Groundcover, which provides observability software that can monitor AI agents, raised a $100M Series C led by One Peak, bringing its total funding to $160M (Meir Orbach/CTech)
https://www.calcalistech.com/ctechnews/article/r19aupvrme
Thinking about some things that @… said in another thread, and as someone who advocates against AI hype and against the use of most generative AI in most circumstances, I feel it's important to say: many of the ethical issues with using generative AI mirror almost directly the ethical issues with living/working on land stolen by colonists, except that they're less harmful.
Arguments like "well we don't really know whose work it's ripping off this time" and "artists that post their art online know it's going to be looked at; this is the same thing" and "well it's inevitable and everyone's doing it so it's unreasonable to make a big deal about it" directly echo arguments like "well now we don't know whose land it was any more exactly" (yes, we do; you can literally go look up the website of their descendants), or "the natives weren't really using the land anyways", or "it's all in the past now, and it's unavoidable." That unavoidable one is actually somewhat true of using stolen land, at least compared to LLM usage.
If you can see through those lies in the case of AI hype but choose not to do so in the case of colonialism, that says something about your priorities and allegiances.
This is not at all a call for people to talk less about AI; rather it's a call for those who take opposing AI hype seriously to look around and make some noise about other injustices too (I realize many of you already do this).
#AI #LLMs #LandBack #GenAI
Charles Ross has a degree in math and a yen for physics.
He says he can sense celestial alignments, and feel the difference between colors of light in a spectrum.
When he needed a well dug for his desert home, he called a dowser.
The artist, 88, belongs to a generation of land artists who shed galleries and cities to work at a scale more common in ancient Egypt and Mesoamerica.
In 1975, he had been crisscrossing the Southwest for four years, hunting for the perfect…
"Dynamic electric vehicle charging incentives induce large shifts in both the timing and location of charging.
Incentives designed to shift charging toward peak solar generation periods result in a 34% increase in midday charging."
https://www.sciencedirect.com/science/arti
Part of the ability to detect bot-generated content is simply *good taste*. Humans maybe cannot describe what is “off” about the crud, yet still can see that it’s off.
Maybe it’s inconsistent perspective lines. Maybe it’s impossible focal aberrations. Maybe it’s the odd number of teeth. The redundant sentences. Excessive adjective use. Those who have developed good taste in text or visual art organically may not be aware of the specific technical issues, yet still recognize slop as slo…
Space waste - an update of the anthropogenic matter injection into Earth’s atmosphere: #SpaceDebris
NASA has announced that it will release a solicitation related to lunar surface power this month
and that it is considering sending a rover powered by a
"radioisotope thermoelectric generator" (RTG) to the moon.
In a press conference,
NASA Administrator Jared Isaacman and NASA Moon Base Program Manager Carlos García-Galšn discussed new award announcements
to Astrobotic, Firefly Aerospace, and Intuitive machines
to deliver NASA science payloads to…
The SMC Blind Spot: A Failure Mode Analysis of State-of-the-Art Beat Tracking
Jaehoon Ahn, Tae Gum Hwang, Moon-Ryul Jung
https://arxiv.org/abs/2605.12287 https://arxiv.org/pdf/2605.12287 https://arxiv.org/html/2605.12287
arXiv:2605.12287v1 Announce Type: new
Abstract: Over the past two decades, the task of musical beat tracking has transitioned from heuristic onset detection algorithms to highly capable deep neural networks (DNN). Although DNN-based beat tracking models achieve near-perfect performance on mainstream, percussive datasets, the SMC dataset has stubbornly yielded low F-measure scores. By testing how well state-of-the-art models detect beats on individual tracks in the SMC dataset, we identify three distinct failure modes: octave errors, continuity errors, and complete tracking failure where all metrics fall below 0.3. We reveal that state-of-the-art models tend to generate "confident-but-wrong" activations. Furthermore, we show that the standard DBN's default minimum tempo of 55 BPM prevents it from inferring the correct tempo for 21\% of SMC tracks, forcing double-tempo predictions on slow music. By exposing such fundamental oversights, we provide concrete directions for improving beat and downbeat detection, specifically emphasizing training data diversification and multi-hypothesis tempo estimation.
toXiv_bot_toot
Shanghai-based AI chipmaker Biren raises ~$892.5M in a new share sale to boost GPU production; Biren's stock is up 150% since its January Hong Kong IPO (Ann Cao/South China Morning Post)
https://www.scmp.com/tech/tech-trends/arti