Diederich

Very good, thank you.

Totally agree. When this current wave of GenAI really started heating up, I guess 2020-2021, my analysis was very straightforward. What are the high level inputs to long-term success? I basically came up with a couple of criteria:

1. Data. Lots of data.

2. Money. Lots of money.

3. Access to necessary hardware.

4. Business alignment/will to do it.

5. Access to talent, current and future.

This is certainly incomplete/naive. In my mind, though, Google was the clear answer.

On a more personal level, I've been deep into the Google ecosystem since I got [email protected] in 2005. (I actually paid 50 cents on ebay to get a very early invite.) There was no question in my mind that Google's AI work would deeply integrate into their whole ecosystem in very powerful and productive ways. (Yes, I can join you to discuss, at length, the various ways that Google's dominance is problematic/scary.)

Having said all that, I'm quite happy that there is, at the moment, a very rich competitive landscape. Indeed, not too long ago, with Gemini Pro 3.1 languishing, I moved most of my deeper thinking work to ChatGPT, which was, for me at least, clearly outperforming Gemini.

While I certainly didn't anticipate it, Google's strategy of making their fast/relatively inexpensive models surprisingly powerful has been a welcomed surprise.

I will be doing just that today.

LWN is one of the cornerstones of my very successful career.

Starting from the beginning, I have (at least) read through every story and every article, every week, since 1998. Especially in the beginning, there was a lot in each article I didn't understand. I would try to do some digging into those topics.

One way or another, just the weekly exposure to absolutely top notch technical writing was foundational to me.

When newer folk would ask me how to really get good with Linux, I would always point them to LWN.net.

I've been a subscriber since the beginning. That small investment is the least I can do given the incalculable value LWN has brought to me.

"It simply does not add up that someone who lacks purely technical skills in an area can make good decisions."

I've been thinking about this and your related points, and I've been (with growing concern) instinctively in agreement.

Another analogy has been coming up. I started programming (as a kid) in the late 1970s, first with BASIC (of course) but pretty quickly moved to machine language for obvious performance reasons, and then to C, followed by many other languages. In the late 1980s, at university, I learned proper assembly language, and used it quite a bit.

Back then, I was pretty good with assembly/machine language. Not super star or expert level, but comfortably solid. Since then though I've spent very little time at that low level.

Granted, such early exposure and experience has been a pretty big fairly indirect benefit. But over the years, I've met and worked with many really smart, productive people who have never had any experience at that low level, and that lack was rarely noticeable.

For any given 'layer of abstraction', there is some use in being familiar with the lower layers. I think, in general, the closer the lower layer is, the more useful the knowledge is. For example, how useful is deep knowledge of CPU microcode to a Java programmer? Perhaps some, but not a lot.

In the tech world, GenAI is likely to push most everyone quite a ways up the tower of abstractions. We're in the middle of that right now, and it certainly feels pretty alarming to me.

The biggest uncertainty that comes into my mind is how insanely fast this change is coming upon us. My crawl up the abstraction tower happened over the course of about 12 or so years, from machine language/assembly to C then to Perl then to many other things. In retrospect, that felt pretty fast.

GenAI is seemingly pushing us in that direction many times more quickly.

> SpaceX will now be beholden to Wall Street

I get and appreciate that sentiment. Musk currently has a controlling interest in SpaceX. Do you expect that to change after the IPO? Thanks!

I get your sentiment, though I think it's likely that people, on average, are going to organically start writing more and more like LLMs.

> I have had the experience of serendipitous discovery when researching relatively recent history.

I would really love to hear about this. (:

"Show of hands for anyone using ChatGPT to shop. Be honest."

I use Gemini to help with shopping decisions pretty frequently. It's been very effective and useful for that.

They don't need a lot of tools to do such a deep 'search' of your car, they're not under any requirement or mandate to make it easy or even possible to repair.

In my 40+ years of driving, I've seen such disassembled cars along the road a hand full of times.

I also lived not too far from that location, and unfortunately got a glimpse of the aircraft as it was spiraling down. The scene on the ground was pretty hellish.