Tootfinder

This https://arxiv.org/abs/2506.05588 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csNE_…

Preprocessing Methods for Memristive Reservoir Computing for Image Recognition
Reservoir computing (RC) has attracted attention as an efficient recurrent neural network architecture due to its simplified training, requiring only its last perceptron readout layer to be trained. When implemented with memristors, RC systems benefit from their dynamic properties, which make them ideal for reservoir construction. However, achieving high performance in memristor-based RC remains challenging, as it critically depends on the input preprocessing method and reservoir size. Despite …

»KI erklärt:
Die #Doku'mentarfilmer Hans Block und Moritz Riesewieck beleuchten in ihrer Videoserie die technischen, gesellschaftlichen und philosophischen Dimensionen Künstlicher Intelligenz. Sie zeigen auf, wie KI unser #Verständnis von

KI erklärt - Kultur und Pop | ARTE
Die Dokumentarfilmer Hans Block und Moritz Riesewieck beleuchten in ihrer Videoserie die technischen, gesellschaftlichen und philosophischen Dimensionen Künstlicher Intelligenz. Sie zeigen auf, wie KI unser Verständnis von Bewusstsein, Verantwortung und Menschsein verändert – und welche grundlegenden Fragen sich daraus für unsere Zukunft ergeben.

Lumina: Real-Time Mobile Neural Rendering by Exploiting Computational Redundancy
Yu Feng, Weikai Lin, Yuge Cheng, Zihan Liu, Jingwen Leng, Minyi Guo, Chen Chen, Shixuan Sun, Yuhao Zhu
https://arxiv.org/abs/2506.05682

Lumina: Real-Time Mobile Neural Rendering by Exploiting Computational Redundancy
3D Gaussian Splatting (3DGS) has vastly advanced the pace of neural rendering, but it remains computationally demanding on today's mobile SoCs. To address this challenge, we propose Lumina, a hardware-algorithm co-designed system, which integrates two principal optimizations: a novel algorithm, S^2, and a radiance caching mechanism, RC, to improve the efficiency of neural rendering. S2 algorithm exploits temporal coherence in rendering to reduce the computational overhead, while RC leverages th…

Preprocessing Methods for Memristive Reservoir Computing for Image Recognition
Rishona Daniels, Duna Wattad, Ronny Ronen, David Saad, Shahar Kvatinsky
https://arxiv.org/abs/2506.05588

Preprocessing Methods for Memristive Reservoir Computing for Image Recognition
Reservoir computing (RC) has attracted attention as an efficient recurrent neural network architecture due to its simplified training, requiring only its last perceptron readout layer to be trained. When implemented with memristors, RC systems benefit from their dynamic properties, which make them ideal for reservoir construction. However, achieving high performance in memristor-based RC remains challenging, as it critically depends on the input preprocessing method and reservoir size. Despite …

Hallo. Kann mir hier jemand evtl ein RC Flugzeug der Klasse bis 250g für Anfänger (Kind, 10J) empfehlen? Nach Möglichkeit nicht zu teuer, K1 will es vom Taschengeld kaufen.
Wir hatten schon eines bestellt, das aber nach dem ersten Rums kaputt war. Habt Ihr einen Tipp?
Danke!
Gerne RT.

Spectral Efficiency Maximization for mmWave MIMO-Aided Integrated Sensing and Communication Under Practical Constraints
Jitendra Singh, Anand Mehrotra, Suraj Srivastava, Aditya K. Jagannatham, Lajos Hanzo
https://arxiv.org/abs/2506.04683

Spectral Efficiency Maximization for mmWave MIMO-Aided Integrated Sensing and Communication Under Practical Constraints
A hybrid transmit precoder (TPC) and receive combiner (RC) pair is conceived for millimeter wave (mmWave) multiple input multiple output (MIMO) integrated sensing and communication (ISAC) systems. The proposed design considers a practical mean squared error (MSE) constraint between the desired and the achieved beampatterns constructed for identifying radar targets (RTs). To achieve optimal performance, we formulate an optimization problem relying on sum spectral efficiency (SE) maximization of …

Linux 6.15-rc4 is out:
https://lore.kernel.org/lkml/CAHk-=wg8VMvbaq6EECWxP7OcrGtUmauFQCjeLT24pXh-H=o-4Q@mail.gmail.com/
'"So let's see if this rc ends up avoiding any silly issues - things certainly loo…

6.14 mainline out on Arch. Compiled and running well. RC series seemed to do just fine with the AMD GPU suspend issues I was encountering before, no lockups upon resuming.
I use a separate USB4 NVMe drive enclosure with Ubuntu for work stuff (keep 'em separate), same result.
I never found the actual commit, so assuming it was done, or something else fixed it 😆
#linux

This https://arxiv.org/abs/2505.05420 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_nli…

Robustly optimal dynamics for active matter reservoir computing
Information processing abilities of active matter are studied in the reservoir computing (RC) paradigm to infer the future state of a chaotic signal. We uncover an exceptional regime of agent dynamics that has been overlooked previously. It appears robustly optimal for performance under many conditions, thus providing valuable insights into computation with physical systems more generally. The key to forming effective mechanisms for information processing appears in the system's intrinsic relax…