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2 yr. ago

  • well, according to the congressional budget office,

    In 2023, federal subsidies for health insurance are estimated to be $1.8 trillion

    and this report by research america shows that the private sector spent around $150 billion on “research and development” in 2019.

    it’s no secret that the private healthcare industry jacks up the prices of things to increase profits. so, some napkin math makes me think it’s not that far-fetched to think that we can save more than $150 billion in healthcare subsidies if we stop privatized healthcare and dramatically lower the costs of medical care. we could then put that $150 billion back into research, without needing to appease the private sector at all.

  • that’s not the full story though. according to the NIH, the US government spent over 30 billion dollars on the covid vaccines.

    and this is not unique to the covid vaccine. here’s a source with two particularly damning quotes:

    “Since the 1930s, the National Institutes of Health has invested close to $900 billion in the basic and applied research that formed both the pharmaceutical and biotechnology sectors.”

    and

    A 2018 study on the National Institute of Health’s (NIH) financial contributions to new drug approvals found that the agency “contributed to published research associated with every one of the 210 new drugs approved by the Food and Drug Administration from 2010–2016.” More than $100 billion in NIH funding went toward research that contributed directly or indirectly to the 210 drugs approved during that six-year period.

  • Tensors

    Jump
  • the "categorical" way of defining tensor products is essentially "that thing that lets you turn multi-linear maps into linear maps", and linear maps (of finite dimensional vector spaces) are basically matrices anyways. so i don't see it as much of a stretch to say tensors are matrices.

    (can you tell that i never took a physics class?)

  • Tensors

    Jump
  • a tensor is a multi-linear map V × ... × V × V* × ... × V* → F, and a multi-linear map V × ... × V × V* × ... × V* → F is the same as a linear map V ⊗ ... ⊗ V ⊗ V* ⊗ ... ⊗ V* → F. and a linear map is ""the same thing as"" a matrix. so in this way, you can associate matrices to tensors. (but the matrices are formed in the tensor space V ⊗ ... ⊗ V ⊗ V* ⊗ ... ⊗ V*, not in the vector space V.)

  • "Limiting training data to public domain books and drawings created more than a century ago might yield an interesting experiment, but would not provide AI systems that meet the needs of today's citizens."

    exactly which “needs” are they trying to meet?

  • telegram has “secret chats” that let you set a self destruct timer for all messages sent in those chats. i don’t know of many other alternatives. and even telegram isn’t a drop in replacement, but it could work, depending on what you’re looking for