edgeX (EDGE) Surge

Charles Hoskinson warns that Cardano risks losing its identity as the "science coin" if DReps fail to approve a key research funding proposal. He explains the ecosystem is in "treasury season" with a tougher funding environment, requesting $52 million this year versus $98 million last year, leading to cuts and layoffs. Hoskinson argues Cardano's research program is its "spine and backbone," responsible for its differentiation through work on proof-of-stake, extended UTXO, Plutus, and academic collaborations. He rejects calls to selectively fund parts of the research group, warning that treating researchers as commodities could lead to an irreplaceable talent drain to better-funded rivals. Hoskinson ties research funding to Cardano's long-term investment case, stating that without it, the project would lose a core value proposition. He ends with a direct appeal to DReps to vote for the proposal, calling it a necessary foundation for Cardano's future.

On June 2, the native token EDGE of the edgeX protocol experienced a violent flash crash, plummeting over 77% from around $1.14 to a low of $0.32 before partially recovering to approximately $0.64. edgeX officially ruled out a hack or platform security flaw, attributing the event to suspected market manipulation by external actors. The incident reignited community concerns regarding the project's transparency and past controversies. Prominent on-chain investigator ZachXBT highlighted that EDGE supply has long been controlled by a small group, with low circulating liquidity. This structure traces back to a disputed airdrop in April 2026, where the majority of tokens were allocated to partner wallets instead of the community, leading to accusations of a "well-designed rug pull." Despite having notable backers like Circle Ventures and Amber Group, and generating substantial protocol fees, edgeX faces criticism for a recurring pattern of "low float, high control, and opaque market making." While the team investigates the crash and emphasizes its core contracts are operational, user sentiment remains severely damaged, with many expressing a lack of trust in the team's integrity. Meanwhile, prediction markets have already opened betting pools on EDGE's future price.

The discussion, triggered by Anthropic's Claude Fable 5 model controversy, debates centralized control vs. decentralized distribution of cutting-edge AI. Participants explore the risks of models with hidden functionalities, government restrictions (like the Fable 5 block and Project Glasswing for Mythos), and the potential security chaos if powerful models like Mythos become widely available. The core tension lies between the need for safety/control (comparing AI to weapons) and the demand for open, permissionless access. The debate then shifts to the feasibility and future of decentralized AI (DeAI). While skeptics argue that decentralized training is inefficient, lacks data, and lags behind centralized R&D, proponents believe algorithm innovations and distributed computing (e.g., on consumer-grade hardware) can lower costs and democratize access. They argue DeAI's value lies in censorship resistance, privacy (e.g., Venice AI), and creating new economic models, not necessarily in outperforming frontier models. The conversation concludes by questioning whether DeAI's main opportunity is in challenging centralized model training or in building crucial supporting infrastructure and novel applications at the intersection of DeFi and AI.

Beyond the familiar performance charts like MMLU-Pro and MMMU, which major AI models strive to ace, stands a key "examiner": Chinese-Canadian researcher Wenhu Chen. An assistant professor at the University of Waterloo and founder of TIGERLab, Chen addresses the crucial need for more rigorous AI evaluation. As models like GPT-4 began scoring near-perfect results on older benchmarks like MMLU, it became difficult to distinguish their true capabilities. In response, Chen introduced MMLU-Pro in 2024, featuring harder, more reasoning-focused questions with more answer choices, successfully reintroducing meaningful performance gaps. His work extends to multi-modal evaluation with MMMU and its enhanced version, MMMU-Pro. These benchmarks test a model's ability to understand and reason with complex information from images, charts, and text across diverse academic subjects, exposing the significant challenges even top models face in genuine comprehension. Chen's background in complex QA, table reasoning, and his experience at Google DeepMind on projects like Gemini inform his approach. He understands that effective benchmarks must anticipate how models might "cheat" by memorizing data or avoiding visual analysis. His lab also actively researches video understanding and generation models (e.g., UniVideo, Vamba), ensuring his evaluation work is grounded in practical model-building challenges. Now at Meta's Super Intelligence Lab, Chen continues his focus on multi-modal data and evaluation, representing the deep yet often unseen contributions of Chinese talent in shaping the fundamental tools of the AI industry.

In a podcast with WuBlockchain, NDV founder Jason Huang discusses recent market dynamics, expressing a bearish outlook on crypto in the near term. He attributes Bitcoin's recent decline to a combination of cyclical selling pressure, the start of a US stock market correction, and liquidity tightening. A key catalyst is the emerging financial strain on MicroStrategy (MSTR). Huang explains that MSTR's model of borrowing to buy Bitcoin created a positive "flywheel" in a bull market. However, with falling BTC prices turning its stock premium into a discount, the model is now under severe stress. While MSTR only sold 32 BTC recently, the market is "front-running" the fear of its massive 80,000+ BTC holdings potentially being liquidated to meet debt obligations. He believes a true market bottom requires a major, capitulation-level event similar to the FTX collapse. Regarding investments, Huang states his fund is up over 20% this year, outperforming Bitcoin by 50-60%. The strategy involves crypto assets and commodities like oil, gold, and silver, but avoids AI stocks due to a perceived lack of trading edge. He is cautious of crowded trades in semiconductors and sees bubbles in the broader market, citing the hype around a potential SpaceX IPO. Despite short-term pessimism, Huang remains long-term bullish on one crypto innovation: stablecoins. He views them as the clearest example of a "faster, better" financial tool with significant room for global adoption. For the future, he is very bearish on Ethereum. For Bitcoin, he anticipates potential for a significant drop below $48,000 before a eventual rebound, but stresses the need to wait for a true panic-driven bottom marked by widespread despair and disinterest in the market.