

The rapid buildout of data centers nationwide has prompted environmental and community scrutiny. Large-scale facilities can consume significant amounts of electricity and water, raising concerns about grid strain and local resource allocation.

Last year, Microsoft withdrew from a planned site in rural Wisconsin after residents raised environmental and financial concerns, illustrating the political and regulatory sensitivity surrounding such projects.

Amazon said it worked with the local utility, Southwestern Electric Power Company, to ensure that it would bear the full cost of energy infrastructure tied to the campuses. The company stated it will pay “100% of the costs” associated with new and upgraded energy infrastructure.

To mitigate electricity demand, Amazon plans to incorporate natural air cooling when feasible, reducing reliance on energy-intensive mechanical cooling systems. The company also said the Louisiana campuses will use only surplus water from the surrounding area, asserting there will be no strain on local water supplies. In addition, Amazon plans to invest up to $400 million in public water infrastructure to support the sites.

Amazon is partnering with data center developer Stack Infrastructure on the project, leveraging the firm’s expertise in constructing and operating hyperscale facilities.

The Louisiana investment points to the structural shift underway in the technology sector. AI has moved from an experimental capability to a foundational computing paradigm, requiring sustained capital outlays comparable to utilities or transportation networks. Data centers are increasingly viewed as critical infrastructure.

For Amazon, the long-term thesis rests on AI-driven revenue growth offsetting the near-term pressure on free cash flow. The company is effectively wagering that enterprises’ migration toward AI-powered services will generate durable demand across cloud storage, compute, machine learning platforms, and related services.

At the state level, Louisiana stands to gain from increased tax revenues, workforce development opportunities, and enhanced infrastructure. However, sustained oversight of environmental impact and grid resilience will likely remain central to public discourse.

Nigeria Targets 5% of GDP for Industrial Financing Under Sweeping 2025 Policy Drive

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By earmarking up to 5% of GDP for industrial financing, Abuja is signaling one of the most aggressive state-backed industrial funding commitments in Nigeria’s recent economic history.


The Federal Government has unveiled plans to allocate up to 5% of Nigeria’s Gross Domestic Product to industrial financing under the Nigeria Industrial Policy (NIP) 2025, marking a decisive shift toward large-scale production, export expansion and structured job creation.

Contained in the framework released by the Federal Ministry of Industry, Trade and Investment, the policy lays out a coordinated strategy to reposition the economy toward mass manufacturing, deeper value addition, and reduced import dependence.

At the heart of the plan is a strengthened development finance architecture anchored on recapitalizing the Bank of Industry and scaling intervention funds in collaboration with the Central Bank of Nigeria.

“We recognize that no policy succeeds without financing,” the document stated. “By setting aside up to 5% of GDP for industrial financing and leveraging public–private partnerships, this government demonstrates its commitment to matching ambition with resources.”

The 5% allocation is designed to crowd in private capital through structured public–private partnerships while lowering financing constraints that have historically hampered Nigeria’s manufacturing sector.

  • Under the framework:
  • The Bank of Industry is expected to be recapitalized to N3 trillion by 2026.
  • Sector-specific intervention funds are projected to rise to N3 trillion.
  • Credit guarantees for MSMEs will be mainstreamed to de-risk lending.
  • New instruments such as interest-drawback schemes and equity-based financing will be introduced.

This approach represents a shift from fragmented credit schemes toward a consolidated industrial financing ecosystem with clearer institutional responsibilities and performance metrics.

If implemented at scale, the allocation could materially alter capital access conditions for manufacturers, especially in agro-processing, textiles, pharmaceuticals, petrochemicals, and light engineering.

President Bola Tinubu formally unveiled the Nigeria Industrial Policy 2025 last week, directing ministries, departments, and agencies to ensure swift execution.

The policy aligns with Tinubu’s “Renewed Hope” agenda, particularly its emphasis on domestic production, import substitution, and industrial self-sufficiency.

A key feature is the enforcement of a “Nigeria First” procurement stance, prioritizing locally manufactured goods in public spending. The framework also seeks to reduce reliance on imported raw materials by encouraging backward integration and local value chains.

By consolidating fiscal, monetary, trade, and industrial measures into a unified strategy, the government is attempting to address longstanding coordination gaps that have limited the impact of previous industrial programmes.

Target: Manufacturing at 25% of GDP

Nigeria’s manufacturing contribution to GDP has historically remained in the low double digits. The NIP 2025 sets an ambitious target: raising manufacturing’s share to between 20% and 25% of GDP by 2030.

Achieving that would require sustained growth in output, infrastructure upgrades, and improved logistics efficiency, particularly in power supply and transport networks.

Industrial expansion at that scale would also carry employment implications. Manufacturing is typically more labor-intensive than extractive industries, suggesting potential for broad-based job creation, particularly among youth.

Beyond domestic production, the policy underscores export competitiveness as a strategic priority. Nigeria’s export base remains heavily concentrated in crude oil. Industrial diversification is positioned as essential to stabilizing foreign exchange earnings and reducing vulnerability to commodity price shocks.

Strengthening non-oil exports — from processed agricultural goods to finished consumer products — would require improvements in standards compliance, logistics, trade facilitation, and market access.

The policy’s integrated design seeks to align export promotion with financing mechanisms, rather than treating them as separate policy domains.

Implementation Risks and Structural Constraints

While the financing commitment is substantial on paper, execution will determine outcomes.

Key variables include:

  • Fiscal sustainability: Allocating up to 5% of GDP requires disciplined budget management and efficient capital deployment.
  • Governance oversight: Transparent allocation and monitoring of funds will be critical to prevent leakages.
  • Infrastructure readiness: Industrial financing must be matched by reliable electricity, transport corridors, and digital infrastructure.
  • Private sector participation: Public–private partnerships depend on investor confidence and regulatory stability.

Recapitalizing development finance institutions alone will not guarantee productivity gains unless funds are channeled into sectors with clear competitive advantages.

Overall, the Nigeria Industrial Policy 2025 represents one of the most comprehensive industrial blueprints in recent years. By embedding financing targets within a structured implementation framework — complete with timelines and measurable performance indicators — the government is attempting to move from policy declaration to institutional execution.

If the 5% GDP allocation is realized and effectively deployed, it could mark a structural pivot away from oil dependence toward diversified industrial growth.

While the scale of ambition is clear, economists reiterate that the test will lie in translating capital commitments into functioning factories, expanded export lines, and sustainable employment across the country.