Plus the cell phone industry paved the way for VOIP by getting everyone used to really, really crappy voice quality. Generations of Bell Labs and Bellcore engineers would rather have resigned than be subjected to what's considered acceptable voice quality nowadays...
HLS is really just a way to empower the client with the ownership of the playback logic. Let the client handle forward buffering, retries, stream selection, etc.
What accounts for this difference? Is there something inherently worse about the nature of cell phone infrastructure over land-line use?
I'm totally naive on such subjects.
I'm just old enough to remember landlines being widespread, but nearly all of my phone calls have been via cell since the mid 00s, so I can't judge quality differences given the time that's passed.
Has it not been like this for a very long time? I was under the impression that "voice frequency" being defined as up to 4 kHz was a very old standard - after all, (long-distance) phone calls have always been multiplexed through coaxial or microwave links. And it follows that 8kbps is all you need to losslessly digitally sample that.
I assumed it was jitter and such that lead to lower quality of VoIP/cellular, but that's a total guess. Along with maybe compression algorithms that try to squeeze the stream even tighter than 8kbps? But I wouldn't have figured it was the 8kHz sample rate at fault, right?
The speech codecs are complex and fascinating, very different from just doing a frequency filter and compressing.
The base is linear predictive coding, which encodes the voice based on a simple model of the human mouth and throat. Huge compression but it sounds terrible. Then you take the error between the original signal and the LPC encoded signal, this waveform is compressed heavily but more conventionally and transmitted along with the LPC signal.
Phones also layer on voice activity detection, when you aren't talking the system just transmits noise parameters and the other end hears some tailored white noise. As phone calls typically have one person speaking at a time and there are frequent pauses in speech this is a huge win. But it also makes mistakes, especially in noisy environments (like call centers, voice calls are the business, why are they so bad?). When this happens the system becomes unintelligible because it isn't even trying to encode the voice.
Huh? What? That's not even remotely true.
If you read your comment out loud, the very first sound you'd make would have almost all of its energy concentrated between 4 and 10 kHz.
Human vocal cords constantly hit up to around 10 kHz, though auditory distinctiveness is more concentrated below 4 kHz. It is unevenly distributed though, with sounds like <s> and <sh> being (infamously) severely degraded by a 4 kHz cut-off.
The 8kbps rates on cellular are the more complicated (relative to G.711) AMR-NB encoding. AMR supports voice rates from about 5-12kbps with a typical 8kbps rate. There's a lot more pre and post processing of the input signal and more involved encoding. There's a bit more voice information dropped by the encoder.
Part of the quality problem even today with VoLTE is different carriers support different profiles and calls between carriers will often drop down to the lowest common codec which is usually AMR-NB. There's higher bitrate and better codecs available in the standard but they're implemented differently by different carriers for shitty cellular carrier reasons.
I'm a moron, thanks. I think I got the sample rate mixed up with the bitrate. Appreciate you clearing that up - and the other info!
1. it takes considerable work on my part to understand it on a cell phone
2. it's much easier on POTS
3. it's not a problem on VOIP
4. no issues in person
With all the amazing advances in cell phones, the voice quality of cellular is stuck in the 90's.
At home, I use VoLTE and the sound is almost impeccable, very high quality, but in the places I roam to, what I get is FM quality 3G sound.
It's not that cellular network is incapable of that sound quality, but I don't get to experience it except my home country. Interesting, indeed.
3G networks in many European countries were shut off in 2022-2024. The few remaining ones will go too over the next couple of years.
VoLTE is 5G, common throughout Europe. However the handset manufacturer may need to qualify each handset model with local carriers before they will connect using VoLTE. As I understand the situation, Google for instance has only qualified Pixel phones for 5G in 19 of 170-odd countries. So 5G features like VoLTE may not be available in all countries. This is very handset/country/carrier-dependent.
Technically, on 5G you have "VoNR"[0], where VoLTE is over 4G.
Also, the phone companies had a pathological aversion to understanding Moore's law, because it suggested they'd have to charge half as much for bandwidth every 18 months. Long distance rates had gone down more like 50%/decade, and even that was too fast.
The rise of the net is Jevons paradox fulfilled. The orders of magnitude less bandwidth needed per cat video drove much more than that in overall growth in demand for said videos. During the dotcom bubble's collapse, bandwidth use kept going up.
Even if there is a near-term bear case for NVDA (dotcom bubble/bust), history indicates a bull case for the sector overall and related investments such as utilities (the entire history of the tech sector from 1995 to today).
Better video compression led to an explosion in video consumption on the Internet, leading to much more revenue for companies like Comcast, Google, T-Mobile, Verizon, etc.
More efficient LLMs lead to much more AI usage. Nvidia, TSMC, etc will benefit.
If the AI market gets 10x bigger, and GPU work gets 50% smaller (which is still 5x larger than today) - but Nvidia is priced on 40% growth for the next ten years (28x larger) - there is a price mismatch.
It is theoretically possible for a massive reduction in GPU usage or shift from GPU to CPU to benefit Nvidia if that causes the market to grow enough - but it seems unlikely.
Also, I believe (someone please correct if wrong) DeepSeek is claiming a 95% overall reduction in GPU usage compared to traditional methods (not the 50% in the example above).
If true, that is a death knell for Nvidia's growth story after the current contracts end.
Nope. Anything inheriantly serial is better off on the CPU due to caching and it's architecture.
Many things that are highly parallizable are getting GPU enabled. Games and ML are GPU by default, but many things are migrating to CUDA.
You need both for cheap, high performance computing. They are different workloads.
No - because this eliminates entirely or shifts the majority of work from GPU to CPU - and Nvidia does not sell CPUs.
Whether your new coprocessor or instructions look more like a GPU or something else doesn't really matter if we are done squinting and calling it graphics like problems and/or claiming it needs a lot more than a middle class PC.
CPU chipsets have borrowed video decoder units and SSE instructions from GPU-land, but the idea that video decoding is a generic CPU task now is not really true.
Now maybe every computer will come with an integrated NPU and it won't be made by Nvidia, although so far integrated GPUs haven't supplanted discrete ones.
I tend to think today's state-of-the-art models are ... not very bright, so it might be a bit premature to say "640B parameters ought to be enough for anybody" or that people won't pay more for high-end dedicated hardware.
Depends on what form factor you are looking at. The majority of computers these days are smart phones, and they are dominated by systems-on-a-chip.
If stock market-cap is (roughly) the market's aggregated best guess of future profits integrated over all time, discounted back to the present at some (the market's best guess of the future?) rate, then increasing uncertainty about the predicted profits 5-10 years from now can have enormous influence on the stock. Does NVDA have an AWS within it now?
Cisco in 1994: $3.
Cisco after dotcom bubble: $13.
So is Nvidia's stock price closer to 1994 or 2001?
It’s very shortsighted to think we’re going to need fewer chips because the algorithms got better. The system became more efficient, which causes induced demand.
Most likely, consumer surplus has gone up.
Not only are 10-100x changes disruptive, but the players who don't adopt them quickly are going to be the ones who continue to buy huge amounts of hardware to pursue old approaches, and it's hard for incumbent vendors to avoid catering to their needs, up until it's too late.
When everyone gets up off the ground after the play is over, Nvidia might still be holding the ball but it might just as easily be someone else.
Anyone currently invested is presumably in because they like the insanely high profit margin, and this is apt to quash that. There is now much less reason to give your first born to get your hands on their wares. Comcast, Google, T-Mobile, Verizon, etc., and especially those not named Google, have nothingburger margins in comparison.
If you are interested in what they can do with volume, then there is still a lot of potential. They may even be more profitable on that end than a margin play could ever hope for. But that interest is probably not from the same person who currently owns the stock, it being a change in territory, and there is apt to be a lot of instability as stock changes hands from the one group to the next.
I'm invested in Nvidia because it's part of the index that my ETF is tracking. I have no clue what their profit margins are.
That would be an unusual situation for an ETF. An ETF does not usually extend ownership of the underlying investment portfolio. An ETF normally offers investors the opportunity to invest in the ETF itself. The ETF is what you would be invested in. Your concern as an investor in an ETF would only be with the properties of the ETF, it being what you are invested in, and this seems to be true in your case as well given how you describe it.
Are you certain you are invested in Nvidia? The outcome of the ETF may depend on Nvidia, but it may also depend on how a butterfly in Africa happens to flap its wings. You aren't, by any common definition found within this type of context, invested in that butterfly.
The ETF is just one more layer of indirection. You might like to read https://en.wikipedia.org/wiki/Exchange-traded_fund#Arbitrage... to see how ETFs are connected to the underlying assets.
You will find that the connection between ETFs and the underlying assets in the index is much more like the connection between your Robinhood portfolio and Nvidia, than the connection between butterflies and thunderstorms.
[0] At least for its stocks. Its bonds are probably held in different but equally weird ways.
Technically, but they extend ownership. An ETF is a different type of abstraction. Which you already know because you spoke about that abstraction in your original comment, so why play stupid now?
An ETF typically holds the underlying assets, and you own a part of the ETF.
Bandwidth is one thing, but the real benefit is that ATM also guaranteed minimal latencies. You could now shave off another 20-100ms of latency for your FaceTime calls, which is subtle but game changing. Just instant-on high def video communications, as if it were on closed circuits to the next room.
For the same reasons, the AI analogy could benefit from both huge processing as well as stronger algorithms.
Which means you need state (and the overhead that goes with it) for each connection within the network. That's horribly inefficient, and precisely the reason packet-switching won.
> An internet based on ATM would have been amazing.
No, we'd most likely be paying by the socket connection (as somebody has to pay for that state keeping overhead), which sounds horrible.
> You could now shave off another 20-100ms of latency for your FaceTime calls, which is subtle but game changing.
Maybe on congested Wi-Fi (where even circuit switching would struggle) or poorly managed networks (including shitty ISP-supplied routers suffering from horrendous bufferbloat). Definitely not on the majority of networks I've used in the past years.
> The horror of packet switching is all the buffering it needs [...]
The ideal buffer size is exactly the bandwidth-delay product. That's really not a concern these days anymore. If anything, buffers are much too large, causing unnecessary latency; that's where bufferbloat-aware scheduling comes in.
The latency benefit would outweigh the cost. Just absolutely instant video interaction.
And for the little bit of impact queueing latency has (if done well, i.e. no bufferbloat), I doubt anyone would notice the difference, honestly.
What I recall is that it was at a time when Internet folks had made enormous advances in understanding congestion behavior in computer networks, and other folks (e.g. my division of Motorola) had put a lot of time into understanding the limited burstiness you get with silence suppression for packetized voice, and these folks knew nothing about it.
You don't actually need all that much buffering.
Buffer bloat is actually a big problem with conventional TCP. See eg https://news.ycombinator.com/item?id=14298576
I already do this. But I cheat - I use a good router (OpenWrt One) that has built-in controls for Bufferbloat. See [How OpenWrt Vanquishes Bufferbloat](https://forum.openwrt.org/t/how-openwrt-vanquishes-bufferblo...)
DCT was developed in 1972 and has a compression ratio of 100:1.
H.264 compresses 2000:1.
And standard resolution (480p) is ~1/30th the resolution of 4k.
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I.e. Standard resolution with DCT is smaller than 4k with H.264.
Even high-definition (720p) with DCT is only twice the bandwidth of 4k H.264.
Modern compression has allowed us to add a bunch more pixels, but it was hardly a requirement for internet video.
It doesn’t have a compression ratio.
Therefore, it has no compression ratio, and it doesn’t make sense to compare it to other algorithms.
The real compression comes from quantization and entropy coding (Huffman coding, arithmetic coding, etc.).
Modern compression algorithms were developed but not even computationally available for some of the time.
Didn't TMSC say that SamA came for a visit and said they needed $7T in investment to keep up with the pending demand needs.
This stuff is all super cool and fun to play with, I'm not a nay sayer but it almost feels like these current models are "bubble sort" and who knows how it will look if "quicksort" for them becomes invented.
That only lasted so long. Then it was heavy machinery (hydraulics, excavators, etc)
Back then a really big motivator for Asynchronous Transfer Mode (ATM) and fiber-to-the-home was the promise of video on demand, which was a huge market in comparison to the Internet of the day. Just about all the work in this area ignored the potential of advanced video coding algorithms, and assumed that broadcast TV-quality video would require about 50x more bandwidth than today's SD Netflix videos, and 6x more than 4K.
What made video on the Internet possible wasn't a faster Internet, although the 10-20x increase every decade certainly helped - it was smarter algorithms that used orders of magnitude less bandwidth. In the case of AI, GPUs keep getting faster, but it's going to take a hell of a long time to achieve a 10x improvement in performance per cm^2 of silicon. Vastly improved training/inference algorithms may or may not be possible (DeepSeek seems to indicate the answer is "may") but there's no physical limit preventing them from being discovered, and the disruption when someone invents a new algorithm can be nearly immediate.