Capital B raised $17.8 million from investors, including Adam Back and TOBAM, saying proceeds could help add 182 BTC to its treasury.

Crypto.com says a new UAE Stored Value Facilities license will let residents pay Dubai government fees in crypto, as the company doubles down on regulated expansion in the Middle East and beyond.

Jio's IPO could significantly impact blockchain adoption, potentially boosting Polygon and Aptos through increased on-chain activity.

The post Reliance Industries plans all-new share offering in Jio Platforms IPO worth up to $4.3 billion appeared first on Crypto Briefing.

Teradyne's growth in AI chip testing could reshape tech markets, impacting GPU availability and potentially squeezing crypto mining operations.

The post Teradyne sees growth potential from AI networking and GPU expansion appeared first on Crypto Briefing.

Michael Saylor defended Strategy’s Bitcoin-backed credit model after critics argued that the company’s STRC dividend structure resembled a Ponzi scheme, saying the business is built around monetizing Bitcoin capital gains rather than relying on perpetual equity issuance.

Speaking in an interview shared via X on May 9, Saylor addressed the market reaction to Strategy’s recent earnings call, where the company said it was prepared to sell Bitcoin, if needed, to fund dividends on its STRC preferred instrument. The remark drew attention because Saylor has long been associated with the phrase “never sell your Bitcoin.”

According to Saylor, the more precise formulation is that Strategy does not intend to be a “net seller” of Bitcoin.

“I’m very famous for saying, never sell your Bitcoin. And that’s why the internet went crazy when we said we might sell it,” Saylor said. “But if I was being more precise, I’d say never be a net seller of Bitcoin. It just wouldn’t have been so viral or so catchy to say never be a net seller of Bitcoin.”

Why Strategy Is Not A Bitcoin Ponzi Scheme

The issue became a point of contention after Peter Schiff and other critics suggested that Strategy’s willingness to sell Bitcoin to support STRC dividends exposed weakness in the model. Saylor rejected that framing, saying the company’s balance sheet should not be treated as if its Bitcoin holdings were unusable or worth zero.

“If you had $65 billion worth of something and people wanted to value it at zero, it’s not very good,” he said. “We don’t want the credit rating agencies to think the company has $0 of assets. We want the credit rating agencies to think we have $65 billion of assets.”

Saylor said the core model is straightforward: Strategy issues credit, uses the proceeds to buy Bitcoin, and expects the asset’s long-term appreciation to exceed the cost of the dividend. He compared the structure to a real estate development company raising capital through credit, acquiring land, improving it, and later monetizing the appreciation through sales, rent, or refinancing.

“What we wanna do is we wanna reinforce the business model is we sell credit to make a capital investment in an asset, Bitcoin, digital capital,” Saylor said. “The capital investment accretes over time faster than the dividend. We then monetize the capital gain and we pay the dividend.”

That distinction is central to Saylor’s response to Ponzi allegations. In his view, critics conflate selling common equity to fund dividends with the broader economic structure of the business. He said Strategy historically used MSTR equity, which he described as a derivative of Bitcoin that typically trades at a premium to Bitcoin, to fund dividends. But the company now wants the market to understand it could also use appreciated Bitcoin directly.

Saylor said that does not mean Strategy expects to shrink its Bitcoin position. He argued that even if the company sold Bitcoin for dividend payments, its credit issuance would allow it to buy substantially more Bitcoin than it sells.

“If we sell Stretch, if we issue Stretch credit equal to 2.3% of our Bitcoin holdings, then that means we will be a net buyer of Bitcoin forever, even if we sell Bitcoin to pay the dividend,” he said. “Another point is that if Bitcoin appreciates 2.3% a year, we can pay the dividends forever, right? And continue to grow value, right? And we can do it without selling any common equity.”

He added that Strategy sold $3.2 billion of STRC in April, while the monthly dividend requirement was roughly $80 million to $90 million. In that scenario, he said, the company would effectively be “buying 30 Bitcoin and selling one Bitcoin,” leaving it a net accumulator.

The interview also directly addressed Schiff’s criticism. Saylor said Schiff’s objection begins with a rejection of BTC itself, making it unlikely that he would accept a credit instrument built on top of it.

“Peter thinks Bitcoin’s a Ponzi scheme. Peter is not really a lover of anything in this space,” Saylor said. “Bitcoin is digital capital and we’ve created a digital treasury company by selling equity and credit instruments to buy capital. I think that Bitcoin is going to continue because it represents economic wealth in tokenized form with full property rights for the world.”

Saylor described STRC as a form of “digital credit” designed to strip out some Bitcoin volatility while producing a defined yield. He said Strategy overcollateralizes the instrument, with “for every $5 of Bitcoin” the company selling “$1 of credit.”

“If you don’t acknowledge Bitcoin as legitimate, you’ll never acknowledge any derivative on top of it as legitimate,” he said. “But for those people that believe that Bitcoin is digital capital, as a store of economic wealth in tokenized form, then what we’re doing is very straightforward.”

At press time, BTC traded at $80,929.

Trump Media & Technology Group’s stock now trades around $8.93. That number tells a story on its own. The parent company of Truth Social once peaked at $97.50 a share back in early 2022, and it has shed more than 90% of its value since then.

CEO Devin Nunes stepped down on April 22, adding leadership uncertainty to a company already under financial pressure.

A Bad Deal Gets Worse

756 million Cronos tokens sit on Trump Media’s books, purchased for close to $114 million as part of a deal with Crypto.com. By March 31, those tokens were valued at just $53 million — less than half what the company paid.

That loss compounded an already bruising quarter driven largely by Bitcoin purchases made near last summer’s market peak. The company bought roughly 9,500 Bitcoin at an average cost of around $108,519 per coin.

At quarter-end, the 9,542 Bitcoin it held carried a cost basis of $1.13 billion but a fair value of only $647 million — a gap of nearly $500 million. Bitcoin has since climbed back above $80,000, pushing the position’s value closer to $770 million.

The total damage for the first quarter of 2026 came to $406 million in net losses, up sharply from $31.7 million during the same period a year earlier.

According to a filing with the Securities and Exchange Commission, nearly $370 million of that figure came from unrealized losses on digital assets and equity holdings — meaning the company has not sold its positions at a loss, but the decline in market value still hit the books hard. An additional $108 million in investment losses was tied mostly to equity securities.

Revenue Barely Moves

While crypto losses dominated the quarter, Trump Media’s core media business generated just $871,200 in revenue — a 6% increase from $821,200 in the first quarter of 2025.

That figure includes $810,100 in media revenue and $61,100 in management fees tied to Truth.Fi ETF offerings. For a publicly traded company sitting on over $2 billion in total financial assets, the revenue line is thin.

The company did manage to generate nearly $18 million in operating cash flow during the quarter, helped by selling options on its pledged Bitcoin holdings.

Of its total Bitcoin position, 4,260 BTC has been pledged as collateral for convertible notes, and another 2,000 BTC is held against covered call options as a hedge.

Featured image from Thomas Fuller/SOPA Images/LightRocket via Getty Images, chart from TradingView

Tether’s second reserve asset is intelligence

Tether’s new QVAC project begins with an unusual phrase for a stablecoin company. The company describes “QVAC Psy” as a family of foundational models “rooted in the principles of Psychohistory.”

The reference to psychohistory belongs to Isaac Asimov’s Foundation universe, where Hari Seldon uses mathematics, statistics, and social dynamics to forecast the behavior of very large populations and shorten the dark age after the Galactic Empire’s collapse.

The Encyclopedia of Science Fiction describes Asimovian psychohistory as an “Imaginary Science,” while Seldon’s work is a plan that predicts future events and preserves knowledge through systemic breakdown.

Tether’s wording functions as a mission statement wrapped in science-fiction language.

The company built the largest stablecoin in crypto by turning reserves, liquidity, and distribution into a monetary infrastructure. QVAC applies the same instinct to intelligence.

Tether’s first reserve asset remains the dollar-like liability at the center of USDt. Its second reserve asset is becoming compute, models, datasets, and the ability to run AI outside centralized clouds.

From dollar reserves to intelligence reserves

Tether’s expansion into AI follows the mechanics of its core business. USDt converts demand for offshore dollars into a reserve stack dominated by short-duration sovereign instruments.

In its Q1 2026 attestation update, Tether reported $1.04 billion in net profit, an $8.23 billion reserve buffer, roughly $183 billion in token-related liabilities, and about $141 billion in direct and indirect exposure to U.S. Treasury bills. That reserve base gives

Tether recurring income, balance-sheet capacity, and room to fund long-duration infrastructure bets from operating strength.

CryptoSlate has already tracked how this reserve engine can turn stablecoin scale into strategic allocation. In January, Tether’s 8,888 BTC purchase showed how interest income and operating profits can translate into recurring Bitcoin demand. QVAC pushes the same logic into a different asset class.

Alongside Bitcoin, gold, startups, energy, mining, communications, and other infrastructure positions, Tether is allocating into intelligence itself. The move extends the company’s self-image from issuer of private dollar liquidity to builder of private digital infrastructure.

The “psychohistory” language fits that direction because Tether is framing AI as a civilizational layer rather than a software vertical. QVAC’s public materials describe an “Infinite Stable Intelligence Platform,” a local-first system for the “decentralized mind,” and an answer to centralized AI.

The QVAC vision page argues that routing every thought through centralized servers is too slow, fragile, and controlled, and then places QVAC as an edge-native foundation for the intelligence that users possess.

That framing mirrors Tether’s broader stablecoin pitch. Money should move without permission. Data should stay with the user. Intelligence should run where the user is.

The most serious claim, however, sits underneath the Asimov reference. Tether is saying that AI becomes more durable when it behaves like resilient infrastructure.

A cloud model can be more capable, yet it carries provider risk, pricing risk, policy risk, latency risk, and data-routing risk.

A local model gives up part of the frontier capability curve in exchange for ownership, privacy, and continuity.

The trade is familiar in crypto. Self-custody is less convenient than an exchange until the exchange fails. Local AI is less convenient than a hosted frontier model until the network drops, the API changes, the account closes, or the data cannot leave the device.

QVAC is an edge stack built around a different race

QVAC’s key distinction is architectural. OpenAI, Anthropic, Google DeepMind, and xAI compete across maximum general capability, coding, multimodality, long-context reasoning, agentic behavior, and enterprise cloud distribution.

QVAC aims at a different axis: deployability, privacy, latency, composability, and survival outside a single provider.

The QVAC welcome documentation defines the project as an open-source, cross-platform ecosystem for local-first, peer-to-peer AI applications across Linux, macOS, Windows, Android, and iOS. The same documentation says users can run LLMs, perform speech recognition and retrieval-augmented generation, and handle other AI tasks locally, or delegate inference to peers via built-in P2P capabilities.

That gives QVAC a different benchmark from the frontier labs. Frontier AI optimizes for the strongest general model available through a centralized service. QVAC optimizes for where inference happens, who controls the runtime, what data leaves the device, and whether an application can continue operating when centralized services become unavailable.

Tether’s April 2026 SDK launch describes a unified development kit that lets developers build, run, and fine-tune AI on any device, with applications designed to run unchanged across iOS, Android, Windows, macOS, and Linux.

It also says that the QVAC SDK uses a unified abstraction layer over local inference engines, including QVAC Fabric, a fork of llama.cpp, plus integrations with whisper.cpp, Parakeet, and Bergamot for speech and translation.

That is closer to an operating layer than a single model release. The open-source AI ecosystem already has powerful pieces: Llama, Qwen, Mistral, Gemma, DeepSeek, Hugging Face, llama.cpp, Ollama, vLLM, LM Studio, and a long tail of local inference projects.

QVAC’s bet is that developers need a coherent edge framework that joins model loading, inference, speech, OCR, translation, image generation, RAG, P2P model distribution, delegated inference, and local fine-tuning through one interface.

QVAC is positioning itself as a distribution layer for intelligence, assuming that good-enough local models will continue to improve.

QVAC Fabric is the technical center of that claim. Tether says Fabric supports fine-tuning across modern consumer hardware through Vulkan and Metal backends, including Android devices with Qualcomm Adreno or ARM Mali GPUs, Apple Silicon devices, and standard Windows or Linux setups with AMD, Intel, or NVIDIA hardware.

It also describes dynamic tiling for mobile GPU memory limits and a LoRA workflow with GPU acceleration and masked-loss instruction tuning.

If that workflow holds up in external developer use, the distinction from typical open-source model releases becomes material. The model weights are one layer. Local adaptation becomes the next layer.

MedPsy is QVAC’s first hard test

MedPsy gives QVAC its first concrete model-level proof point. The Hugging Face technical report, published May 7, presents QVAC MedPsy as a family of text-only medical and healthcare language models built for edge deployment at 1.7 billion and 4 billion parameters.

The claim is ambitious: smaller models, trained through a tightly controlled medical post-training pipeline, can outperform larger medical baselines while remaining practical for laptops, high-end mobile devices, and smartphone-class applications.

QVAC says MedPsy-1.7B scores 62.62 across seven closed-ended medical benchmarks, above Google’s MedGemma-1.5-4B-it at 51.20, despite being less than half its size.

It also says MedPsy-4B scores 70.54, slightly above MedGemma-27B-text-it at 69.95, while being nearly seven times smaller.

On HealthBench and HealthBench Hard, QVAC reports a wider gap, with MedPsy-4B scoring 74.00 and 58.00 versus MedGemma-27B-text-it at 65.00 and 42.67 under the CompassJudger evaluation shown in the report.

Those results, if independently reproduced, would support the core QVAC thesis: domain-specific, edge-scale models can challenge much larger systems in constrained, high-value categories.

The training recipe also shows how QVAC plans to compete. The report says MedPsy uses Qwen3 backbones and then applies multi-stage supervised fine-tuning and reinforcement learning to medical QA tasks.

It generated more than 30 million synthetic rows during experimentation, used a two-stage curriculum, and selected Baichuan-M3-235B as the single teacher model for long-form reasoning supervision. QVAC also states that the training corpus has not yet been released. That caveat is central.

The strongest public benchmark claims still come from QVAC itself, and the training data needed to fully interrogate contamination, coverage, prompt construction, and teacher influence remains unavailable.

The edge angle becomes sharper in quantization. QVAC says GGUF variants are published for llama.cpp and QVAC SDK, with Q4_K_M reducing file size by 69% while losing less than one average score point for both MedPsy sizes.

The report recommends Q4_K_M with imatrix calibration as the size-and-quality trade-off: 2.72 GB for the 4B model and 1.28 GB for the 1.7B model. The QVAC models FAQ also warns that MedPsy is text-only, English-only, unsuitable for emergencies, vulnerable to hallucination, and dependent on developers preserving privacy across the full application architecture. That gives the technical center its proper shape.

MedPsy is promising because medicine has strong reasons to prefer local inference. It remains unproven until external researchers reproduce the benchmark ladder and test it under real clinical workflow constraints.

The unresolved fight is convenience versus control

The local-versus-cloud AI debate is usually framed as a choice between privacy and performance. QVAC reframes it as convenience against control.

Cloud AI wins on ease. The user opens an app, sends a prompt, receives an answer, and avoids the operational burden of model weights, device memory, quantization, embeddings, or runtime compatibility.

The provider absorbs the complexity. That convenience is powerful, and it explains why centralized AI platforms have scaled so quickly. The user gets frontier capability with minimal setup.

QVAC asks developers and users to accept more responsibility in exchange for a different security model. The reward is local execution, offline operation, reduced data exposure, lower dependency on API access, and a path toward peer-to-peer inference and model distribution.

Tether’s SDK launch says QVAC-powered apps can keep working in low-connectivity environments and that “if the internet goes down, the AI keeps working.” Its 2025 QVAC announcement went further, describing AI agents running directly on local devices, peer-to-peer networking for device-to-device collaboration, and WDK integration that would allow AI agents to transact in Bitcoin and USDt.

That is the full Tether thesis: money, computation, and autonomous agents should share the same sovereign design pattern.

The decentralization claim isn't quite as straightforward as some would like. QVAC is meaningfully decentralized at the inference layer when a user can download a model, run it locally, and keep sensitive data on device.

It is more decentralized than a hosted API because the provider no longer sits inside every prompt.

It also adds peer-to-peer primitives through the Holepunch stack, including delegated inference and decentralized model distribution, according to Tether’s SDK materials. Those are substantive design choices.

Governance is a separate layer. QVAC is funded, named, coordinated, and promoted by Tether. The flagship apps, model family, SDK roadmap, and “Stable Intelligence” language all originate from a single corporate sponsor.

That structure coexists with the local-first value proposition. It narrows the decentralization claim to where the evidence is strongest.

QVAC decentralizes where inference can happen. The broader ecosystem still needs evidence of distributed control over default registries, release channels, safety conventions, model inclusion, and long-term governance.

Replication is the next threshold

QVAC’s credibility now sits on replication. If MedPsy’s results reproduce outside QVAC’s own evaluation harness, Tether will have a credible first example of its intelligence-reserve thesis: small, open, locally deployable models that can compete with larger cloud-oriented systems in a sensitive domain.

If independent testing narrows or reverses the benchmark gap, QVAC still has an infrastructure argument, while its model claim carries less weight. The broader fight then returns to the oldest trade in technology: convenience concentrates power, while control imposes work.

That is where the Asimov pitch becomes useful. Psychohistory in Foundation was concerned with large systems under stress. Tether’s version focuses on infrastructure under centralization. The language is grand, and the technical proof remains early, but the direction is coherent.

Tether is leveraging the cash flows of the world’s largest stablecoin to build an AI stack focused on local execution, peer networks, open tooling, and edge-scale models. It is extending the stablecoin premise from money to intelligence.

The question is no longer whether a stablecoin company can afford to build AI. Tether clearly can.

The question is whether QVAC can produce models and infrastructure strong enough to make users accept the friction of local control.

MedPsy is the first measurable threshold. Independent replication will determine whether QVAC’s psychohistory language remains a metaphor or begins to resemble the early operating logic of a serious edge-AI stack.

The post Tether launches decentralized local AI using Isaac Asimov’s Psychohistory straight out of Foundation appeared first on CryptoSlate.

Crypto projects with more than $3 billion in total value locked have migrated their cross-chain infrastructure to Chainlink’s Cross-Chain Interoperability Protocol (CCIP) following a $292 million exploit at KelpDAO, which heightened scrutiny of bridge security across decentralized finance.

Chainlink confirmed the migration wave, saying four protocols, including KelpDAO, Solv Protocol, Re, and Tydro, had begun decommissioning legacy oracles and bridge systems in favor of CCIP.

The shift has also fed into LINK’s market performance. CryptoSlate data shows the token rose 15% to $10.52, its highest level since January, as traders responded to the acceleration in CCIP adoption.

Blockchain analytics firm Santiment said the rally came alongside a tightening in LINK’s available supply on exchanges. According to the firm, LINK's exchange reserves fell by 13.5 million LINK over five weeks, representing more than 10.5% of the exchange-held supply recorded in early April.

The price move reflects a broader reassessment of Chainlink’s role in crypto infrastructure. After years of being known primarily for price feeds and oracle services, the network is now becoming a direct beneficiary of DeFi’s search for safer cross-chain rails.

Why are DeFi protocols embracing Chainlink’s CCIP?

Cross-chain bridges allow tokens, NFTs, and data to move between otherwise separate blockchain networks. This means these platforms let users shift liquidity between ecosystems, such as moving assets from Ethereum to Solana, without relying on a centralized exchange.

That function has become essential as DeFi has spread across multiple blockchains. Lending markets, staking tokens, stablecoins, and tokenized assets increasingly depend on infrastructure that can move value between networks without fragmenting liquidity or locking users into a single chain.

However, bridges have also become one of crypto’s most frequently attacked pieces of infrastructure. This is because they often rely on complex verification systems and hold large pools of locked assets, making them attractive targets for hackers.

Chainalysis has described cross-chain bridges as one of the blockchain industry’s major security risks. As of 2022, more than $2 billion had been stolen across 13 bridge hacks, with North Korean-linked groups among the most active attackers.

That history has pushed DeFi protocols toward infrastructure that can offer more standardized security controls. Chainlink’s CCIP, which launched on mainnet in July 2023, has become one of the main beneficiaries of that shift.

CCIP uses Chainlink’s decentralized oracle networks, the same infrastructure behind the data feeds that secure large parts of DeFi. Chainlink says those networks now include more than 2,000 decentralized oracle networks in production, securing over $110 billion in value and powering more than 70% of DeFi.

Unlike many traditional bridges, which can depend on a narrow set of validators or verification pathways, CCIP is designed to transmit both data and token value across chains through Chainlink’s oracle infrastructure.

That gives protocols a way to move assets while reducing reliance on bespoke bridge designs.

For protocols managing hundreds of millions of dollars in assets, cross-chain infrastructure is now being evaluated less as back-end plumbing and more as a core part of risk management.

LayerZero attempts to contain the fallout

Meanwhile, the migration wave has put LayerZero, the cross-chain platform previously used by KelpDAO, under pressure to explain its role in the $292 million breach.

LayerZero issued an apology on May 9, about three weeks after the April 18 breach. The company acknowledged that its post-exploit communication had fallen short and conceded that its security model allowed a high-value application to operate with insufficient safeguards.

LayerZero had initially maintained that its infrastructure worked as designed and that responsibility sat with the application configuration.

However, its more recent comments struck a different tone, acknowledging that it should have exercised stronger oversight over how its decentralized verifier network was used.

The company said it “made a mistake” by allowing its Decentralized Verifier Networks (DVNs) to function as the sole verifier for high-value cross-chain transactions without adequate guardrails.

It noted:

“We didn't police what our DVN was securing, which created a risk we simply didn't see. We own that.”

The admission goes to the heart of the dispute. LayerZero’s architecture gives application developers the flexibility to configure verification as they see fit. That customizability has long been part of the protocol’s appeal, particularly for teams seeking more control over their cross-chain security assumptions.

The KelpDAO exploit has exposed the weakness of that approach when teams operate with a too-narrow verification setup. If an application depends on a single verifier, a compromise in that layer can become a direct threat to user funds.

Meanwhile, LayerZero also disclosed a previously unreported incident from three years ago involving one of its multisig signers.

The company said the signer mistakenly used LayerZero hardware to conduct a personal trade. The signer was removed, wallets were rotated, and LayerZero later moved to a custom-built multisig framework.

The disclosure appeared intended to show that the protocol had addressed earlier internal security lapses. However, it also added another layer of scrutiny at a moment when clients were already reassessing their exposure.

LayerZero said the KelpDAO exploit affected only a single application, representing 0.14% of network applications and roughly 0.36% of total value on the protocol. It also said no other application was affected.

That defense leaves LayerZero with a narrow but difficult argument. The company is trying to show that the exploit was isolated while also admitting that the configuration should not have been allowed to secure so much value without stronger oversight.

Can LayerZero restore institutional confidence?

The central question now is whether LayerZero’s apology and technical explanation can slow the migration of protocols toward Chainlink.

Tom Wan, head of data at Entropy Advisors, questioned whether the damage to institutional confidence had already been done. He wrote

“Can an apology stop their clients from leaving to Chainlink, or is this just the beginning?”

LayerZero has tried to answer that concern with usage data. The company said more than $9 billion had moved through its infrastructure since the April attack, a figure meant to show that users and applications continue to rely on the protocol despite the KelpDAO incident.

Wan also noted that several major assets, including USDe, WBTC, and weETH, remain active on LayerZero.

That continued usage suggests the protocol has not suffered a full loss of confidence, even as several prominent projects shift parts of their cross-chain stack elsewhere.

LayerZero also retains defenders who argue that the protocol’s flexibility remains its core advantage.

In that view, customizability is not a flaw by itself. The risk arises when application teams fail to align their security configuration with the volume of capital flowing through their systems.

Lorenzo Romagnoli, co-founder of USDT0, said LayerZero’s model requires asset issuers to take security seriously from the start. USDT0, the largest asset on the LayerZero network, has moved $4 billion across chains without incident.

Romagnoli said:

“LayerZero is the golden standard for cross-chain interoperability because of its high level of customizability. Unfortunately, this means application owners need to invest serious resources to match the security standard that the capital moving through our rails demands.”

Romagnoli said USDT0 operates its own proprietary veto-powered DVN, with invariance checks tailored to its specific risk profile. He argued that the protocol remained unaffected because it treated security as part of the product, rather than a feature inherited automatically from the underlying rails.

That defense captures the wider debate now facing cross-chain infrastructure. Protocols want flexibility, but they also need defaults and guardrails strong enough to protect large pools of user capital. The KelpDAO exploit has made that trade-off harder to ignore.

For Chainlink, the migration wave strengthens CCIP’s position as a security-focused cross-chain standard, as DeFi teams reassess vendor risk.

For LayerZero, the challenge is to demonstrate that its customizable model can meet institutional expectations without exposing high-value applications to weak configurations.

The post Chainlink emerges as the unlikely $3B winner of KelpDAO exploit as DeFi projects dump LayerZero appeared first on CryptoSlate.

Bitcoin (BTC) price keeps stalling near $82,000, and the chart is not the real reason. The blame sits with a US buyer base that has been missing since October.

The chart looks ready for a rally. A looming bullish EMA crossover hints at the same setup that delivered 10.72% in April. The catch sits at a key chart-specific level, as one group of buyers keep selling every reclaim attempt.

Bitcoin’s 50-Day and 100-Day EMA Crossover Echoes April’s 10.72% Setup

Bitcoin’s daily chart shows four exponential moving averages (EMA) stacked closely together.

The 20-day sits at $78,805, the 50-day at $76,016, and the 100-day at $76,538. The 200-day stands at $82,020 as the immediate ceiling. EMAs are weighted moving averages that respond faster to recent price than simple averages do.

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The 50-day is now closing in on the 100-day, with the gap tightening by the day. A bullish crossover could complete within days. The setup matters because a similar compression played out between the 20-day and 100-day in late April. Once that crossover completed, Bitcoin price action delivered a 10.72% rally over the following weeks.

The catch sits at the 200-day. Bitcoin tried to reclaim the 200-day EMA over the weekend and failed. The May 6 attempt ended in a quick reversal. The May 10 attempt did the same.

Until the 200-day flips from resistance to support, the looming 50-day and 100-day crossover stays a setup without a trigger. The next question is what is keeping bulls from finishing the job. The answer sits in the on-chain data.

Funding Rates and Coinbase Premium Both Point to a US-Driven Bear Tilt

Bitcoin funding rates have undergone a regime shift over the past three months. From May 2025 through late January 2026, the rate was mostly positive, signaling long-side dominance.

Since late January, that flipped. CryptoQuant data shows funding has stayed mostly negative for around 90 days. The latest reading sits at -0.0031% on May 10. The series hit close to -0.02% earlier in the cycle, the deepest negative print in the period.

A funding rate below -0.01% signals strong short dominance, where leverage is crowded on the bearish side. Counterintuitively, that crowding can ease downside pressure and raise short-squeeze risk if price holds.

The spot side tells a similar story but started earlier. The Coinbase Premium Index measures the price gap between Coinbase and other major exchanges. A positive premium signals US-based buyers are paying up. A negative premium signals US sellers are dominant.

Since late October 2025, the premium has stayed mostly negative. The dominant tone is red, with only brief green spikes.

Six months of negative readings means US spot demand has been absent or net negative. That demand usually acts as the swing factor in Bitcoin rallies. Without it, every reclaim attempt gets met with supply from the same cohort.

This metric flipped positive on May 5 (right before the 200-day EMA reclaim attempt). On May 6 it turned negative, resulting in the EMA rejection.

The timing matters. The Coinbase Premium flipped negative three months before funding rates did. Spot weakness led the derivatives shift, not the other way around. A green flip in the Coinbase Premium would confirm US institutional demand is returning. Until then, the price chart has to do all the work alone.

Bitcoin Price Needs to Clear $82,000 to Open the Path to $90,450

With the 200-day EMA still acting as resistance, Bitcoin price has to clear $82,020 cleanly. The upside levels come into play only after that.

Volume tells part of the story. Since April 13, daily volume has trended lower even as price ground higher. That fading participation is one of the reasons every reclaim attempt has stalled.

The next test above the 200-day is $83,608, the 0.236 Fibonacci level. Clearing it confirms the 200-day is no longer suppressing price. The path then opens toward $86,223 and $88,336.

A push beyond $88,336 puts $90,450, the 0.618 Fibonacci, into play as the next major resistance, also highlighted in our crypto market piece.

To the downside, $79,381 is the immediate support. A break below opens $74,903 as the next horizontal floor. Loss of $74,903 sets up a deeper test of $70,493.

Bitcoin price is locked in a tight setup. The 200-day EMA, Coinbase Premium, and funding rate all need to flip green together before any meaningful upside. A move above $82,020 without US buyers showing up risks repeating the May 6 and May 10 failures.

$82,020 separates a 10.72%-style follow-through repeat from a slide back to $74,903 if sell volume returns.

The post Bitcoin Stalls at $82,000 Because US Buyers Have Been Missing Since October appeared first on BeInCrypto.

The S&P 500 has surged to fresh record highs in 2026, powering through milestone after milestone as Wall Street toasts another banner year.

Strip out the artificial intelligence stocks, though, and the rally all but disappears, leaving a market that has gone essentially nowhere since February.

S&P 500 ex-AI Index Flat Since February as Benchmark Climbs 8%

BeInCrypto recently reported that AI-linked stocks now account for a record 45% of the S&P 500’s market capitalization. Strong rallies in hyperscalers and AI-related stocks have helped push the index higher, as investors continue betting on the sector’s long-term growth potential.

The S&P 500 has climbed nearly 7% since early February. While the war-driven volatility caused notable losses in March, the rally accelerated in April, with the index gaining 15.5% since March 30.

However, the gains have not been evenly distributed across the market. According to Google Finance data, the US 500 Excluding Artificial Intelligence Enablers Price Return Index (SPXXAI) has fallen 1.84% since its February launch. 

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Even after rebounding from its March lows, the index is up only around 5.07%. The contrast highlights how heavily AI-related stocks are driving the broader market rally. 

Goldman’s earlier work flagged the divergence well before the current rally. Across three years through early 2026, the headline S&P 500 returned 76% versus 32% for the ex-AI version.

“The gap highlights how a handful of AI giants are driving nearly all market gains, fueling growing concerns that the current bull market is becoming dangerously reliant on the AI trade alone,” Coin Bureau wrote.

This is not just the case for US equities. Bloomberg recently reported that Asia’s AI-driven stock rally has been concealing broader market weakness, with surging tech shares offsetting the economic pressure and investor uncertainty stemming from the US-Iran conflict.

“Outside of AI, there is a genuine absence of catalysts, and many companies’ spending plans and margin outlooks remain on hold until there is greater clarity on the conflict,” said Fabien Yip, a market analyst at IG International. 

While AI giants continue to lift headline indices to record highs, much of the broader market remains sluggish amid geopolitical tensions and economic uncertainty.

As a result, investor confidence increasingly hinges on whether the AI boom can continue sustaining market momentum on its own.

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The post AI Stocks Drive Nearly All of S&P 500’s Gains, Data Reveals appeared first on BeInCrypto.

In the first week of May 2026, the cryptocurrencies have seen a huge interest from investors through spot exchange-traded funds (ETFs). These ETFs let people buy crypto without having to deal with wallets or exchanges.

Last week, from May 4 to May 8, 2026, data from SoSoValue showed strong net inflows across Bitcoin, Ethereum, XRP and Solana spot ETFs. This signals growing confidence amid rising prices. Bitcoin’s ETF alone managed to bring in $623 million, while total assets hit record highs.

Bitcoin Spot ETFs: BlackRock Dominates with Record Inflows

Bitcoin spot ETF had an amazing week. The ETF products saw an inflow of $623 million, as per SoSoValue. This number also means that more money poured in than it flowed out, which pushed holdings of these products. Moreover, with this inflow, Bitcoin ETFs have now marked six straight weeks of steady investor demand.

The star performer was BlackRock’s ETF IBIT, which saw a weekly net inflow of $596 million. That is more than 95% of the total weekly gains for Bitcoin ETFs. IBIT’s total weekly gains for Bitcoin ETFs. IBIT’s total historical net inflow now stands at an impressive $66.10 billion.

Then there is Ark & 21 Shares ETF ARKB, with a solid weekly net inflow of $53.09 million. ARKB’s cumulative historical net inflow has reached $1.71 billion.

On the contrary, not every ETF product managed to gain. Grayscale Bitcoin Trust GBTC saw the largest net outflow. The product saw $62.28 million flowing out. This number also indicates that investors are moving to cheaper options such as IBIT.

As of now, the total net asset value of all Bitcoin spot ETFs is $106.61 billion. The ETF net asset ratio, which is nothing but how much of Bitcoin‘s market is held buy these ETFs, sits at 6.67%. Overall, historical net inflows for Bitcoin ETFs total $59.34 billion.

As institutional money flowed into these ETF products, the price of the token has also increased. At press time, the price of the BTC0.14%token stands at $80,833.60 with an uptick of 0.1% in the last 24-hours as per CoinGecko. Moreover, earlier today, the token price touched $82,342, hinting at more upside if inflows continue.

Ethereum Spot ETFs Gain Momentum Despite Mixed Flows

Ethereum spot ETFs also posted positive numbers. The products managed to bring in $70.49 million last week, as per SoSoValue. This comes as Ethereum’s ecosystem grows with DeFi apps and layer-2 solutions. After a week of outflows from April 27 to May 1, Ethereum ETFs bounced back with fresh positive inflows.

BlackRock’s ETF ETHA led the pack and it managed to bring in $100 million in weekly net inflows. ETHA’s total historical net inflows now hit $12 billion, this also indicates a stronghold in crypto ETFs.

Grayscale’s Ethereum Mini Trust ETH came in second, as the product saw $6.3257 million in weekly net inflows. Its cumulative historical net inflows total $1.94 billion, a bright spot for Grayscale after Bitcoin struggles.

Fidelity’s ETF FETH did not follow the same trend. The product saw the biggest outflow of the week, which was $32.1563 million. Still, FETH’s overall historical net inflows stand at $2.26 billion, so it is not out of the game.

As of now, Ethereum spot ETFs have a total net asset value of $13.73 billion which is 4.49% of Ethereum‘s total market cap. Cumulative historical net inflows have reached $12.09 billion.

At press time, the price of the ETH0.29% token stands at $2,338.91 with an uptick of 0.5% in the last 24-hours as per CoinGecko. Moreover, earlier today, the price of the token hit $2,379.

XRP Spot ETFs See Steady Inflows

Just like Ethereum, XRP ETF products also saw one week of negative inflows from April 27 to May 1, following three straight weeks of positive inflows, before rebounding with renewed inflows last week (from May 4 to May 8). The XRP ETF products saw an inflow of $34.21 million in the said period as per SoSoValue.

Canary ETF XRPC topped the list with $13.5393 million in weekly net inflows. XRPC’s total historical net inflows is now $438 million, building a strong base. Bitwise ETF XRP followed closely, with $12.3621 million weekly net inflows and $434 million in total historical inflows. These two funds captured most of the action. As of press time, XRP spot ETFs’ total net asset value is $1.120 billion. The ETF net asset ratio is 1.26%.

At press time, the price of the XRP1.91% token stands at $1.45 with an uptick of 2.5% in the last 24-hours as per CoinGecko. Moreover, the price of the XRP token hit $1.50 yesterday.

Solana Spot ETFs Break Out with Strong Weekly Gains

Solana spot ETFs recorded $39.23 million in net inflows last week from April 27 to May 1, as per SoSoValue. The Bitwise ETF BSOL managed to bring in $36.3915 million weekly. BSOL’s total historical net inflow is $862 million.

Fidelity ETF FSOL added $2.8399 million weekly, with historical net inflows at $161 million. Together they drove most of Solana’s ETF momentum.

Currently, Solana spot ETFs hold $987 million in net assets. The ETF net asset ratio is 1.82%, showing ETFs are carving out a bigger role. Cumulative historical net inflows are $1.060 billion.

At press time, the price of the token stands at $95.28 with an uptick of 1.9% in the last 24-hours as per CoinGecko.

Final Thoughts

The ETF flows indicate that there is a growing confidence in crypto, with bitcoin leading the charge. Bitcoin ETFs brought in $623 million, showing strong institutional demand, while BlackRock’s IBIT remains dominant with $66.10 billion in historical inflows.

Ethereum added $70.49 million, indicating that the interest is beyond Bitcoin. XRP and Solana also saw steady inflows of $34.21 million and $39.23 million respectively. Prices also stayed positive, with Bitcoin hovering around $80,000, Ethereum at $2,300, XRP at $1.45 and SOL at $95.

Overall, Bitcoin is still dominating the crypto ETF space, Ethereum, XRP and Solana ETF activity still suggests that the investors are also moving their money into other cryptocurrencies as well. The prices of the said tokens could also increase if the ETF inflows continue.

Also Read: Bitcoin ETFs Pull $46.3M, Extend Inflow Streak to 5 Days

The pioneer cryptocurrency Bitcoin (BTC) retraced from its weekly high of $82,833 amid the renewed uncertainty in the middle east war. The pullback gained additional momentum as BTC’s futures logged their 67th straight day of negative funding rates— a move that highlights sellers’ conviction for a prolonged correction in its price. However, the historical data identifies this setup sets the stage for a potential recovery in the market. Here are key levels to watch in Bitcoin price in May 2026.

Why Bitcoin Price Reverted From $83,000 Barrier

Bitcoin price is up 0.18% on Saturday to trade at $80,344. This shallow uptick follows the re-escalating geopolitical tension as U.S. airstrikes against Iranian military facilities, Following attacks on American naval destroyers in the Strait of Hormuz.

President Donald Trump has called this strike a “Love tap” in an ABC interview, while adding that the ceasefire with Iran is still intact but harder action is possible if Tehran refuses a deal. The move triggered notable volatility in oil market prices as benchmark index Brent Crude rose 2.9% to approximately $103 per barrel.

Thus, the broader crypto market witnessed a quick pullback, dragging BTC to $80,000 level.

What Are Funding Rates, and Why Do They Matter Now?

Perpetual futures contracts are those that are not bound to expire ever, and that track the Bitcoin spot price, in which exchanges implement a periodic payment scheme called funding rate, to ensure that the price of the perpetual market remains grounded. When the majority of traders are bullish and long positions dominate, long holders pay short sellers. The opposite is when bearish sentiment gains the upper hand and shorts stack up – the shorts pay the longs.

If the funding rate is negative, it indicates an imbalance in the market, favoring wagers against the market. Short sellers are paying a continuous, compounding cost to maintain their positions. 

According to K33 Research, the Bitcoin futures funding rates have been negative for straight 67 days, projecting its longest streak in a decade. Such a long period highlights short sellers’ determination to pay premium to long holders and hold their position against Bitcoin even during a recovery momentum.

“I care about this regime for one simple reason: timing,” said Vetle Lunde, Head of Research at K33. “Lasting negative funding rates have a very strong track record of flagging where you should buy with conviction.”

History Says Bitcoin Often Rallies After Extended Negative Funding

When K33’s data is compared with on-chain analytics providers such as Glassnode and CoinGlass, it shows a similar trend in every case of long periods of negative funding.

The COVID Crash Bottom occurred in March 2020: The world markets froze and Bitcoin lost control and dropped to $3,800. Traders started to bet further price drops, leading to funding rates going sharply negative. Rather, the bottom was created and Bitcoin entered a record run that saw it surpass $60,000 within a year.

June – August 2021 – China Mining Ban: Bitcoin’s future was suddenly placed under a cloud of fear following Beijing’s sudden ban on crypto mining. The price slipped back to $30,000 and funding rates turned negative for 49 days. The market calmed, the shorts started to give way and Bitcoin rallied to a new all-time high later that year.

November 2022 – The FTX Collapse: FTX, one of the world’s largest crypto exchanges, has collapsed, leaving a shudder in the crypto industry. Funding turned into a negative and open interest increased on the short side as traders took on more contagion bets and the price of Bitcoin settled around $15,500. It had reached $23,000 when the short side had essentially all capitulated by the end of January 2023.

2023 — Silicon Valley Bank Crisis: Negative funding coincided with a brief fall in Bitcoin price to under the $20,000 mark during the banking crisis.The negative funding coincided with a slight drop in Bitcoin’s price to under $20,000 during the banking stress. Within a few weeks, a recovery occurred.

In each of these instances, the theme is the same: short sellers have been piling on for a long time and they go wrong — and when they begin to cover the squeeze makes the rally even bigger.

The Short-Squeeze Coiling Beneath the Surface

The current situation is very volatile, especially because of the structure of open interest. On major exchanges, open interest is also going up but funding continues to be in negative territory, where new short trades are being made and not unwinding. The combination of rising open interest and negative funding is a classic “loaded spring” set-up: With fuel increasing for a short squeeze, waiting for a catalyst to set it off.

This week, FxPro chief market analyst Alex Kuptsikevich highlighted that Bitcoin surged to $82.8K on Wednesday and failing to breach 200-day moving average, is “not a sign of buyer exhaustion,” and a few analysts have pointed to $83,200 as the technical threshold that if breached could lead to a forced short cover and ascent to $93,000.

K33 also pointed out that Bitcoin activity on the Chicago Mercantile Exchange (CME) has remained quiet even as the cryptocurrency has regained ground, as overall institutional positioning is far from the high of 2024 and 2025. Participation is still resuming, but with a certain hesitation.

Bitcoin Price at a Crossroad as Channel Breakout May Fail

Over the past week, the Bitcoin price showed a notable rally from $74,912 to a weekly high of $82,833. Amid this recovery, the coin buyers gave a decisive breakout from the resistance trendline of a rising channel pattern in daily charts.

While the breakout was expected to further fuel the bullish momentum, the escalated geopolitical tension pushed Bitcoin BTC0.14% within the channel range again to trade $80,388. This could be a retesting period for Bitcoin price to reattempt channel breakout and bolstering its position for a continued recovery.

The post-breakout rally could challenge immediate resistance of $84,330, followed by a leap to $98,000.

On the contrary, if sellers continue to defend the channel resistance at $81,300 mark, the Bitcoin price could witness renewed selling pressure and potential retest of $73,500 support.

Bitcoin has triggered another daily Kumo breakout, putting a historically bullish technical signal back in focus. Analyst Josh Olszewicz, who posts as CarpeNoctom, shared a chart on X tracking BTC’s forward performance after every daily Kumo breakout since 2015.

“BTC forward performance of daily kumo breakouts since 2015,” CarpeNoctom wrote, alongside a TradingView chart showing the latest breakout dated May 6, 2026.

What This Means For Bitcoin Price

The historical table attached to the chart shows a notably positive skew across completed signals. After prior daily Kumo breakouts, Bitcoin was higher one week later in 22 of 26 cases, with an average gain of 6.21% and a median gain of 5.08%. One month out, BTC was positive in 20 of 26 cases, with an average return of 14.05% and a median of 12.00%.

The signal’s stronger historical profile appears over longer windows. Three months after breakout, Bitcoin was higher in 18 of 26 cases, with an average gain of 39.48% and a median of 26.37%. Six months later, BTC was positive in 22 of 26 cases, with an average return of 74.36% and a median of 46.04%. The one-year data is even more striking: across completed samples, Bitcoin was higher in 22 of 25 cases, with an average gain of 186.01% and a median gain of 129.46%.

The largest one-year forward returns came during major bull-market phases. Breakouts on Sept. 4, 2016 and Oct. 7, 2016 preceded one-year gains of 615.08% and 617.09%, respectively. The April 1, 2017 signal was followed by a 525.35% one-year advance, while the April 23, 2020 breakout led to a 581.82% one-year gain. Another October 2020 breakout produced a 237.35% three-month move, a 430.84% six-month move, and a 393.65% one-year return.

The chart also shows that the signal has not been uniformly reliable. Breakouts during weaker or late-cycle conditions produced negative forward returns in several cases. The Aug. 13, 2021 breakout was followed by a 48.89% one-year decline, while the Oct. 1, 2021 signal preceded a 59.90% one-year drop. More recently, the April 22, 2025 breakout showed positive returns over one week, one month, three months, and six months, but was down 16.31% after one year.

The most recent completed signal before the May 2026 breakout, dated Oct. 1, 2025, also remains a cautionary data point. Bitcoin rose 3.98% after one week, but fell 7.60% after one month, 25.46% after three months, and 43.74% after six months. Its one-year return is not yet available in the table.

For traders, the chart frames the Kumo breakout less as a standalone prediction and more as a historically asymmetric trend signal. The median returns suggest the pattern has often appeared near meaningful upside continuation, but the failed signals cluster around periods where broader market structure deteriorated after the breakout.

At press time, BTC traded at $80,735.

Solana started a fresh increase above the $90 zone. SOL price is now consolidating and might aim for more gains above the $96 zone.

• SOL price started a fresh upward move above the $90 and $92 levels against the US Dollar.
• The price is now trading above $92 and the 100-hourly simple moving average.
• There is a bullish trend line forming with support at $92.20 on the hourly chart of the SOL/USD pair (data source from Kraken).
• The pair could extend gains if it clears the $96.50 resistance zone.

Solana Price Starts Fresh Surge

Solana price started a decent increase after it settled above the $88 zone, outperforming Bitcoin and Ethereum. SOL climbed above the $92 level to enter a short-term positive zone.

The price even smashed the $95 resistance. A high was formed at $96.85, and the price is now consolidating gains. There was a minor decline toward the 23.6% Fib retracement level of the recent upward move from the $87.61 swing low to the $96.85 high.

Solana is now trading above $92 and the 100-hourly simple moving average. Besides, there is a bullish trend line forming with support at $92.20 on the hourly chart of the SOL/USD pair.

On the upside, the price is facing resistance near $96.20. The next major resistance is near the $96.50 level. The main resistance could be $98. A successful close above the $98 resistance zone could set the pace for another steady increase. The next key resistance is $102. Any more gains might send the price toward the $105 level.

Downside Correction In SOL?

If SOL fails to rise above the $96.50 resistance, it could start another decline. Initial support on the downside is near the $94.00 zone. The first major support is near the $92.20 level, the trend line, and the 50% Fib retracement level of the recent upward move from the $87.61 swing low to the $96.85 high.

A break below the $92.20 level might send the price toward the $90 support zone. If there is a close below the $90 support, the price could decline toward the $88 support in the near term.

Technical Indicators

Hourly MACD – The MACD for SOL/USD is gaining pace in the bullish zone.

Hourly Hours RSI (Relative Strength Index) – The RSI for SOL/USD is above the 50 level.

Major Support Levels – $94.00 and $92.20

Major Resistance Levels – $96.50 and $98.00.