CORE (CORE) рост

Cross-chain protocol AllBridge Core suspended operations after suffering a $1.65 million flash loan exploit on its Solana deployment. The attacker manipulated a stablecoin pool's exchange rate using a $1.12 million USDC loan from Kamino, creating a price imbalance to perform a profitable arbitrage. Stolen funds were moved to Ethereum via privacy pools. This is the protocol's second such attack, following a $573,000 exploit in April 2023. The suspension causes operational delays, reduces cross-chain liquidity, and highlights persistent security vulnerabilities in bridge protocols and automated market maker systems.

New Fire Research Institute argues that despite the recent U.S. June CPI decline to 3.5% year-on-year—primarily driven by energy—core goods inflation remains persistent, with core PCE likely showing slight growth. Federal Reserve Chairman Wash has emphasized the Fed's independence and a "zero tolerance" stance on inflation, suggesting a continued hawkish posture that will pressure risk assets, especially if energy prices rise again. Concurrently, the semiconductor memory sector faces structural pressures, as seen in significant sell-offs for Micron and SK Hynix. High leverage in markets like South Korea is triggering deleveraging, amplifying volatility. Investors are also questioning the sustainability of AI-related capital expenditures. In contrast, the crypto market showed relative stability last week, with BTC and ETH gaining slightly. Positive developments include a shift to net inflows for U.S. Bitcoin spot ETFs, a narrowing Coinbase discount, and strong activity on the Robinhood Chain ecosystem. The potential advancement of the U.S. CLARITY Act provides a policy catalyst. Overall, the probability of an independent crypto bull run in the short term is low, given overarching macro pressures. However, fundamentals are improving with ETF inflows and robust on-chain activity, providing solid support. Technically, BTC and ETH show strong support at key moving averages. New Fire Research maintains that Bitcoin around $60,000 represents a high-value allocation zone, with limited downside risk near current levels. The true bull market catalyst awaits a confirmed market bottom combined with a macro policy shift and legislative progress.

"VISReg: A New Self-Supervised Learning Method Tackles Representation Collapse in JEPA World Models" Yann LeCun has highlighted the new self-supervised learning (SSL) work VISReg (Variance-Invariance-Sketching Regularization), which addresses the core challenge of "representation collapse" in JEPA-based world models. SSL often collapses, mapping different inputs to similar vectors, losing discriminative power. While methods like VICReg and SIGReg attempted to regularize the representation distribution, they suffered from issues like vanishing gradients during collapse or coupled scale and shape optimization. VISReg overcomes these by decoupling the regularization into independent "scale" and "shape" objectives. It uses a variance term to prevent amplitude collapse (providing constant gradient even during collapse) and a sliced Wasserstein distance (SWD) based sketching target with stop-gradient to align the distribution shape to an isotropic Gaussian, without interfering with scale. This approach, requiring only ~15 lines of PyTorch core code, offers linear computational complexity and scales efficiently across multiple GPUs. Evaluated across 15 datasets (in-domain, out-of-distribution/OOD, dense prediction), VISReg outperforms 7 mainstream SSL methods (MoCoV3, DINO, iBOT, I-JEPA, MAE, data2vec) without relying on heuristic tricks like EMA or stop-gradient. Key results include: superior average OOD accuracy; matching DINOv2's OOD performance using only ~1/10 of the data (ImageNet-22K vs. LVD-142M); better transfer learning fine-tuning results across multiple datasets; and competitive performance in semantic segmentation and generative guidance. VISReg also demonstrates robustness on low-quality data like long-tailed or low-rank datasets where other methods fail. The work provides a more stable, efficient, and generalizable regularization solution for SSL and JEPA models.

Core Scientific reported a $41.9 million payment to terminate a contract with Block and its subsidiary Proto for the supply of Bitcoin mining chips. This move finalizes its exit from plans to grow its hash rate, shifting its business model entirely towards AI colocation. The agreement, announced in July 2024, was for 3nm chips providing roughly 15 EH/s of hash rate. Following the cancellation, Core Scientific stated it will no longer invest in new mining hardware to maintain or expand its cryptocurrency mining capacity. Instead, it will generate cash flow from its existing mining fleet while repurposing its data centers, potentially selling or decommissioning ASIC miners. In Q2 2026, revenue from AI colocation surged to $136.7 million from $10.6 million a year earlier, representing 83% of total revenue. In contrast, its own Bitcoin mining revenue fell 66% to $21.5 million. Quarterly Bitcoin production dropped 53% year-over-year. AI colocation capacity reached 437 MW by mid-July 2026, with CoreWeave accounting for all current hosting revenue and approximately 77% of Core Scientific's total revenue in H1 2026. The company also announced a partnership with AMD for up to 2.5 GW of potential data center capacity, with initial 15-year agreements for about 530 MW estimated to bring in over $14 billion in contract revenue. Total Q2 revenue grew to $164.2 million, while capital expenditures jumped to $797.5 million. As of June 30, 2026, the company reported long-term debt of $4.3 billion and free liquidity of $1.82 billion. The shift aligns with a broader industry trend of major Bitcoin miners accelerating a pivot to AI amid pressure on Bitcoin mining profitability.

Analysts from Bernstein revealed details of a deal between Core Scientific and AMD with a potential total value of over $14 billion. According to the report, initial contracts for 530 MW of capacity could generate this revenue over 15 years, with AMD acting as a credit guarantor for part of the bitcoin miner's infrastructure. The partnership, announced on July 28, has the potential to allocate up to 2.5 GW of data center capacity for AI. Bernstein broke down the 530 MW into 377 MW of direct triple-net lease for AMD and 152 MW for an unnamed cloud provider backed by AMD's credit. This structure is seen as lowering financing costs and counterparty risk. AMD also received warrants to buy 30 million Core Scientific shares at $23.47 each, which vest upon reaching the 2.5 GW target. Average annual revenue from the deal is estimated at around $0.9 billion, or about $1.8 million per megawatt, which is 5-25% below recent AI hosting deals by other miners. However, the 377 MW triple-net lease for AMD carries a margin close to 100%. Core Scientific expects capital expenditures for the deal to be $11-12 million per MW, totaling about $6 billion. Bernstein views this partnership as a new phase in the transformation of former bitcoin miners into AI infrastructure operators, with AI chipmakers like AMD now acting as direct anchor tenants. Recent similar deals include Hut 8 allocating 704 MW to a tenant believed to be Nvidia, and AMD reserving 200 MW with Riot Platforms. Core Scientific also paid Block $41.9 million to terminate a mining chip supply contract as part of its accelerated diversification into AI.