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“They cut off a finger.” MEP @knafo_sarah reacts to the recent wrench attacks targeting Bitcoin entrepreneurs in Paris, telling @_dsencil at @parisblockweek that France needs 100,000 new prison cells. Hear her full take 👇

LATEST: 🏦 A BIS-led project with 40+ financial institutions found tokenized central bank reserves and deposits could significantly cut settlement times and costs in cross-border payments.

Tebogo Moropa Zero-tariff policy shortens customs clearance, cuts trade costs, and creates new market opportunities for African producers. Yordanos Solomon Calls for Chinese investment in local factories to bring down prices and lower living costs for young people. Hailab Amaha Easier exports to China expand market access for African products and provide China with quality goods—a win-win. #ChinaAfrica# #WinWin# #GlobalTrade#

ELON MUSK: “FOR THE NEXT FEW YEARS AMERICA IS LIKELY TO WIN THE RACE IN AI. THEN IT WILL BE A FUNCTION OF WHO CONTROLS THE AI CHIP FABRICATION. IF MORE OF THE FACTORIES ARE OWNED BY CHINA THEN CHINA WILL WIN." "RIGHT NOW ALL THE CHIP FABS ARE IN TAIWAN. 100%." "IF CHINA INVADES TAIWAN IN THE NEAR TERM THE WORLD WILL BE CUT OFF FROM ADVANCED AI CHIPS." "I THINK IT'S ESSENTIAL FOR NATIONAL SECURITY THAT WE BEGIN MANUFACTURING OUR OWN CHIPS IN THE US.”

High-paid tech workers are cutting life down to the basics so they can invest and retire by 30 One Meta engineer makes over $300K a year and still owns no car, couch or TV More successful Gen Z are choosing calm life over career and money

Behind the MiMo API Price Reduction: The deepest price cut, up to 99%, is for Input (Cache Hit). The core reason is our inference framework now supports hierarchical KV cache optimization for SWA. Production inference engine tests show this optimization increases cached token capacity by 5x, equivalent to an 80% reduction in caching costs. Combined with Cache Read Overlap among multiple Full Attention modules in the Hybrid model, actual costs are further reduced. Prices for Input (Cache Miss) and Output are also reduced by 60%-80%. This mainly benefits from the extreme 1:7 Full:SWA sparsity ratio brought by the model architecture (the prefill compute of the 70-layer MiMo-V2.5-Pro roughly equals a 10-layer GQA model). This kept our original inference costs well below the industry average, naturally leaving a 2x-3x profit margin in pricing. This price adjustment simply reflects our decision to pass these structural cost efficiencies directly to developers. Operating at these newly reduced API prices, our production inference engine is running at near full capacity, and we can still essentially break even. We previously advised LLM companies not to "blindly cut prices" precisely because very few model architectures and inference optimizations can keep API costs from running at a loss. If more architectures that save compute and KV cache emerge, along with better inference Infra to drive down API costs, this will form an excellent virtuous cycle in the industry. More crucially, affordable, high-performance model APIs will drive real, sustained, and at-scale inference demand. This upstream demand pulls forward the development of the entire AI infrastructure chain—including chips, servers, optical transceivers, PCBs, liquid cooling, power, energy storage, and data centers—serving as a strategic fulcrum for a systemic revaluation of AI hardware. In the long run, this injects more affordable and accessible compute into both training and inference pipelines, accelerating the parallel evolution of global AGI across multiple regions and technical routes. For more technical details, we will release a detailed Blog post later.