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Ethereum co-founder Vitalik Buterin published a new article titled "Obfuscation (Part 3): Local Mixing," which delves into a cryptographic obfuscation technique being explored—"Local Mixing." He claims it may become a new foundational cryptographic tool following elliptic curves, RSA, and lattice-based cryptography.Vitalik states that current mainstream obfuscation techniques mainly rely on complex mathematical assumptions, often resulting in extremely high computational overhead. In contrast, Local Mixing adopts a completely different approach, not relying on elliptic curves, large integer factorization, or lattice cryptography. Instead, it draws on experiences from symmetric cryptography and hash function design, continuously shuffling, reconstructing, and hiding circuit structures to eliminate information leakage while maintaining functionality.The Local Mixing technique primarily includes steps such as reversibility, hardening, mixing, splitting, crossing walk, and "gadgetization." By introducing random structures into the circuit, rearranging logic gates, and employing nonlinear hiding mechanisms, it makes it difficult for attackers to recover the original computational logic.Vitalik points out that this technology is still in its early stages, with security not yet validated over the long term and facing challenges such as random attacks and linear analysis. However, he believes that Local Mixing represents a completely new path for cryptographic exploration, aiming to construct more efficient indistinguishable obfuscation (iO) schemes.If breakthroughs in Local Mixing technology are achieved, it could lead to new quantum-resistant public key encryption schemes and promote the development of general obfuscation techniques. The field still requires years of cryptanalysis and optimization validation, but AI-assisted research may significantly accelerate this maturation process. Vitalik states that obfuscation technology is seen as the "final frontier" of cryptography because, theoretically, other cryptographic primitives can be constructed based on obfuscation and one-way functions. Local Mixing may not only reduce the costs of traditional obfuscation schemes but could also become an important direction for future cryptographic infrastructure.

Former NVIDIA research scientist Sanja Fidler announced the co-founding of VeedaAI with long-time collaborators ZGojcic and HuanLing6. The company is dedicated to building simulated realities for Physical AI, serving as a key infrastructure layer for robotic interactive learning and evaluation, allowing robotic intelligence to learn at scale through trial and error in virtual worlds.Fidler stated that real-world trial and error training for robots is unsafe, costly, and time-consuming, necessitating the use of simulated realities to achieve scalable interactive learning. The team believes that world models are the core technology, capable of learning from vast amounts of sensor and physical world data to generate simulated environments with quality, diversity, and physical realism. VeedaAI has received support from Khosla Ventures and Radical Ventures, and team members have years of experience in simulation, generative AI, 3D, robotics, and embodied intelligence.

Bitget CFD announces the official launch of the sub-account feature, aimed at providing institutional clients, professional trading teams, and high-net-worth users with more refined multi-strategy management, achieving 100% physical isolation between different strategies and positions. Sub-accounts share the main account's KYC status, eliminating the need for repeated authentication. By default, up to 5 independent CFD accounts can be created with one click, supporting the deployment of different strategies such as EA, high-frequency trading, long-term trends, and hedging in independent accounts, ensuring that various strategies operate in a clean and independent environment.At the same time, the main account can uniformly view the real-time net value, margin ratio, current orders, and historical orders of each sub-account, and retains the authority to reset the trading password and read-only password for sub-accounts, to meet the needs of professional teams in account management, permission control, and internal risk control. Risk notifications such as additional margin requirements and forced liquidation warnings for each sub-account will also independently reach the corresponding email and App Push, further enhancing the efficiency of multi-strategy collaboration and risk response.

Justin Drake posted on the X platform that Ethereum L1 will no longer use the SNARK-friendly hash function Poseidon, which has dominated since 2019, and will instead turn to traditional hash functions such as SHA2 or BLAKE2s.This adjustment is based on advancements in the field of SNARK design, shifting the focus from "SNARK-friendly hashing" to "hash-friendly SNARK." By aligning Boolean operations in traditional hashing with binary field native, the proof performance of traditional hashing in SNARK has reached 1 million per second, with an overhead of about 100 times.Research from Binius and Flock has driven relevant progress. The Ethereum Foundation's post-quantum team is advancing this route, with a roadmap that includes deploying production-level leanVM in 2027, and deploying in the consensus layer, execution layer, and data processing layer in 2028.Justin Drake also stated that the enhanced capabilities of AI in cryptanalysis have recently led to setbacks for the lattice-based scheme HAWK and the homomorphic scheme SQIsign, with hash-based schemes being used for post-quantum signatures on the blockchain. The trend of open-source automated research is also accelerating, with SNARK.fast achieving 1.8 million BLAKE3 proofs per second.

According to official news, OpenAI has released research results stating that its next-generation AI model Astra has made progress in the fields of mathematics and theoretical computer science, involving areas such as high-dimensional geometry, coding theory, group theory, quantum complexity, post-quantum cryptography, and extremal combinatorial mathematics. The 10 published results include: the high-dimensional sphere packing problem, binary and spherical coding problems, non-sofic group problems, Connes rigidity conjecture, arithmetic circuit complexity problems, quantum parallel repetition problems, nearest vector problems, Ehrhart volume conjecture, multi-color Ramsey number problems, and extremal graph theory conjectures.It is reported that these results were derived using an internal version of the Astra model, with the computational cost of finding solutions amounting to approximately $2000 (calculated based on Sol API prices).Subsequently, human researchers used the same model to assist in compiling the results into a paper and generated verifiable proof certificates through the Lean formal proof system.

Quantum Dynamics, a Physical AI platform company, recently completed a seed round financing of over 100 million yuan, jointly invested by Yunqi Capital and SenseTime. The company's founder was the CTO of Cainiao Group and also the technical leader of Alibaba's international digital business sector.The funds will primarily be used for the research and development of core Physical AI technologies, talent team building, and global market expansion, accelerating the full-link construction of intelligent systems aimed at the physical world from underlying models to scenario-based implementation. Quantum Dynamics was established in the first half of 2026, focusing on the deep integration of AI and the real physical world, developing its own underlying platform for Physical AI applicable across all industries.

According to a report by The Information citing informed sources, a Shanghai state-owned company whose name has not been disclosed has begun producing domestically-made immersion DUV lithography machines, planning to manufacture about 5 units this year and increase to about 20 units by 2027. The first batch of equipment will be delivered to major foundries such as SMIC, Hua Hong Semiconductor, and ChangXin Technology, but the equipment still needs to undergo verification for accuracy, stability, and production line compatibility, a process that may take several months or even longer.Currently, most components of the equipment come from domestic sources, but some key parts still rely on Japan, and the performance and manufacturing quality lag behind ASML. In comparison, ASML is set to deliver about 131 immersion DUV lithography machines as early as 2025. Although domestic equipment has made the leap from prototype testing to small-scale production, there is still a significant gap before it can replace ASML on a large scale. Previously, Reuters reported that the U.S. is considering tightening restrictions on the export of lithography equipment to China and on maintenance services in China, and the delivery of domestic equipment coincides with this backdrop.

According to The Block, Physical AI data engine company Axis Robotics has completed a $12 million seed round of financing, led by Hack VC, with participation from Nomad Capital, Pi Network Ventures, 10K Ventures, and others.Axis plans to build a large-scale "human-in-the-loop" global data engine to address the scarcity of training data for robots, difficulties in generalization, and compatibility issues with different hardware. Its platform covers task generation, simulation remote operation, mobile Ego data collection, and automated cleaning and labeling pipelines. Currently, it has over 100,000 active data contributors, generating approximately 1,200 hours of simulation data and 20,000 hours of real-world scenario data each month, and has established commercial partnerships with several hardware and industrial clients, including Booster Robotics and Geely Auto.

Bitget launches the "Flash Football Cup" contract trading event, which runs from July 13 to July 20. During the event, users who complete the specified contract trading volume tasks can receive corresponding USDT rewards; if users reach the specified threshold of cumulative contract trading volume within 72 hours after registration, they can also receive an additional viewing-related gift.In addition, users who complete tiered trading volume tasks can earn points, which can be used to redeem World Cup-related physical merchandise and USDT rewards. The physical prize pool includes signed jerseys from stars like Cristiano Ronaldo, Lionel Messi, Erling Haaland, and Luka Modrić, as well as special edition collectibles from Wuliangye and Labubu.

Crypto KOL Phyrex published a system analysis of rToken issued by Reality under Bitget, believing that rToken should not be understood merely as "tokenized stocks." Its core value lies in achieving asset composability after connecting to a unified account, breaking the limitations of RWA liquidity islands.Phyrex focused on three directly implementable trading strategies: amplifying directional exposure to US stocks, Delta Neutral arbitrage, and staking lending cycles. For institutions, the core value of rToken lies in three major mechanisms: direct order connection to the US stock order book to achieve no de-pegging risk, UTA unified account joint margin to enhance asset efficiency, and weekend collateral valuation anchored to Friday's closing price to ensure controllable risk, ultimately enabling the management of Crypto, stock tokens, and derivative positions within the same account, reducing the costs of multi-platform rebalancing and fund transfers.

According to PR Newswire, QIZ Security announced the completion of a $17 million seed round financing, led by Bessemer Venture Partners and Merlin Ventures, with participation from Evolution Equity Partners, Qbeat Ventures, Singtel Innov8, Qino Cyber Capital, and others.The company positions itself as a management platform for crypto assets and post-quantum cryptography (PQC), providing continuous crypto asset discovery, risk modeling, and governance, helping large clients in finance, telecommunications, healthcare, and critical infrastructure achieve "crypto agility" to address the risk of "Q-Day," when quantum computing capable of breaking existing encryption systems may emerge as early as 2029, and collaborates with Cisco, AWS, Google, CrowdStrike, Deloitte, EY, IBM, and others to promote enterprise quantum security migration planning.

According to the Economic Times, the physical AI startup Mowito has completed a $3 million Pre-Seed round of financing, led by Version One Ventures, with participation from All In Capital, Unisol, and iSeed. AI researcher Soumith Chintala and founders from Foundry Robotics, Coformer.ai, Better Capital, and others participated as angel investors.Mowito was founded in 2024 by Puru Rastogi, Adityanag Nagesh, and Safar V. It builds AI foundational models for industrial robotic arms, addressing the bottleneck of software programming in manufacturing automation by allowing robots to learn tasks through human demonstration rather than explicit programming—engineers do not need to rewrite control code when product lines change. Mowito's software can run on standard, unmodified industrial robots, serving automotive and electronics manufacturing clients. This round of financing will be used for expansion into the U.S. market, expanding engineering and marketing teams, and deepening deployment in manufacturing sites.

Vanguard Group's recruitment information shows that it is hiring a Head of Digital Assets for its Personal Wealth business. The job requirements include over 10 years of relevant experience, a deep understanding of digital assets (tokenization, stablecoins, custody, settlement, etc.), and the ability to innovate and manage risks within a regulatory environment.This position will be responsible for developing Vanguard's strategy, roadmap, and execution in the digital asset space, including assessing digital asset capabilities, product development, operational models, and cross-functional collaboration with departments such as product, technology, operations, risk, legal, and compliance. Additionally, it will represent Vanguard in external communications with industry participants, regulatory agencies, and clients.It is reported that Vanguard has allowed brokerage clients to trade crypto ETFs and mutual funds since last December, but the company has clearly stated that it has no plans to issue its own crypto investment products, believing that digital assets are still inconsistent with its long-term investment philosophy.

On July 1, according to WEEX TradFi data, the recent performance of the US stock technology sector has been mixed, with funds continuously focusing on Physical AI, robotics, and related supply chain directions that have actual implementation expectations. Among them, AMD rose about 7.7% in 24 hours, Symbotic (SYM) rose over 6.6%, Texas Instruments (TXN) rose about 4.4%, NVIDIA (NVDA) rose about 2.6%, Tesla (TSLA) rose about 2.1%, and Analog Devices (ADI) rose about 1.4%.WEEX Labs believes that market funds are shifting from a single computing power narrative to core links in the Physical AI supply chain with implementation expectations, including Tesla's Optimus production line transformation and NVIDIA's Physical AI Day, which continuously strengthen expectations for hardware and software collaboration, leading to increased attention in related sectors.

According to Jinshi News, Nvidia has released "Halos for Robotics," which is the industry's first full-stack safety system for physical artificial intelligence.

According to the Nikkei Asia report, the Japanese government recently announced plans to achieve over 370 trillion yen (approximately 15.59 trillion yuan) in public-private joint investment in 17 strategic areas by fiscal year 2040. Among these, approximately 10.5 trillion yen (about 442.3 billion yuan) will be specifically allocated to the field of physical AI.It is reported that the Japanese government expects physical AI technology to play a key role in scenarios such as industrial automation, unmanned transportation, and infrastructure inspections, to alleviate the labor shortage caused by the intensifying aging population and the imbalance between labor supply and demand, thereby comprehensively enhancing productivity. In addition, to mitigate the potential risks of high-performance artificial intelligence, Japan also announced a new AI policy draft last week, planning to further strengthen relevant threat control and safety assessment mechanisms.