Crypto KOL Ansem has continued pumping his eponymous meme coin, with ANSEM’s market cap briefly surging past $78 million.

According to monitoring by Beating, a16z co-founder Marc Andreessen noted that many AI practitioners and industry insiders consider Zhipu GLM-5.2 to be the first Chinese AI model that can match or even outperform open models from leading U.S. labs on most tasks, while also being balanced across multiple capability dimensions. This development carries "extremely critical timing significance" amid accelerating global AI competition, as large model capabilities are gradually shifting from being dominated by a small number of U.S. labs to a multipolar competitive landscape. Click the original link below to join Beating’s Feishu AI News Channel, which provides 24/7 uninterrupted monitoring of global AI hotspots and news.

Michael Saylor, founder of MicroStrategy, has once again shared updates on Bitcoin Tracker, remarking, “We are gonna need more charts.” Per historical trends, MicroStrategy typically announces increases to its Bitcoin holdings the day after such statements.

BofA Securities chief strategist Michael Hartnett outlined three thresholds for a "full risk-off" trigger this summer in his latest Fund Flow Report: the Mag7 ETF falling below $60, USD/JPY dropping below 110, and the yield curve inverting again. None of these conditions have been met yet, but related signals are building. U.S. stock funds posted a net outflow of $8.5 billion, the first such outflow since March, following a historic $119.2 billion net inflow. The divergence where hyperscale cloud providers continue to underperform chip stocks has pushed the sustainability of AI capital spending to the core of market debate: Apple’s MacBook price hikes and Microsoft’s Xbox price increases are both directly tied to rising memory costs. Rack memory prices at Vera Rubin have surged by 435% cumulatively, and Goldman Sachs forecasts AI capital spending could reach as high as $1.4 trillion by 2027. Hartnett’s core ongoing question is: How much further do cloud providers need to fall before the market starts pricing in capital spending cuts? U.S. equity funds have shifted ahead of the curve, with liquidity flowing out of tech giants and into cyclical assets including semiconductors, small-caps, housing, and REITs — a move the market interprets as a front-run bet on a policy shift toward "affordability". For asset classes, Hartnett believes gold remains highly valuable for allocation below $4,000, and going long on long-dated U.S. Treasuries is currently the most contrarian long-term trade. The U.S. dollar is only suitable for short-term holding rather than long-term allocation, while going long on emerging markets over the long term is his strategic stance. Since Fed Chair Waller took office on May 22, U.S. Treasuries have risen by 3.2% cumulatively, while stocks have fallen by 1.6%, with bonds outperforming significantly.

Bank of America Securities chief strategist Hartnett outlined three triggers for a "full risk-off" environment this summer in his latest Fund Flow Report: Mag7 ETF falling below $60, USD/JPY dropping below 110, and the yield curve inverting again. None of these conditions have been met yet, but signals are building. U.S. equity funds have posted a net outflow of $8.5 billion, the first such outflow since March, following a historic $119.2 billion net inflow. The divergence where hyperscale cloud providers continue to underperform chip stocks has put the sustainability of AI capital expenditure at the center of market debate: Apple’s MacBook price hikes and Microsoft’s Xbox price increases are both directly tied to rising memory costs. Vera Rubin rack memory prices have surged 435% cumulatively, and Goldman Sachs projects AI capital expenditure could reach as high as $1.4 trillion by 2027. Hartnett’s core ongoing question is: How much further do cloud providers need to fall before the market begins pricing in capital expenditure cuts? U.S. equity funds have already shifted ahead of time; liquidity flowing out of tech giants is pouring into cyclical assets like semiconductors, small-caps, housing, and REITs, a move the market interprets as a front-run bet on policy shifting toward "affordability." At the asset class level, Hartnett believes gold still holds strong allocation value below $4,000, and going long on long-dated U.S. Treasuries is the most contrarian long-term trade right now. The U.S. dollar is only suitable for short-term holding rather than long-term allocation, and his strategic view is to go long on emerging markets over the long term. Since Fed Chair Waller took office on May 22, U.S. Treasuries have risen 3.2% cumulatively, while stocks have fallen 1.6%, with bonds significantly outperforming.

Samsung Electro-Mechanics is in final negotiations with a major U.S. tech firm over a supply contract for MLCCs (multi-layer ceramic capacitors) for AI servers. Worth around 500 billion won, the deal equals 10% of its component division’s annual revenue last year, making it an extremely large-scale order. Industry sources speculate the client is a leading player with significant clout in the data center sector. Each AI server requires 15,000 to 25,000 MLCCs—over 10 times the number used in a smartphone—with a unit price more than triple that of smartphone-grade MLCCs, earning the component the nickname "golden rice of the AI industry". Samsung Electro-Mechanics currently holds the No.2 position in the global MLCC market with a 20%+ share. The contract is expected to significantly boost its standing in the AI server MLCC market. Industry observers note the deal essentially secures quality validation from a global "big buyer", which will prompt other major tech firms to follow suit. Turning to its glass substrate business, Samsung Electro-Mechanics will formally sign a joint venture agreement with Japan’s Sumitomo Chemical this week. The two firms will invest a combined 500 billion won to set up a glass substrate JV, with Samsung holding a majority stake and contributing around 300 billion won. The JV will be based at the Pyeongtaek plant of Sumitomo Chemical’s South Korean subsidiary Dongwoo Fine-Chem, with production scheduled to launch in early next year. Glass substrates, which offer superior heat resistance to traditional plastic substrates and can accommodate more HBM (high-bandwidth memory) and GPUs, are hailed as "rule changers" for AI semiconductor packaging. Samsung Electro-Mechanics aims to lock in a high-quality supply chain in advance for mass production, while Sumitomo Chemical is using this partnership to enter the next-generation packaging materials market.

Serenity has released an analysis on whether automotive and robotics supply chains are converging, taking Germany’s Schaeffler (market cap ~€7.47 billion) as a key case study. Schaeffler has partnered with 45 humanoid robot firms, with its product portfolio covering core components including bearings, gearboxes, sensors/ECUs, actuators, and power electronics. The company estimates its products make up roughly 50% of a humanoid robot’s bill of materials, and targets 10% of the segment’s market share. However, Schaeffler’s 2030 robotics revenue forecast is only in the hundreds of millions of euros—far lower than Elon Musk’s optimistic outlook for the market. Serenity dubs this a typical "sandbagging forecast," a deliberate understatement. Serenity also highlighted other notable targets, such as Nabtesco (focused on joint reducers) and Sanhua Intelligent Controls, which supplies components for Tesla’s Optimus robot. On the investment front, Serenity argues these traditional auto parts firms are currently undervalued due to drag from their core automotive businesses, while humanoid robots and AI-powered vehicles will serve as key growth vectors. The chairman of TSMC recently also cited AI vehicles as a growth vector. But a critical prerequisite is the emergence of killer apps and leading downstream players—similar to ChatGPT or Anthropic—to truly drive the entire upstream supply chain ecosystem. Currently, robotics business accounts for only ~1% of these firms’ total revenue, so the market remains focused on immediate bottlenecks like memory chips and MLCCs in the short term. Serenity predicts that as humanoid robots evolve along different architectural routes, future "unexpected supply chain bottleneck surprises"—akin to HBM or MLCC—will emerge, bringing pricing power and revaluation opportunities for early-positioned companies. In terms of timing, post-2027 is likely to act as a clear catalyst.