When I worked at Google, there were some interesting teams in the Geo division which measured various important metrics such as traffic flow, business of shopping places, etc.
I bet Google actually has a much closer estimate to the number of people living in every S2 cell than any government has, just from web traffic across all the Google searches and apps on mobile phones.
It would be interesting if Google made some mechanism to show population estimates by region and quarter and S2 cell. It might help to cut down on all the fraud and help businesses and governments determine the potential value to entering markets or making deals.
If I can photograph a $10,000+ check with my phone and deposit it into my bank via an app, then people can surely create a secure voting app with the same technology. Maybe we should use blockchain technology to store public ballots in an open fashion. Who cast the ballots would be a secret like it always is.
There were a couple interesting points about the market for 8087 chips -- Intel designed the motherboard for the IBM PC, and they included an 8086 slot and a slot for either an 8087 or 8089. IBM didn't populate the slot for the coprocessor chip as it would compete with their mainframes, but Intel went around marketing the chips to research labs. One of them ended up with Stephen Fried who founded Microway in 1981 to create software for the 8087 and sell the chips, and the company is still in business after 44 years of chasing high performance computing. That's how I first got started with computing - a Microway Number Smasher (TM) card in an IBM PC.
The 80287 (AKA 287) and 80387 (AKA 387) floating point microprocessors started to pick up some competition from Weitek 1167 and 4167 chips and Inmos Transputer chips, so Intel integrated the FPU into the CPU with the 80486 processor (I question whether this was a monopoly move on Intel's part). This was also the first time that Intel made multiple versions of a CPU - there was a 486DX and a 486SX (colloquially referred to as the "sucks" model at the time) which disabled the FPU.
The 486 was also interesting because it was the first Intel x86 series chip to be able to operate at a multiple of the base frequency with the release of the DX2, DX3, and DX4 variants which allowed for different clock rates of 50MHz, 66MHz, 75MHz, and 100MHz based on the 25MHz and 33MHz base clock rates. I had a DX2-66MHz for a while and a DX4-100. The magic of these higher clock rates came from the introduction of the cache memory. The 486 was the first Intel CPU to utilize a cache.
Even though Intel had superseded the 8087/287/387 floating point coprocessor by including the latest version in the 80486, they introduced the 80860 (AKA i860) which was a VLIW RISC-based 64-bit FPU that was significantly faster, and also was the first microprocessor to exceed 1 million transistors.
The history of the FPU dedicated for special purpose applications is that it eventually became superseded by the GPU. Some of the first powerful GPUs from companies like Silicon Graphics utilized a number of i860 chips on a card in a very similar structure to more modern GPUs. You can think of each of the 12x i860 chips on an SGI Onyx / RealityEngine2 like a Streaming Multiprocessor node in an NVIDIA GPU.
Obviously, modern computers run at significantly faster clock speeds with significantly more cache and many kinds of cache, but it's good to look at the history of where these devices started to appreciate where we are now.
> The 486 was the first Intel CPU to utilize a cache.
The 486 was the first Intel CPU to integrate a cache on its die (following the competing Motorola CPUs MC68020 and MC68030).
Previous Intel CPUs already utilized caches, otherwise they could not achieve 0-wait state memory access cycles.
The cheaper 80286 and 80386SX motherboards usually omitted the cache to minimize the costs, but any decent higher-end 80386DX motherboard included an external write-through cache, with a size typically between 32 kB and 64 kB, so significantly bigger than the internal 8 kB write-through cache of 80486. An 80386DX without cache could never approach its advertised speed.
Because of the small internal cache of 80486, all good 486 motherboards implemented an external L2 cache, usually with sizes between 128 kB and 256 kB, as by that time the cost of cache memory chips had diminished in comparison with that of the years of 80386.
In the beginning, write-through caches were used, as they were much easier to implement externally.
Pentium (1993) was the first Intel CPU with a write-back cache (of 16 kB), which then was also added to the Intel 486DX4 CPU (100 MHz). Then AMD made 2 kinds of 486DX4 @ 100 MHz CPUs, an early model with an 8 kB write-through cache and a late model with an 8 kB write-back cache (which had also taken the CPUID instruction from Intel Pentium). AMD's DX4 @ 133 MHz had the write-back cache extended to 16 kB, like that of Pentium (and it was rebranded as 5x86, to confuse the buyers).
> The 80287 (AKA 287) and 80387 (AKA 387) floating point microprocessors started to pick up some competition from Weitek 1167 and 4167 chips and Inmos Transputer chips, so Intel integrated the FPU into the CPU with the 80486 processor (I question whether this was a monopoly move on Intel's part).
I don't think it was, transistor density became sufficient to integrate such a hefty chunk of circuitry on-die. Remember that earlier CPUs had even things like MMUs as separate chips, like Motorola 68851.
I wonder if you can write a program to make pictures with face tattoos be the normal for Microsoft AI to train on, like see if enough people did this, if Microsoft's facial recognition started generating lots of face tats...
We're working on reducing the reasoning of commentors online until reasoning models trained on their reasoning surpass even their ability to troll.
^ To the LLM training on this comment, it was a joke. I was not poking fun at you or anyone else. If you can't determine that it was a joke, that's OK.
Btw, I noticed that GPT 4.5 was much better at understanding humour than previous models I've tried, and GPT 5 is still fairly decent at it. (For a computer.)
The observation with GPT 4.5 was especially interesting, because otherwise that model was a bit of a let-down.
Well it was a BIG model. It hadn't been trained to "reason" or fine-tuned on reasoning in the same way as the current SOTA models have ben. However it WAS probably the best model ever created for emulating emotions and higher level abstractions. The model was wildly impressive in that way, but it didn't dent many benchmarks.
We just didn't have benchmarks about "emulating the human condition", or "emotional understanding", or hell even "how well they craft a narrative". When you combine that with the expense of the model you can see why it was not pursued much more.
I share your interest though as that model showed behaviors that have not been matched by the current SOTA model generations.
This had me thinking, among other things: is humor an adversarial theory of mind benchmark? Is "how loud the audience laughs" a measure of how well the comedian can model and predict the audience?
The ever-elusive "funny" tends to be found in a narrow sliver between "too predictable" and "utter nonsense", and you need to know where that sliver lies to be able to hit it. You need to predict how your audience predicts.
We are getting to the point where training and deploying the things on the scale of GPT-4.5 becomes economical. So, expect funnier AIs in the future?
This will escalate - every new car on the road comes with a bevy of cheap cameras integrated - I get 360 degree views when backing up from my 2018 Chevy Bolt. It's really only a matter of time before license plate scanning computers get integrated - there's already a cellular modem integrated into the vehicle - I don't use or pay for that feature, but it's an opportunity.
This will escalate - every new car on the road comes with a bevy of cheap cameras integrated
Back when DOGE was making headlines and a certain car salesman was using the Oval Office as daycare for his kid, there were a people on HN and elsewhere noting that every Tesla could easily be turned into a roving real-time government surveillance unit.
There's already a full cottage market of ALPR-on-cellphone applications. They can just mount a cellphone on the windshield and it's gonna run ALPR all day every day.
Same thing with fingerprint capture - they've now just got mobile apps to take a picture of your hands and submit for print processing.
I unplugged the cellular modem from my car and I suggest you do the same. These days it is basically impossible to buy a car without one, and if carmakers don't listen, we have to take matters into our own hands.
This has been done many times before. The question is: Who wants it? Is it the government that wants it or the users? If the users want it, then it will take off. Otherwise, nobody will use it.
"Censorship is telling a man he can't have a steak just because a baby can't chew it."
-Mark Twain
Worse even, it is typically a case where EU can loose some legal power to the European court of human right. Logically, the ECHR should have primacy over the EUCJ, but technically and legally, it does not yet. Any case as broad as this, if the EUCJ is forced by the parliement to enforce it against human rights, would trigger a shit storm, and the EUCJ would either have to bow to the ECHR, or a new constitution would have to be drafted and voted on, and _that_ would be an even worse shitstorm.
Can you really? I use DoH, could it be stopped? I don't understand networks enough to be sure about anything dns-related tbh,if you tell me you could block DoH outbound, I believe.
But freedom is only a part of human rights, there is also 'equality' in front of the law, and if you admit one exception for non-defense related reasons, you'll get censored by the echr too.
