Silicon Valley has plenty of safety-related companies, engineers, and cultures. Medical devices, biotech, chip and hardware, aerospace, and even new companies, like Waymo, have deep safety-based products and cultures. The problem in this case is actually quite specific to frontier AI labs. They have been pushed by market forces and a lack of regulation and skip well-known safety practices.
Their idea of safety is centered around outright delusional cult nonsense-- the EA/lesswrong infinite p(doom), destruction of the entire universe psychosis--, marketing objectives ("no, ours is more dangerous!"), and anti-competitive objectives ("outlaw open weight models!" "china bad!")-- largely diverting attention away from material safety concerns like "prevent your training/testing from hacking stuff" and "avoid telling vulnerable people insane stuff that harms them".
The assumptions we made about code always led to the biggest issues. If you assumed a junior engineer, or even a senior engineer not familiar with the local practices, would not make certain mistakes, then those mistakes always slipped through. If anything, the AI makes us be _better_ reviewers, since we need to check more of our assumptions at the door. I used to check the compiler assembly output, in case I could optimize it either by hand, or by changing my code to use a do-while instead of a for loop. I don't do that anymore. The same thing is happening with AI-generated code. I used to have to check it all very carefully, and regenerate code when the AI chose to add a whole new mechanism to the code base rather than re-using an existing mechanism, to keep the code solid. That happens less and less, and soon, it won't make sense to read over the code at all. Maybe in some specific circumstances that will be necessary, but less and less overall. And that's ok. We have moved to higher and higher levels of abstraction over the decades that I've been coding, and each time we can take on bigger problems and invent new things.
Yes, mRNA vaccines are promising for many but not all cancer types, and there are many ongoing clinical trials. There's also a lot we yet don't know about how to design them.
One of the leading problems is that we don't know how to pick the right neoantigens (mutant cancer proteins) which can trigger the optimal immune response.
Moderna used a simple heuristic, "how likely is this antigen to show up on the cell surface?" which makes sense, since an antigen has to show up on the cell surface for the immune system to see it. But there's so much missing from this model, and we just don't have enough data. Failures in clinical trials of mRNA vaccines may well be caused by this problem. (Yes, this is a good problem for AI, if we can get enough data).
mRNA is a general technique for targeted cancer therapy. It's the message RNA containing the instructions from a gene to create a specific protein. It's much easier to work with, reprogrammed, manufactured, and delivered. There're a number of approaches to use mRNA against cancer cells. One is using cancer related antigens, similar to the vaccine approach. mRNA is programmed to generate the antigen proteins in the body, which are attached to the cancer cells. The body's T-cells can then attack the tagged cancer cells.
The problem now is finding the correct antigens targeting the cancer cell type. Cancer cells are similar to health cells. You don't want to program a mRNA to generate antigen proteins that target health cells, which causes autoimmune problems.
This is not quite correct. An mRNA vaccine that creates healthy antigens will fail because it won't do anything, not because it will trigger autoimmune issues. Your cells are already covered in normal antigens, and your immune system already knows to not attack them. It is true that it is difficult to find the right antigens to target, but the reasons for that are more complicated.
Individualized immune cancer therapy has been touted as the next big thing for half a century. It's nothing new, and with few exceptions, such as skin cancer, has failed to yield much. scientists, for decades, have tired to harness the immune system to attackcancer and it almost never works.
Those few exceptions have been monumental in how they've changed cancer treatment. Skin cancer has been particularly well treated with immunotherapy, but other cancers have also benefited from the exact same research and drugs (as it turns out, the specific mutations the immunotherapies like Keytruda target express in other cancers). The reason skin cancer gets so much attention is because it's one of the most commonly diagnosed and treated cancers. (Colon is more common, I believe, but it often doesn't get detected. Get your colonoscopies folks).
It has moved fast enough that I've heard from multiple oncologists that the all 5 year survivability numbers are dated because the treatments are newer than the studies.
We've come a LONG way in a very short period in terms of cancer treatment. It still sucks, but not as much as it once did.
Non-small cell lung cancer (NSCLC) treatment has been revolutionized by the checkpoint inhibitors (as well as some other drugs targeting specific mutations).
I don't like words like "revolutionized" as they set wrong expectations.
For non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (such as pembrolizumab, nivolumab, or atezolizumab), median overall survival typically ranges from about 10 to 20 months in advanced stages as opposed to 10-12 months for standard chemotherapy treatments.
That's great news especially as they would likely be better tolerated. Bt let's please not call living a handful of months longer as a 'revolution'.
> Individualized immune cancer therapy has been touted as the next big thing for half a century. It's nothing new, and with few exceptions, such as skin cancer, has failed to yield much. scientists, for decades, have tired to harness the immune system to attackcancer and it almost never works.
"Almost never" is doing a lot of work. You may be aware that most drugs fail over the course of development and human trials?
Anyway, checkpoint inhibitor therapy is a massive boon to oncology and was only brought into widespread use over the past 15 years.
Every cancer is different. Immunotherapy is highly effective, even curative, for some cancers. For my cancer, chemotherapy is curative, while other cancer's just shrug chemotherapy off like it's nothing.
Having a plethora of drugs and treatments is vital because cancer is not "one thing". Each type of cancer will respond better to some treatments than others.
Personalized mRNA vaccines are in fact, extremely new, and only made possible by recent advances across multiple fields. This comment reveals a total lack of basic understanding on this topic.
I believe the comment was talking specifically about immunotherapy rather than personalized mRNA. But I'd agree it's still misinformed as immunotherapy has been a game changer across multiple cancers.
u/danjl was originally asking about "this class of drugs", which is more reasonably interpreted as referring to personalized mRNA vaccines rather than the much broader concept of (personalized or not) immunotherapy.
The comment is wrong because it's stupid. Just because we've known that personalized immunotherapy was a promising idea for a long time, and have been trying it with the limited tools we had (CAR T being the poster child, and while an incredible advancement for blood cancers and many other diseases, it is notoriously dangerous and expensive), does not mean we had the technology to accomplish it. Today's results are only possible because of recent advancements in multiple fields, and to respond with "they've tried immunotherapy for decades" is profoundly ignorant. You may as well say, "scientists have been trying to cure cancer for years."
> This comment reveals a total lack of basic understanding on this topic.
My thoughts as well, Keytruda alone has been a miracle to many many people at this point (quoting GP: "scientists, for decades, have tired [sic] to harness the immune system to attack cancer and it almost never works."), I frequently get ads for local CAR-T centers (unthinkable a little over a decade ago)
I suspect the net result will be that more Pro $100 subscribers upgrade to $200/mo. If you explicitly do simpler stuff with Opus, you generally have enough Fable time for most programming and planning tasks.
A product is much more than the software and its reliability. The business side is just as big of a lift. You need to build a business, not just a product. A business includes understanding the value proposition, not just a potential solution in the form of a tool. It includes understanding how the software fits in to the target customer's workflow, and how it provides real value. You need to be able to communicate that value proposition to the customers, investors and your employees, amongst other stakeholders. Later, this transforms into understanding the sales cycle and how to use marketing to grow your users. The business side has always been the hard part. Software was always easy to build. The hard part is knowing what to build that really provides value.
