You try 3D printing a house on a Pentium, or running inference models. We needed the compute. We need so much compute it boggles the mind and we don't know what to do with it.
Only then, as we are drowning in compute, does it spill over into other areas and allow that compute to be used as leverage towards enhancing or automating areas compute has yet to break into. Only then are crazy ideas like having large clusters of transistors act as neurons in a neural net actually possible, and efficient enough.
This is at least what I mean when I occasionally say something flippant like "(technology/computers/software) will eat the world". Maybe our relentless pursuit of more compute isn't the best way to solve complex problems, but it increasingly seems like it may be a way.
Whether you print a benchy using a tabletop 3d printer using PLA, or a using a gigantic gantry crane pouring cement, the compute power required is the same.
3D printing firmware and all of it's associated design software (CAD/CAM) would run fine on computing technology 10 years old.
Construction speed is bottlenecked by the lack of investment in new techniques, not for the lack of compute power.
Real buildings must take into account material costs, weight bearing, soil conditions, thermal cycling through various paths, and human and seismic induced dynamic loads. The larger the buildings get, the exponentially more compute is needed to solve these problems.
“Anyone can build a bridge that stands, but it takes an engineer to build a bridge that barely stands.”
Investment in new techniques is limited due to the limited prospects of saving money. Construction is an efficient business; gains are possible but hard, and material transportation prices play a much larger role than one might be used to.
It doesn’t feel very efficient, especially residential construction. My neighbor is building a garage with some finished space above. It’s sat without a garage door for literally months now - everything else is done.
I often wonder how soon into the project was the garage door ordered and how was that order tracked? Was the lead time calculated and a fallback option presented? These are things that we just take as a matter of course in software. They are also routine in industries that are software-intensive (finance, insurance, retail, to a lesser extent logistics)
The construction business - especially residential construction and remodeling - seem insanely inefficient to me. Jobs that should take a few days of wall clock time often take weeks due to poor planning and scheduling.
It’s interesting that certain high value specialties within construction end up being extremely efficient. You can get a new HVAC system (assuming that you don’t need to install ductwork) in a couple of days. Ditto for a new roof or a new driveway. The process is finely tuned.
It would be wonderful to have the ability to apply computational power to jobs that are not as repeatable today. Scan the house and identify constraints. Automatically design the systems, measurements and layout and assemble a BOM to minimize the effects of supplier lead times. Submit detailed RFPs to subcontractors and track their performance to plan. Etc.
> It doesn’t feel very efficient, especially residential construction. My neighbor is building a garage with some finished space above. It’s sat without a garage door for literally months now - everything else is done.
If all you have to improve the construction industry is better scheduling and supply-chain management, that's something. But the poster above seemed to be hinting at things more like new construction techniques.
haha. the exact same language was used when major semicon foundries was stuck at 14nm for a while.
sometimes solving multiple hard problems simultaneously is easier and yields better results than trying to solve individual problems on their own, due to synergies that can be taken advantage of.
however, the “divide and conquer” adage has stuck too hard into the minds of ordinary people and going against it - that’s the really hard part.
Denver is taking the same approach, and, really, it's the only tool we have for preventing huge increases in traffic as population increases and actually getting people to rely on public transit. I live in a transit-oriented development zone near train+bus stop and love how easy it is to walk to anything I want.
Transit-oriented development is the only sensible approach I've seen to scaling a modern city.
You’re pretty angry for someone who has limited knowledge on this topic!
It’s highly subsidized by the gov’t so the fee is trivial compared to the benefit. 2019 budget is $99B. Monthly cost is a little over $200 if you pay full freight.
Unless you’ve got other insurance, you’d be stupid not to go with Part D. You’d pay more with a private plan.
Medicare Part D plans (private insurers) compete for customers and get money from CMS for offering coverage that confirms to CMS standards.
It’s far more than “negotiating block and cost averaging”.
I learned some cool new features coming in Ruby 2.7 and I am very much looking forward to them now.
The rest of this post is drivel, complaints, and ends with begging questions answered in his opening bullets. How does this optimize ruby for happiness? Flexibility and choice.
Backwards compatibility is maintained. You can write the same old ruby you wrote before if you want to avoid change. I'm very happy to have some new syntax tools in the toolbox.
This is good for everyone. Hopefully the adoption is swift and we can pretend the myriad Thunderbolt/USB-C/USB 3.0 issues, differences, and confusion never happened.
I didn't know they sold homes. Kind of amazing. It's a surprising footnote in the tragedy of Sears.
The popular narrative of an out-of-touch company unable to compete with the likes of Amazon is false. The CEO is a hedge fund manager who pillaged the company, sold off it's best assets (sometimes to himself), loaded up the company with debt, and used it to pay himself millions.
> Over the years of propping Sears up, Lampert threw his own money into the effort, and his friends and supporters said this wasn’t only in self interest: He wanted to keep the lights on and people employed. He and ESL were willing to lend at much lower rates than others were demanding. He had Sears pay almost $2 billion into the unfunded pension plan in the past five years.
> The traditional story of financial engineering is that smart hedge-fund guys structure complicated transactions that enrich themselves at the expense of ordinary workers. But it’s at least possible that Sears is the opposite story, the story of a smart hedge-fund guy structuring complicated transactions that blew through his fortune to keep ordinary workers employed through a financial crisis. Of course that’s not mainly a matter of disinterested kindness: If he just wanted to give his money away to workers, he wouldn’t have needed the complicated transactions. It’s mostly just a gamble that didn’t pay off: He expected that the complicated transactions would help Sears to recover and make him even richer, but they didn’t.
> I genuinely don’t know what to make of Lampert and Sears. There is a version of the story in which he rapaciously extracted assets from Sears, enriching himself while starving the business, and another version in which he selflessly pumped money into the company to keep it afloat at his own expense. (“Although he has been criticized for selling Sears assets, spending on stock buybacks and collecting interest on loans to Sears, he said it is unlikely he will come out ahead financially on his long-running Sears bet,” notes the Journal.)
You need to see one of the old Sears catalogs, the ones that were two+ inches thick and sold ploughs, wagons, blacksmithing tools, everything you could imagine of use to homesteaders. It's fascinating to flip through, excellent coffee table reading material.
Or maybe don't get your facts from a publication that has a demonstrated strong bias by MBFC and frequently writes articles celebrating the return of socialism to the American political discourse.
Or, and this is their worst offense, maybe direct one that allows me to connect over SSL and doesn't 302 redirect HTTPS to HTTP. It's 2018.
And this much more balanced article doesn't back up what you originally said and is pretty much in line with the Bloomberg article.
Sears' financial troubles began long before he ever got involved and he presided over the company's decline. He did things to protect his investment but didn't pillage the company in the way that you originally stated.
It's not all doom and gloom. Major American cities are also being invaded by a litany of battery powered vehicles, especially through ebike and electric scooter rental services. Some places, like here in Denver, seem to be embracing this with open arms and it could eventually help with both congestion and pollution.
Inexpensive power-dense batteries will unlock a real revolution, not just in car-like transportation, but transportation you can pick up and carry with you, or stow under your desk at work.
Electric skateboards, electric kick scooters, electric mopeds, electric giant wheels you straddle like a snowboard (OneWheel), electric unicycles, electric rollerskates... these are just a few of the device categories exploding in popularity.
I think the battery transport revolution is already upon us, it's just harder to see because it's much smaller than we expected.
I think most of us want our code to see the light of day. If given an actual problem to solve, we aren't going to toil away at tiny details forever. We want to see it run!
A good manager knows this and will give you room to find that balance yourself, unless you have demonstrated you need help with that.
I read an interesting twist on perfectionism: try to the "perfect compromise". Quality has multiple dimensions and you can't optimize all of them perfectly. Instead, choose which dimension is actually most important for the current problem and prioritize it.
A few years ago I invented[1] the term 'acceptimal', meaning 'acceptably optimal'. It's not the absolute best solution, but it's a pragmatic compromise between time, cost, performance, and simplicity which performs acceptably close to optimally.
[1] Or at least I've never heard anyone else use it who didn't get it from me.
I was lucky that my first technical role was where I found the best manager I've had. He was my 2nd supervisor in that first role.
After that I got to be pickier than most about where to go next, so my results might be rosier than others. In total I've had 7 "supervisors" in my technical career. 2 of them were amazing and I would take a (small) pay cut right now to work with either. 2 were good, mostly hands off, and easy to work with. The other 3 were nice people with good intentions, but significant managerial shortcomings. None of them were bad or insufferable.
In one case, an extraordinary mentor almost entirely made up for shortcomings of the manager. Working with great people alongside you often makes the incompetency of the people above a little less relevant, or at least more tolerable.
He tore down barriers and made sure interactions with other parts of the organization or external parties were as frictionless as possible. He would take any non-technical chores off our plate where possible. He would give clear and frequent feedback, good and bad, and really cared about where I wanted to go with my career and what kind of projects I wanted to work on. He trusted me when I said I would do something and would just make sure everything was out of my way until I asked for help or deadlines were being missed.
He was a shield for those of us who worked for him.
Only then, as we are drowning in compute, does it spill over into other areas and allow that compute to be used as leverage towards enhancing or automating areas compute has yet to break into. Only then are crazy ideas like having large clusters of transistors act as neurons in a neural net actually possible, and efficient enough.
This is at least what I mean when I occasionally say something flippant like "(technology/computers/software) will eat the world". Maybe our relentless pursuit of more compute isn't the best way to solve complex problems, but it increasingly seems like it may be a way.