Japan's New 2nm 144-Core Chips Made TSMC & NVIDIA Chips Look Like TRASH!

Japan's new chips bring together a working 2nm prototype and Fujitsu's 144-core Monaka processor, but those are two different projects. Rapidus is building a foundry in Hokkaido; Monaka uses TSMC silicon. This video draws the mechanisms behind the headlines and separates working hardware, company estimates and targets for 2027. Figures drawn from community discussions are individual user reports or estimates, illustrative rather than averages. Complete Local AI course: join the waitlist → https://localanalysis.ai/md/curso How are 2nm chips made, and what does the node name actually tell you? We follow the gate-all-around transistor, IBM's technology transfer, Rapidus Japan and the difference between transistor density and manufacturing yield. We also examine the reported wafer prices, the single-wafer production approach and why a faster turnaround could matter for AI chips without proving a performance lead over TSMC. Fujitsu Monaka, MN-Core L1000 and NTT IOWN tackle different limits: CPU efficiency, moving model weights from memory, and carrying data with light. The drawings explain Monaka's 3D stack, the proposed memory-on-logic design and the optical interconnect roadmap. We compare those claims with NVIDIA chips, CUDA and Blackwell, including the benchmarks, production dates and missing evidence that would be needed to establish a real alternative. 00:00 A 2nm factory in the snow of Hokkaido 02:12 What a 2 nanometer chip means today 04:08 The 2 nanometer transistor and who bet on it 06:15 Working transistors in under three years 08:59 Can Rapidus match TSMC on density? 10:12 One wafer at a time 12:10 Why speed matters so much in AI 13:16 What a wafer costs and what comes next 15:09 Monaka, 144 cores at 2 nanometers 16:17 Air-cooled and made in Japan 17:55 What Fujitsu's announcement leaves out 19:00 Preferred Networks, the company almost nobody knows 20:19 MN-Core L1000 and the memory problem 21:38 Going public to be able to manufacture 22:50 NTT wants to move data with light 25:05 Does NVIDIA have reasons to worry? 27:12 A whole alternative, outside Taiwan 28:24 My take #Rapidus #NVIDIA #Semiconductors