Tootfinder

Nigeria is advancing its renewable energy goals by investing in local solar panel production, aiming to generate 30% of its electricity from renewables by 2030.
https://cleantechnica.com/2025/11/17/african-nations-promote-locally-produced-solar-pan…

African Nations Promote Locally Produced Solar Panels - CleanTechnica
Solar manufacturing is beginning to take place in many parts of Africa as local companies leverage the transfer of technology.

Evidence that AI is normal technology include AI systems that are good enough to be useful but not good enough to be trusted, continuing to require human oversight that limits productivity gains;
prompt injection and security vulnerabilities remain unsolved, constraining what agents can be trusted to do;
domain complexity continues to defeat generalization, and what works in coding doesn’t transfer to medicine, law, science;
regulatory and liability barriers prove high enou…

What If? AI in 2026 and Beyond
The market is betting that AI is an unprecedented technology breakthrough, valuing Sam Altman and Jensen Huang like demigods already astride the world. The

Dispersion-Aware Modeling Framework for Parallel Optical Computing
Ziqi Wei, Yuanjian Wan, Yuhu Cheng, Xiao Yu, Peng Xie
https://arxiv.org/abs/2511.18897 https://arxiv.org/pdf/2511.18897 https://arxiv.org/html/2511.18897
arXiv:2511.18897v1 Announce Type: new
Abstract: Optical computing represents a groundbreaking technology that leverages the unique properties of photons, with innate parallelism standing as its most compelling advantage. Parallel optical computing like cascaded Mach-Zehnder interferometers (MZIs) based offers powerful computational capabilities but also introduces new challenges, particularly concerning dispersion due to the introduction of new frequencies. In this work, we extend existing theories of cascaded MZI systems to develop a generalized model tailored for wavelength-multiplexed parallel optical computing. Our comprehensive model incorporates component dispersion characteristics into a wavelength-dependent transfer matrix framework and is experimentally validated. We propose a computationally efficient compensation strategy that reduces global dispersion error within a 40 nm range from 0.22 to 0.039 using edge-spectrum calibration. This work establishes a fundamental framework for dispersion-aware model and error correction in MZI-based parallel optical computing chips, advancing the reliability of multi-wavelength photonic processors.
toXiv_bot_toot