“Plants Really Do 'Scream' Out Loud. We Just Never Heard It Until Now. : ScienceAlert”, time to build ultrasonic ai interpreter sciencealert.com/plants-really-…

No, they aren't. Nullius en Verba. en.wikipedia.org/wiki/Nullius_i…

Well done, and good luck!

You can download the Arxiv embeddings (titles and abstracts, 6gb and 8gb respectively) at the link below. There's a lot of datasets to choose from, so we need your help to figure out what to work on next. Let us know by voting! Download or vote here: alex.macrocosm.so

youtu.be/PQMNCXR-WF8

I'm voting for @macrocosmcorp to embed all repositories on Github and open-source the weights. alex.macrocosm.so/download

How to grow fresh air | Kamal Meattle youtu.be/gmn7tjSNyAA via YouTube

Star jelly - Weird. en.wikipedia.org/wiki/Star_jelly

New paper: How can you tell if a transformer has the right world model? We trained a transformer to predict directions for NYC taxi rides. The model was good. It could find shortest paths between new points But had it built a map of NYC? We reconstructed its map and found this:

The sun's corona is weirdly hot, and Parker Solar Probe rules out one explanation phys.org/news/2024-07-s…

Nature research paper: Parallel molecular data storage by printing epigenetic bits on DNA go.nature.com/3Ujwvv0

Compelling alignment with ⁦⁦⁦Stuart Hameroff⁩ long-standing hypothesis: ultrasound alone may modulate brain function nature article explores potential in Alzheimer’s treatment, including microglial activation & blood-brain barrier permeability nature.com/articles/d4247…

I’m stoked to share our new paper: “Harnessing the Universal Geometry of Embeddings” with jack morris, Collin Zhang, and Vitaly Shmatikov. We present the first method to translate text embeddings across different spaces without any paired data or encoders. Here's why we're excited: 🧵👇🏾

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Join us for a cutting-edge conversation at the frontier of autonomous AI learning. 📷 Featuring: Andrew Zhao - Tsinghua University 📷 In conversation w/ Cecile Tamura - Ploutos 📷 Stream link: app.ploutos.dev/streams/venomo…

Many SAEs learn latents that activate on almost all tokens. Are these undesired phenomena or meaningful features? In our new work, we show that many of these "dense" latents are real, interpretable signals in LLMs. Paper: arxiv.org/abs/2506.15679 👇 summary thread by lily (xiaoqing)

#Ohm’s law can break down in materials lacking inversion symmetry, leading to nonlinear currents and quadratic voltage responses—unlocking new pathways for spintronics and microscale RF devices. Nature Materials doi.org/g9r7cn phys.org/news/2025-07-o…

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