Цена CORE(CORE)

Recent market rumors suggest Kraken is planning a strategic investment in Aave, sparking widespread interest. Although Aave's co-founder clarified some inaccurate details in the reports, this event highlights a significant trend: centralized exchanges are accelerating their entry into the core areas of on-chain finance. Kraken's interest in Aave reflects its strategic expansion beyond simple trading into more profitable, higher-barrier financial services like DeFi asset management. Aave, a leading DeFi lending protocol, offers a mature lending model, deep liquidity, and a growing ecosystem, making it a key gateway to future on-chain finance. Despite a major security incident in April that caused significant withdrawals, Aave's core architecture, governance, and market trust remained intact. The protocol's strong fundamentals are underscored by its $134 million in annual revenue, suggesting its valuation may be undervalued. Aave is also designing a new tokenomics model (Aavenomics 3.0) featuring an automated token buyback mechanism to better capture value for token holders, signaling DeFi's evolution towards sustainable value models. Ultimately, this potential move signals accelerated convergence between CeFi and DeFi. Kraken's target is not just an asset but a strategic position in the future of on-chain financial infrastructure, while Aave aims to prove DeFi can evolve into a cash-flow-generating, global financial system.

In his speech "Training Sand to Think: Artificial General Intelligence & Future of Physics," Adam Brown, a core contributor to Gemini, outlines the rapid and transformative evolution of AI. He describes how large language models (LLMs), grown rather than programmed through pre-training and fine-tuning, have progressed from performing poorly on high-school math tests to achieving gold-medal level at the International Mathematical Olympiad and recently making a genuine mathematical breakthrough by disproving a decades-old conjecture. Brown attributes this acceleration to the "Scaling Law," where predictable performance gains come from increasing compute, data, and model size. He draws parallels to the history of chess AI, predicting a similar trajectory for scientific research: moving from tools to "centaur" human-AI collaboration, and eventually to autonomous, superhuman "AI scientists." Even if progress halted today, AI already reshapes physics as a tireless tutor, powerful programming assistant, and exhaustive literature reviewer. However, Brown argues progress will continue due to immense economic runway and technical optimizations. He envisions a near-future golden age of human-AI collaboration in science, potentially leading to billions of replicated, superhuman AI researchers, making the coming years the most exciting in physics' history.

In 2026, OpenAI's Codex saw explosive growth, with weekly active users surging over 5x to 5 million since January, driven largely by the February launch of its desktop app. Codex desktop lead Andrew Ambrosino explains key shifts behind its evolution. A core change is the inversion of development costs: implementation is now cheap, while curation and taste—judging which of many AI-generated prototypes is valuable—have become the new scarcities. Ambrosino defines taste as a blend of aesthetics, systems thinking, direction, and semantic coherence in interaction. He notes AI still struggles with design because evaluating it requires human cultural context and abstract reasoning about how components relate—capabilities beyond current models. Timing is critical: the same Codex app would have failed months earlier; success hinges on the model's capabilities at launch. Roles are blurring within his team, with engineers, designers, and PMs overlapping significantly. However, Ambrosino cautions against eliminating specialized roles entirely, as each field retains deep expertise. On AI-assisted development, the focus has shifted from measuring code written by AI to distinguishing between supervised and unsupervised generation. A current challenge is teaching models to simplify code, not just add complexity. The merger of Codex and ChatGPT stems from observed user behavior: non-developers adopted Codex for general knowledge work despite its developer-centric interface. This revealed a collapsing boundary between specialized tools and universal assistants. The vision is a "home base" that orchestrates tasks across external professional tools (like Excel or Premiere Pro) via connectors, rather than rebuilding everything internally. An internal example showed Codex helping edit video by interacting with Premiere Pro's files and even writing a plugin for it. The future direction is a unified, extensible platform that serves as a central hub for automating and managing work across any specialized tool the user employs.

**Title: Want to Get the Robinhood Chain Airdrop? Which Ecosystem Projects Are Worth Watching?** **Summary:** Robinhood Chain, a key part of Robinhood's push into Layer 2, aims to build a comprehensive ecosystem covering stock tokens, RWAs, perpetual contracts, and spot trading. With its mainnet launch on July 2, 2026, came a 90-day gas fee waiver for swaps, cross-chain transactions, and Perp trading. While the ecosystem's TVL was still modest at around $76.73 million as of July 6, 2026, several early projects present potential opportunities. Key projects highlighted include: * **Arcus:** A stock token and crypto DEX built by dYdX Labs and Robinhood Crypto, focusing on spot and perpetual contracts. Future ARCUS tokens are expected to prioritize the existing dYdX community. * **Lighter:** A ZK-powered decentralized perpetual and spot exchange deployed on Robinhood Chain. It has committed $11 million worth of LIT tokens to the Robinhood community, with users earning points (and double points via Robinhood Wallet) for trading, convertible to LIT. * **Morpho:** Integral to the newly launched "Robinhood Earn" program in the US, where user-supplied USDG stablecoins are lent out via Morpho vaults, targeting a 7% APY. * **Rialto:** An on-chain spot exchange supporting crypto, stocks, ETFs, and commodities. It will initially list over 90 Robinhood stock tokens and uses a "propAMM" system where market makers provide quotes from their own inventory. * **Arrakis:** A non-custodial, on-chain market maker protocol for token issuers to manage concentrated liquidity on DEXs. * **Meridian:** A platform on Robinhood Chain focusing on RWA perpetual contracts and prediction markets, settled in USDe. It rebranded from Ethereal and had previously planned to allocate 15% of its future governance tokens to ENA stakers. * **Native:** An on-chain price discovery and execution system recently deployed on Robinhood Chain, though the team has stated there are no current plans for a token launch. The article emphasizes that this is not investment advice and urges participants to conduct their own research (DYOR).

This article provides an overview of the emerging Robinhood Chain ecosystem, a Layer-2 network launched by Robinhood. As of July 6, 2026, the ecosystem's TVL stands at approximately $76.73 million. Key projects highlighted for potential opportunities include: * **Arcus**: A DEX for stock tokens and crypto, co-built by dYdX Labs and Robinhood Crypto, focusing on spot and perpetual trading. Future token distribution is expected to prioritize the dYdX community. * **Lighter**: A ZK-powered DEX for perpetuals and spot trading on Robinhood Chain, offering an incentive program for users. * **Morpho**: Supports Robinhood Earn, a feature allowing US users to lend stablecoin USDG for an estimated 7% APY. * **Rialto**: An on-chain spot exchange supporting crypto, stocks, ETFs, and commodities, utilizing a propAMM model for liquidity. * **Arrakis**: A non-custodial on-chain market maker protocol for token issuers. * **Meridian**: A platform for RWA perpetual contracts and prediction markets, settled in USDe. * **Native**: An on-chain price discovery and execution system now deployed on Robinhood Chain. The article concludes with a disclaimer, advising readers to conduct their own research (DYOR) and assess risks.