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Pulse · theguardian.com

theguardian.com · Oct 29

AI Agent Memory Systems to consider to optimize enterprise workflows

Using AI for roles from executive assistants to chiefs of staff, companies are boasting about doing more with less, creating tension with their human workers

Pulse · m.economictimes.com

m.economictimes.com · Oct 29

Meet Lukas Biewald, who lost his CEO role at his first startup; how an unpaid internship at OpenAI helped

After reportedly leaving the CEO role, Lukas Biewald felt that he needed to strengthen his technical knowledge as deep learning advanced. He then spent time building robots, experimenting with TensorFlow in a Raspberry Pi and studying neural networks. He taught introductory deep-learning classes to thousands of engineers, which helped him understand the problems developers faced when building AI models.

Pulse

Top picks this weekarXiv

arXiv

Oct 27

Honeycomb-Surfels: Compact Hexagonal Primitives for Efficient Scene Rendering and Reconstruction

Novel view synthesis and 3D reconstruction have advanced rapidly with radiance fields and splatting, yet their memory and computational demands limit their use in resource-constrained settings. We introduce Hexels: novel planar hexagonal surface elements with a first-order spatial color field for efficient 3D scene and 2D image representation. Hexels exploit locally planar regions with smoothly varying appearance using fewer, larger primitives. Their hexagonal support provides an area- and boundary-efficient domain, while the local color field captures appearance variation within each primitive. Across 34 scenes, Hexels improve PSNR over memory-matched 2DGS by 4.53-7.38 dB across datasets while requiring lower training VRAM. We further ablate Hexels by showing that per primitive, Hexels outperform 2DGS by upto 4.74 dB while using lower training VRAM and having 2.31 times faster FPS. Even in unconstrained settings, Hexels offers complementary quality-memory trade-offs. For efficient 3D surface reconstruction, Hexels reduce error by 28.9% compared with memory-matched 2DGS across 15 DTU scans. On 6 Tanks and Temples surface scenes, Hexels achieves the highest mean F1 among compared…

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arXiv

Sep 18

Time series generation with spectrally aligned latent flow matching

Latent flow models have proven to be a reliable and cost-effective method for time series generation. However, the latent compression induces unwanted artefacts, such as a spectral mismatch with respect to the underlying dataset, thus hindering their use as training surrogates.…

arXiv

Sep 18

GS-PQM: A Parameter-Domain Quality Metric for Compressed Gaussian Splatting

Recent advances in Gaussian Splatting (GS) compression have enabled substantial reductions in GS model size. Reliable objective quality assessment is therefore essential for comparing compression methods and guiding the development of more efficient GS codecs. Existing GS…

arXiv

Sep 18

Multiplicative Optimism for Constant Regret in Games

We introduce Multiplicatively Optimistic Regret Matching (MORM), an uncoupled learning rule for finite general-sum games. Under simultaneous full-information self-play, every player achieves external regret $O(\sqrt n\log d)$ uniformly over all horizons, using only one-step…

arXiv

Sep 18

Data Processing for Offline Evaluation in Recommender Systems: a Survey

Offline evaluation is the dominant experimental paradigm in recommender systems research, enabling reproducible and cost-effective comparisons on historical interaction data. Yet, while considerable attention has been devoted to recommendation models and evaluation…

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