comments (10)

  • Whenever Meta claims their models are open source, you have to double-check.

    SAM License (https://github.com/facebookresearch/sam3/blob/main/LICENSE):

    > iv. Your use of the SAM Materials will not involve or encourage others to reverse engineer, decompile or discover the underlying components of the SAM Materials.

    > v. You are not the target of Trade Controls and your use of SAM Materials must comply with Trade Controls. You agree not to use, or permit others to use, SAM Materials for any activities subject to the International Traffic in Arms Regulations (ITAR) or end uses prohibited by Trade Controls, including those related to military or warfare purposes, nuclear industries or applications, espionage, or the development or use of guns or illegal weapons.

    > b. If you institute litigation or other proceedings against Meta or any entity (including a cross-claim or counterclaim in a lawsuit) alleging that the SAM Materials, outputs or results, or any portion of any of the foregoing, constitutes infringement of intellectual property or other rights owned or licensable by you, then any licenses granted to you under this Agreement shall terminate as of the date such litigation or claim is filed or instituted. You will indemnify and hold harmless Meta from and against any claim by any third party arising out of or related to your use or distribution of the SAM Materials.

    The DINOv3 License (https://github.com/facebookresearch/dinov3/blob/main/LICENSE...) is similar but with the model names swapped.

    It's always nice when a model's weights are released, but Meta's models are not open source because their weights always come with weird restrictions.

    commoner

  • I'm no fan of Facebook or its social effects but I can't deny the wonderful downstream effect of their open source.

    Popular microscopy models like Cellpose[0] have leaned heavily on the cornucopia of open and SOTA power. I have no doubt thousands of biologists have benefitted from the capabilities these models bring. I think it was unthinkable just 5 years ago that a single biologist with just a laptop could do mass-segmentation at this kind of fidelity.

    Then there's Napari and it's plugin ecosystem[1] that wouldn't exist without the Chan Zuckerberg Initiative. Again, I'm not trying to glaze them but as someone in the biotech/microscopy space I can't understate how often I use and benefit from their open source.

    [0] https://cellpose.readthedocs.io/en/latest/models.html [1] https://chanzuckerberg.com/rfa/napari-plugin-grants/

    momojo

  • The scoop: X-ray imaging of various strictures for scientific purposes produces colossal reams of data, previously hard to analyze. Meta provides machine analysis, both segmentation and classification, using unsupervised learning models.

    > a fully reconstructed, semantically labeled 3D volume delivered back to the scientist physically standing at the beamline [x-ray] instrument, ready for interpretation while the experiment is still running. Total turnaround: approximately 15 minutes.

    nine_k

  • This fits with my impression of the 'personality' of various models:

    Meta: Perceptive (strong vision)

    Gemini: Fastest

    Claude: Smartest

    OpenAI: Prettiest

    Zaheer

  • this page hijacks your tab's back button history :\

    jyr0s

  • ELI5.

    brcmthrowaway

  • Gonna need to have a talk with LLNL. I'm sure they didn't choose the name, but seems a tad leaning in to use the name of tech from Star Trek meant to produce untold abundance that instead became an unintentional doomsday device.

    nonameiguess

  • So, not LLM models, right?

    Also on this:

    > The numbers are staggering: The DOE's light and neutron source facilities now produce tens of petabytes of data annually

    Come on, petabytes are not staggering for entreprise software.

    iLoveOncall

  • As a former proposal specialist (B2B, B2G, non DoD) I looked into the Genesis Mission procurement site and process.

    Unless someone can correct me, the total amount of grant monies is $280,000,000 or so.

    It became obvious that it’s not worth my time to engage in the “mission” as they call it, even if I could benefit some worthwhile causes.

    That’s a pittance and pretty insulting to the purported benefit of funding scientific endeavors. I’m not even attempting to be political here. $280 Million versus $XX Billion for warfighting is a seriously gross misallocation of public monies, IMHO.

    Total lackluster reporting on the scale and scope of the actual numbers, but not surprising.

    6stringmerc

  • That is — incredible

    mawadev