Artificial intelligence (AI) has successfully outgrown its initial software training phase to trigger the largest physical computing buildout in modern history. By mid-2026, the global AI compute market is no longer driven by speculative model prototyping, but by the massive deployment of operational inference systems and agentic AI architectures.

Tech giants and cloud hyperscalers are projected to deploy over $700 billion in capital expenditures this year alone, targeting high-performance graphics processing units (GPUs), custom application-specific integrated circuits (ASICs), gigawatt-scale data center expansions, and liquid cooling architectures.

As the global semiconductor market approaches the $1 trillion milestone in 2026, traditional capital boundaries are dissolving. The rise of tokenized stocks, digital assets that track real-world equities 1:1 on public blockchains, allows crypto-native capital to integrate directly into global equity markets. In addition to tokenized stocks, platforms like BingX TradFi let global investors trade leading U.S. stock futures using USDT collateral. This framework provides 24/7 fractional exposure to premier AI compute and GPU hardware leaders without requiring traditional, cross-border brokerage accounts, channeling liquidity straight into the core infrastructure of the modern digital economy.

The Global AI Compute Market Overview in 2026: Key Structural Trends

The AI hardware landscape has evolved into a highly complex, interconnected supply chain. General-purpose GPU stockpiling has given way to targeted data center architectures. The 2026 compute supercycle is defined by four foundational structural trends:

1. The Inference and Agentic AI Boom

While training foundational large language models (LLMs) remains a fixed capital cost, 2026 marks the official inflection point where inference workloads, running live, operational models, account for approximately two-thirds of all AI compute demand. The explosive growth of multi-step, autonomous Agentic AI architectures requires a massive shift in hardware optimization.

Agentic AI demands a much higher central processing unit (CPU) to GPU ratio, moving from the historical training ratio of 1:8 down to a balanced 1:1 ratio. Consequently, data center economics now prioritize the total cost per inference token and power efficiency above raw computing brute force.

2. Custom Silicon Acceleration (XPUs)

To protect gross margins and bypass premium third-party markups, major cloud providers are aggressively deploying custom-designed internal chips, often termed XPUs or custom ASICs. Tailored explicitly for proprietary inference algorithms, these custom accelerators are growing at a faster rate than generalized hardware. This shift is structurally altering deployment ratios inside hyperscaler data centers and creating a booming co-design ecosystem for specialized semiconductor architects.

3. Persistent Supply Chain Bottlenecks: CoWoS and HBM4

The primary constraint on global AI output is no longer chip design, but highly localized physical bottlenecks. Advanced packaging solutions, specifically Chip-on-Wafer-on-Substrate (CoWoS), remain entirely sold out through the end of 2026.

Simultaneously, High-Bandwidth Memory (HBM), the rapid-response memory architecture essential for feeding high-performance GPUs, is experiencing severe structural shortages. Leading memory producers have already locked in forward capacity allocations through 2027, granting immense pricing power to suppliers positioned directly on these constraints.

4. Power and Cooling Constraints

Raw electricity and thermal management have become the definitive bottlenecks for next-generation data centers. With single high-density server racks exceeding 120 kW in power requirements, modern gigawatt-scale AI factories are entirely unfeasible under traditional air-cooling mechanics. This infrastructure reality has forced data center operators to execute massive capital allocations toward advanced liquid cooling systems, power distribution networks, and structural energy efficiency innovations.

What Are the Best AI Compute and GPU Stocks to Watch in 2026?

The following list identifies the leading AI compute designers, foundry operators, and critical supply chain hardware providers driving the global AI technology cycle in the second half of 2026.

1. NVIDIA (NVDA)

• 2026 Valuation Benchmark: $5.3 Trillion Market Cap
• Core Role: Dominant GPU Designer and CUDA Software Moat

NVIDIA remains the absolute leader of the AI hardware universe, commanding roughly 75% to 80% of the enterprise AI accelerator market. Building on the massive deployment of its Blackwell architecture, NVIDIA is ramping up production for its next-generation Vera Rubin platform slated for late 2026. The Rubin architecture introduces integrated custom CPU-and-GPU frameworks packed with advanced HBM4 memory, targeting up to a 10x improvement in performance-per-watt efficiency to directly solve hyperscaler power constraints.

NVIDIA's true competitive defense is its CUDA software platform, which anchors millions of global developers to its ecosystem. Backed by an estimated $1 trillion in combined Blackwell and Rubin order visibility extending through 2027, the company enjoys massive revenue visibility.

2. Advanced Micro Devices (AMD)

• Core Role: High-Performance CPU & Alternative AI GPU Architecture

AMD has successfully established itself as the primary market alternative to NVIDIA's accelerator monopoly, particularly for cost-sensitive enterprise deployments and scaled inference workloads. The company’s MI300 and MI350 series AI accelerators have achieved deep penetration across hyperscaler networks like Meta and OpenAI.

Crucially, the 2026 shift toward Agentic AI. which demands higher CPU core counts, plays directly into AMD’s core competency as a leader in high-performance data center CPUs (EPYC series). Furthermore, AMD's chiplet-based GPU architectures offer superior memory density, rendering them highly competitive for memory-bound inference algorithms.

3. Broadcom (AVGO)

• Core Role: Custom AI ASICs and High-Speed Networking Fabrics

Broadcom represents the ultimate beneficiary of the custom silicon revolution. Rather than commercializing off-the-shelf general GPUs, Broadcom functions as the primary co-design partner helping hyperscalers build proprietary infrastructure, notably co-developing Alphabet's highly successful Tensor Processing Unit (TPU) and custom silicon for Meta.

Broadcom dominates nearly 70% of the custom ASIC market and maintains a clear runway toward a $100 billion custom chip business by fiscal year 2027. Additionally, Broadcom provides the critical ultra-high-speed switching and networking silicon required to bind tens of thousands of independent processors into synchronized data factories.

4. Taiwan Semiconductor Manufacturing Company (TSM)

• 2026 Valuation Benchmark: $2.1 Trillion Market Cap
• Core Role: Monopolistic Pure-Play Advanced Fabrication

TSMC is the indispensable physical backbone of the global AI boom, acting as the exclusive foundry partner fabricating advanced silicon blueprints for NVIDIA, AMD, Broadcom, Apple, and Qualcomm. Holding an effective monopoly over leading-edge 3nm and 2nm process nodes, alongside its highly constrained CoWoS advanced packaging facilities, TSMC captures premium pricing power across the entire hardware stack.

Supported by insatiable compute demand, TSMC projects the global semiconductor market to approach $1.5 trillion by 2030, while aggressively executing multi-billion-dollar physical expansions across Arizona to build geographically distributed, secure fabrication nodes.

5. Micron Technology (MU)

• Core Role: Next-Generation High-Bandwidth Memory (HBM) Production

Micron Technology has completed its evolution from a cyclical commodity memory supplier into a mission-critical bottleneck asset. Modern AI processors are inherently memory-bound, meaning performance is limited by how quickly data can transition into the compute core.

Micron’s ultra-dense High-Bandwidth Memory (HBM3E and next-gen HBM4) is universally required across top-tier GPU platforms. Driven by the severe 2026 memory crunch, Micron has fully pre-sold its entire HBM production capacity multi-years forward, locking in long-term, high-margin enterprise contracts with leading hyperscalers.

Comparison of Leading AI Compute and GPU Companies

Based on current 2026 data, leadership positions, and consensus outlooks, here is an updated comparison table of the top AI compute and GPU stocks to watch or trade.

Ticker	Primary AI Category	Core Product / Advantage	2026 Catalysts & Financial Outlook
NVIDIA (NVDA)	GPU Architecture / Design	Blackwell & Vera Rubin GPUs; CUDA Platform Moat	Retains 75-80% market share; $1T backlog visibility through 2027 from Blackwell + Rubin.
AMD (AMD)	CPU & GPU Design	MI350/MI400 Accelerators; EPYC Data Center CPUs	Highly favored for Agentic AI 1:1 CPU ratios; strong memory density inference alternative.
Broadcom (AVGO)	Custom Silicon & ASICs	Hyperscaler custom XPUs; high-speed data center fabrics	Dominates 70% of custom ASIC market; visible path to $100B custom revenue by FY27.
TSMC (TSM)	Advanced Foundry	2nm/3nm Node Fabrication; CoWoS Packaging	Complete structural packaging monopoly; capacity entirely sold out through 2026; massive AZ expansion.
Micron (MU)	Advanced Memory	High-Bandwidth Memory (HBM3E / next-gen HBM4)	HBM capacity fully pre-sold mult-years forward; structural multi-year high-margin pricing power.

BingX provides global market participants with highly optimized, crypto-native tools to capture price exposure across the premier AI compute and GPU ecosystem. Traders can execute macro theses through two distinct, secure pathways depending on capital allocation styles and structural preferences.

For investors targeting direct, non-leveraged asset exposure tracking real-world equities on a 1:1 economic basis, the BingX Spot market provides secure access to tokenized tech shares issued via regulated asset frameworks.

For active market participants seeking to capture near-term earnings momentum, hedge existing structural spot allocations, or utilize directional flexibility, BingX TradFi offers USDT-settled perpetual contracts mirroring leading U.S. technology equities.

Risks and Key Considerations When Trading AI Compute Stocks

Despite the undeniable multi-year structural tailwinds backing the AI hardware cycle, market participants must manage capital allocation against significant systemic risks:

• Valuation Compression and Capex Sensitivities: Premium structural valuations leave AI compute equities vulnerable to sharp corrections. If mega-cap hyperscalers indicate a shift from a compute-constrained environment to a balanced supply-demand dynamic, structural multiples will compress rapidly.
• Geopolitical Manufacturing Dependencies: Leading-edge hardware fabrication remains highly concentrated within specific geographic corridors. Export restrictions, regional friction, or supply shocks affecting East Asian foundries present a constant risk profile to assets like TSMC.
• Rapid Technological Obsolescence: The hardware space moves incredibly fast. For example, if a hyperscaler develops an in-house inference chip that substantially outperforms external general-purpose alternatives, legacy pricing models and third-party margins will deteriorate swiftly.
• Tokenized Asset Governance Structures: Tokenized equity pairs function exclusively as structured price-tracking vehicles. They capture 1:1 real-world economic movements using crypto rails but do not convey corporate voting architecture, physical stock delivery, or traditional shareholder legal rights.

Final Thoughts: Should You Add AI Compute Stocks to Your 2026 Portfolio?

The technology sector in mid-2026 features a sharp divergence: while consumer-facing software monetization is still expanding, the hardware infrastructure builders are generating massive, verified, and recurring cash flows today. Diversifying capital across distinct structural layers of the compute stack, ranging from design leaders like NVIDIA and AMD to supply-chain bottleneck constraints like TSMC and Micron, offers a comprehensive mechanism to gain exposure to this global technology cycle. Utilizing tokenized spot vehicles or flexible stock futures via BingX TradFi enables global capital to execute these macro-driven equity theses efficiently using unified, crypto-native rails.

However, navigating this high-growth ecosystem requires absolute capital discipline. Semiconductor and AI compute infrastructure assets are inherently volatile and highly sensitive to sudden supply-chain realignments. Market participants should carefully assess their individual risk profiles, maintain strict risk mitigation protocols, and treat these high-beta technology exposures as a specialized component of a well-balanced, globally diversified portfolio.

Explore XRP vs Bitcoin wealth distribution in 2026. Discover which cryptocurrency is more centralized, with detailed analysis of top holder concentration, Ripple escrow, exchange reserves, and investor implications.

As of early April 2026, XRP and Bitcoin display clear differences in wealth distribution. XRP exhibits higher concentration among its top addresses, driven primarily by its fully pre-mined supply and Ripple Labs substantial escrow holdings. Bitcoin, issued gradually through decentralized mining, supports a broader long-term distribution despite notable institutional accumulation.

Key Takeaways

• Bitcoin operates with a hard-capped supply of 21 million coins. As of March 2026, its circulating supply reached approximately 20 million BTC, representing more than 95% of the total maximum, with the remaining less than 1 million coins expected to be mined over the next approximately 114 years.
• XRP maintains a fixed total supply of 100 billion tokens, all created at launch. Its circulating supply stands at approximately 61 to 66.6 billion XRP as of early April 2026, with roughly 33.3 to 34 billion XRP held in Ripple-managed escrow accounts.
• Wealth in XRP remains more concentrated at the top tier of addresses compared with Bitcoin. A significant portion of XRP top holdings consists of exchange custody wallets and Ripple escrow, representing pooled or programmatic control rather than single speculative entities. Bitcoin positions itself as the more decentralized store of value, while XRP functions mainly as a payment utility token with a distinct structural profile.
• Institutional adoption continues for both assets. Bitcoin attracts larger corporate treasuries and spot exchange-traded funds, reinforcing its role as digital gold.

What Is Bitcoin (BTC)?

Bitcoin is the first cryptocurrency, introduced in 2009 by the pseudonymous Satoshi Nakamoto. It runs on a decentralized peer-to-peer network secured through proof-of-work mining. Network participants validate transactions and secure the blockchain, receiving newly minted bitcoin as block rewards. The protocol enforces a maximum supply of 21 million BTC, with new issuance halving roughly every four years. This predictable, slowing release schedule underpins Bitcoin value proposition as a scarce, inflation-resistant asset.

BTC Wealth Distribution and Concentration

Source: BTC Top Holders 2026 Arkham

Bitcoin wealth distribution appears more decentralized than that of many pre-mined cryptocurrencies, although large holders exist. Top addresses include dormant early-mined coins, exchanges, exchange-traded funds, and corporate treasuries.

Addresses holding 10,000 BTC or more collectively account for roughly 14% of total supply when grouped. The top 1,000 addresses control over 15% in broader analyses. Exchanges hold approximately 10 to 12% of Bitcoin on behalf of users. When viewed as raw individual addresses without entity consolidation, concentration remains lower than in XRP.

Notable institutional positions include BlackRock iShares Bitcoin Trust with hundreds of thousands of BTC, public companies such asStrategy (formerly MicroStrategy) maintaining significant corporate treasuries exceeding 700,000 BTC in some reports, and governments holding seized assets. Satoshi Nakamoto associated addresses are estimated to hold about 1.1 million BTC, or roughly 5.5% of supply, though these remain largely inactive. The gradual mining-based issuance over more than 17 years has encouraged wider participation, contributing to a more dispersed ownership base compared with assets created entirely at inception.

What Is Ripple (XRP)?

Ripple Labs created XRP as the native digital asset of the XRP Ledger, a blockchain designed for fast and low-cost cross-border payments and settlements. Unlike Bitcoin, the entire 100 billion XRP supply was pre-mined at launch. The ledger employs a consensus mechanism rather than energy-intensive proof-of-work, achieving transaction finality in seconds. XRP serves primarily as a bridge currency to facilitate liquidity between different fiat currencies for financial institutions and payment providers.

XRP Wealth Distribution and Concentration

Source: XRPScan

XRP wealth distribution shows higher top-end concentration due to its pre-mined structure and Ripple ongoing reserves. As of early April 2026, Ripple Labs controls approximately 33.3 to 34 billion XRP in programmatic escrow, representing about one-third of the total supply. Monthly unlocks of 1 billion XRP occur, with the majority typically re-locked after partial usage, resulting in a net circulating supply increase of around 200 to 300 million XRP per month.

The top 10 XRP addresses hold approximately 18.56 to 20% of the circulating supply, equivalent to roughly 11 to 12 billion XRP. The top 50 addresses control about 43 to 44%. Many of these leading wallets belong to major exchanges such as Bithumb (approximately 1.79 billion XRP), Binance (approximately 1.68 billion XRP), Uphold, and UPbit, which custody assets on behalf of millions of retail and institutional users. Ripple escrow and operational wallets also feature prominently.

For individual holders, the threshold to reach the top 10% of all XRP addresses is roughly 2,200 to 2,350 XRP. Entering the top 1% requires approximately 46,000 to 46,500 XRP, a level met by around 76,000 to 77,000 wallets. The total number of XRP addresses has grown steadily, exceeding 7.5 million, with the largest increases occurring among smaller-balance accounts. While raw address concentration appears elevated, a substantial share reflects custodial holdings and escrow rather than control by a handful of private speculators.

Wealth Distribution Comparison: XRP vs. Bitcoin (Early April 2026)

Metric	Bitcoin (BTC)	XRP
Total Supply	21 million (hard cap)	100 billion (pre-mined)
Circulating Supply	~20.01 million (~95.3%)	~66.6 billion
Top 10 Addresses (% of circulating)	~Lower individual dominance (raw addresses)	18.56 – 20%
Top 50 Addresses (% of circulating)	Not directly comparable (broader)	43 – 44%
Major Entity Concentration	Satoshi ~5.5%, Coinbase ~5%, BlackRock ~4%	Ripple escrow ~33%, Exchanges dominate top wallets
Primary Supply Mechanism	Gradual mining (decentralized)	Pre-mined + monthly escrow releases
Individual Top 1% Threshold	Significantly higher balances required	~46,323 XRP
Individual Top 10% Threshold	Much higher balances required	~2,200 – 2,350 XRP

Source: XRPSCAN, BitInfoCharts, Arkham

This table illustrates the structural differences in supply issuance and holder concentration between the two assets.

Is XRP or Bitcoin Wealth More Centralized?

A side-by-side comparison reveals structural contrasts. Bitcoin top-tier concentration sits lower, with large address groupings accounting for roughly 14% in the highest brackets, versus XRP top 10 addresses at 18.56 to 20% and top 50 at 43 to 44% of circulating supply.

Bitcoin's decentralized mining process has distributed new coins across a global network of participants over time, fostering broader ownership even as institutions accumulate. XRP's pre-mined model and Ripple's significant escrow position create inherent concentration, tempered by predictable release schedules and the custodial nature of many top exchange wallets. Bitcoin benefits from deeper institutional integration, including spot exchange-traded funds holding tens of billions in assets and corporations treating it as a treasury reserve. XRP adoption ties more closely to its utility in cross-border payments.

In summary, Bitcoin exhibits lower centralization in wealth distribution. Its fixed supply, slow issuance, and proof-of-work consensus support a more dispersed holder base over the long term. XRP, optimized for payment efficiency, carries a more centralized wealth profile stemming from its creation mechanics.

Role of Exchanges and Institutional Wallets in Bitcoin, XRP Wealth Distribution

Exchanges and institutional wallets play a major role in shaping perceived concentration for both assets. In XRP, major platforms such as Bithumb, Binance, Uphold, and UPbit dominate many of the top 10 and top 50 addresses, holding billions of XRP each on behalf of their customers. These custodial wallets represent diversified retail and institutional user bases rather than single controlling entities.

Exchanges like Coinbase and Binance, along with Bitcoin ETF issuers such as BlackRock and Fidelity, hold large aggregated amounts of Bitcoin. Corporate treasuries, including Strategy, and government-held seized coins also feature prominently. These institutional and custodial holdings increase visible concentration on rich lists but reflect broad underlying ownership rather than centralized control by a few individuals. For both assets, distinguishing between custodial pools and true whale wallets is essential when assessing decentralization.

What Centralization Means for Investors

Higher wealth concentration can influence market dynamics in meaningful ways. In more centralized assets like XRP, large holders or coordinated releases from escrow have the potential to create sudden supply pressure or coordinated selling, increasing volatility. In Bitcoin, while large entities exist, the broader distribution and slower new supply reduce the impact of any single actor.

Market manipulation risks rise with concentration, as sizable wallets could theoretically move prices through large trades, especially in lower-liquidity conditions. Liquidity impact varies as well. XRP often experiences amplified price moves from the same dollar inflow or outflow due to its smaller market capitalization relative to Bitcoin. Bitcoin generally offers deeper liquidity and more resilient order books, partly due to its wider holder base and institutional infrastructure.

Investors should view centralization not as binary but as a spectrum. Bitcoin lower relative concentration aligns with its store-of-value narrative, potentially offering greater stability. XRP higher concentration ties to its utility focus, which may deliver faster transaction benefits but introduces different risk considerations around supply events and large-holder behavior.

Conclusion

Wealth distribution data highlights Bitcoin advantage in relative decentralization, consistent with its established role as a scarce and widely adopted digital asset. XRP delivers strong utility in global payments but reflects greater top-end concentration due to its pre-mined origins and Ripple escrow management.

Investors should weigh these supply dynamics, use cases, and risk profiles when comparing the two assets. Bitcoin generally offers a more stable store-of-value proposition with broader distribution characteristics, while XRP functions as a higher-volatility utility token within the Ripple ecosystem. Both continue to draw institutional interest, influencing their paths in the maturing cryptocurrency market.

The wait is over: OpenAI Pre-IPO Token Airdrop is now live on BingX!

Complete the tasks and claim your airdrop, it´s that easy!

There are limited spots, so don´t miss your chance. Find the link in the first comment.

8 years of building.

From pioneering copy trading to 40M+ traders worldwide, to partnering with Scuderia Ferrari HP.

This is just the beginning. ∞ ahead.

To further enrich trading scenarios and meet users’ diverse trading needs, BingX has launched EventX.

The first batch supports mainstream events across politics, sports, and other major sectors, allowing users to trade around global trending events.

1. What is EventX

EventX is a new trading product from BingX that lets you trade around global hot events (politics, sports, etc.). Every event you follow can become a trading opportunity.

EventX supports both Leverage and Markets (Classic mode), allowing users to choose flexibly based on their risk preferences.

Core mechanism of event contracts: Probability equals price.

The price of an event contract reflects the market’s expected probability of the event occurring; users are effectively trading the market’s changing expectations about the event outcome.

Event probability from 0% to 100% corresponds to a price range from 0.00 to 1.00.

Higher market confidence in an outcome leads to a higher probability and price.

Lower market confidence in an outcome leads to a lower probability and price.

Prices reflect the market consensus on the likelihood of an event occurring. For example, if an event's price of "Yes" is 0.75, the market estimates a 75% chance of that outcome happening. If the event occurs, users trading "Yes" profit. If it does not occur, users trading "No" profit.

2. What are the advantages of EventX

1. World’s first leverage mode

Up to 10x leverage to amplify returns and improve capital efficiency.

2. Limited-time 0 fees

Enjoy 0 trading fees during the public beta period to reduce trading costs.

*During the public beta, EventX trading is available with 0 fees in certain regions. Actual fee rates are as displayed on the EventX product page.

3. Start with $1, low entry threshold

Open a position with as little as $1. No complex steps required, so beginners can participate quickly.

4. One-stop coverage of multiple event categories

Covering events across multiple global fields—every major event you follow is a trading opportunity.

3. What’s the difference between “Markets” and "Leverage" sections

	Markets	Leverage
Who it's for	Beginners / conservative users	Advanced traders
How trading works	Final result of the event	Trade short-term fluctuations in event probability
Leverage	No leverage	Supports leverage, up to 10X
Funding rate	No	Yes
Settlement method	Hold to expiration for auto settlement, or sell early	Close manually, or the system will automatically close your position at the auto-close time

4. How EventX works

EventX turns real-world events into tradable instruments. Each event normally has a clear outcome. You can choose “Yes” or “No” based on your judgment: if you think the event will occur, trade “Yes” (long); if you think it will not occur, trade “No” (short).

Event prices fluctuate between 0.00 and 1.00 USDT and directly correspond to the market’s expected probability of occurrence (0%–100%). For example, a price of 0.4 means the market believes there is a 40% chance the event will occur.

In the Markets section (classic mode), hold positions until settlement; the winning side receives 1.00 USDT per share, and the losing side receives 0. The leveraged mode supports up to 10× leverage for trading short-term probability swings. Both modes allow you to buy or sell to exit at any time before event settlement/auto-close, without needing to hold until final settlement/close.

EventX’s event design uses the external, established prediction market Polymarket as a reference. At event settlement, EventX will refer to Polymarket’s final result for the corresponding event and its related adjudication rules as the core basis.

Jito is a unified Solana infrastructure project built to simplify and optimize liquid staking while capturing Maximal Extractable Value (MEV) for users. It combines liquid staking with advanced MEV infrastructure to deliver higher yields and improve network performance. The project focuses on capital efficiency, transparency, and decentralization while removing the traditional trade-offs of locking up SOL.

As a core infrastructure layer on Solana, Jito empowers users to stake SOL, receive liquid JitoSOL, and earn both staking rewards and MEV income. With strong community governance through the JTO token, it aims to provide a complete staking and optimization experience for modern Solana users.

Key Takeaways

• Jito operates the dominant MEV client and liquid staking pool in Solana.
• Users stake SOL to receive JitoSOL, which earns combined staking rewards and MEV revenue.
• JTO is the governance token that allows holders to vote on protocol decisions and treasury management.
• The project significantly improves Solana network efficiency and validator decentralization.
• BingX stands as the top choice for trading JTO on the spot market, offering secure and efficient access.

What Is Jito (JTO)?

Jito (JTO) is the governance token for the Jito Network, a leading liquid staking and MEV optimization protocol built on the Solana blockchain. It allows users to stake SOL and receive JitoSOL, a liquid staking token that remains fully usable in DeFi while earning both standard staking rewards and additional MEV income. Instead of traditional staking that locks capital, Jito provides liquidity through JitoSOL, enabling users to continue participating in lending, trading, and yield farming.

What Are the Use Cases of Jito?

Users stake SOL to receive JitoSOL for liquid staking, allowing them to earn enhanced yields while using the token across DeFi protocols for lending, collateral, or trading. Validators and node operators run the Jito client to improve block efficiency and earn additional revenue from MEV.

JTO holders participate in governance by voting on critical proposals that shape the protocol's future. The ecosystem also supports advanced MEV strategies and block assembly tools that benefit the entire Solana network by increasing transparency and fairness in transaction processing.

How to Buy JTO on BingX Spot Market?

You can access JTO through the spot market and use them within their respective ecosystems.

1. Log in or Create a BingX Account
2. Deposit Funds
3. Go to the Buy Crypto section to deposit funds into your account. BingX supports several payment options such as bank transfer, credit or debit card, and peer-to-peer (P2P) transactions.
4. Find the JTO/USDT Pair: Navigate to the Spot trading section and search for JTO/USDT and select the pair to view the trading interface.
5. Use BingX AI tools to analyze JTO trends and make smarter trading decisions.
6. Place Your Order: choose between a Market Order or a Limit Order to set your preferred entry, enter the amount and confirm the order.

You can also trade JTO Futures on BingX with up to 75X leverage.

BingX is proud to announce two-time football world champion Enzo Fernández as our Global Ambassador. The partnership builds on BingX’s global sports partnership strategy following its recent partnership with Scuderia Ferrari HP and renewal with Chelsea FC, arriving at a pivotal moment ahead of the 2026 FIFA World Cup, positioning BingX to engage billions of fans worldwide on football’s greatest stage.

As one of the most exciting talents of his generation, Fernández, who plays for Chelsea FC, and represents the Argentina national team, embodies ambition, precision, and resilience. Through this collaboration, BingX aims to connect the precision and performance of elite sport and digital finance, inspiring a new generation of users to take control of their future. The partnership will unfold through global campaigns, digital experiences, and fan-focused initiatives throughout the 2026 World Cup period and beyond.

This announcement marks a significant milestone in BingX’s global expansion and evolution of our brand identity as a premium, globally recognized platform. Following our partnership with Chelsea FC in 2024 and a multi-year collaboration with Scuderia Ferrari HP in early 2026, Enzo Fernández has become the company’s first individual athlete Global Ambassador. Fernández’s journey from Buenos Aires to the pinnacle of world football mirrors BingX's own trajectory of growth, determination, and global ambition. 

“This partnership marks an important step in BingX’s growth across Latin America," said Pablo Monti, Spokesperson of BingX. “Enzo Fernández represents a rare combination of adaptability, intelligence, and control under pressure. These qualities strongly resonate with BingX and reflect the mindset behind how BingX helps users navigate fast-moving financial markets with confidence across crypto, stocks, forex, commodities, and beyond.”

 “I’m proud to join BingX as a Global Ambassador,” said Enzo Fernández. “For me, success is built in the unseen moments: the discipline, the belief, and the consistency behind every decision. That mindset is what drew me to BingX. It’s a platform known for trust and reliability, and I’m looking forward to the journey ahead and what we can build over time. Together, we want to inspire people to trust themselves, take control, and build their own path forward.”

The day is finally here: EventX is live on BingX!

What is EventX?

EventX is a new contracts feature designed to transform real-world events into tradable opportunities. EventX allows users to trade on the probability of events across a variety of categories, with zero fees for a limited time and exclusive leverage of up to 10x.

By combining intuitive market structures with flexible trading mechanisms, EventX expands on BingX’s multi-market ecosystem, enabling users to turn their convictions into actionable trades through a streamlined and accessible experience:

• Flexible Dual Trading Mode: Choose Classic Mode for simple event trading, or switch to Leverage Mode for 10X amplified outcomes.
• Limited-Time Zero Fee: Competitive fees and integrated VIP tiers reduce trading costs and support more efficient trading.
• Diversified Global Events: Trade on major global events across politics, sports, entertainment, economics, crypto, and more.
• Simple Market Structure: Each market is built on Yes/No outcomes, making participation straightforward and easy to understand.

Want to be among the first to try this new feature? Find the link to join in the first comment.

As the digital asset industry matures, traders are no longer evaluating exchanges based solely on token listings or leverage levels. Platform stability, product depth, execution quality, risk management, AI capabilities, and multi-market access have become defining factors in determining long-term trust.

Against this backdrop, BingX has continued expanding its futures ecosystem with a focus on improving the overall trading experience while broadening access across both crypto and traditional financial markets, supported by a growing derivatives infrastructure that combines perpetual futures, standard futures, AI-powered trading tools, and TradFi market access.

A Comprehensive Futures Ecosystem

BingX offers both perpetual futures and standard futures, giving traders flexibility across different market strategies and risk preferences.

 The platform also supports a broad range of trading markets beyond crypto, including:

• Crypto assets
• Commodities
• Foreign exchange (FX)
• Stocks
• Additional TradFi-linked products

Through BingX TradFi, users can access more than 100 tradable assets with up to 500x leverage and 24/7 trading availability for select markets.

BingX also features a deep integration with TradingView, enabling advanced charting and strategy execution directly within the platform, while copy trading functionality provides users with additional ways to participate in futures markets.

Futures Trading 2.0: Upgrading the Trading Experience

In March 2026, BingX introduced Futures Trading 2.0, a major upgrade designed to improve the futures trading experience across execution, charting, and risk management.

 The upgrade focuses on three core areas:

 Seamless Order Placement

• Streamlined trading interface
• Simplified margin and position settings
• Unified order entry points
• Faster position management tools including Lightning Close

 Enhanced Market Charts

• Improved candlestick chart performance
• Expanded technical indicators and drawing tools
• New Liquidation Line functionality
• Greater transparency for order book and pricing data

Redesigned TP/SL Tools

• Simplified take-profit and stop-loss configuration
• Trigger settings based on price movement percentages
• Profit- and loss-level trigger functionality
• More intuitive risk management workflows

BingX AI: AI-Native Trading Infrastructure

As part of its vision to become the first AI-native crypto exchange, BingX has developed a growing suite of AI-powered trading tools designed to help users analyze markets, discover strategies, manage positions, and improve trading decision-making:  

• BingX AI Bingo: An AI-powered trading assistant that provides personalized market insights, trend analysis, position guidance, and trader-focused recommendations.
• BingX AI Master: An AI trading strategist powered by more than 1,000 strategies from top investors, helping users discover, select, and optimize trading strategies.
• BingX AI Skills Hub: AI-native infrastructure that enables AI agents to interact with futures trading, spot trading, and account management functions through natural language workflows.
• BingX AI Claw: A real-time AI market intelligence system that generates explainable trading signals based on technical indicators, sentiment analysis, news developments, and capital flows.

Together, these tools are designed to make futures trading more accessible while helping users navigate increasingly complex market conditions with greater efficiency and confidence.

With Futures Trading 2.0 and its expanding BingX AI ecosystem, BingX is positioning itself as a more intelligent and integrated trading platform for the next phase of digital finance.

BingX is pleased to announce that EventX will officially launch on May 12th, 2026!

What is EventX?

Trade more than just coin prices: Major events happening around the world are now your trading targets.

🌍 Geopolitics
Where is the Middle East headed next?

🏆 Sports
Who will win the 2026 World Cup?

🏛️ Macroeconomy
Will the Fed cut rates in June?

₿ Crypto Market
Can BTC break $200,000 by year-end?

💻 Tech Companies
Will the next IPO open below its offering price?

Subscribe early and get up to $50 as a launch reward! Link in the first comment!

Implied Volatility (IV) is one of the most powerful — and overlooked — tools in crypto trading. Most traders focus only on price, but IV tells you something different: how big a move the market expects next.

It doesn’t predict direction. It predicts magnitude.
And that’s where the edge is.

What Is Implied Volatility (IV)?

Implied Volatility = the market’s expectation of future price movement, derived from options pricing.

• High IV → big moves expected (fear / uncertainty)
• Low IV → small moves expected (calm / complacency)

Think of IV like an insurance premium:
When risk is high, protection gets expensive.

IV vs Historical Volatility (HV)

• IV = future expectations
• HV = past price movement

Key insight:

• IV > HV → options expensive → selling premium favored
• IV < HV → options cheap → buying premium favored

In crypto, this difference (Volatility Risk Premium) has historically benefited sellers.

How to Read IV Levels (Quick Guide)

IV is annualized, but here’s what it really means:

• ~40% IV → calm market (~2% daily moves)
• ~60% IV → normal volatility
• ~80%+ IV → fear / large swings

Important: IV does NOT tell you direction — only how big the move might be.

Don’t Use Raw IV — Use These Instead

IV Rank (IVR) → where current IV sits vs last year
IV Percentile (IVP) → how often IV was lower than now

Quick rules:

• IVR < 20 → low → options cheap
• IVR > 60–80 → high → options expensive

What Is IV Crush (And Why It Wrecks Beginners)?

Before big events (Fed, ETF approvals, halving):
→ IV rises (uncertainty)

After the event:
→ IV collapses (certainty)

Result:
Even if price moves your way, your trade can lose money.

This is why experienced traders often sell options before events, not buy them.

DVOL = Crypto’s “Fear Index” (Like VIX)

• <40 → calm market
• 40–60 → normal
• 60–80 → elevated volatility
• 80+ → panic / large moves

Volatility Skew (Hidden Sentiment Signal)

• Put skew (common): downside protection expensive → bearish sentiment
• Call skew (rare): upside demand → bullish sentiment

How to Actually Use IV (Even If You Don’t Trade Options)

High IV (Fear / Chaos)

• Options: sell premium
• Spot: look for capitulation bottoms
• Futures: reduce leverage, widen stops

Low IV (Calm / Complacency)

• Options: buy premium
• Spot: accumulation phase
• Futures: range trading → expect breakout soon

Practical Trading Signals

• IV spike + price drop → potential bottom
• Low IV + sideways price → breakout incoming
• IVR > 80 → reduce leverage
• Persistent put skew → institutions hedging

Common Mistakes

• Thinking IV predicts direction (it doesn’t)
• Buying options when IV is high (overpaying)
• Using DVOL as a price signal
• Ignoring IV in futures trading

Bottom Line

IV tells you when the market is:

• Scared (high IV) → expect volatility
• Complacent (low IV) → expect expansion

Use it to:

• Manage risk
• Adjust leverage
• Anticipate big moves

Not to predict direction.

Most traders ignore IV. Use it to your advantage!

Mexico, we're pulling up!

BingX 8th Anniversary Meetup is happening. KOL talks. Parties. Networking.

Come through, meet the community and tap in IRL!

Tesla’s revenue for Q1 2026 rose 16% year-over-year to $22.4 billion, with gross margin climbing to 21.1%, a recent high. The key takeaway from this earnings report is the underlying shift in Tesla’s profit structure: hardware is becoming more profitable, software is scaling faster, and previously conceptual businesses are starting to generate real revenue.

1. Overall Financials: Profit Quality Matters More Than Revenue Growth

Gross margin reached 21.1%, up 478 basis points year-over-year, marking a strong rebound after several quarters of price cuts. Operating profit jumped 136% to $940 million. While operating expenses also grew (+37%), improvements in revenue quality outpaced cost increases. Free cash flow came in at $1.44 billion (+117% YoY), cash reserves rose to $44.7 billion, and recourse debt remained minimal at just $20 million—indicating a very strong financial position.

Revenue increased 16% year-over-year, driven by higher vehicle deliveries, growth in FSD subscriptions, and a favorable foreign exchange impact (around $0.9 billion).

Operating profit surged 136%, with automotive gross margin hitting a new high of 21.1%, reflecting effective cost control.

GAAP net income was relatively low at $477 million, with a $976 million gap versus non-GAAP figures, largely due to $1.03 billion in SBC (including CEO compensation) and losses on digital assets.

Operating expenses rose 37% to $3.78 billion, mainly driven by AI-related R&D and SBC.

2. Three Major Segments: One Cooling, One Stable, One Surging

 Automotive Key Takeaways: (73% of total revenue)

• Revenue reached $16.2 billion with 358,000 vehicles delivered. While overall growth appears steady, the internal structure is evolving. FSD subscribers surpassed 1.28 million (+51% YoY), and the business has fully transitioned to a subscription model.
• Software is becoming an increasingly important contributor to margins.
• Automotive gross margin (excluding credits) rose to 19.2%, up 670 basis points year-over-year, supported by lower material costs, higher average selling prices, and additional FSD revenue.
• Global expansion of Model Y and Model 3 continues, with the new Model YL launching in markets outside China.
• Delivery growth slowed to 6% year-over-year and declined 14.4% quarter-over-quarter. Production exceeded sales, leading to higher inventory levels.
• A declining share of carbon credit revenue is a positive sign, indicating stronger core profitability.

Energy Key Takeaways (the weakest segment this quarter):

• Revenue came in at $2.4 billion, down 12% year-over-year, with energy storage deployments of 8.8 GWh also declining sequentially. The main issue is supply constraints, as the Megapack 3 factory is still under construction.
• Seasonal factors contributed to the decline, but this remains within a normal range of fluctuation.
• The new Megapack 3 facility in Houston is expected to begin production this year, while Shanghai capacity expansion continues, supporting strong long-term growth.
• Tesla’s in-house solar panels have also started to see meaningful deployment, featuring a design with 18 independent power zones.

 Services & Others Key Takeaways (the standout segment):

• Revenue reached $3.7 billion, up 42% year-over-year, making it the fastest-growing segment and now the second-largest revenue source, surpassing energy.
• Growth is being driven by Tesla Insurance, maintenance services, and Robotaxi mileage revenue.
• The shift to a subscription-based FSD model is increasing both penetration and attach rates. The Safety Score 100 system is also lowering insurance costs, creating a reinforcing feedback loop.
• Robotaxi launched driverless operations in Dallas and Houston in April and is expanding quickly.
• FSD (supervised driving) has been approved in the Netherlands, opening the door to broader EU expansion.

3. Strategic Progress: Four Key Areas Showing Real Advancement

Robotaxi: This remains the most visible breakthrough. Commercial driverless operations began in Dallas and Houston in April, with paid mileage nearly doubling quarter-over-quarter. Expansion plans are underway in Phoenix, Miami, and Las Vegas. Cybercab has started pilot production in Texas and is expected to gradually replace Model Y as the core fleet vehicle.

Optimus (humanoid robot): Construction of a million-unit factory is about to begin, marking a transition from lab development to large-scale commercialization. The Fremont first-generation line is designed for 1 million units per year, while the long-term target for the Texas second-generation line is 10 million units annually. These targets are ambitious, but recent construction progress suggests they are moving beyond concept.

AI chips and vertical integration: This may be the most underappreciated area of progress. Tesla continues to strengthen its full-stack AI capabilities, with training compute doubling and in-house inference chips advancing to tape-out. The Cortex 2 supercomputing cluster is now online, with combined capacity exceeding 230,000 H100-equivalent GPUs. The AI5 inference chip has completed tape-out, and a semiconductor joint venture with SpaceX is under construction, aiming for full integration across logic, memory, and advanced packaging. If successful, Tesla could establish a significant cost advantage in AI inference.

Battery and materials: Tesla is continuing to vertically integrate its entire battery supply chain—from lithium refining to cathode materials to LFP and 4680 cells. Battery pack capacity remains the main bottleneck for scaling vehicle production. Meanwhile, the charging network grew 19% year-over-year to 79,918 chargers, with V4 chargers offering three times the power density.

4. Risks: Four Key Concerns

Inventory days rose to 27, up from 22 a year ago. If inventory is not reduced in Q2, pricing pressure could return.

Energy revenue declined year-over-year, and any further delays in Megapack 3 production could weigh on full-year performance.

Operating expenses increased 37%, with AI investment and CEO equity compensation likely to continue pressuring margins in the near term.

Management also highlighted trade policy and geopolitical uncertainty, with supply chain regionalization requiring substantial capital investment.

5. Bull vs. Bear Factors

Bullish:

• Automotive gross margin reached 21.1% (19.2% excluding credits), showing a meaningful improvement in profitability.
• FSD subscribers exceeded 1.28 million (+51%), and the subscription model supports recurring revenue growth.
• Robotaxi paid mileage doubled quarter-over-quarter, with expansion accelerating.
• Full vertical integration across batteries, chips, and AI enhances supply chain resilience.
• Services revenue grew 42% and is now the second-largest segment, improving the overall profit mix.
• Strong liquidity, with $44.7 billion in cash and minimal recourse debt, provides ample flexibility.

Bearish:

• Delivery growth slowed to 6% year-over-year and declined 14.4% sequentially, with inventory days rising to 27.
• GAAP net income was only $477 million, weighed down by $1.03 billion in SBC and digital asset losses.
• Operating expenses rose 37%, driven by AI R&D and CEO compensation.
• Energy segment revenue declined 12% year-over-year due to seasonal factors.
• Battery pack capacity remains a key constraint on production scaling.
• Significant capital expenditures across multiple initiatives: Cybercab, Semi, Optimus, chip manufacturing, and battery plants, are progressing simultaneously, increasing financial pressure.

The latest earnings cycle from Meta Platforms, Microsoft, Amazon, and Apple revealed a clear shift in market psychology.  

Revenue growth remained strong across the board. AI adoption accelerated. Cloud demand stayed resilient. Yet stock reactions showed that investors are increasingly focused on a different question: How quickly can massive AI infrastructure spending translate into durable returns? 

Across the hyperscalers, the debate has moved from “who is winning AI” to “who can monetize AI efficiently enough to justify unprecedented capital expenditure.” 

Meta: Advertising Strength vs. Escalating AI Spending

Meta Platforms delivered one of the strongest top-line performances of the quarter. 

Revenue reached approximately $55.5 billion, up 33% year-over-year, marking the company’s fastest growth rate since 2021. The advertising business remained the core engine, with AI-driven targeting improvements translating directly into higher advertiser ROI.  

The company also highlighted several AI milestones:

• AI glasses daily active users tripled year-over-year
• The Muse Spark model entered internal AI model competition efforts
• The Llama ecosystem continued expanding alongside advertising optimization tools

 

Meta’s earnings reinforced the idea that advertising remains one of the clearest commercialization pathways for AI. The company’s AI flywheel is already measurable:

AI targeting improvements → better advertiser ROI → stronger ad demand → higher revenue growth.

However, the market reaction showed that investors are no longer rewarding growth alone.

Meta raised 2026 capital expenditure guidance to $115 billion–$135 billion, nearly double 2025 levels. Reality Labs is still expected to lose roughly $4.77 billion per quarter, while the company simultaneously implemented 8,000 layoffs and 6,000 hiring freezes.  

The contradiction became difficult for investors to ignore:

• AI infrastructure spending is accelerating aggressively
• Cost-cutting measures remain widespread
• Long-term AI monetization outside advertising is still unclear

After-hours trading reflected those concerns, with shares falling roughly 5%–6.8%.

The core issue was not revenue quality. It was uncertainty around the return timeline for AI investment. 

Meta’s bullish case remains straightforward:

• No “sell” ratings among 42 analysts
• Advertising monetization is already validated
• Llama’s open-source ecosystem may strengthen competitive positioning

 

The bearish argument is equally direct:

• Capital efficiency remains unproven
• AI spending may continue rising into 2027
• Business AI monetization is still largely undeveloped

Mark Zuckerberg acknowledged during the earnings call that Business AI remains free for most enterprises today. That admission underscored the company’s largest long-term risk: monetization at scale has not yet been fully established. 

Microsoft: Strong AI Commercialization, Higher Expectations

Microsoft delivered what was arguably the clearest evidence of enterprise AI monetization so far.

Revenue reached $82.9 billion, up 18% year-over-year, while EPS came in at $4.27 versus expectations of $4.06. 

The standout metric was Azure growth:

• Azure revenue grew 40%
• Currency-adjusted growth reached 39%
• AI annualized revenue surpassed $37 billion, up 123% year-over-year

 

Microsoft also reported:

• Microsoft Cloud revenue of $54.5 billion, up 29%
• More than 20 million paid Microsoft 365 Copilot users
• Copilot seat growth accelerating for a fourth consecutive quarter

 

From a monetization perspective, Microsoft currently has the strongest visibility among large-cap AI companies. 

Its model combines:

• AI subscriptions through Copilot
• AI infrastructure consumption through Azure

 

That dual-engine approach gives Microsoft a more direct path to measurable AI revenue than most peers.

Yet the market response remained restrained.

The problem was not weak performance. The problem was that expectations had already moved higher.

Azure’s 39% constant-currency growth exceeded expectations of 38% by only one percentage point. Guidance for next quarter pointed to similar growth levels rather than further acceleration.  

At the same time:

• Cloud infrastructure costs rose 47% year-over-year
• Margins faced pressure from AI expansion
• Questions emerged around future Copilot pricing models

 

Investors are now debating whether Azure’s 40% growth represents:

• A durable new baseline
• Or the early stages of a growth plateau

 

Bulls point to the scale opportunity:

• AI revenue is still less than 15% of total company revenue
• Enterprise AI penetration remains early
• Microsoft continues expanding across infrastructure, software, and models

 

Bears focus on different risks:

• Pricing pressure from open-source models
• Potential saturation in Copilot seat growth
• Margin compression from rising compute costs

 

Strategically, Microsoft continues building across multiple layers of the AI stack, including:

• A $5 billion partnership with Anthropic
• Intel 18A foundry participation
• Expansion of proprietary AI infrastructure

 

That breadth may ultimately prove to be Microsoft’s biggest long-term advantage. 

Amazon: AWS Re-Acceleration Changes the Narrative

Amazon delivered one of the quarter’s most important cloud datapoints.

Total revenue reached $181.5 billion, up 16.6% year-over-year and ahead of expectations.

More importantly, AWS revenue grew 28% year-over-year: the fastest pace in 15 quarters.

That single metric directly challenged concerns that AWS was entering a prolonged slowdown phase. 

Amazon also reported:

• Advertising revenue of $17.24 billion
• Next-quarter revenue guidance of $196.5 billion
• Guidance approximately 4% above analyst expectations

 

The earnings strengthened the argument that AWS remains central to enterprise AI infrastructure demand.

However, investors quickly focused on earnings quality.

Quarterly net profit included $16.8 billion in pre-tax gains tied to Amazon’s Anthropic investment. Excluding that one-time contribution, operating profit growth may have appeared significantly weaker. 

At the same time:

• 2026 capital expenditure is expected to reach $125 billion
• Amazon continues aggressively expanding AI infrastructure
• The company announced a $25 billion Mississippi data center investment
• AWS expansion costs remain extremely high

 

The market reaction reflected a distinction investors increasingly care about:

Real operating leverage versus temporary accounting gains.

The broader investment debate around Amazon centers on whether AWS can maintain rapid growth while preserving margins.

S&P Global revised AWS margin expectations to 35.7%, down from 37.7% previously. 

The concern is straightforward:

Can Amazon sustain aggressive AI expansion without structurally sacrificing profitability?

Supporters argue that AWS’s 28% growth erased fears of an “IBM-style” cloud slowdown and restored confidence in long-term demand.

Skeptics focus on capital intensity and the sustainability of margins if infrastructure spending continues rising.

Andy Jassy continues emphasizing long-term AI investment discipline, but investor patience appears increasingly finite. 

Apple: AI Expectations Meet a Transition Period

Apple had not yet released Q2 FY2026 results at the time of data collection, but expectations remained elevated. 

Consensus estimates pointed toward:

• Revenue of approximately $112.7 billion
• EPS around $2.05

 

The market’s focus remains concentrated on three areas:

• iPhone demand
• Services growth
• Apple’s AI strategy

 

In the prior quarter, Apple reported:

• Revenue of $143.8 billion
• iPhone growth of 23%
• Services revenue reaching $30 billion

 

China played a significant role in recent iPhone momentum, and investors are watching closely to determine whether that strength can continue.

Services remain Apple’s most important profit engine.

The business: including the App Store, Apple Music, iCloud, and Apple Pay, operates with a gross margin of 76.5%, making continued services expansion critical for EPS growth.

Apple’s AI positioning differs substantially from peers. 

Rather than emphasizing standalone AI products, the company is integrating AI capabilities directly into the ecosystem through:

• Siri enhancements
• AI photo tools
• iOS 27 features

 

That approach may appear less aggressive than competitors, but potentially more monetizable if it drives device upgrades and services engagement. 

Still, several major uncertainties remain:

• CEO transition from Tim Cook to John Ternus
• Legal pressure on App Store commission structures
• Questions about whether Apple is lagging in AI investment
• Ongoing geopolitical risk tied to China exposure

 

The Epic litigation represents one of the most important long-term valuation risks. If App Store monetization rules change materially, the services business could face structural pressure.

Despite those concerns, some institutional forecasts remain optimistic, including projections for continued EPS acceleration supported by services expansion and hardware upgrade cycles.

The Bigger Theme: AI Spending Has Become the Main Story

Across all four companies, one conclusion stands out:

The market is no longer rewarding AI ambition by default. 

Investors are increasingly evaluating:

• AI monetization visibility
• Capital efficiency
• Margin durability
• Payback periods

 

Microsoft currently leads in measurable AI monetization through Azure and Copilot.

Meta has the clearest AI advertising commercialization.

Amazon is leveraging AWS infrastructure demand to re-accelerate cloud growth.

Apple is pursuing ecosystem-driven AI monetization with lower visible infrastructure spending. 

At the same time, AI capital expenditure levels are reaching historic scale:

• Meta: $115 billion–$135 billion
• Amazon: $125 billion
• Microsoft: roughly $144 billion annualized based on quarterly spending trends

 

The industry-wide debate is shifting toward a harder financial question:

How long can hyperscalers sustain enormous AI investment before investors demand stronger free cash flow conversion?

For now, revenue growth remains strong enough to support the narrative.

But this earnings season showed that markets are becoming significantly less tolerant of “spend first, monetize later.”

BingX has also launched its Trade the World campaign, designed to expand user access to global markets through its growing TradFi suite. The initiative brings together multi-asset trading and reward-driven engagement, enabling users to participate in opportunities across equities, indices, and commodities within a unified platform.

Pharos (PROS) is a next-generation, high-performance Layer-1 blockchain built specifically for RealFi, combining real-world assets (RWAs) and institutional finance with on-chain efficiency. Developed by former Ant Group leadership, it aims to fix liquidity fragmentation by turning assets like real estate, commodities, and energy into programmable, tradable on-chain instruments.

Launched on April 28, 2026 with its Pacific Mainnet and $PROS token, Pharos delivers 30,000+ TPS, sub-second finality, and 2 Gigagas/sec throughput, positioning itself as a fast, scalable settlement layer for global finance and AI-driven economies.

Key Highlights

• RealFi-native design: Built from the ground up for institutional RWAs, not retrofitted like typical L1s
• Sub-second settlement: Eliminates slow TradFi T+2 delays
• Built-in compliance: zk-KYC + programmable AML at protocol level
• Massive scalability: Modular SPN architecture supporting up to 1B users
• Agentic Web ready: Enables AI agents to transact via the x402 payment protocol

How It Works

Pharos uses a 3-layer modular stack:

• L1-Base: Data + hardware acceleration
• L1-Core: AsyncBFT execution (30k+ TPS)
• L1-Extension: SPNs (custom app-specific chains for finance, AI, trading, etc.)

$PROS Token Utility

• Gas fees
• Staking (PoS security)
• Governance
• Collateral + access to RWA vaults

Tokenomics (1B supply)

• 21% ecosystem/community (incl. airdrops)
• 40% team + investors (vested)
• 25% foundation
• 14% incentives
• 0% inflation first 6 months → 5% annually after

Why It Stands Out

Compared to Ethereum/Solana-style L1s, Pharos is institution-first, with native compliance and modular infrastructure designed for real-world financial systems—not just DeFi/NFTs.

Risks to Consider

• Very early mainnet stage (high volatility)
• Depends heavily on institutional adoption
• Regulatory pressure likely
• Strong competition in RWA sector
• Low circulating supply initially

Bottom Line

Pharos is a focused bet on RealFi + RWA tokenization, combining speed, compliance, and scalability into a “digital financial city.” Its success will depend on real institutional usage and growth of its ecosystem—especially in AI-driven and cross-border finance use cases.

As digital finance becomes more accessible, scams are becoming more convincing. Many no longer rely on obvious warning signs or poor execution. Instead, they use pressure, fake credibility, and increasingly sophisticated impersonation tactics to make suspicious offers look legitimate.

According to BingX Academy, users are often exposed to the same core manipulation patterns, repackaged in more polished forms. Recognizing those patterns early can make a major difference.

 1. Artificial urgency

One of the clearest red flags is pressure to act immediately.

Scammers often create a false sense of urgency to prevent users from slowing down and checking the facts. It may come in the form of a limited-time offer, an “account issue” that supposedly needs instant action, or a last-minute opportunity that disappears if no immediate deposit or click is made.

The tactic is simple: reduce time, increase pressure. The moment a message tries to force speed into a financial decision, caution should go up.

 2. Guaranteed returns or oversized bonus offers

Another common red flag is a promise that sounds unusually generous or unusually certain.

Sometimes it appears as a claim that an investment will generate guaranteed returns. Other times it comes packaged as a marketing hook, such as a 100% bonus on deposit, an exclusive reward for immediate action, or a “risk-free” way to multiply funds quickly.

Different formats, same objective: trigger excitement before the person takes time to think critically.

In digital finance, any claim built around certainty, no downside, or outsized rewards deserves extra scrutiny. If the message sounds too easy, too profitable, or too good to be true, it probably is.

3. Identities that look real, but do not hold up under verification

Scams no longer need to look suspicious to be dangerous. In the age of AI-generated content and deepfakes, fake credibility can look surprisingly polished.

A fraudulent message may appear to come from a known brand, a support representative, a founder, or even a public figure. Profile pictures, names, and communication styles can all be imitated. Video content and livestreams can make impersonation even more convincing.

That is why identity verification now needs to be more rigorous than before. It is no longer enough for something to look professional or familiar. If a message, account, or person cannot be confirmed through official channels, users should not assume it is genuine.

4. Requests for passwords, codes, seed phrases, or rushed transfers

Few signals are more serious than an unexpected request for sensitive information or immediate fund movement.

This can include passwords, one-time verification codes, wallet credentials, recovery phrases, or instructions to transfer funds quickly for “verification,” “security,” or “activation” purposes. In many cases, the first request seems small. The real damage begins once access has been shared or funds have already moved.

Sensitive account information should never be treated casually, especially under pressure. If a request feels invasive, rushed, or difficult to verify, the safest move is to stop immediately and reassess.

5. Fake apps, phishing links, and lookalike websites

Not every scam starts with a person. Some start with a link that looks almost right.

Fraudsters often create fake websites, app download pages, or login screens that imitate legitimate brands closely enough to fool users who are moving too fast. A slightly altered domain name, an unofficial app link shared in a message, or a cloned interface can all be enough to capture passwords, codes, or other sensitive data.

That is what makes phishing so effective: the trap often looks familiar until users inspect it closely. If an app is being promoted through a non-official source, or a website address does not exactly match the original domain, users should assume there is risk and verify before continuing.

How can users better protect themselves?

While scam tactics are becoming more sophisticated, the core protection habits remain straightforward.

Users can reduce risk by double-checking domains carefully and using only official websites. Apps should be downloaded only from official sources, not through direct links shared in private messages or suspicious pages. Passwords, verification codes, seed phrases, and sensitive account details should never be shared.

It is also increasingly important to verify identities more carefully. Profile photos, screenshots, or even livestream videos are no longer enough. Users should be especially cautious with livestreams or video meets that appear to feature public figures, founders, or company representatives. As deepfake content becomes more convincing, it is worth checking whether the same message appears on official channels before taking any action.

And just as importantly, users should treat urgency, guaranteed returns, and oversized bonus offers with skepticism. In digital finance, slowing down is often one of the strongest forms of protection. 

Conclusion

Most scams in digital finance do not begin with advanced technical tricks. They begin with pressure, imitation, and misplaced trust.

That is why awareness still matters. When a message pushes urgency, promises certainty, hides behind unverified identity, asks for sensitive information, or directs users toward suspicious links and apps, those signs should not be ignored.

In an environment where scams are becoming more polished, judgment remains one of the most important defenses users have.

Crypto is no longer moving on its own—this week it traded like an extension of big tech. Bitcoin and Ethereum rode the same wave of AI optimism and liquidity, while lingering concerns around rates and geopolitics kept volatility alive. The “up-only” phase is fading, replaced by a more macro-driven market.

BITCOIN ENTERS A DIGESTION PHASE
BTC is still strong, but momentum has cooled. ETF inflows are providing steady demand, while leverage is unwinding. The result is choppier price action: dips get bought, rallies get sold, and the market starts to settle into a range.

ETHEREUM LAGS, BUT ITS ROLE HOLDS
Ethereum continues to follow Bitcoin, but without the same strength. Institutions still prefer BTC for exposure, leaving ETH as a higher-beta trade for now. Underneath, though, it remains the core infrastructure powering DeFi, stablecoins, and on-chain activity.

DEFI COOLS, ADOPTION CONTINUES
On-chain data shows a more cautious tone. Leverage is coming down as traders reduce risk, but stablecoin usage and DeFi adoption keep growing. It’s a classic late-rally shift: less speculation, more foundation building.

CRYPTO BECOMES A MACRO ASSET CLASS
The bigger shift is structural. Bitcoin is acting like a macro proxy for risk, while Ethereum and DeFi resemble a higher-growth financial layer. With banks and fintechs integrating stablecoins and tokenization, crypto is increasingly tied to the same forces driving traditional markets.

WHAT COMES NEXT?
The most likely path is consolidation, with markets moving sideways as leverage resets. A bullish breakout would need strong macro support and fresh inflows, while any shock could trigger a sharper pullback—especially in higher-beta assets.

So the real question is: are we just pausing before the next leg up, or already setting the stage for a deeper reset?

The Kelp DAO Hack isn’t just another “smart contract exploit.” It’s something deeper—and honestly more worrying.

Here’s the full breakdown:

🧠 What is Kelp DAO

Kelp DAO (under KernelDAO) is a liquid restaking protocol that issues rsETH — basically a token representing restaked ETH.

You can:
• Earn staking + EigenLayer rewards
• Still use that same capital across DeFi

Sounds great… until this happened.

💥 The Hack (April 18, 2026)

At ~17:35 UTC, an attacker drained:

👉 116,500 rsETH (~$292M)
👉 ~18% of total supply

⚙️ How the attack actually worked (this is the scary part)

This was NOT a smart contract bug.

Instead:

• Kelp used a 1-of-1 verifier setup with LayerZero (basically one node validating cross-chain messages)
• Attacker compromised RPC nodes
• Injected a fake cross-chain message
• Launched a DDoS to force the system to trust the malicious node
• Result: minted unbacked rsETH out of thin air

Then it gets worse…

👉 They used ~90k rsETH as collateral on lending platforms (like Aave)
👉 Borrowed $190M–$236M in real assets (ETH, WETH, etc.)

So they didn’t just steal—they turned fake collateral into real money.

🧑‍💻 Who did it?

Widely attributed to North Korea’s Lazarus Group.

LayerZero even publicly blamed Kelp’s risky configuration.

🧨 Immediate Fallout (April 18–20)

• Kelp paused contracts within ~46 minutes
• Aave & others froze rsETH markets
• Estimated Aave bad debt: $124M–$230M
• DeFi panic: $13B–$20B TVL withdrawn
• AAVE token dropped ~10%

This spread FAST across the ecosystem.

🔄 What’s happened since (April 21–24)

💸 Funds & recovery

• Attacker already laundered ~$175M ETH
• But: ~30,766 ETH (~$71M) frozen by Arbitrum via emergency action
• Funds sitting in a recovery wallet (awaiting DAO vote)

🏦 Aave situation

• Liquidity stress, some markets reopened
• Worst-case estimate: ~100k ETH bad debt
• Ongoing governance debates on how to handle it

🤝 “DeFi United” bailout effort

Yes—DeFi is literally coordinating a rescue.

So far:

• Arbitrum: 30.7k ETH (frozen funds)
• Ether.fi: 5k ETH
• Lido: 2.5k stETH
• Stani (Aave founder): 5k ETH personally
• Mantle: proposed 30k ETH loan
• Plus LayerZero, Ethena, Kraken, others

📊 Result:
• ~50% of losses covered (worst-case scenario)
• Potentially 100% covered if losses are socialized across all rsETH holders

⚠️ Why this hack is different

This is the key takeaway:

👉 Everything on-chain looked valid
👉 The system was tricked using fake off-chain data

Meaning:

Even “secure” smart contracts can be drained if the infrastructure feeding them lies.

🧩 Current status (April 24)

• ✅ Hack stopped
• ✅ ~$71M frozen
• ❌ Majority of funds gone / being laundered
• ⚠️ ~100k ETH potential bad debt (Aave worst case)
• 🤝 Partial bailout underway

🧠 Final thought

This might be the most important DeFi exploit of 2026—not because of size alone, but because it exposed a new attack surface:

>

And DeFi is way more interconnected than people realized.

Curious what you think:

👉 Should losses be socialized across all rsETH holders?
👉 Or should protocols like Aave eat the loss?

This debate is just getting started.

8 → ∞ #BingXInfin8

Strong Q1 for BingX!

AI adoption just crossed 5M users, TradFi hit 50% of trading volume, and the ecosystem keeps expanding fast.

Let´s explore the highlights 👇