This article has a striking absence, that being the name "John Atanasoff"[0], whose electronic digital calculator was seen and examined by Mauchly in 1941, and who spoke to Mauchly multiple times during the years when ENIAC was being built.
It was this connection that ultimately blocked Eckert and Mauchly from patenting the idea of the digital computer.[1]
…and whose digital calculator was _just_ a calculator (not a general purpose computer) that read values from a mechanical drum (so not fully electronic), and sat in a basement until it was later disassembled. That this device managed to qualify as prior art is mostly just an exhibit of how the trial system isn’t especially good at divining truth. So annoying that the ABC is a permanent barnacle on the ENIAC story.
The ABC's memory was not mechanical, even if the drum was driven directly by an electric motor. It was a self-refreshing series of capacitors using the same general mechanism as modern, non-persistent memory (self-regenerating I think?). It's was one of the other parts of the ABC that invalidated the Eniac patents, in addition to the ABC's binary adders. But the memory itself was entirely digital.
Sorry, I shortened to the point of inaccuracy - I should have said not fully electronic _speed_. Not meant to say that it was mechanically reading and writing values per se, just that the slow rotation of a mechanical drum was essential for its operation and ultimately had a limiting effect on the speeds it could compute. Thus the electronic storage and compute was rather defeated by inclusion of a mechanical element in the “critical path”, so to speak. I think that’s accurate to say?
Not any more accurate than it is to say the electronic storage and compute of any computer is defeated by the latency of its memory. Virtually all early memory devices were deeply limited.
Really the ABC was most limited by its use of a custom I/O device which used electrically burned holes in special paper to input the initial problem state and output the solution. Atanasoff never got it working reliably, which is the main reason the ABC was never fully functional before WWII.
In any case, the fixed nature of the ABC is often why its considered the first "digital electronic computer" and the ENIAC the first "general purpose digital electronic digital computer" (or later, the first "programmable digital electronic digital computer", after it was rebuilt in '46 - '47 to operate more like a modern computer).
Unfortunately I'm not familiar enough with Zuse's computers or the Colossus to say if those statements are really accurate.
> It was this connection that ultimately blocked Eckert and Mauchly from patenting the idea of the digital computer.
Why would a connection be relevant? A patent can be blocked by prior art, but that theoretically happens whether you know about the prior art or not.
Knowledge is relevant to how guilty you are over infringing an existing patent, and it's relevant to copyright, but I didn't think it was relevant to patentability.
I heartily recommend both (if you can find them) "The First Electronic Computer: The Atanasoff Story" (for a technical look at the computer itself, by Arthur and Alice Burks) and "Who Invented The Computer?" (for a history of the ABC as it applies to the patent trial, by Alice Burks).
With that experience, why have you stayed with that provider? It would seem to be no harder, and quite satisfying, to open new accounts with another provider for you and your wife, and then cancel these accounts.
Basically every provider seems to have a similar level of customer support.
For banking in particular, I already bank with a half-dozen banks because they have different products/services that are optimal for some specific use cases (i.e. I min-max my bank accounts, credit cards, and investment accounts.) — however, customer support seems to be universally bad.
If you're curious about why I'm using that particular bank, I'm forced to use them for some investment accounts because my employer matching benefits uses them. For the credit card, they're one of the few banks that offer proper co-applicants (rather than just supplemental users) which really works best for the way my wife and I have our finances organized. And flights in my city are dominated by a single airline where the only way to avoid paying for baggage is to get the co-branded credit card from this bank.
Taiwanese researchers found that a carbohydrate-binding protein (i.e. a legume lectin) from lablab beans effectively blocks the infections of influenza viruses and SARS-CoV-2.[60] Researchers from Finland and USA found that extracts from chewing gum manufactured from lablab bean seeds had broad-spectrum anti-viral properties, likely due to the binding action of Flt3 Receptor Interacting Lectin (FRIL) on viruses; the anti-viral effect was similar to that of purified FRIL
Relevant: A San Francisco company is advertising humanoid robot housecleaning services[1]. However those 'bots require local supervision and a human controller watching through its video feed.
Presumably that company could use the Gemini Robotics product to eliminate the remote controller.
I actually like Tau's videos a lot better than Google's. An agile robot getting out of a car carrying a tote is actually novel and difficult and useful. In contrast, what Google is showing here is mostly glorified pick and place with low success rates on a needlessly complex robot and a voice LLM slapped on top to pre-announce its moves like an anime character, with fancy video editing and bubbly music to distract you from how slow it is.
Sure Tau is teleoperated, but teleoperating an agile movement like that is actually really hard to get right and still involves AI to keep the robot balanced. Tau is a lot closer to real deployment than Google, and when it performs useful tasks it is simultaneously collecting the data to eventually automate those tasks.
I've done, and still do, regular blogging. I have a domain, and everything I post is mine. However it can't be "indieweb" because I used Wordpress. Hence my current blog is dependent on a corporation, as were a couple of older ones that were built in Blogger (and still exist, last updated nearly a decade ago).
That dependency is because isn't feasible for me to own my own server. If I did, it would either be virtual, in amazon's or microsoft's cloud, or it would be real hardware but still in some corporate server farm. It just wouldn't be practical for me to own (and maintain) a physical server with an UPS and permanent uplink to the net.
I have my own hosted server on some old nuc pc I got for free. You don't need an UPS or permanent uplink. A blog isn't so important that the world will end if your blog goes offline for a day. How often do you lose power or internet, is that one time a year really that big of a deal?
Says, not inflation-adjusted. With reason; adjusting those 1960-1980 prices for inflation would make the graph a lot taller.
Pricing "per GB" before 1990 is unrealistic, though; nobody thought in GB or purchased GB quantities, or conceived of GB systems. I remember a moment circa 1973 when I saw an IBM CE about to do an upgrade on a 370 system at Cal Berkeley. He had a box with several carefully-packed, large circuit boards. "So, is that a megabyte?" I asked. "Yup, that's a meg."
The author clearly wasn't implying that these were 1GB chips. They just wanted to show a graph scaled per unit of memory. It could just as well have been per byte, and the graph would've been identical but the values on the left would be changed by a factor of a billion.
You could argue that you'd rather see a "price per typical-sized RAM chip as sold at the time". That would also be a perfectly valid thing to graph (though a bit more subjective), but it doesn't invalidate this one. Since per byte (or GB or whatever you want to say) has continued downward all this time, it makes the recent spike all the more notable.
(I'm not sure it's right to label vacuum tubes and core memory as "DRAM" though.)
The problem with "price per typical-sized RAM chip as sold at the time" is not so much that it's subjective, but you'd get artificial spikes in the data.
For me, the key take home from the graph as stands is that price per GB right now is about the same as 2020. That seems reasonable, it's more expensive than it was, but only outrageous if you forget what it was like only a short while ago.
But back in 2020, 4GB or 8GB sticks were most common, a few years ago it was up to 8GB, 16GB or 32GB, and now 2x8GB seems to be the most common high-end configuration or 2x4GB for low-end again. If you'd jumped from 8GB sticks to 32GB sticks and back again, it would seem like there was a spike up around 2021-2 and that memory was cheaper now than a few years ago.
I think the main driver for the data is that probably consumers or the market decides on a reasonable price for memory, and people buy whatever they can get for that money. When I had a Z80 computer in the mid 80s, 64KB expansion RAM was about £100. For a similar computer but a few years earlier, a 32KB expansion RAM was about the same price. When I had an Amiga in the early 90s, a 512KB expansion RAM was again around the same price. In the 2000s, a couple of MB was around the same price. Maybe 5 years ago, the market was split a bit and a 4GB RAM was around £60 and 8GB around £120, but maybe this reflects "under $100" as the ideal target. A few years ago, it was similar but 8GB for around £80 and 16GB for around £160, now it's "doubled" in price, it's just back to 8GB for £120 again. But whatever the decade, it seems people are prepared to spend about £100 on memory for an average PC.
IMO you'd really need to graph the price of how much RAM is needed to comfortably run contemporary OS + software combinations. That will get you an actual picture of the pain inflicted by the RAM prices.
And yes, RAM demand goes up with the average RAM in computers but it does lag and it's not yet clear if it will go down with increasing ram prices as IT corporations can still afford the more expensive RAM needed for the developers to run the RAM-hungry applications they need to run, which means they won't be dogfooding their software in a normal budget user environment and are less motivated to optimize for a reasonably priced amount of RAM.
Depressing to see how much discussion on HN (!!) has resulted from a objectively terrible graph reading. I mean... in the process of our infiltration by finance bros and VC money, have we genuinely forgotten how exponentials work?
What? Gold underwent a massive revaluation with the end of Bretton Woods in 1971. It was prior to then that government were actively involved in making the price of gold artificially low.
Fun fact: under 31 U.S. Code § 5117 a troy ounce of gold is still valued at 42 and 2/9ths dollars.
Gold became much ‘cheaper’ in the period 1945-70 because there was a series of technical revolutions in South Africa mining (never mind the apartheid …) This is why Breton Woods lasted as long as it did.
The countries like France that conspired in resentment to break it as ‘privilege’ are now effectively in flames.
The right to a civil jury trial in the 7th Amend. to the US Constitution is only available where the value in controversy exceeds twenty dollars (a massive sum in 1791, and a trifle now).
You got it backwards; ending the gold standard was very much a unilateral decision by the United States because Nixon couldn't handle making politically unpopular decisions to cut spending and/or end the Vietnam war. Many countries that had their gold reserves held via US dollars were livid.
Well, there's an arguable point of fiscal policy there, and a conspiracy rathole that no one wants to excavate.
But none of that matters here. As grandparent comment indicates, you're making a pretty fundamental math error. This is a log chart. Government may have devalued currency. It did not do so exponentially.
I wouldn't go so far as to say "nobody". Electric Boat had 2 GB memory in one of its systems at that time, with the hardware capacity to increase to 4 GB. It sounded insane at the time, but it absolutely existed, and thereby seems reasonable to include it in any research of historical pricing.
Yes, you really need "dollars per amount of RAM you need for standard computing tasks." Windows 11 requires a bare minimum of 4 GB of RAM, Window 10 only needed 1 GB.
If what you're interested in is fluctuations in production versus demand then you absolutely do not want a subjective metric. Measures of the form dollars per unit, units per watt, units per flop, etc are what you're interested in.
Discussion of memory in terms of words and their bit length, time to complete a task is more meaningful to intent on use and compaction, see greycode technique. Dollars of slop a unit sacrifice skills in the industrial base for the gain of paper profits at the repeating business meetings.
Have you ever actually tried using Windows 10 with 1GB of RAM? I wouldn't consider it suitable for "standard computing tasks."
And that's the hangup, what do you consider a "standard computing task?" On what OS? Running what software? How well? Plenty of people were still using XP in 2009, so is 256 MB of RAM okay for "standard computing tasks" in 2009?
> Have you ever actually tried using Windows 10 with 1GB of RAM? I wouldn't consider it suitable for "standard computing tasks."
I have [0], and it's actually not quite as bad as you would expect. It certainly wasn't fast, but I had no problem using it for basic web browsing and document editing. The painfully slow hard drive and processor speeds on that computer actually caused more issues than the lack of RAM.
I remember installing Windows 10 on my laptop when I was in high school, it was a decommissioned Thinkpad T410s from my dad's work. 4GB of RAM, Nehalem i5, a very early consumer SSD (OCZ, if I recall). I vividly remember my first thought being "wow this is really slow." Win7 ran like a champ on that machine.
My experience with Win10 on that laptop actually led me to buy a dumb gamer laptop for college. As those all do, it died prematurely, so I ended up back on the T410s for a while. I put KDE Neon on it. It was great!
If you're saying that you can install and use Win10 on a laptop with 1 GB of RAM, well yes I acknowledge that is true. But it's a purely academic exercise, it's not actually a usable computer for the overwhelming majority of people.
Maybe it would have been fine for my grandma. She was using a Pentium II running Windows XP to go on Facebook in the early 2010s.
Well it's complicated. Y2K was a combination of logic issues and the consequences of certain inefficient ways to store dates, like text and BCD. Migrating to binary could fit plenty of dates into the same space or even less.
In particular, 16 bits is enough to store the entire date, year month day, from 1900 into mid 2079. Any date format that couldn't go past 1999 was probably using 24-48 bits.
Abstractions on abstractions on abstractions; background tasks and their abstraction stacks; increased cache and buffer sizes to take advantage of increased typical memory capacity. For an example of the latter, handling TCP on a Commodore 64 is a problem because the memory can only fit about 45 packets with nothing left over, but now you can just allocate a megabyte receive buffer per connection.
Neither do the developers, because until recently, RAM was so cheap it didn’t matter, and we were in a situation where almost no one ever needed to consider “how much RAM will this take?” when writing code.
Like Homer Simpson said about alcohol: "To alcohol! The cause of, and solution to, all of life's problems", we developers can say about AI (assuming AI-assisted coding can save memory in popular programs, OSes, etc)
I once held in my hand the main part of a ferrite core memory module from the early 70s. It was kilobytes at best.
I also recall looking at recommended requirements for Dungeon Keeper 2 - 266MHz CPU, 64MB RAM and thinking "that's absurd - no such device exists!". I was a kid back then, so what did I know?
Later on in college a friend showed us his absolute monster of a laptop with a whopping 8GB of RAM - he could spin up several VMs on one device! Groundbreaking on a (nominally) portable device.
So yeah, safe to say the notion of gigabytes of RAM anywhere close to a regular person belongs firmly to the 21st century.
So total system cost per unit of memory is going up.. 2GB costs in 1985 was $2 million (from the graph), a cray-2 was $16 million (from wikipedia). A GPU server with 8xB200 today can be had for ~$500k (estimate), 1.5TB memory is $25k (from the graph).
The natural unit of measure for integrated circuits is a power of 2 since that's what the systems operate in. It's so natural that early 9 and 36 bit architectures were squeezed into 8 and 32 bits as it just works so much more efficiently.
Long term storage and communications? Those start to introduce things like human division of timings, frequencies, and other analog systems like rotating disks. It still generally makes sense fab actual flash chips in various powers of 2 though. The discrepancy there tends to be various forms of 'overhead' for the translation table / wear level indirection, over-provisioning, and even variations in density caused by different levels of physical cell utilization.
Still, most network stuff ships around packets of 'up to' 1500 bytes ( https://en.wikipedia.org/wiki/Ethernet_frame and lets just exclude jumbo frames ) so arguably it'd be better to talk about all computer measures in binary powers of two, exclude the marketing huckster trying to make things more impressive by shoehorning SI engineering units into a realm that uses binary math.
Per Wikipedia, it "is a colorless, odorless, non-flammable, and non-toxic gas."
When used as a contrast agent for ultrasound, it "has been used to examine the vascularity of tumours" -- which would be similar to its use in the OP. Then
"[i]t remains visible in the blood for 3 to 8 minutes, and is exhaled by the lungs."
So -- not collected and excreted by the liver, as I at first thought.
"Multimodal AI systems are increasingly deployed on the assumption that their benchmark performance reflects genuine visual understanding. Our results fundamentally challenge these assumptions. Across every model-benchmark pair tested, the accuracy that frontier models achieved without any access to images exceeded the additional accuracy they gained when images were provided. Moreover, a text-only 3-billion-parameter model, trained solely on question-answer pairs stripped of images, outperformed all frontier multimodal systems and human radiologists on a held-out chest radiology benchmark. Taken together, these results demonstrate that high benchmark accuracy does not reliably indicate visual understanding."
Basically, they are so good at extracting clues from the text of the questions, and extrapolating from them, that they proceed to answer _as if_ they had an image to view. With confidence, of course.
https://507movements.com/mm_027.html