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When markets break, traders turn to AI

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Vugar Usi

Disclosure: The views and opinions expressed here belong solely to the author and do not represent the views and opinions of crypto.news’ editorial.

I’ve watched enough liquidation cascades to know that prices move faster than narratives, timelines fill with confident takes, and even experienced traders start reacting to the loudest signal in the room. In those minutes, the core challenge is maintaining a coherent decision process when the environment tries to break it.

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Summary

  • Volatility exposes attention limits: When markets cascade, traders don’t just need predictions — they need compressed context. AI becomes the “second screen” that restores coherence under stress.
  • Usage spikes during chaos, not calm: Data shows AI engagement surges around liquidation events, revealing that traders use it to filter noise and slow emotional reactions.
  • Interpretation shapes market structure: As more traders rely on AI for real-time context, the quality of those interpretations can either dampen herding or amplify systemic risk.

That’s why the most meaningful shift I’m seeing is practical. Traders reach for AI during chaos because it compresses information, restores context, and slows emotional reaction time when the market speeds up. Engagement rises broadly over time, and then surges when markets stress-test attention. AI increasingly sits inside the crypto market structure, so those surges carry implications beyond product adoption.

When the screen turns red, attention becomes the bottleneck

During extreme volatility, traders struggle with context collapse. Price action, breaking news, on-chain chatter, funding changes, liquidation data, and social sentiment hit at once. The mental bandwidth required to interpret it all becomes the constraint.

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A growing body of research links information overload to degraded decision accuracy under limited attention. A Federal Reserve paper lays out that mechanism and the measurable market effects.

In that environment, many traders gravitate toward tools that turn the flood into something legible. The demand shifts toward fast summaries, context comparisons, and clearer explanations of what has changed.

What tool usage time reveals about trader intent

Since August 2025, MEXC reports that 2.35 million users have used its AI trading suite, generating 10.8 million total interactions. Average daily active users reached about 93,000, with a single-day peak near 157,000; the conversational bot represented the largest share of activity in the suite.

Those totals matter, but the shape of usage matters more. Spikes cluster around stress events, when traders seek a compressed understanding quickly.

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When the market accelerates, traders increase their use of AI as a lens for interpretation. That pattern also clarifies what traders mean when they say “AI helps me trade.” In volatile conditions, “help” often means filtering noise, summarizing the moving parts, and restoring situational awareness. The decision remains theirs, and the tool shapes what they can see in time.

AI as stress infrastructure for clarity and restraint

A lot of AI conversation in trading still centers on prediction. In lived market conditions, traders often value something else: coherence.

During volatility, a trader’s biggest risk is often cognitive. Stress narrows attention. Social proof grows louder. Rumor fills the gaps left by speed. Tools that provide fast context can lower the odds of impulsive action driven by panic and narrative momentum.

AI’s real utility shows up at the trader level. It can behave like an editor, distilling what’s known and flagging what’s uncertain — or helping the user anchor on relevant variables while the market tries to drag them into reaction.

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That distinction matters because it draws a line between support and substitution. Support tools improve comprehension under stress. Substitution tools encourage delegation of judgment when uncertainty is highest.

Why this matters for market structure

Now zoom out. AI affects markets beyond retail-facing tools. AI adoption in capital markets spans trading and market intermediation, and carries risks tied to opacity, governance challenges, and correlated behavior when many systems respond similarly.

AI-driven trading can contribute to faster markets and higher volatility during stress, especially when strategies converge or react in similar ways to shocks. Crypto magnifies these dynamics. The market runs 24/7. Reflexive sentiment moves quickly. Professional market makers and retail traders often share the same venues and the same velocity of information. In that setting, exchange design and information presentation become part of how markets behave under pressure.

This is why I believe exchanges are increasingly evaluated on a broader definition of quality. Liquidity and fees remain essential, but users also judge the platform’s capacity to keep them oriented when volatility peaks. At scale, orientation becomes stability.

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When large numbers of traders use AI tools during volatility to interpret the market in real time, the quality of those interpretations shapes behavior. A clearer context reduces crowding into the same rumors and overreactions. Poor context can accelerate herding, especially when uncertainty is highest.

The next phase of AI in crypto markets is accountability and provenance

If traders use AI primarily for interpretation during stress, the next phase is about accountability. Accountability starts with making it obvious what sources an insight relies on, what is confirmed versus inferred, and what the tool cannot responsibly conclude in real time. Analysts explicitly frame market-wide risks that can emerge from broad AI adoption, especially around correlated behavior and stress dynamics.

It also changes how AI-powered features should be framed. Tools that present themselves as authoritative forecasts can encourage over-delegation at the exact moment when humility and restraint matter most. Tools that emphasize context can encourage deliberation without pretending to eliminate uncertainty.

As AI spreads through trading and market infrastructure, monitoring and governance need to keep pace because systemic risks reveal themselves most sharply during stress.

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AI is becoming the translation layer for speed

The industry often talks about AI as a trader. Many users already treat it as a translator. When markets break, traders lean on AI to convert noise into signal, speed into digestible context, and emotional pressure into something closer to restraint. That’s why adoption rises during volatility, and that’s why the stakes are bigger than feature engagement charts suggest.

With more participants relying on similar kinds of real-time interpretation under stress, AI shapes how the crowd understands events. At that point, AI influences behavior at scale, and behavior at scale becomes market structure.

Disclosure: This article does not represent investment advice. The content and materials featured on this page are for educational purposes only.

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Vugar Usi

Vugar Usi

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Vugar Usi is an award-winning business leader and communications strategist with 15 years of experience driving growth across Fortune 500 giants, tech unicorns, and Web3 disruptors.  As Chief Operating Officer at MEXC, Vugar plays a key role in driving the company’s next phase of global expansion. He supports MEXC’s international compliance strategy and overall market readiness, leveraging his experience at top exchanges and leading Web3 ventures. His expertise contributes to product innovation, platform enhancements, and CSR initiatives that reinforce MEXC’s position as a comprehensive, responsible, and forward-looking global platform. With decade-long experiences scaling Fortune 500 brands and leading Web3 ventures, Vugar brings a proven track record in high-velocity growth. As former COO of Bitget, he helped elevate the exchange from a top-20 player to the world’s second-largest crypto platform, expanding its user base fivefold to 120 million. His background—including roles shaping narratives at Facebook, advising global leaders at Bain & Company, redefining brand strategies at Coca-Cola and SONY, and co-founding a MarTech unicorn—positions him to propel MEXC’s continued growth and global standing.

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Crypto World

Meta (META) Stock Drops as Company Plans Major Layoffs to Finance Massive AI Investment

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META Stock Card

Key Highlights

  • Meta may eliminate approximately 20% of its total workforce — potentially affecting 16,000 workers
  • The workforce reduction aims to finance a massive $600 billion AI infrastructure investment extending to 2028
  • Mark Zuckerberg has directed top executives to develop headcount reduction strategies
  • The company recently purchased AI agent platform Moltbook and invested $2 billion in Chinese AI firm Manus
  • Meta’s “Avocado” AI system has underperformed against internal benchmarks

Meta Platforms appears poised to execute its largest workforce reduction since 2022, with internal discussions pointing toward eliminating 20% or more of current staff. Given Meta’s December employee count of approximately 79,000, this translates to around 16,000 positions potentially being eliminated.


META Stock Card
Meta Platforms, Inc., META

The information surfaced Thursday via Reuters, which spoke with three individuals with direct knowledge of the discussions. However, neither timing nor precise figures have been finalized. When contacted, a Meta representative characterized the reporting as “speculative” and focused on “theoretical approaches.”

These potential reductions stem from Meta’s ambitious artificial intelligence strategy. The social media giant has pledged to invest $600 billion in data center construction and AI infrastructure through 2028 — an expenditure requiring significant cost reductions in other areas.

Zuckerberg’s vision has become increasingly apparent. Speaking in January, he noted witnessing “projects that used to require big teams now be accomplished by a single very talented person.” This efficiency narrative underpins Meta’s current trajectory.

According to two Reuters sources, senior executives have already instructed department heads to develop workforce reduction plans. While still in preliminary phases, the strategic direction appears firmly established.

Aggressive AI Investment Strategy

These workforce changes coincide with Meta’s aggressive AI spending. Meta recently completed the acquisition of Moltbook, an AI agent-focused social platform. Additionally, the company is committing at least $2 billion toward Chinese AI startup Manus.

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To attract elite AI researchers, Meta has extended compensation packages valued at hundreds of millions of dollars spanning four years to scientists joining its superintelligence division.

The paradox is striking: the very AI investments necessitating specialized hires may simultaneously trigger widespread job eliminations. The astronomical costs of constructing AI infrastructure are pushing the company toward operational streamlining across other divisions.

Should the 20% reduction materialize, it would represent Meta’s most significant downsizing since its “Year of Efficiency” initiative. That restructuring eliminated 11,000 positions in November 2022, with an additional 10,000 cuts following in early 2023.

Meta follows an industry-wide trend. Amazon announced 16,000 job eliminations earlier this year. Block reduced its workforce by nearly 50%, with CEO Jack Dorsey explicitly attributing the cuts to AI capabilities reducing staffing requirements.

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Challenges with Avocado AI Model

Meta’s substantial AI investments haven’t guaranteed smooth execution. The company’s Llama 4 models faced scrutiny following questionable performance on initial benchmarks. Behemoth, the flagship variant, was ultimately canceled ahead of its anticipated summer launch.

Meta’s superintelligence division is currently developing Avocado, a new model designed to rebuild credibility in the company’s AI efforts. However, early results have reportedly disappointed internal stakeholders.

Bernstein analysts have identified a “trough of disillusionment” affecting consumer AI adoption — an apt description of Meta’s current AI product positioning.

META stock declined 3.83% during regular trading following the news, though shares recovered modestly in after-hours activity as market participants evaluated the potential margin benefits of reduced headcount.

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Current figures show Meta employed 78,900 people as of its December regulatory filing. A 20% workforce reduction would decrease that total to approximately 63,000 employees.

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Crypto World

XRP Network Activity Surges While Token Price Searches for Macro Bottom

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xrp price

TLDR

  • The XRP Ledger recorded 2.7 million daily payments, marking a 12-month peak, even as XRP’s value dropped 26% since January
  • Automated market maker pools expanded to nearly 27,000 while tokenized real-world assets on the platform climbed 35% over 30 days to $461 million
  • The token currently hovers near $1.42, representing a 62% decline from its December 2025 high of $3.65
  • Technical analysts highlight critical support between $0.80–$0.95, while a surge past $3.32 could unlock targets ranging from $27–$48
  • Despite XRP’s $84 billion market capitalization, XRPL’s total value locked remains at a modest $47.54 million

The XRP Ledger is experiencing unprecedented network utilization, yet the token’s market performance tells a contrasting story. Currently valued at approximately $1.42, XRP has shed 26% of its value year-to-date and sits 62% beneath its late-2025 zenith of $3.65.

xrp price
XRP Price

Successful payment transactions on the XRP Ledger recently climbed above 2.7 million daily, establishing a new 12-month benchmark. This represents a substantial increase from approximately 1 million recorded in late 2025, with the blockchain consistently handling 20 to 26 transactions every second.

(CoinDesk)
Source: XRPScan

The platform’s automated market maker infrastructure has expanded to encompass nearly 27,000 pools, facilitating trading for more than 16,000 distinct tokens. Currently, twelve million XRP sits deposited within these liquidity pools.

The value of tokenized real-world assets on the ledger climbed to $461 million, representing a 35% expansion over the preceding 30 days. During this same timeframe, stablecoin transfer volume reached $1.19 billion, with the total stablecoin market cap on XRPL standing at $339 million distributed among 35,800 holders.

A significant portion of this network utilization connects to Ripple’s RLUSD stablecoin and tokenized instruments that employ XRP temporarily as a bridge asset. These operations don’t generate enduring demand for holding the token long-term.

Why Activity Isn’t Lifting XRP’s Price

When XRP facilitates a cross-border transaction for mere seconds to connect two fiat currencies, it doesn’t create persistent buying pressure. The blockchain processes more volume, but the token functions as a fleeting intermediary.

According to DeFiLlama, the XRP Ledger’s total value locked reaches only $47.54 million. By comparison, Solana maintains approximately $4 billion in TVL. Ethereum commands over $40 billion.

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(DefiLlama)
Source: DefiLlama

Daily decentralized exchange volume on XRPL fluctuates between $4 million and $8 million. For a Layer 1 blockchain carrying an $84 billion market valuation, these figures remain relatively modest.

The 30-day RWA transfer volume of $149 million — representing an increase exceeding 1,300% — does suggest genuine institutional participation in the asset tokenization sector.

What Analysts Are Watching

Analyst EGRAG CRYPTO highlights a critical accumulation zone spanning $0.80 to $0.95, where several technical signals align, including convergence of the 21, 50, and 100 exponential moving averages alongside a sustained ascending trendline.

Should XRP recapture the 21 EMA and escape its present corrective formation, the subsequent price objective would land near $2.20. The base-building phase could extend through Q2–Q3 2026.

Analyst Ali Martinez recognizes a long-term ascending triangle configuration with horizontal resistance positioned around $3.32. A decisive move above this threshold projects macro objectives spanning $27 to $48.

Analyst Crypto Patel observes a validated multi-year triangle breakout, with a projected bull-market target approaching $50.

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The $1.27–$1.30 support region has withstood numerous retests. Historically, XRP delivers an average 18% gain during March.

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Spot Bitcoin ETFs Log Their First Five-Day Inflow Streak of 2026

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Spot Bitcoin ETFs Log Their First Five-Day Inflow Streak of 2026

US spot Bitcoin exchange-traded funds (ETFs) logged their first five-day inflow streak of 2026, bringing in roughly $767.32 million this week.

The funds recorded $180.33 million in net inflows on Friday, extending the run of positive flows that began earlier in the week. The strongest day of the streak came on Tuesday, when spot Bitcoin (BTC) ETFs attracted $250.92 million, according to data from SoSoValue.

The last time the funds saw a comparable streak was in late November 2025, when spot Bitcoin ETFs logged five consecutive days of net inflows from Nov. 25 to Dec. 2, bringing in a combined $284.61 million.

Spot Bitcoin ETF flows so far this year. Source: SoSoValue

Overall, the ETFs now hold $91.83 billion in net assets, with cumulative net inflows reaching $56.14 billion and roughly $4.93 billion in total value traded on the day.

Related: BlackRock says ‘exotic’ crypto ETFs not part of its strategy

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Ether ETFs see 4-day inflow streak

Meanwhile, US spot Ether (ETH) ETFs recorded $26.69 million in net inflows on Friday, extending a four-day run of positive flows. The streak began on Tuesday, when the funds added $12.59 million, followed by $57.01 million on Wednesday and a stronger $115.85 million on Thursday, the largest inflow during the period.

The four-day stretch has brought roughly $212.14 million into spot Ether ETFs, reversing the outflows seen earlier in March. As of today, cumulative net inflows into US spot Ether ETFs stands at $11.79 billion, while total net assets across the funds reached $12.26 billion, with about $1.30 billion in value traded on the day.

The recent stretch marks the first sustained inflow run for spot Bitcoin and Ether ETFs this year after a volatile start to 2026 that saw several days of heavy outflows across the products.

Related: Bitcoin ETFs add $251M as Goldman Sachs tops XRP ETF holders

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Bitcoin range-bound as Middle East tensions rise

Rising tensions in the Middle East and volatility in energy markets are weighing on global risk sentiment. According to Bitunix analysts, escalating conflict around the Strait of Hormuz and elevated oil prices have increased macro uncertainty and reduced expectations for aggressive Federal Reserve rate cuts, prompting investors to focus on short-term liquidity rather than long-term risk exposure.

Against this backdrop, Bitcoin remains range-bound. Bitunix said derivatives liquidation heatmaps show a key short-liquidity cluster near $71,300, which is acting as near-term resistance, with a larger concentration between $72,000 and $73,500.