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ust

UST is an algorithmic stablecoin in the Terra blockchain ecosystem, designed to maintain a value peg to the US dollar through smart contract mechanisms. The supply of UST is dynamically adjusted based on market demand to ensure price stability. As a core component of the Terra platform, UST is widely used in payments, lending, and decentralized finance (DeFi) applications. Its design goal is to provide a stable value storage and medium of exchange without the support of centralized institutions.
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first_img Data: In the first half of 2026, there were only 2,932 active job openings in the cryptocurrency industry, a drop of over 97% compared to the peak in 2022

According to the latest report from Tiger Research, as of June 18, 2026, the number of active job openings in the cryptocurrency industry is only 2,932, a significant decrease of over 97% from the estimated peak of about 130,000 in 2022.The report shows that the wave of layoffs in the cryptocurrency industry continues in the first half of 2026. March was the month with the highest concentration of layoffs, with several companies including Gemini, Crypto.com, Algorand, OP Labs, PIP Labs, and Messari announcing layoffs at the same time. Some companies were acquired at low prices after multiple rounds of layoffs; for example, Messari was acquired by Blockworks for about $10 million in June 2026 after experiencing three rounds of layoffs, while its previous valuation had reached $300 million.In terms of recruitment structure, positions in centralized exchanges (CEX) account for the highest proportion, reaching 30.8% (904 positions), mainly contributed by OKX, Bybit, and Binance. The stablecoin and payment sector accounts for 13.4%, but is highly concentrated in two companies, Tether and Ripple.In addition, the demand for AI skills in job postings continues to rise, with the proportion of cryptocurrency job postings mentioning artificial intelligence skills increasing from 23% in early 2025 to 53.1% in March 2026.

Chainalysis plans to launch an on-chain tracking standard system, proposing an "address clustering ontology" to unify blockchain forensic methods

According to CoinDesk, blockchain analysis company Chainalysis has released a new methodological proposal aimed at establishing a unified on-chain fund tracking standard framework for law enforcement agencies and investigators, to identify address clusters and determine their possible control relationships.The proposal defines the on-chain analysis structure in the form of "ontology," focusing on systematically breaking down the currently unstandardized concept of "cluster" in the industry into wallet segments and functional roles, and describing on-chain relationships through a two-layer structure: the first layer defines the transaction graph structure, and the second layer assesses inference confidence.Chainalysis stated that the framework aims to enhance the interpretability and legal applicability of on-chain forensic methods, and is designed and validated based on its practical experience in relevant cases within the U.S. Department of Justice, including the analytical application in the mixing service Bitcoin Fog case.The company's Chief Scientist Jacob Illum pointed out that the goal of the proposal is to answer "on what evidence basis can these addresses be considered to belong to the same entity," while emphasizing that on-chain analysis itself cannot directly identify the ultimate user identity and still requires legal investigative methods combined with centralized entities such as exchanges.Chainalysis indicated that the standard proposal is currently open for discussion within the industry, hoping to promote the formation of more unified technical specifications for on-chain analysis methods in the fields of law enforcement and compliance.

Kimi B's head of the department: There is a bubble in the AI industry, but the fundamentals are solid; the price increase of APIs is due to tight computing power

According to a report by 21 Finance, Huang Zhenxin, the head of Kimi B-end at Moonshot AI, stated in a recent communication meeting that there is indeed a bubble in the current AI industry, but the fundamentals are very solid. Enterprises can now clearly calculate the return on investment (ROI), and the substantial transformation in productivity brought by AI has already occurred.Regarding the recent phenomenon of widespread price increases among model vendors, Huang Zhenxin pointed out that the core reason lies in the rising global computing power costs, and chip production capacity cannot meet the explosive growth in Token demand. He emphasized that evaluating the cost-performance ratio of models should not only look at the unit price of input and output but should also focus on the Cache hit rate. It is reported that Kimi's original factory Cache hit rate has reached over 90%, significantly reducing actual computing costs.In addition, Huang Zhenxin revealed that Kimi will continue to challenge innovations in underlying architecture to sustain the Scaling Law, and its Muon optimizer, which has been validated on a large scale, is now widely adopted by several mainstream large models in the industry. Regarding the "last mile" of enterprise AI implementation, he believes that as the foundational capabilities of models continue to strengthen, the technical paradigms at the application layer will also continue to simplify.

FTC approves Musk's acquisition of Mesh antitrust application, involving AI data center optical network layout

According to the latest disclosure by the Federal Trade Commission (FTC), Musk has obtained antitrust approval for the acquisition of the optical network startup Mesh Optical Technologies, which means the FTC has completed a rapid antitrust review and will not challenge the transaction on competitive grounds, clearing a major regulatory hurdle for the advancement of the deal. However, it has not yet been disclosed whether the transaction has been signed or completed.Mesh was founded by former SpaceX engineers, and its core product is optical transceivers for AI data centers, which can improve energy efficiency, reduce latency, and enhance reliability compared to traditional network hardware, in order to meet the demand for millions of optical connections brought about by the growth of AI computing clusters. The founding team was involved in the development of the laser communication system for SpaceX's Starlink satellite network and plans to deploy optical communication technology into space in the future, adapting to the inter-satellite laser communication needs of orbital data centers and AI satellite networks. The company completed over $50 million in financing led by Thrive Capital in February of this year.Acquiring Mesh is one of SpaceX's initiatives to strengthen the competitiveness of large-scale computing clusters. Currently, SpaceX has listed AI computing power as a core business segment, and its xAI has been operating a total of approximately 1GW computing power with the Colossus and Colossus II training clusters, making it the first company to deploy coherent gigawatt-level AI training clusters; among them, Colossus II will add over 400MW of computing power and introduce over 220,000 GB300 chips. It has signed computing power cooperation agreements with Anthropic, Google, Reflection AI, and others, directly competing with large-scale cloud providers such as Amazon Web Services, Microsoft Azure, and Google Cloud. This year, SpaceX has also reached a Terafab chip manufacturing plan with Tesla and Intel, extending its vertical integration capabilities in chip design and manufacturing.In the past week, SpaceX's stock price ended its upward trend, closing at $153.23 per share, down over 32% from its peak of $225.64 per share.

OpenAI has launched the next generation GPT-5.6 series models, currently available only to trusted partners using Codex and the API

According to official news, OpenAI has officially launched the preview version of the next-generation GPT-5.6 series models, including the flagship model Sol, the balanced model Terra, and the fast low-cost model Luna. GPT-5.6 introduces a brand new maximum reasoning effort and features a super strong mode that accelerates complex tasks through sub-agents.The flagship model Sol introduces the Ultra mode, which combines maximum reasoning intensity with sub-agent collaboration. In the Terminal-Bench 2.1 command line workflow test, Sol achieved a score of 88.8%, which increased to 91.9% in Ultra mode, surpassing GPT-5.5's 83.4% and Claude Fable 5's 88.0%. The mid-range model Terra performs close to GPT-5.5 while being priced at half, and the lightest model Luna is designed specifically for everyday automation tasks. Sol is priced at $5 per million input tokens and $30 for output, and it supports reducing secondary call costs by utilizing prompt caching.In terms of security, the security assessment confirmed that Sol did not exceed the critical thresholds of the Preparedness Framework cybersecurity. OpenAI has invested over 700,000 A100 equivalent GPU hours in automated red team exercises, equipping the entire series of models with a defense stack that includes rejection mechanisms, real-time abuse classifiers, and account-level audits. Although the current limited release follows the U.S. government's security framework, OpenAI emphasizes that it does not want a government-led access mechanism to become the long-term default model, as it would limit defenders' access to cutting-edge tools.
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