We have also produced treatments that work to some extent for some forms of cancer.

We don’t have a 100% reliable silver bullet that deals with everything with a simple five minute shot, but…

solving word hunger?

So, this was principally artificial selection to modify plants rather than genetic engineering (and I think that most people who say ‘biotech’ in 2026 mean genetic engineering), but there were a lot of people who did anticipate global famines until we made some substantial technological advancements with plants some decades back:

https://en.wikipedia.org/wiki/Green_Revolution

The Green Revolution, or the Third Agricultural Revolution, was a period during which technology transfer initiatives resulted in a significant increase in crop yields.[1][2] These changes in agriculture initially emerged in developed countries in the early 20th century and subsequently spread globally until the late 1980s.[3] In the late 1960s, farmers began incorporating new technologies, including high-yielding varieties of cereals, particularly dwarf wheat and rice, and the widespread use of chemical fertilizers (to produce their high yields, the new seeds require far more fertilizer than traditional varieties[4]), pesticides, and controlled irrigation.

At the same time, newer methods of cultivation, including mechanization, were adopted, often as a package of practices to replace traditional agricultural technology.[5] This was often in conjunction with loans conditional on policy changes being made by the developing nations adopting them, such as privatizing fertilizer manufacture and distribution.[4]

Both the Ford Foundation and the Rockefeller Foundation were heavily involved in its initial development in Mexico.[6][7] A key leader was agricultural scientist Norman Borlaug, the “Father of the Green Revolution”, who received the Nobel Peace Prize in 1970. He is credited with saving over a billion people from starvation.[8] Another important scientific figure was Yuan Longping, whose work on hybrid rice varieties is credited with saving at least as many lives.[9] The basic approach was the development of high-yielding varieties of cereal grains, expansion of irrigation infrastructure, modernization of management techniques, distribution of hybridized seeds, synthetic fertilizers, and pesticides to farmers. As crops began to reach the maximum improvement possible through selective breeding, genetic modification technologies were developed to allow for continued efforts.[10][11]

Studies show that the Green Revolution contributed to widespread eradication of poverty, averted hunger for millions, raised incomes, increased greenhouse gas emissions, reduced land use for agriculture, and contributed to declines in infant mortality.[12][13][14][15][16][17][excessive citations]

I have a black and white laser printer — a Brother, FWIW — that works great. It sits there and when I print the occasional document, flips on and quietly and quickly does its thing. I remember printers in past decades. Paper jams. Continuous-tractor feed paper having the tractor feeds rip free in the printer. Slow printing. Loud printing. Prints that smeared. Clogging ink nozzles on inkjets.

It replaced a previous Apple black-and-white laser printer from…probably the early 1990s that I initially got used which also worked fine and worked until the day I threw it out — I just wanted more resolution, which current laser printers could do.

The only thing that I can really beat the Brother up for is maybe that, like many laser printers, to cut costs on the power supply, it has a huge power spike in what it consumes when it initially comes on; I’d rather just pay for a better power supply. But it’s not enough for me to care that much about it, and if I really want to, I can plug it into power regulation hardware.

It’s not a photo printer, and so if someone wants to print photos, I can appreciate that a laser printer isn’t ideal for that, but…I also never print photos, and if I did at some point, I’d probably just hit a print shop.

For some workloads, yes. I don’t think that the personal computer is going to go away.

But it also makes a lot of economic and technical sense for some of those workloads.

Historically — like, think up to about the late 1970s — useful computing hardware was very expensive. And most people didn’t have a requirement to keep computing hardware constantly loaded. In that kind of environment, we built datacenters and it was typical to time-share them. You’d use something like a teletype or some other kind of thin client to access a “real” computer to do your work.

What happened at the end of the 1970s was that prices came down enough and there was enough capability to do useful work to start putting personal computers in front of everyone. You had enough useful capability to do real computing work locally. They were still quite expensive compared to the great majority of today’s personal computers:

https://en.wikipedia.org/wiki/Apple_II

The original retail price of the computer was US$1,298 (equivalent to $6,700 in 2024)[18][19] with 4 KB of RAM and US$2,638 (equivalent to $13,700 in 2024) with the maximum 48 KB of RAM.

But they were getting down to the point where they weren’t an unreasonable expense for people who had a use for them.

At the time, telecommunications infrastructure was much more limited than it was today, so using a “real” computer remotely from many locations was a pain, which also made the PC make sense.

From about the late 1970s to today, the workloads that have dominated most software packages have been more-or-less serial computation. While “big iron” computers could do faster serial compute than personal computers, it wasn’t radically faster. Video games with dedicated 3D hardware were a notable exception, but those were latency sensitive and bandwidth intensive, especially relative to the available telecommunication infrastructure, so time-sharing remote “big iron” hardware just didn’t make a lot of sense.

And while we could — and to some extent, did — ramp up serial computational capacity by using more power, there were limits on the returns we could get.

However, what AI stuff represents has notable differences in workload characteristics. AI requires parallel processing. AI uses expensive hardware. We can throw a lot of power at things to get meaningful, useful increases in compute capability.

• Just like in the 1970s, the hardware to do competitive AI stuff for many things that we want to do is expensive. Some of that is just short term, like the fact that we don’t have the memory manufacturing capacity in 2026 to meet need, so prices will rise to price out sufficient people that the available chips go to whoever the highest bidders are. That’ll resolve itself one way or another, like via buildout in memory capacity. But some of it is also that the quantities of memory are still pretty expensive. Even at pre-AI-boom prices, if you want the kind of memory that it’s useful to have available — hundreds of gigabytes — you’re going to be significantly increasing the price of a PC, and that’s before whatever the cost of the computation hardware is.

• Power. Currently, we can usefully scale out parallel compute by using a lot more power. Under current regulations, a laptop that can go on an airline in the US can have an 100 Wh battery and a 100 Wh spare, separate battery. If you pull 100W on a sustained basis, you blow through a battery like that in an hour. A desktop can go further, but is limited by heat and cooling and is going to start running into a limit for US household circuits at something like 1800 W, and is going to be emitting a very considerable amount of heat dumped into a house at that point. Current NVidia hardware pulls over 1kW. A phone can’t do anything like any of the above. The power and cooling demands range from totally unreasonable to at least somewhat problematic. So even if we work out the cost issues, I think that it’s very likely that the power and cooling issues will be a fundamental bound.

In those conditions, it makes sense for many users to stick the hardware in a datacenter with strong cooling capability and time-share it.

Now, I personally really favor having local compute capability. I have a dedicated computer, a Framework Desktop, to do AI compute, and also have a 24GB GPU that I bought in significant part to do that. I’m not at all opposed to doing local compute. But at current prices, unless that kind of hardware can provide a lot more benefit than it currently does to most, most people are probably not going to buy local hardware.

If your workload keeps hardware active 1% of the time — and maybe use as a chatbot might do that — then it is something like a hundred times cheaper in terms of the hardware cost to have the hardware timeshared. If the hardware is expensive — and current Nvidia hardware runs tens of thousands of dollars, too rich for most people’s taste unless they’re getting Real Work done with the stuff — it looks a lot more appealing to time-share it.

There are some workloads for which there might be constant load, like maybe constantly analyzing speech, doing speech recognition. For those, then yeah, local hardware might make sense. But…if weaker hardware can sufficiently solve that problem, then we’re still back to the “expensive hardware in the datacenter” thing.

Now, a lot of Nvidia’s costs are going to be fixed, not variable. And assuming that AMD and so forth catch up, in a competitive market, will come down — with scale, one can spread fixed costs out, and only the variable costs will place a floor on hardware costs. So I can maybe buy that, if we hit limits that mean that buying a ton of memory isn’t very interesting, price will come down. But I am not at all sure that the “more electrical power provides more capability” aspect will change. And as long as that holds, it’s likely going to make a lot of sense to use “big iron” hardware remotely.

What you might see is a computer on the order of, say, a 2022 computer on everyone’s desk…but that a lot of parallel compute workloads are farmed out to datacenters, which have computers more-capable of doing parallel compute there.

Cloud gaming is a thing. I’m not at all sure that there the cloud will dominate, even though it can leverage parallel compute. There, latency and bandwidth are real issues. You’d have to put enough datacenters close enough to people to make that viable and run enough fiber. And I’m not sure that we’ll ever reach the point where it makes sense to do remote compute for cloud gaming for everyone. Maybe.

But for AI-type parallel compute workloads, where the bandwidth and latency requirements are a lot less severe, and the useful returns from throwing a lot of electricity at the thing significant…then it might make a lot more sense.

I’d also point out that my guess is that AI probably will not be the only major parallel-compute application moving forward. Unless we can find some new properties in physics or something like that, we just aren’t advancing serial compute very rapidly any more; things have slowed down for over 20 years now. If you want more performance, as a software developer, there will be ever-greater relative returns from parallelizing problems and running them on parallel hardware.

I don’t think that, a few years down the road, building a computer comparable to the one you might in 2024 is going to cost more than it did in 2024. I think that people will have PCs.

But those PCs might running software that will be doing an increasing amount of parallel compute in the cloud, as the years go by.

They exist — and in fact, I have an Android tablet in my backpack right now — but a lot of people felt that they were going to become a major computing paradigm, and that hasn’t happened.

In practice, the PC today is mostly a conventional laptop. Hybrid laptops with touchscreen exist, but they aren’t the norm.

Mobile OS tablets also exist, but they haven’t managed to take over from smartphones or approach their marketshare, and there are fewer options on the market than there were a few years back; “mobile OS” tablets today are mostly, as best I can tell, a specialized device to use for video-watching with a larger screen than exists on a phone, with a larger screen and better built-in speakers, but without the sensors and radio suite. Not all that much uptake.

Oh, nice catch, thanks. I read it as “safe, without exploitable backdoors”, but that’s not what he was saying.

Flying cars. The idea has intuitive appeal — just drive like normal, but most congestion problems go away!

https://en.wikipedia.org/wiki/Flying_car

We’ve made them, but the tradeoffs that you have to make to get a good road vehicle that is also a good aircraft are very large. The benefits of having a dual-mode vehicle are comparatively limited. I think that absent some kind of dramatic technological revolution, like, I don’t know, making the things out of nanites, we’ll just always be better off with dedicated vehicles of the first sort or the second.

Maybe we could have call-on-demand aircraft that could air-ferry ground vehicles, but I think that with something on the order of current technology, that’s probably as close as we’ll get.

Well, it depends on the frequency range you’re talking about. In common usage, “radiation” often means something like ionizing radiation, but technically, UV light is a frequency of electromagnetic radiation.

https://en.wikipedia.org/wiki/Electromagnetic_radiation

In physics, electromagnetic radiation (EMR) or electromagnetic wave (EMW) is a self-propagating wave of the electromagnetic field that carries momentum and radiant energy through space.[1][2] It encompasses a broad spectrum, classified by frequency (inversely proportional to wavelength), ranging from radio waves, microwaves, infrared, visible light, ultraviolet, X-rays, to gamma rays.[3][4]

And if you include the ultraviolet frequency range, we did it decades ago:

https://www.dailymail.co.uk/sciencetech/article-1080042/Meet-Mr-Green-Genes--worlds-glow-dark-cat.html

Meet Mr Green Genes - the world’s first glow-in-the-dark cat

His eyes glow ghoulishly in the right light, just like any other cat’s - but so do his nostrils, gums and tongue.

Mr Green Genes of New Orleans in the U.S. is the country’s first ‘glow in the dark’ ginger tom.

In daylight he looks normal, but put him in a darkened room and switch on an ultraviolet light, and his face will beam out a bright green.

And so these humans would…be willing to do much to avoid the unchaining of these aquatic cats, you say?

https://en.wikipedia.org/wiki/One-time_pad

The one-time pad (OTP) is an encryption technique that cannot be cracked in cryptography. It requires the use of a single-use pre-shared key that is larger than or equal to the size of the message being sent.

deleted by creator

It’s not very high profile, but there are definitely a number of major plant cultivars that have been genetically engineered.

searches

https://www.ers.usda.gov/data-products/adoption-of-genetically-engineered-crops-in-the-united-states/recent-trends-in-ge-adoption

We just don’t really talk about it much, because the changes are things like better disease resistance or something useful but not especially mediagenic. We don’t have, oh, cats that can breathe underwater or something like that in 2026.

Tablets have had a couple of “waves”. They’ve never really gone away, but also haven’t really become the norm, either, not in the larger-than-a-current-smartphone sense.

https://en.wikipedia.org/wiki/Tablet_computer#Early_tablets

I’m long-term bullish on VR, if you mean having a HMD designed to provide an immersive 3D environment. Like, I don’t think that there are any fundamental problems with VR HMDs, and that one day, we will have HMDs that will probably replace monitors (unless some kind of brain-computer interface gets there first) and that those will expand do VR, if dedicated VR headsets don’t get there first. Be more portable, private, and power-efficient than conventional displays.

But the hardware to reasonably replace monitors just isn’t there today; the angular resolution isn’t sufficient to compete with conventional monitors. And I just don’t think that at current prices and with the current games out there, dedicated VR HMDs are going to take over.

I do agree with you that there have been several “waves” by companies trying to hit a critical mass that haven’t hit that point, but I think that there will ultimately come a day where we do adopt HMDs and that even if it isn’t the first application, VR will eventually be provided by those.

The post doesn’t really say what the goal is, which makes it hard to answer the question.

• Redundancy to improve storage reliability?

• Higher bandwidth?

• Something that can be presented to the camera or a computer as a larger single disk?

So an internet

The highest data rate it looks like is supported by LoRa in North America is 21900 bits per second, so you’re talking about 21kbps, or 2.6kBps in a best-case scenario. That’s about half of what an analog telephone system modem could achieve.

It’s going to be pretty bandwidth-constrained, limited in terms of routing traffic around.

I think that the idea of a “public access, zero-admin mesh Internet over the air” isn’t totally crazy, but that it’d probably need to use something like laser links and hardware that can identify and auto-align to other links.

https://meshmap.net/

These guys appear to have a global visualization of the Meshtastic network nodes that they can see.

No. What in my comment gave you that impression?

Google Maps

This is New York City, and from the Google Street View image, it looks like there’s not a lot of street parking there.

My guess is that a number of cities with a lot of density, like NYC, probably should mandate a certain amount of public parking garage space for users in an area. Multistory parking garage space isn’t cheap, but using up street space via committing space to street parking also has costs in terms of congestion, even if the business owner doesn’t bear the costs.

EDIT: I also note, by way driving the point home with a sledgehammer, that in my Google Street View image, there’s a different vehicle parked on the sidewalk in the same spot, a red sports car.

GitHub explicitly asked Homebrew to stop using shallow clones. Updating them was “an extremely expensive operation” due to the tree layout and traffic of homebrew-core and homebrew-cask.

I’m not going through the PR to understand what’s breaking, since it’s not immediately apparent from a quick skim. But three possible problems based on what people are mentioning there.

The problem is the cost of the shallow clone

Assuming that the workload here is always --depth=1 and they aren’t doing commits at a high rate relative to clones, and that’s an expensive operation for git, I feel like for GitHub, a better solution would be some patch to git that allows it to cache a shallow clone for depth=1 for a given hashref.

The problem is the cost of unshallowing the shallow clone

If the actual problem isn’t the shallow clone, that a regular clone would be fine, but that unshallowing is a problem, then a patch to git that allows more-efficient unshallowing should be a better solution. I mean, I’d think that unshallowing should only need a time-ordered index of commits referenced blobs up to a given point. That shouldn’t be that expensive for git to maintain an index of, if it doesn’t already have it.

The problem is that Homebrew has users repeatedly unshallowing a clone off GitHub and then blowing it away and repeating

If the problem is that people keep repeatedly doing a clone off GitHub — that is, a regular, non-shallow clone would also be problematic — I’d think that a better solution would be to have Homebrew do a local bare clone as a cache, and then just do a pull on that cache and then use it as a reference to create the new clone. If Homebrew uses the fresh clone as read-only and the cache can be relied upon to remain, then they could use --reference alone. If not, then add --dissociate. I’d think that that’d lead to better performance anyway.