Diederich

I have a 2017 Tesla S100D. (Yay back when we had letters and numbers!)

As you probably know, there's a 12 volt battery in these cars. That battery is automatically recharged by the big 100kWh main battery.

Some years back, I bought a 12 volt, 2000W inverter and connected it to this 12 volt battery in the Tesla, ran a couple of extension cords, and powered our refrigerator, extra freezer, and a number of other things with it for many hours. The main battery percentage in the car showed an appropriate drop. This actually wasn't during an outage, it was contingency testing. We already have a natural gas, 3600 watt generator that connects to one of our panels and use that during (unfortunately frequent) outages.

In my 2017, it's a bit of work to get to that battery, but it's quite doable and seemingly quite safe. The obvious, very rough/estimated/simplistic math is the 100kWh main battery divided by 2kW is about 50 hours. Different factors would push that number up and down of course.

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 diederich@gmail.com 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.

I'm watching it now: https://www.youtube.com/watch?v=y_ecCDqTSJs As always, Tim is doing a fantastic job.

> 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 believe the inflation adjusted price per piece has remained fairly consistent? https://flowingdata.com/wp-content/uploads/2013/02/priceperp...

Perhaps sets of a given physical size have more pieces now compared to before? Not sure.

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

I would really love to hear about this. (:

I found this the other day: https://www.youtube.com/watch?v=ksFhXFuRblg "NBC Nightly News, June 24, 1975" I strongly urge people to watch this, it's 30 minutes but there are many very illuminating insights within. One word for you: Exxon.

While I was young in 1975, I did watch ABC's version of the news with my grandparents, and continued up through high school. Then in the late 1980s I got on the Internet and well you know the rest.

"Back Then", a high percentage of everybody I or my grandparents or my friends came into contact with watched one of ABC, NBC, or CBS news most nights. These three networks were a bit different, but they generally they all told the same basic stories as each other.

This was effectively our shared reality. Later in high school as I became more politically focused, I could still talk to anybody, even people who had completely opposite political views as myself. That's because we had a shared view of reality.

Today, tens of millions of people see the exact same footage of an officer involved shooting...many angles, and draw entirely different 'factual' conclusions.

So yes, 50 years ago, we in the United States generally had a share view of reality. That was good in a lot of ways, but it did essentially allow a small set of people in power to decide that convincing a non-trivial percentage of the US population that Exxon was a friendly, family oriented company that was really on your side.

Worth the trade off? Hard to say, but at least 'back then' it was possible, and even common, to have ground political discussions with people 'on the other side', and that's pretty valuable.

"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.

I used the same prompt keepamovin used and changed it to CNN, which produced this:

https://realms.org/pics/cnn.html

Some interesting similarities.

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.

How did that look on the host system CPU/memory wise?

Of the dozens of contributions I've made over the decades, some recent, either zero or one of them have been reverted.

Location: Olympia, WA, USA

Remote: Yes

Willing to relocate: No

Technologies: Python, Perl, GoLang, HTML, JavaScript, SQL, Mysql, MongoDB, Postgres, Linux, AWS, GCloud, OCI, Oracle Cloud, Git, Bash Docker, Kubernetes Cloud, Kubernetes Bare Metal, Terraform, Pulumi, Helm, Flask, Networking, Routing, Switching, Load Balancing, F5, VPN, OpenSSL, InfoSec, Firewalls, DNS, DHCP, TLS, Regulatory, PCI, SOX, HIPAA, Monitoring, Nagios, Prometheus, Grafana, Jenkins, Github, Gitlab

Résumé/CV: https://realms.org/hire/

Email: diederich@gmail.com

I am seeking a hands-on, team-oriented role at a stable, technologically innovative company where we will be able to facilitate evolutionary and revolutionary adoption of various technologies, intended to produce consistently growing operational return on investment.

I am passionate about improving operational processes and flows via the collaborative approach of design and architecture. Fundamentally, I am a programmer with decades of hands-on operational experience, ranging from all kinds of Linux system administration to databases to strong networking skills. Collaboratively designing and shipping high availability is my forte. Through many and diverse focus areas, LiveOps achieved 99.99% availability in Q4 2011. Above all, I seek to understand, assimilate and process all of the issues, big and small, that stand in the way of efficient and smooth operations, using that analysis to design elegant integration solutions. Shipping that automation so my co-workers can get their work done is job one.

Is this deficiency likely to persist long-term as LLMs grow more powerful?

Recently, something quite rare happened. I needed to Xerox some paper documents. Well, such actions are rare today, but years ago, it was quite common to Xerox things.

Over time, the meaning of the word 'Xerox' changed. More specifically, it gained a new meaning. For a long time, Xerox only referred to a company named in 1961. Some time in the late 60s, it started to be used as a verb, and as I was growing up in the 70s and 80s, the word 'Xerox' was overwhelmingly used in its verb form.

Our society decided as a whole that it was ok for the noun Xerox to be used a verb. That's a normal and natural part of language development.

As others have noted, management doesn't care whether the serverless thing you want to use is running on servers or not. They care that they don't have to maintain servers themselves. CapEx vs OpEx and all that.

I agree that there could be some small hazard with the idea that, if I run my important thing in a 'serverless' fashion, then I don't have to associate all of the problems/challenges/concerns I have with 'servers' to my important thing.

It's an abstraction, and all abstractions are leaky.

If we're lucky, this abstraction will, on average, leak very little.

I watch this video at least once a year, and make my immediate family do the same.

Everyone in the United States should watch this video, or something similar, on a regular schedule.

As great as the first part is, I actually think the second part, with officer George Bruch, is even more important.

It's not as smooth, it's not flashy. Officer Bruch comes across as just a regular guy who wants to help you.

I've long viewed the world primarily through the lens of incentives and motivations. When officer Bruch is talking to you in a little room, you just want to tell your story, get it off your chest, and he makes it very, very easy to do that. In fact, if the roles of these two guys were reversed, and professor Duane, with his slick and fun personality, was interviewing you, you'd likely trust him less.

Even though it feels like it, officer Bruch is not your friend. He's not on your side. It doesn't feel like it, but his incentives and motivations are mostly in conflict with yours, whether you are guilty or innocent.

I think you mean legality -> lethality? That had me stumped for a moment!

This sounds very interesting; can you share more? Thanks!

...and search. That was amazing.

https://news.ycombinator.com/item?id=1 is always fun to look at, 18.5 years ago.

> temporarily throw all the materials into a trash

Just curious, did they pull it out of the trash later on?

Perhaps too provocative of a question for this forum:

Assuming that this plant (and potentially others) ends up substantially reproducing the capabilities that are currently available only in Taiwan, how much would that fact change the US'/the west's response to a possible Chinese attack on Taiwan?

> To remove inequality requires a totalitarian government. Be careful what you wish for.

Are a lot of people actively and actually suggesting the full removal of inequality? Finding ways to reduce it is a very different thing.

This is an outstanding analysis, thank you, and very succinctly summarizes my own views.