marsten

When I was at Google during the IPO I saw people with similar challenges. I can empathize with what he's going through, it can be hard to find a sense of purpose when "the need to provide" is suddenly gone and you realize that many of your life choices were made based on that goal.

I can also empathize with those who consider him a whiny brat. It's hard to get someone to care about your plight when in their eyes you've achieved success. It's just different levels on Maslow's hierarchy.

That manual is a great find! Dr. Kurtz was surely way ahead of his time in aiming to bring computing to the masses, well before the microcomputer revolution. BASIC was an easy onramp to programming that hooked a ton of people on computing, especially kids of the 70s/80s like me. He shaped the future as much as anyone.

Based on the bounds discussed at https://old.reddit.com/r/Cubers/comments/8chfuu/i_found_a_ge... it appears that a 34x34x34 cube can be algorithmically solved in under 100,000 moves.

Maximum number of moves scales as n^2.

There are many jobs where people prefer other people to fill those roles, irrespective of the ability of machines. Most people don't want to watch computers play chess, or spend money on computer-generated art, or go to a robot therapist.

Ah, you say: But such jobs don't employ many people! Most people do things that nobody cares if they're automated away. Surely we can't all be chess players or artists?

To which I say: The job market will adapt, and people will move into those jobs where customers prefer to have a human. We have no real idea what those jobs are today, but some of them might be the things you wish you had more of, but are too expensive for most of us to hire someone for. (Interior decorator? Personal chef? ...)

The most interesting thing to me by far was the lack of a steering wheel on the Robocab.

Without manual controls, vague promises ("puffery"?) about autonomy won't drive vehicle sales as they do today across all Tesla's models. The Robocab as shown literally cannot function (or make a dime of revenue) until they've fully solved autonomy and have convinced regulators of the same.

My favorite pizza place in Sunnyvale became employee-owned, and shortly after decided they only wanted to stay open 3 days a week.

I'm happy for those employees but man, I also wish I could get pizza on Monday.

Note there is an error in the paper going from equation (60) to (63): inequality (63) should read 10^-8 Hz < mu < 10^2 Hz. This is fairly important from an observational standpoint!

This shouldn't be an either-or situation; you do all of the above. A simple validating parser in the client would be easy to write and would have easily caught a null payload.

What looks especially bad for Crowdstrike is how many things (relatively simple things) had to fail in order for this to slip through. It's like walking into Fort Knox, grabbing a gold bar, and walking out unimpeded. A complete systemic failure.

That's exactly the kind of content I love on the internet, when someone smart dives deep on an obscure topic and then shares it with the rest of us.

There's a strong geopolitical angle as well. If you force American companies to license all training data for LLMs, that is such a gargantuan undertaking it would effectively set US companies back by years relative to Chinese competitors, who are under no such restrictions.

Bottom line, if you're doing something considered relevant to the national interest then that buys you a lot of leeway.

It's an interesting idea, that scarcity and inconvenience could make one a more thoughtful practitioner.

A similar situation applies to writing. When people wrote with quills on parchment under candlelight, they did the structuring and editing in their minds beforehand. Now, word processors encourage us to vomit words onto the page and rarely do we edit them down to a similar level of quality.

The upper bound given in the paper is on emitters of one terawatt EIRP (10^12 Watts) and above. EIRP means an isotropic emitter would need to be this powerful to be detected. A beamed transmitter that happened to be pointing in our direction could be somewhat weaker in total power, and still be detectable.

It's important to realize that this is at least 100,000 times more powerful than our most powerful Earth-based narrowband emitters. So we would not detect ourselves in this search - not even close.

Moreover, we have no good reason to believe that an advanced species would have cause to radiate 1 TW into space. Our own terrestrial emissions are becoming weaker over time, not stronger, as we optimize for total system bandwidth in our communications.

So I wouldn't draw too many strong conclusions here about alien life. We are still very much searching for our lost keys directly under the lampposts.

From the accounts I've read of other scientists in the Manhattan Project, Oppenheimer had a connector style of personality that made him very well-suited to the role. For this type of job you don't want an Einstein who is prone to thinking deeply on one problem for weeks at a time. Oppenheimer seemed to be the one person who understand broadly what everyone was doing.

To be clear, gravitational waves follow the same inverse square law as EM radiation, in terms of power. This is after all just a statement of conservation of energy.

The linear drop-off you're referring to is when we look at it in terms of field strength (in this case the spacetime strain). Since power is proportional to field squared, this implies a linear drop-off in the field. It just so happens that for GWs it's easier to detect the field, whereas for (most) EM radiation it's easier to detect power.

There are field-detection methods for EM radiation as well, which are useful for weak signals. Homodyne and heterodyne detection are good examples.

Urs was the last of the Google old guard left. I wish him the best! He's tried to extricate himself from leadership before and that never worked out; hopefully it sticks this time.

In principle yes, gravitational waves dissipate energy into ordinary matter they pass through. However the coupling is extremely weak (that gravitational waves are so hard to detect is testament to this).

In fact this weak coupling is what makes GWs so interesting for observational astronomy: They propagate from the source to our detectors virtually unchanged. (This is in contrast to EM radiation, which is very easy to scatter.) For example the farthest we can see back with EM radiation is about 200k years after the Big Bang, when the plasma of the early universe recombined into neutral hydrogen. By contrast gravitational waves can see back to the Big Bang itself, so it is a truly unique source of information as compared with light.

On the other hand, insurance companies may have no interest underwriting unusual risks when the business opportunity is small. "Deep-sea submarine tourism" is a tiny market.

Interestingly there are no photos or video of Egan publicly available. All we have over the last 30 years is his/her/its textual output. I'm 50/50 on whether "Greg Egan" is in fact a LLM.

Spot on, this is my experience as well. A lot of the once-sketchy parts of Berkeley, Oakland, East Palo Alto, etc. have gentrified and become safer since the 70s and 80s. Part of that has been big shifts in racial makeup and socioeconomics. Starting in the mid-late 90s tech began to really dominate Bay Area employment, bringing in a lot of new (well-paid) people and forcing out many others.

If you're a new California homeowner, I recommend you never look up what others on your street pay in property tax.

This is the Faustian bargain of technology: We advance collectively but each of us becomes a tiny cell in some giant organism we can't even perceive. Living entirely apart from that will someday be as impossible as a skin cell in your arm trying to strike out on its own.

Another useful distinction when talking about long timeframes is the amount of ongoing attention needed to maintain the data. A true archival medium is one that, if stored in a reasonable environment, can be ignored and still be read at the end. By contrast many of the "obvious" ways of keeping data involve copying or regenerating it periodically as media degrade.

Nickel is chemically and mechanically durable and doesn't easily oxidize like iron does.

In raw form your journals may be more than anyone would care to read, but AI tools could make them interesting to future people.

(a) Tools that synthesize down your life story and most interesting thoughts into N pages, (b) AIs that train on all that data to create a virtual version of you after you're gone (several companies already do this).

Cloud storage is useful for personal backup, but it's tricky on the millennium timescale of the article since no company will survive very long.

If you kept duplicate copies at the top N cloud providers at any given time, then you could probably go for 1000 years if N>=3. But this would require an active effort to keep your data alive as companies came and went. A true archival copy can be ignored and still be readable.

You only realize how uninformed the media is when it covers something you know very well. I experienced this in grad school when Newsweek magazine profiled some work my lab was doing (physics), and they made a lot of simple mistakes we could've easily corrected.

> there will likely be a higher than average representation from people who would sit in the 10%

And also an under-representation of "average users".

Python the language has always benefitted from its relative simplicity, which I attribute to people like GVR saying "no" to specialized features that accrue on languages like barnacles on a ship (looking at you C++).

With newer languages we see core design teams being much more opinionated about tooling for build and dependendency/packaging management. This is no doubt in response to the dumpster fires of C++ and Python, where "the ecosystem will sort itself out" clearly hasn't worked.