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Ghidra is a lifesaver for legacy systems that have a bunch of home-spun executables that make bespoke things function and rotate out random technicians over the years, when they fail it is a pain to figure out what they explicitly do, so reverse engineering them is sometimes the only option when a new tool needs to be built that does the same thing but without the parts that are deprecated. I hadn't seen this class before so I look forward to filling in my knowledge gaps around this software, thank you.

This is inline with a Zen practice called "beginner's mind", and is so useful in many areas, thank you for this inspiration.

I upvoted something this morning and got an immediate "Are you enjoying Reddit?" popup that was a gateway to leave a review, I am curious if that is related.

Which data points are you referencing from your source? There is a spike YOY between 2019 to 2020.

Annual for 2019: 1 out of 420

Annual for 2020: 27 out of 265

Is that not enough of a percentage increase for you? Edit: Apologies for not seeing the other users' replies who have already made this point.

"I simply had no idea that ChatGPT was capable of fabricating entire case citations or judicial opinions, especially in a manner that appeared authentic"

This is the main criticism of the service, how did a lawyer miss this talking point?

You scan your face with the headset and the other person sees an avatar that is a scan of your face. Kinda defeats the purpose of "Face"time but I have not used it yet but with the speed of development I could see it improving to the point that the distinction between the avatar and your real face will be hard to tell apart.

The announcement coming from WWDC makes me think that the first wave is mostly for developers to build on, and then the cheaper/more advanced headsets coming later will be the ones marketed to regular users. I was on the fence until Palmer Luckey gave it a thumbs up, now I am cautiously optimistic.

Apologies for not being clear, "truth" might be too triggering of a word these days, but the models will need some level of objective accuracy to be useful, and it would be interesting to see where the "uncensored" models fall on that accuracy metric, and how people react to what information it displays once the guard rails are off.

The first thought I had at the release of ChatGPT is how people will react strongly when it doesn't match their internal bias / worldview.

Now I am curious to ask these "uncensored" models questions that people fight about all day on forums... will everyone suddenly agree that this is the "truth", even if it says something they disagree with? Will they argue that it is impossible to rid them of all bias, and the specific example is indicative of that?

As a network guy I am blissed out by this, thank you for sharing. Often when I study the concepts I repeatedly have that same shock of how much is going on under the hood across large distances at tremendous speed.