Industry News

Tracks company news, strategic changes, funding activities, and personnel adjustments across the blockchain and crypto industries, delivering a full-spectrum industry overview for our users.

The End of the Public Chain 'Money-Splashing' Era

The article argues that the traditional L1 blockchain grant model for ecosystem funding is fundamentally broken, not just in need of minor adjustments. It claims that over the past four years, billions of dollars have been poured into grants from major L1s like NEAR, Avalanche, and Aptos, yet this has failed to produce lasting, breakthrough projects or sustainable ecosystems. Instead, it has created a cycle where teams optimize for grant applications and short-term KPIs rather than building viable products for real users. The model is criticized for fostering a "hostage" situation: foundations are trapped by their own metrics and feel compelled to disburse funds to show growth, while teams become dependent on grant cycles, shaping their roadmaps around fundable proposals rather than market needs. This leads to a proliferation of "zombie" projects that survive on grants but lack organic growth. The author contrasts this with direct equity and token investments, like those made by Solana Ventures, which create long-term, aligned partnerships. The piece concludes that the era of grants for cold-starting ecosystems is over. The future winners will be L1s that compete by attracting truly great companies through strategic investments and by being the best place to build, not the most generous grant committee.

marsbit4h ago

The End of the Public Chain 'Money-Splashing' Era

marsbit4h ago

Brother Sun "Rights Protection" Stands Up Against the Trump Family, WLFI Is the Real Scythe in the Crypto Circle

The article details the controversy surrounding World Liberty Financial (WLFI), a cryptocurrency project linked to the Trump family. It reports that WLFI allegedly used the DeFi lending protocol Dolomite, whose co-founder is also a WLFI advisor, as a disguised channel to sell tokens by collateralizing around 5 billion WLFI tokens to borrow approximately $75 million in stablecoins. Despite WLFI's claims that the loans were for ecosystem development and posed no liquidation risk, critics argue it was a way for insiders to cash out, shifting risk to retail investors. The piece highlights WLFI's significant price decline—over 66% since its September 2025 launch—and suggests the Trump family and insiders are the main source of selling pressure, as they control nearly 74% of the token supply. It also revisits WLFI’s prior move to blacklist 272 addresses, including those of investor Justin Sun, under the pretext of preventing large-scale sell-offs, which now appears to be an effort to reduce competition for their own sales. Sun publicly accused WLFI of exploiting users, freezing assets, and treating the crypto community as a "personal ATM." WLFI countered by threatening legal action. The author notes that while Sun’s criticism may gain sympathy, a legal battle in the U.S. against the well-connected Trump family would be risky for him. Finally, the article concludes that WLFI exemplifies how powerful elites can exploit crypto’s regulatory gray areas for profit, and urges the community to reject such projects driven more by political privilege than genuine decentralized finance ideals.

Odaily星球日报6h ago

Brother Sun "Rights Protection" Stands Up Against the Trump Family, WLFI Is the Real Scythe in the Crypto Circle

Odaily星球日报6h ago

Claude's Intelligence Decline: Suicide or Playing Dead?

Recent reports indicate that Claude Opus 4.6, Anthropic's flagship model, has experienced a significant decline in performance, with its global ranking dropping from 2nd to 10th on BridgeBench. Accuracy fell sharply from 83.3% to 68.3%, while the hallucination rate nearly doubled. Users expressed frustration over the model's reduced capability for complex tasks. However, leaked internal screenshots suggest Anthropic is shifting focus toward a broader strategy: developing Claude Projects, a full-stack application builder. This platform allows users to create functional applications—such as AI chatbots, interactive games, and SaaS dashboards—with minimal coding, potentially making traditional programming obsolete. Anthropic’s move appears to prioritize platform ecosystem development over model leaderboard rankings. With annual revenue reaching $30 billion, largely from API usage, the company aims to reduce dependency on commoditized AI models by creating a sticky, integrated environment where users build and deploy directly within its ecosystem. This strategic pivot reflects a broader industry trend where becoming an indispensable infrastructure matters more than having the highest-performing model in benchmarks.

marsbit6h ago

Claude's Intelligence Decline: Suicide or Playing Dead?

marsbit6h ago

GenZVerse Unveils a Utility-First Web3 Platform That Prioritises Real Impact Over Speculation

GenZVerse introduces a utility-first Web3 platform built on Polygon’s Layer 2 blockchain, designed to prioritize tangible value over speculation. The platform integrates its native token into four core utility domains: governance voting, access to services, community rewards, and staking incentives—each tied to verifiable user actions rather than market speculation. It features fully open-source code, auditable smart contracts, and a transparent DAO structure to ensure accountability. The five-year roadmap focuses on phased development toward full decentralization by 2029, aiming to support millions of users with sustainable, community-driven growth.

TheNewsCrypto7h ago

GenZVerse Unveils a Utility-First Web3 Platform That Prioritises Real Impact Over Speculation

TheNewsCrypto7h ago

Crypto.com Collaborates with UFC® for UFC Freedom 250 at White House

UFC and Crypto.com have partnered for the historic UFC Freedom 250 event at the White House on June 14, celebrating the U.S. 250th birthday and Crypto.com’s 10-year anniversary. As co-presenting partner, Crypto.com will award a $1 million bonus pool in CRO tokens to selected fighters, marking the largest bonus in UFC history. The event will feature top fighters, including a main event between Ilia Topuria and Justin Gaethje, and a co-main event with Alex Pereira vs. Ciryl Gane. UFC President Dana White and Crypto.com CEO Kris Marszalek praised the historic collaboration. The event will be exclusively distributed in the U.S. by Paramount+.

TheNewsCrypto8h ago

Crypto.com Collaborates with UFC® for UFC Freedom 250 at White House

TheNewsCrypto8h ago

1 Billion DOT Minted Out of Thin Air, Yet Hacker Only Made $230,000

On April 13, a security breach occurred involving the Polkadot bridge on the Ethereum network, where an attacker exploited a replay vulnerability in the MMR proof mechanism of Hyperbridge’s ISMP protocol. By reusing a historically valid proof and pairing it with a malicious request, the attacker bypassed verification and gained admin and minting rights over the wrapped DOT contract on Ethereum. They then minted 1 billion wrapped DOT tokens—2,805 times the existing supply—and attempted to liquidate them. However, due to extremely low liquidity in the wrapped DOT market, the massive sell-off crashed the token’s price by 99.98%, from $1.22 to approximately $0.000128. The attacker ultimately exchanged the tokens for only about 108.2 ETH (worth roughly $237,000), with gas costs as low as $0.74. The same exploit had been used previously in attacks on MANTA and CERE tokens, resulting in a total loss of around $242,000. Polkadot confirmed that the incident only affected DOT bridged via Hyperbridge to Ethereum and did not impact the native Polkadot network or DOT on other bridges. Exchanges including Upbit and Bithumb temporarily suspended DOT deposits and withdrawals as a precaution. The event highlights ongoing vulnerabilities in cross-chain infrastructure and the critical role of liquidity in limiting actual damages during large-scale exploits. It also reflects a broader trend of increasing DeFi security incidents in early 2026.

marsbit8h ago

1 Billion DOT Minted Out of Thin Air, Yet Hacker Only Made $230,000

marsbit8h ago

The Creator of Kling Returns to Alibaba and Builds Another Dark Horse

The article discusses the rise of HappyHorse-1.0, an AI video generation model developed by Alibaba, which topped the Artificial Analysis leaderboard in both text-to-video and image-to-video categories in April 2026. The model was created under the leadership of Zhang Di, who returned to Alibaba in November 2025 after working at Kuaishou, where he led the development of the Kling model. HappyHorse is open-source and commercially available, similar to Alibaba's Qwen model. Zhang Di's background includes extensive experience in large-scale data systems and machine learning at Alibaba and Kuaishou, which contributed to the rapid development of HappyHorse within just five months. The model uses a 15-billion-parameter transformer architecture with native multimodal training, supporting multiple languages and lip-sync capabilities. It also focuses on reducing inference time and cost, making it practical for commercial use. The primary application of HappyHorse is in e-commerce, where it can generate product videos to enhance user engagement and conversion rates by creating contextual and personalized content. This aligns with Alibaba's strengths in commerce, advertising, and data feedback loops. The model's success with open-source approach contrasts with challenges faced by closed-source models like OpenAI's Sora (shut down due to high costs) and ByteDance's Seedance 2.0 (paused over copyright issues). HappyHorse represents a strategic move for Alibaba to integrate AI video generation into its core business ecosystems.

marsbit13h ago

The Creator of Kling Returns to Alibaba and Builds Another Dark Horse

marsbit13h ago

Giants Collectively Raise Prices, Is the AI Price Hike Wave Coming? Can We Still Afford Lobster Employees?

Major AI companies, including Alibaba Cloud, Baidu Intelligent Cloud, Tencent Cloud, and Zhipu, have recently announced significant price increases for AI computing and storage services, with hikes ranging from 5% to over 460% in some models. This trend follows similar moves by global giants like Amazon AWS and Google Cloud earlier this year. The price surge is driven by explosive demand for computing power, fueled by the rapid adoption of AI agents like OpenClaw (referred to as "Lobster" in the article), which consume tokens at rates dozens or even hundreds of times higher than traditional AI applications. This has created a severe supply-demand imbalance. Additionally, shortages in high-end hardware—such as AI chips and high-bandwidth memory (HBM)—have constrained computing capacity and raised operational costs. The industry is shifting away from loss-leading pricing strategies toward value-based models, prioritizing sustainable development over market-share competition. A new "token economy" is emerging, where pricing is increasingly based on token usage, complexity, and speed rather than flat fees. This reflects AI computing's evolution from a generic service to a specialized, high-value resource. Some companies are even considering token allowances as part of employee benefits, highlighting its growing role as both a production tool and a cost factor. The article concludes by questioning whether AI services will remain affordable as compute costs continue to rise.

marsbit14h ago

Giants Collectively Raise Prices, Is the AI Price Hike Wave Coming? Can We Still Afford Lobster Employees?

marsbit14h ago

How Should Crypto VCs Survive? When Top Projects No Longer Need Institutional Funding

Cryptocurrency venture capital is at a watershed moment. Token exits, once the primary driver of outsized returns, are undergoing a major reset. The definition of token value is being rewritten in real-time, yet no standard valuation framework has emerged. Key market shifts include the rise of tokens with real, on-chain revenue (like HYPE), which exposed the weakness of governance tokens with no fundamentals; a supply shock from meme coins (e.g., PUMP) fragmenting liquidity; and competition from prediction markets, stock perps, and leveraged ETFs diverting retail speculative capital. This has compressed token lifecycles and cratered holding periods. VCs now face critical questions: Are they underwriting equity, tokens, or a hybrid? What is the best practice for on-chain value accrual beyond potentially toxic buybacks? Will the "crypto premium" vanish entirely, forcing valuations to align with public equities and crashing many Layer 1 tokens? The result is a divergence: early-stage investors are becoming more price-sensitive on token projects, while appetite for equity deals is growing. Later-stage crypto VCs are increasingly competing with traditional funds in "Web2.5" deals. To survive, crypto VCs must find their product-market fit with founders. Capital alone is no longer sufficient. Winning the best deals—from projects that may not even need institutional funding—requires providing unmatched brand value and non-capital advantages.

marsbit14h ago

How Should Crypto VCs Survive? When Top Projects No Longer Need Institutional Funding

marsbit14h ago

Tens of Millions of Errors Per Hour: Investigation Reveals the 'Accuracy Illusion' of Google AI Search

A New York Times investigation, in collaboration with AI startup Oumi, reveals significant accuracy and reliability issues with Google's AI Overviews search feature. Testing over 4,300 queries showed the accuracy rate improved from 85% (powered by Gemini 2) to 91% (Gemini 3). However, given Google's scale of ~5 trillion annual searches, this 9% error rate translates to nearly 57 million incorrect answers generated hourly. A critical finding is the prevalence of "unsubstantiated citations." For correct answers, the rate of citations that do not support the AI's summary surged from 37% to 56% with the Gemini 3 upgrade, making it difficult for users to verify information. The AI heavily relies on low-quality sources, with Facebook and Reddit being among its top-cited websites. Furthermore, the system is highly manipulable. A BBC journalist successfully "poisoned" it by publishing a fabricated article; Google's AI began presenting the false information as fact within 24 hours. Google disputed the study's methodology, criticizing its use of the SimpleQA benchmark and an AI model (Oumi's own) to evaluate another AI. The company maintains its AI Overviews, combined with its search ranking systems, perform better than the underlying model alone. Critics note this defense does little to bolster user confidence in the feature's reliability.

marsbit16h ago

Tens of Millions of Errors Per Hour: Investigation Reveals the 'Accuracy Illusion' of Google AI Search

marsbit16h ago

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