Agility
AGILSD Liquidity Layer & LSD Trading Platform
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Project Overview
Agility is both an LSD liquidity distribution platform and an aUSD trading platform. Its vision is to unlock liquidity for LSD holders and explore more LSD trading scenarios, as well as providing deep liquidity for other LSD-related protocols.
Gate launches KIMIUSDT (Moonshot AI) pre-market perpetual contract trading
according to official sources, Gate has now launched KIMIUSDT (Moonshot AI) pre-market perpetual contract trading (USDT settlement), supporting 1-10x leverage.Moonshot AI is an AGI unicorn independently developing general-purpose large models, ranking among the top tier of AI startups in China in terms of financing scale and technical performance.
Paradis Labs: Agility Plans Fourth Quarter SPAC Listing via CCXI, with Approximately $640 Million in Private Placement
Odaily Odaily Planet Daily reports that Paradis Labs announced on the X platform that Agility plans to go public via a SPAC merger with CCXI around the fourth quarter, with its stock ticker changing to AGLT. Its private placement fundraising amounts to approximately $640 million, with support from investors including AMZN, NVDA, SoftBank, DCVC, among others. Approximately 100 Digit humanoid robots have been deployed across 9 facilities including those of AMZN, GXO, Schaeffler, Toyota, and MELI. In Schaeffler's 8 deployed units and GXO's 3 pre-booked deployments, accuracy rates stand at around 98%. Agility states that the payback period for owning one Digit humanoid robot is approximately 1.1 years. Orders for Digit v5 exceed $300 million, with the version slated for release in 2026; the pipeline includes over 30 customers.Agility is the first company to utilize NVDA Halos for full-stack robotics safety. Its RoboFab facility in Oregon has an annual production capacity exceeding 10,000 units, with approximately 75% of components sourced from the United States. As annual production scales up to over 10,000 units, the bill of materials cost is expected to drop from $125,000 to approximately $15,000 to $20,000. Paradis Labs indicates that, combining technology and commercialization, Agility is the most advanced among Western humanoid robot OEMs; Figure's deployment at BMW remains controversial, TSLA currently does not sell any units externally, Apptronik has no current deployments, and Boston Dynamics has robotic products but its public listing progress is slower, with no customers expected at least until 2027.
DeepSeek sparks new round of "AI talent war"? Hiring for development, product, research, and various other positions
tonight, DeepSeek officially released recruitment information, stating that humanity is on the eve of AGI and inviting candidates to join DeepSeek to witness the development process of AGI. The recruitment information shows that open positions include full-stack development/algorithm, AI core system R&D, operations, product, model data strategy product manager/engineer, deep learning researcher, and functional departments. Work locations include Beijing and Hangzhou.Previously, several DeepSeek employees had been posting recruitment ads for various talents on platforms like Xiaohongshu and X, such as HR@一只大蜗牛 and Cui Tianyi from the Harness group. Earlier still, DeepSeek announced the completion of over $7 billion in financing, with a valuation exceeding $50 billion. The financing amounted to approximately RMB 50 billion, with Liang Wenfeng personally contributing RMB 20 billion. This large-scale recruitment may indicate a further escalation in the intensity of the domestic AI talent war, as AI professionals are entering a period of high market demand.
OpenAI Lawsuit: Microsoft CEO Satya Nadella Testifies in Court as Altman-Musk Dispute Escalates to Core Partnership Relations in the AI Giant
Odaily Odaily News: In the OpenAI lawsuit, Satya Nadella testified in court as Microsoft's CEO at the U.S. District Court in Oakland, California. The case centers on the ongoing legal dispute over OpenAI's non-profit structure and its path to commercialization. The lawsuit, filed by Elon Musk in 2024, accuses Microsoft of "aiding and abetting the breach of charitable trust obligations" during OpenAI's transition from a non-profit organization to a commercial entity. Microsoft has been making strategic investments in OpenAI since 2019, with cumulative investments reaching approximately $13 billion by 2023, making it one of OpenAI's most important external supporters.During the trial, Satya Nadella reviewed the early partnership between Microsoft and OpenAI, mentioning that the two parties had established deep technological and computing power collaboration before the launch of ChatGPT. In his earlier testimony, Musk stated that Microsoft's additional investment of approximately $10 billion in OpenAI in 2023 was the key turning point that prompted him to file the lawsuit, adding that the scale of the investment altered OpenAI's original non-profit-oriented structure. During the trial, Musk stated: "We are concerned they are turning a charitable organization into a commercial tool." He also questioned Microsoft's potential dominant position in the development of Artificial General Intelligence (AGI) and pointed out that its deep integration with OpenAI could impact the competitive landscape of the industry.The case is currently still under trial, and the debate surrounding OpenAI's governance structure, non-profit status, and control over the AI industry is expected to continue. (CNBC)
Serenity: US AI Companies Lower Inference Costs to Counter the "Model Distillation" Challenge
"White-Haired Stock Guru" Serenity stated that while some observations in the UBS report hold anecdotal truth, the more noteworthy trend is the increasing number of Chinese-language reports regarding the distillation of Anthropic's models. Currently, many US startups and tech companies are opting to use cheaper Chinese models (such as DeepSeek) in their AI applications, as their unit task costs are significantly lower than those of inference models from Gemini, OpenAI, and Anthropic.Serenity believes this trend, driven by capitalism, creates a "typical paradox"—companies naturally gravitate towards lower-cost solutions, thereby eroding the leading advantage of US models. He proposes that the US needs to address this on two fronts:First, build stronger access control and authentication systems, such as "heavy KYC frontier models" for domestic US use and tiered access mechanisms for allies, to reduce the risk of model distillation and misuse. This could also be accompanied by introducing an identity verification system akin to "AI-grade banking authentication" (e.g., biometrics + short-lived permission tokens) to raise the barrier for model calls, and using regulatory measures to restrict account sharing and access resale.Second, enhance the cost efficiency of inference models, allowing them to comprehensively outperform competitors like DeepSeek in both price and performance.Serenity also noted that some high-end models are currently frequently targeted for "distillation exploitation." Ideally, access to models nearing the AGI level should involve increased friction costs. In summary, the core challenge for the US AI industry lies in achieving both "low-cost inference capabilities" and establishing model access security mechanisms comparable to those in the financial system.
Viewpoint: Mythos’ breach of the NSA signals that AGI is drawing near; 9% inflation will not become the norm
Anthony Pompliano, Chairman of Bitcoin treasury company ProCap Financial, posted on X stating that Mythos allegedly breached the U.S. National Security Agency’s (NSA) classified systems within hours—a development that will further intensify public concerns about AI risks and prompt increased regulatory intervention. Yet the more critical signal conveyed by this incident is that AGI (Artificial General Intelligence) is, in fact, drawing near. Current AI technologies not only surpass humans in capability but are also self-training and improving at an incomprehensible pace—“humans cannot compete with these models.”
Meta, Google, and Other Tech Giants Face the Allocation Problem of AI Computing Power for Internal Use vs. Sales
during the company's second-quarter earnings call, Meta CEO Mark Zuckerberg stated that Meta currently does not have a business selling computing power to customers, but such offerings are in the plans. He indicated that a significant portion of Meta's computing power will be used for training AI models, supporting agent products, and developing core businesses, while the company also anticipates expanding services to large enterprise clients.Both Google and Meta have slightly raised their capital expenditure expectations for this year. Google stated that related spending could increase further in 2027, while Microsoft maintained its capital expenditure forecast. Google's cash flow turned negative for the first time in the second quarter, and Meta's cash flow decreased by 91% compared to the same period last year.Microsoft CFO Amy Hood noted that customer demand for its cloud business still exceeds available capacity. Google said last week that it will purchase more third-party computing power while building more internal capacity to meet customer needs.Google CEO Sundar Pichai stated that the primary objective for Google in using its self-developed tensor processing units (TPUs) is to ensure the allocation of necessary resources for the development of AGI frontiers. Google is working with partners to deploy TPUs in other data centers to unlock more capacity.
Gate launches KIMIUSDT (Moonshot AI) pre-market perpetual contract trading
according to official sources, Gate has now launched KIMIUSDT (Moonshot AI) pre-market perpetual contract trading (USDT settlement), supporting 1-10x leverage.Moonshot AI is an AGI unicorn independently developing general-purpose large models, ranking among the top tier of AI startups in China in terms of financing scale and technical performance.
Vitalik Publishes Long Essay Reflecting on AI Evolution: Deep Human-Machine Integration May Be the Optimal Solution to Address AGI Risks
According to a series of tweets posted by Ethereum co-founder Vitalik Buterin on X on July 20, he engaged in deep reflection on AI capability growth and the future of humanity. Vitalik divides the evolution of machine capabilities into three stages: the Industrial Revolution (physical repetitive labor), the Computer Age (mental tasks definable by logic), and the LLM Era (mental and partial physical tasks defined based on massive samples). He points out that the current core question lies in: whether LLMs plus subsequent improvements can ultimately cover all unique human capabilities, or if a fourth or fifth technological wave is still needed. Regarding the definition of AGI, Vitalik proposes: AGI refers to AI that, if uploaded into a robotic body and humans suddenly disappear, can still independently continue civilization. He emphasizes that once AGI is realized, it will be an "irreversible turning point," and humanity's dominance over Earth will remain only due to historical inertia rather than capability advantage. Regarding the future path, Vitalik hopes for deep human-machine integration—erasing the human-machine binary boundary through technologies such as brain-computer interfaces and consciousness uploading, enabling humans to remain competitive before the technology ceiling arrives. He also calls for maintaining global political and economic diversification, avoiding monopolization of AI advantages by a single nation or corporation, and expresses support for AI development "slowdown" and "pause" proposals, leaning towards achieving decentralized slowdown via an open-source weights model rather than relying on coercive political means.
Serenity: Institutions Begin to Revalue Humanoid Robot Businesses, Chinese Manufacturers' Overall Production Capacity Expected to Reach 100,000 Units by Year-End
"White-Haired Stock Guru" Serenity posted on X platform, pointing out that IBK Research released a report last month on the Boston Dynamics supply chain. The report indicates that Boston Dynamics plans to achieve an annual production capacity of 30,000 units only by 2028, while Chinese robot manufacturers are expected to reach a total production capacity of 100,000 units by the end of 2026. This may lead institutions to begin revaluing the humanoid robot sector.In terms of the competitive landscape, the U.S. camp includes Tesla, Figure, Apptronik, and Agility Robotics, while Boston Dynamics is controlled by South Korea's Hyundai Motor Group. Major Chinese players include Unitree Robotics, Fourier Intelligence, AGIBOT, UBTECH Robotics, and XPeng Robotics. European companies include Neura, Pal Robotics, Wandercraft, and Oversonic.Additionally, IBK Research estimates that Atlas shipments will reach 11,290 units by 2028, and will increase to 20,000, 30,000, 40,000, and 50,000 units respectively between 2029 and 2032. However, Serenity questioned this linear growth model, arguing that the actual volume ramp-up curve is more likely to follow an S-curve. Serenity predicts that shipments could reach 15,000 to 20,000 units by 2028, increase to 40,000 to 70,000 units by 2029, and further rise to 90,000 to 140,000 units by 2030.
GPT-5.6 Full Series Models Officially Integrated into B.AI API Network
B.AI announces that OpenAI's latest generation GPT-5.6 full lineup of models has officially been integrated into the B.AI API network. Effective immediately, developers can directly access three distinctly positioned models through B.AI's single interface: GPT-5.6 Sol specializes in ultimate reasoning and complex tasks; GPT-5.6 Terra is perfectly suited for daily workloads; GPT-5.6 Luna prioritizes ultra-fast response and cost-efficiency. Whether you are building agents, optimizing workflows, or exploring the boundaries of AGI applications, B.AI provides you with flexible and stable compute support. Log in to the B.AI platform now to unlock the full capabilities of GPT-5.6 and let the next generation of AI work for you.
B.AI Will Make Its Debut at WebX 2026 Conference, Now Launching the "Treasure Hunt Journey" Rewards Event
B.AI has officially launched the "B.AI x WebX 2026 Treasure Hunt" reward campaign and confirmed its participation in the WebX 2026 conference held in Tokyo, Japan, accelerating the expansion of its AGI global footprint. To celebrate this debut in Japan, an interactive lucky draw event officially goes live from July 9 to July 15. Participants who follow the official account (@BAI_AGI), retweet the post, write down one thing they most want to achieve with B.AI, add the hashtag #BAIWebXJapan, and tag three friends can share the base prize pool of 100 USDT; if the number of participants exceeds 500, the total prize pool will be upgraded to 300 USDT. In addition, during this WebX conference, B.AI will unveil more exciting content centered around AI Credits and offline interactions, securing exclusive benefits for global ecosystem builders ahead of the conference opening.
Related news
Meta, Google, and Other Tech Giants Face the Allocation Problem of AI Computing Power for Internal Use vs. Sales
during the company's second-quarter earnings call, Meta CEO Mark Zuckerberg stated that Meta currently does not have a business selling computing power to customers, but such offerings are in the plans. He indicated that a significant portion of Meta's computing power will be used for training AI models, supporting agent products, and developing core businesses, while the company also anticipates expanding services to large enterprise clients.Both Google and Meta have slightly raised their capital expenditure expectations for this year. Google stated that related spending could increase further in 2027, while Microsoft maintained its capital expenditure forecast. Google's cash flow turned negative for the first time in the second quarter, and Meta's cash flow decreased by 91% compared to the same period last year.Microsoft CFO Amy Hood noted that customer demand for its cloud business still exceeds available capacity. Google said last week that it will purchase more third-party computing power while building more internal capacity to meet customer needs.Google CEO Sundar Pichai stated that the primary objective for Google in using its self-developed tensor processing units (TPUs) is to ensure the allocation of necessary resources for the development of AGI frontiers. Google is working with partners to deploy TPUs in other data centers to unlock more capacity.
Amazon Restructures AI Strategy, Gradually Phasing Out Most Nova Flagship Models and Betting on Frontier Model R&D
According to Business Insider, citing sources familiar with the matter, Amazon is comprehensively adjusting its artificial intelligence strategy. Following layoffs in the AGI department and the closure of related laboratories, the company is further consolidating fragmented model R&D directions. The company plans to gradually phase out most internal flagship Nova models, including Premier, Omni, Reel, and Canvas, and will concentrate engineering and compute resources on new frontier model development plans.
Three of the Four 2026 Fields Medalists Announce They Will Not Shift to AI Research
Three Out of Four 2026 Fields Medalists Announce They Will Not Shift to AI Research At the 2026 International Congress of Mathematicians, three of the four Fields Medalists publicly stated they would not shift to AI research, despite believing their work would soon be automated by AGI. In its report, SemiAnalysis cited computer scientist Dijkstra's viewpoint, commenting that programming is one of the hardest fields in applied mathematics, and weaker mathematicians had better remain in pure mathematics research. The Fields Medal is one of the highest honors in the mathematics community, awarded every four years to mathematicians under 40 who have made outstanding contributions. This stance reflects the complex attitude of top mathematicians towards the impact of AI.
Liang Wenfeng: The Most Important Thing Now Is Coding Agent, the Long-Term Goal Remains AGI
that, according to "elsewhere," it has compiled and organized 52 statements made by DeepSeek founder Liang Wenfeng during a previous meeting. Liang Wenfeng stated that DeepSeek currently has only one main line, which is the technical route towards AGI. Products are merely "byproducts" of this process. The most important direction at this stage remains the Coding Agent. Following that, the focus will be on solving continuous learning, before further achieving AI self-iteration and ultimately moving towards embodied intelligence.In terms of commercialization, Liang Wenfeng indicated that DeepSeek does not pursue profit maximization, only obtaining reasonable profits. Open source and low pricing are both part of a "restrained" strategy. The goal is not to compete for more market share, but to increase the probability of ultimately achieving AGI. He also stated that DeepSeek has no intention of becoming the next super app, nor will it make directions such as 3D, video generation, or world models its current main focus.When discussing major model competition, Liang Wenfeng believes that the future gap will mainly be reflected in cost, time, and user experience, with cost being the most important. He also added that maintaining team stability is the company's "only non-negotiable" matter.
Gate launches KIMIUSDT (Moonshot AI) pre-market perpetual contract trading
according to official sources, Gate has now launched KIMIUSDT (Moonshot AI) pre-market perpetual contract trading (USDT settlement), supporting 1-10x leverage.Moonshot AI is an AGI unicorn independently developing general-purpose large models, ranking among the top tier of AI startups in China in terms of financing scale and technical performance.
Vitalik Publishes Long Essay Reflecting on AI Evolution: Deep Human-Machine Integration May Be the Optimal Solution to Address AGI Risks
According to a series of tweets posted by Ethereum co-founder Vitalik Buterin on X on July 20, he engaged in deep reflection on AI capability growth and the future of humanity. Vitalik divides the evolution of machine capabilities into three stages: the Industrial Revolution (physical repetitive labor), the Computer Age (mental tasks definable by logic), and the LLM Era (mental and partial physical tasks defined based on massive samples). He points out that the current core question lies in: whether LLMs plus subsequent improvements can ultimately cover all unique human capabilities, or if a fourth or fifth technological wave is still needed. Regarding the definition of AGI, Vitalik proposes: AGI refers to AI that, if uploaded into a robotic body and humans suddenly disappear, can still independently continue civilization. He emphasizes that once AGI is realized, it will be an "irreversible turning point," and humanity's dominance over Earth will remain only due to historical inertia rather than capability advantage. Regarding the future path, Vitalik hopes for deep human-machine integration—erasing the human-machine binary boundary through technologies such as brain-computer interfaces and consciousness uploading, enabling humans to remain competitive before the technology ceiling arrives. He also calls for maintaining global political and economic diversification, avoiding monopolization of AI advantages by a single nation or corporation, and expresses support for AI development "slowdown" and "pause" proposals, leaning towards achieving decentralized slowdown via an open-source weights model rather than relying on coercive political means.