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Arkham Exchange Transitions from Centralized Exchange to a fully decentralized exchange (DEX)

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Arkham Exchange is transitioning from a centralized exchange (CEX) model to a fully decentralized exchange (DEX).

This was confirmed by Arkham CEO Miguel Morel. The announcement came after initial reports from CoinDesk suggested the platform might shut down due to low trading volumes around $700,000 daily at the time, user adoption challenges, and issues like a bloated/slow mobile app launched in late 2025.

The exchange is not shutting down—it’s pivoting to decentralization. Morel emphasized that “the future of crypto trading is decentralized,” criticizing centralized platforms as “bloated and unresponsive.” Decentralized trading especially perpetual futures is seen as cheaper, faster, and offering users self-custody of assets.

This aligns with broader market trends: In 2025, DEX trading volumes particularly onchain derivatives surged significantly, with perpetual DEX volumes approaching $12 trillion and DEX/CEX ratios hitting record highs. No specific timeline for the full transition has been provided yet, and the platform will remain operational during the shift.

Arkham Exchange, launched by the blockchain analytics firm Arkham Intelligence backed by investors like Sam Altman, originally supported spot and perpetual trading but has struggled to compete with major CEXs. This move reflects a strategic adaptation amid a challenging (bearish) crypto market environment and growing preference for decentralized options.

A DEX model emphasizes self-custody, meaning users retain direct control of their funds via wallets rather than relying on the exchange’s custody. This reduces risks from hacks, freezes, or mismanagement common on CEXs past incidents like FTX.

Perpetual futures and spot trading would become “cheaper and faster” per Morel, with lower fees and no intermediaries. DEXs often face higher slippage in low-liquidity environments and require users to manage wallets/private keys, which can be a barrier for less experienced traders.

Existing Arkham users may need to migrate assets during the transition, introducing temporary friction if not handled seamlessly.

The move addresses low trading volumes around $640K–$700K daily in early 2026, user adoption struggles, and criticisms of the platform becoming “bloated and slow” especially after the late-2025 mobile app launch. By going DEX, Arkham leverages its core strength in on-chain analytics—integrating real-time intelligence directly into trading interfaces could differentiate it from competitors.

The perpetuals/derivatives market is highly competitive, with on-chain volumes surging to ~$12T in 2025 (DEX/CEX ratios hitting highs). Dominated players like Hyperliquid, Aster, and others capture most flow, so Arkham must bootstrap liquidity via incentives or integrations to avoid remaining a niche player.

Building and maintaining a DEX requires adopting or developing secure, scalable protocols likely on chains like Solana or Ethereum L2s for perps, focusing on decentralization rather than centralized listing speed or fiat on-ramps.

This validates the growing preference for DEXs, especially in derivatives, where on-chain options offer transparency, censorship resistance, and alignment with crypto’s ethos. It highlights difficulties for new CEX entrants—even backed by strong analytics like Arkham—in competing against giants like Binance, and Bybit without massive liquidity or unique edges.

Signals adaptation in a tough environment — Amid bearish market conditions (low overall volumes, “bear market jitters”), the pivot shows platforms evolving rather than folding, potentially inspiring similar shifts elsewhere.

Arkham’s analytics edge could carve a niche for “intelligent” DeFi trading, but success depends on execution in a crowded field. As the native token of Arkham Intelligence, ARKM could gain demand if integrated into the new DEX for governance, fee discounts, staking rewards, or protocol incentives.

This might boost its value long-term by tying it more directly to platform activity. Short-term price reactions could vary based on transition progress and market sentiment, but the pivot positions ARKM as more ecosystem-essential than before.

This is a bold adaptation rather than capitulation—aligning with the view that “the future of crypto trading is decentralized.” Success hinges on smooth execution, liquidity attraction, and leveraging Arkham’s data strengths.

Kyrgyzstan’s Crypto Sector Generated More Tax Revenue in 2025 than the Country’s Largest Commodities Market

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Kyrgyzstan’s cryptocurrency sector generated more tax revenue in 2025 than the country’s largest commodities market, specifically the Dordoi Bazaar; a major wholesale trading hub for goods and commodities in Bishkek.

Crypto transaction volume exceeded $20.5 billion in 2025 with some reports mentioning figures up to $31 billion depending on definitions and periods. This resulted in $22.8 million in tax revenue for the state budget.

Taxes collected from the Dordoi Bazaar described as Kyrgyzstan’s largest commodity trading hub/market totaled just over $7.9 million. Additional voluntary patent taxes (a simplified tax system for small businesses and individuals) amounted to $13.6 million.

Combined, the bazaar and patent taxes reached about $21.5 million — still below the crypto sector’s contribution alone. Temir Kazybaev, Chairman of Kyrgyzstan’s Association of Virtual Asset Market Participants, highlighted this milestone, noting that crypto turnover taxes have outpaced these traditional sources.

The sector includes over 200 licensed virtual asset exchangers and some mining operations, with crypto increasingly used for fast payments and cross-border flows in the region. This reflects Kyrgyzstan’s growing regulated crypto ecosystem, which has become a fast-expanding economic driver despite the country’s modest overall size.

Note that separate mining-specific taxes appear lower; tens of millions of soms in earlier periods, equivalent to lower USD figures, so the $22.8 million primarily stems from trading/exchange activities rather than mining.

Kyrgyzstan’s economy has historically relied on traditional sectors like remittances, agriculture, gold mining, hydropower, and informal trade hubs like Dordoi Bazaar (a major re-export center for Chinese goods to Central Asia and beyond).

The crypto sector’s rapid rise adds a high-growth, digital revenue stream, reducing dependence on volatile commodities or bazaar-based trade. This shift positions crypto as a “core economic infrastructure” in some analyses, with transaction flows not just asset appreciation driving steady tax income via licensed virtual asset service providers (VASPs).

The $22.8 million primarily from turnover/exchange taxes provides additional fiscal space for public investments, social spending, infrastructure, or debt management. Kyrgyzstan’s overall GDP is modest ~$17-18 billion in recent years, so this represents meaningful incremental revenue in a low-tax-yield environment.

It signals effective regulation and licensing over 200 licensed exchangers, boosting government confidence in the sector. Crypto turnover exploded from ~$8 million in 2022 to over $20.5 billion (some reports cite up to $31 billion) in 2025, tripling year-over-year in places.

This reflects practical adoption for fast cross-border payments, remittances, and regional flows, especially amid geopolitical dynamics. It creates jobs in licensing, compliance, and tech, while attracting capital and reducing informal economy reliance.

As a small, landlocked nation, Kyrgyzstan benefits from becoming a crypto gateway in Central Asia, potentially drawing more investment and positioning it ahead of neighbors in digital finance.

Some reports link parts of the activity like ruble-pegged stablecoins on Kyrgyz platforms to Russia-facing flows bypassing Western sanctions. This has drawn targeted sanctions, risking international pressure, reputational damage, or restrictions that could disrupt growth.

Crypto markets are inherently volatile; a downturn could shrink turnover and tax revenue quickly. Mining taxes (separate and smaller, e.g., tens of millions of soms earlier) have fluctuated, showing sector sensitivity.

While regulated, rapid growth could strain oversight, raise money laundering risks, or widen inequality if benefits concentrate in urban and tech-savvy areas rather than rural and traditional sectors like bazaars. Outpacing Dordoi Bazaar underscores a structural shift from physical/informal trade to digital flows, potentially pressuring legacy markets unless they adapt.

This development is largely viewed positively in crypto media and regional reports as evidence of Kyrgyzstan’s emerging role in the digital economy, with tangible fiscal gains and growth momentum. However, sustaining it requires balanced regulation to mitigate external risks.

Anthropic Expands Claude’s Free Tier as OpenAI’s Ad Offering Intensifies AI Rivalry

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Anthropic has expanded Claude’s free tier with file creation, third-party integrations, and task “Skills,” while reiterating that the chatbot will remain ad-free — a pointed contrast to OpenAI’s plans to introduce advertising in ChatGPT.

Anthropic is upgrading the free version of its Claude chatbot, broadening access to features previously reserved for paying users in a move that appears strategically timed against OpenAI’s planned advertising integration into ChatGPT.

On Wednesday, the company announced that free Claude users can now create and edit files, connect to external services through “Connectors,” and deploy reusable task-based “Skills.” The update significantly narrows the functional gap between Claude’s free and paid tiers.

The announcement concluded with the tagline “No ads in sight,” underscoring Anthropic’s public commitment to keep Claude ad-free even as debate over monetization models intensifies across the AI industry.

Enterprise Features Move Into the Free Tier

Anthropic introduced file creation capabilities for paid users in September. Beginning this week, free-tier users can also generate and edit Excel spreadsheets, PowerPoint presentations, Word documents, and PDFs. The file-generation feature is powered by Claude’s Sonnet 4.5 model.

The upgrade positions Claude as more than a conversational chatbot, extending it into productivity workflows typically associated with office software suites. By enabling structured document creation directly within chat interactions, Anthropic is strengthening Claude’s appeal for students, freelancers, and small teams who may not subscribe to premium plans.

The introduction of “Connectors” further expands functionality. Free users can now link Claude to third-party services, including Canva, Slack, Notion, Zapier, and PayPal. This integration layer allows Claude to access external content and perform cross-platform tasks, increasing its utility within professional environments.

Anthropic also expanded access to “Skills,” a feature that allows users to preload folders of instructions, scripts, and reference materials so Claude can execute repeatable tasks in structured ways. The capability effectively creates customizable mini-workflows within the chatbot interface.

Additional improvements include longer conversation memory, more interactive responses, and enhanced voice and image search functionality.

Together, the upgrades represent a meaningful shift: Claude’s free tier now functions as a lightweight AI productivity platform rather than a limited demo product.

The Advertising Divide

The timing of the expansion aligns with OpenAI’s stated intention to introduce advertising into ChatGPT for free users. While OpenAI has not detailed the precise format or timing of ad deployment, the plan marks a potential pivot in the economics of consumer AI services.

Anthropic has framed its approach in sharp contrast. The company reiterated that Claude will remain ad-free, stating that inserting advertisements into conversations would be incompatible with its vision of the assistant as a tool for work and deep thinking. The company has said that more than 80% of its revenue comes from enterprise customers, reducing reliance on consumer monetization.

The rivalry spilled into public messaging. In a Sunday Super Bowl advertisement, Anthropic depicted competing chatbots awkwardly inserting product placements into conversations, a clear reference to advertising-driven models. OpenAI Chief Executive Sam Altman described the ads as “funny” but “clearly dishonest,” saying OpenAI would not deploy advertising in the manner portrayed and positioning ads as a way to expand access for users who cannot afford subscriptions.

The exchange reflects a broader strategic divergence. One model prioritizes enterprise revenue and subscription tiers, maintaining a clean conversational environment. The other signals openness to diversified monetization to subsidize free access at scale.

The expansion of Claude’s free tier also comes amid intensifying competition across the generative AI market. Large models are increasingly converging in baseline capabilities, shifting differentiation toward ecosystem integration, workflow depth, and pricing structures.

Anthropic is raising the competitive bar for free-tier offerings by offering file generation, cross-platform connectors, and structured skills at no cost. The move may pressure rivals to either enhance their own free features or accelerate monetization efforts.

There is also a trust dimension. Advertising inside AI conversations raises questions about content neutrality, recommendation bias, and data use. An ad-free stance allows Anthropic to position Claude as an assistant optimized for utility rather than engagement-driven monetization.

At the same time, expanding free-tier functionality increases compute costs. File generation, external API calls, and extended memory sessions require sustained infrastructure investment. Anthropic’s enterprise-heavy revenue mix may help absorb those costs, but the long-term sustainability of a robust ad-free free tier depends on continued commercial adoption among paying customers.

The upgrade signals that competition in AI is moving beyond raw model performance toward platform architecture and business model identity. As OpenAI experiments with advertising and Anthropic doubles down on subscription and enterprise revenue, users are being offered distinct visions of how conversational AI should function — and how it should be funded.

OpenAI Researcher Resigns, Warns the Company is Going Facebook’s Way with Ads

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On Wednesday, OpenAI researcher Zoë Hitzig published a powerful guest essay in The New York Times announcing her resignation on Monday—the same day OpenAI began testing advertisements inside ChatGPT for free and low-tier users.

Hitzig, an economist, published poet, and junior fellow at the Harvard Society of Fellows, spent two years at OpenAI helping shape model development, pricing, and deployment strategy. Her departure adds to a striking wave of high-profile exits from leading AI labs this week, reflecting growing unease among researchers as companies accelerate the commercialization of AI.

Hitzig did not condemn advertising outright. Instead, she argued that the intimate, confessional nature of data users share with ChatGPT—medical fears, relationship struggles, religious beliefs, and personal vulnerabilities—creates an unprecedented “archive of human candor” that makes advertising especially dangerous. She warned that OpenAI risks repeating Facebook’s trajectory: early promises of user control and transparency gradually eroded, leading to privacy scandals and Federal Trade Commission findings that marketed changes actually reduced user power.

“I once believed I could help the people building A.I. get ahead of the problems it would create,” Hitzig wrote. “This week confirmed my slow realization that OpenAI seems to have stopped asking the questions I’d joined to help answer.”

She highlighted existing tensions: OpenAI claims it does not optimize for user activity solely to generate ad revenue, yet reporting suggests the company already optimizes for daily active users, often by making models more flattering and sycophantic—behavior that can increase emotional dependence. Hitzig pointed to documented cases of “chatbot psychosis” and wrongful death lawsuits alleging ChatGPT reinforced suicidal ideation or validated paranoid delusions leading to violence.

She proposed structural alternatives: cross-subsidies (e.g., high-value AI labor paid by businesses subsidizing free access), independent oversight boards with binding authority over data use, and data trusts or cooperatives giving users control over their information, citing precedents like Switzerland’s MIDATA cooperative and Germany’s co-determination laws. She concluded with two feared outcomes: “a technology that manipulates the people who use it at no cost, and one that exclusively benefits the few who can afford to use it.”

The essay landed amid a week of significant departures across AI labs:

  • Anthropic: On Sunday, Mrinank Sharma, who led Anthropic’s Safeguards Research Team and co-authored a widely cited 2023 study on AI sycophancy, announced his resignation. In an open letter, Sharma warned that “the world is in peril” and said he had “repeatedly seen how hard it is to truly let our values govern our actions” inside the organization. He plans to pursue a poetry degree—coincidentally aligning with Hitzig’s background as a published poet.
  • xAI: At least nine employees, including co-founders Yuhuai “Tony” Wu (who resigned Monday) and Jimmy Ba (Tuesday), publicly announced departures over the past week, according to TechCrunch. Six of xAI’s original 12 co-founders have now left. The exits follow Elon Musk’s announcement of an all-stock merger with SpaceX ahead of a planned IPO, valuing xAI at $1.25 trillion, though the timing’s relation to vesting schedules or other factors remains unclear.

These departures appear unrelated in specifics but coincide with a period of rapid commercialization across the AI industry that has tested internal cultures. Researchers who joined to pursue fundamental questions about AI safety, alignment, and societal impact increasingly face pressure to prioritize productization, revenue, and scaling—often at odds with cautious, long-term research agendas.

The timing of Hitzig’s resignation, on the day OpenAI launched ads in ChatGPT, amplified its impact. OpenAI began testing clearly labeled ads at the bottom of responses for free and $8/month “Go” tier users in the U.S., while Plus, Pro, Business, Enterprise, and Education subscribers remain ad-free. The company insists ads will not influence model answers and personalization is opt-in, using chat history and past ad interactions—but not sharing raw chats with advertisers.

The rollout followed a week of public sparring with rival Anthropic, which ran Super Bowl ads declaring Claude would remain ad-free and depicting other AI chatbots awkwardly inserting product placements. OpenAI CEO Sam Altman called the ads “funny” but “clearly dishonest,” insisting OpenAI would never run ads in the manner depicted and framing the model as a way to bring AI to users who cannot afford subscriptions. Anthropic countered that including ads in Claude conversations “would be incompatible with what we want Claude to be: a genuinely helpful assistant for work and for deep thinking,” noting that over 80% of its revenue comes from enterprise customers.

Hitzig’s essay and the surrounding departures highlight a broader reckoning in the AI research community. As companies shift from research-focused origins toward revenue-generating products, tensions between safety/alignment priorities and commercial imperatives have intensified. The wave of exits—spanning OpenAI, Anthropic, and xAI—suggests that many researchers who joined to shape AI’s future are questioning whether their values can still be realized inside these organizations.

As Hitzig warned, the path forward risks creating either manipulative free tools or exclusive premium services—outcomes that could shape public trust in AI for years to come.

How Trust Signals Differ Across Online Industries

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Life online has become incredibly familiar, with users moving from website to website and clicking on buttons like “Buy Now” and “Sign Up.” But with each of these interactions comes a decision that has a very real question tacked onto it: “Can I trust this?” Trust is important no matter what business you’re interacting with, but online, it can sway a visitor’s decision in an instant.

People often rely on subtle cues to decide which sites feel trustworthy. Yet what reassures them changes based on industry norms and what’s at stake. We’ve come to recognize that trust signals carry different weight in different contexts.

What “Trust Signals” Actually Are

Trust signals refer to any type of cue that helps someone decide whether a platform is credible and safe. Whether they’re blatantly obvious (like a big security badge) or subtle (like carefully worded copy), they all work to build confidence. Some other examples of signals might include a recognizable credit card logo at checkout, customer testimonials on the homepage, or text that clarifies how personal data is used and protected. In many instances, these indicators are functional and designed to directly protect users from risk, but some are purely emotional and intended to provide a sense of reliability.

Certain trust signals can be found across vastly different platforms, but they’re typically not universal. Even if they appear on two separate sites, they can work differently depending on context. Sometimes, a seemingly trustworthy signal in fintech might do little for someone using an ecommerce app. For business owners, it means learning how to provide the right reassurance for the right situation. Do it right, and a user can go from uncertain to engaging, paying, and sharing.

Ecommerce: Familiar Reassurance

Although online shopping is extremely popular, it still can’t replicate the tactile experience of browsing items in a physical store. To bolster trust, shoppers rely on distinct visual and procedural signals to know if a site is trustworthy before making a purchase.

Social proof is a huge factor here, as customers will often scour customer reviews and testimonials to understand their experiences. Perhaps they found the quality wasn’t what they expected, or the shipping took much longer than what it said on the site. Secure checkout processes and recognizable payment options also give shoppers confidence that the purchase process is simple and that their financial information will be protected. As well, they want to know that customer support is easy to access, with clear contact options.

Entertainment Platforms: Low-Stakes Trust

Trust operates a little differently on entertainment platforms like streaming services, mainly because there’s a lower perceived risk. Because users aren’t purchasing a tangible product and free trials or previews are often available, they don’t usually have as many hesitations as they would on an ecommerce site.

Users are typically more willing to explore a platform if it offers an easy exit, such as a free trial or a simple cancellation process. Brand identity and platform reliability are also essential trust signals, manifesting in smooth performance, consistent design, and predictable functionality that makes the experience feel frictionless.

Online Gambling: Risk-Based Trust

In contrast to entertainment platforms, trust is non-negotiable in online gambling because of the sheer personal and financial risk. Although gambling platforms are now held to strict regulatory standards in certain countries, players still demand real proof. Licensing and audits are the first signs that games are fair and that the platform operates legally. Similar to ecommerce, payment security is a must to demonstrate that deposits and withdrawals are handled safely.

Other measures of responsibility and transparency, such as clear rules and responsible gaming tools, add an extra layer of reassurance, showing players that the platform prioritizes their well-being. Many people rely on resources that review Canadian casino sites to get a faster, more informed look before signing up, giving them the external validation they need.

Fintech: Authority as Assurance

With real consequences at stake, fintech platforms need to showcase their authority to gain trust. Users entrust these platforms with their money and personal data without being able to personally validate it themselves. Regulation and compliance show that the platform is monitored by official authorities. At the same time, transparency around fees and data use helps users know exactly what’s happening with their money and personal information.

And, of course, brand reputation and longevity give extra peace of mind. A fintech platform tied to a bank with a decades-long track record of reliability feels much safer than a random startup with no established history.

How Risk Raises the Bar

Naturally, higher stakes require stronger trust signals. As more could go wrong, users need more than a few familiar cues to feel confident enough to share personal data or make financial transactions. Platforms need to offer actual proof that a platform is safe, reliable, and fair. Low-risk environments call for lighter reassurance, but high-risk sectors require more layers and multiple angles. Trust needs to be tangible and hard to question, and only then will people act without second-guessing.

Why No Single Trust Marker Works Everywhere

Trust is a spectrum, and that’s why a universal checklist doesn’t exist across industries. Companies need to understand their audience and tailor trust signals accordingly. Users often rely on mental shortcuts when evaluating trust, and the better the design elements of social proof, the faster they can get from curiosity to action. Trust markers have changed, so what reassured someone five years ago may already feel inadequate today. Both platforms and users need to adapt to new norms and standards or risk falling behind.