Developments in the world economy, international trade, finance, energy, agriculture and food supply. Source-linked reporting appears in this section. Page 19.
NTT, NTT Innovative Devices, Japan Semiconductor, Furukawa Electric and Shinko Electric said a proposal led by NTT Innovative Devices was selected for a Japanese NEDO advanced-semiconductor programme. The project will develop manufacturing, testing and packaging methods for optical chiplets used to connect processors with light.
Japan’s NEDO selected Preferred Networks and Tenstorrent for a joint xPU design project incorporating photonics-electronics integration. Their five-year research programme targets processor systems for training and inference across scientific, physical and agentic AI workloads.
The sponsored-research agreement funds a one-year fabrication and testing programme for straintronic magnetic tunnel junction devices, which the parties say could inform energy-efficient AI hardware.
The Transport General Authority reported more than 40.9 million rail passengers, 3.9 million tonnes of freight and 46,300 containers in Q3 2026. Urban services accounted for most passenger journeys.
Source: Saudi Press Agency / Transport General Authority
Socionext says it is extending agentic AI from front-end design tasks into physical design for a large-scale 3nm system-on-chip, using Cadence InnoStack AI Super Agent.
The UAE Ministry of Energy and Infrastructure said on 20 October that a delegation led by Sharif Al Olama completed a five-day working visit to China. Mubadala, the Abu Dhabi Investment Office and AD Ports Group were represented.
At the Africa Raw Materials Summit in Abuja, Nigeria’s innovation minister called for science, technology and partnerships to turn more of Africa’s raw materials into products made on the continent.
Source: Federal Ministry of Information and National Orientation
A preprint describes an analog memory architecture that stores multiple high-dimensional vectors in superposed form, aiming to reduce the number of memory cells needed for neural-network weights and embeddings. The authors say they demonstrate vector storage and retrieval.
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