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@seeingwithsound@mas.to
2025-05-26 18:08:19

#Ambisonics algorithm: Can it beat human hearing? theneurotimes.com/ambisonics-a "Can the ambisonics algorithm in AudioDome re…

@andycarolan@social.lol
2025-06-26 14:53:32

Did I mention that I was Ko-fi ambassador of the month for May? #KoFi #Ambassador

@seeingwithsound@mas.to
2025-05-28 10:39:45

Neuralink raises $600 million in funding, valuing brain-computer interface company at $9 billion ainvest.com/news/neuralink-rai

@arXiv_physicssocph_bot@mastoxiv.page
2025-06-27 08:52:49

Ambiguities, Built-in Biases and Flaws in Big Data Insight Extraction
Serge Galam
arxiv.org/abs/2506.21262 arxiv.org/…

@arXiv_hepth_bot@mastoxiv.page
2025-06-27 08:44:29

Ambiguities in the generation of CFJ-terms in a 5-dimensional extension of QED in one loop
H. G. Fargnoli, J. C. C. Felipe, G. Gazzola
arxiv.org/abs/2506.20961

In *today's* #WatchDogsLegion was a prophecy, not a video game:
vice.com/en/article/beekeeper-

@arXiv_csFL_bot@mastoxiv.page
2025-05-28 10:09:50

This arxiv.org/abs/2310.02204 has been replaced.
link: scholar.google.com/scholar?q=a

@richardtol@mastodon.social
2025-05-27 05:32:06

Weather affects economic growth in the short run. In the long run, the effect is insignificant except in a few extreme cases.
ideas.repec.org/p/arx/papers/2 @…

@netzschleuder@social.skewed.de
2025-06-17 18:00:04

ambassador: Philippines Ambassador bombing (2000)
A temporal network representing snapshots of relationships among individuals directly or indirectly associated with Philippines Ambassador Residence Bombing 2000, Jakarta. Nodes are people, and an edge exists if they are associated with each other. Definition of the edge weight is unknown.
This network has 16 nodes and 13 edges.
Tags: Social, Offline, Weighted, Temporal

ambassador: Philippines Ambassador bombing (2000). 16 nodes, 13 edges. https://networks.skewed.de/net/ambassador#2003
@berlinbuzzwords@floss.social
2025-05-28 11:00:11

Join Dennis Berger, Marco Petris, and Volker Carlguth to explore 'Intent-Based Clustering.' An approach to overcome some limitations of modern hybrid search systems. Discover how upfront LLM-supported in-depth query understanding can be applied in various steps, including retrieval, clustering, validation, and presentation. Learn about the process of moving from prototype to production for large-scale, high-volume e-commerce searches.

Session title: What you see is what you mean; intent based ecommerce search
Dennis Berger
Marco Petris
Volker Carlguth