Exactly this. Most diagnosis isn’t about pinpointing the underlying exact cause, it’s ruling out the really bad stuff and minimising harm. Differential diagnosis just isn’t real world medicine.
I'm not at all familiar with the American justice system, but would the fact that this case specifically describes the targeting of minors with such addictive tactics change things at all?
I interpreted that section as alphafold not learning physics, but rather correlations within a constrained setting that a-priori correspond to physically sound inferences. It has a specific architecture that allows the model to make inferences that are more physically plausible than not, but not that it’s discovering actual, causally verifiable laws of nature (like what I’d assume are encoded into another non-ML approach to the folding problem for example).
It’s true that this could lead to unintended consequences as humanity is directly experimenting with a complex balanced natural system. But another perspective is that we have already done/are doing exactly that by pumping CO2 into the atmosphere at rates that wouldn’t have happened in nature. I know “two wrongs don’t make a right”, but it’s perhaps worth considering the price of course correcting our already hugely impactful behaviours, as the butterfly had flown years ago.
Car panels are convex on nearly all other cars for very good reason. Flat panels are structurally susceptible to damages which wouldn’t mark a standard panel. Adding a highly reflective surface was another great move.
This is really interesting work, congratulations! A lot of negativity in the comments seems to stem from cynicism around doctors and their billing, but in a country like the UK I know removing essentially "admin tasks" from the GP would be very welcome and give time back to the clinician, allowing them to spend more time focussing on the patient and outcomes.
Great answer. Imbuing a deep learning model with well thought out inductive biases is one of the strongest ways of guiding your model to interpret the data the way you want it to. Otherwise it’s kind of shooting in the dark and hoping to get lucky.
I can’t stand it when people lazily personify ML models, but it’s akin to giving someone with no experience some wood and then pointing to a shed and saying “make one of those from this”. Instead you’d expect them to be much more successful if you also give them a saw, a drill, some screws etc.
If anything, you might be thankful of a full suspension mountain bike on some of our "gravel" trails in the UK. There's such a wide range from US-style back county roads all the way to bridleways with baby-head sized rocks that you probably wouldn't want to be riding on something typically sold as a gravel bike.