371–380 of 500 posts
I'm rooting for DeepSeek (or any competitor) against OpenAI because I don't like Sam Altman. I'm confident in admitting it.
The enemy of your enemy is only temporarily your friend.
I'm curious if someone more informed than me can comment on this part: > Besides things like the rise of humanoid robots, which I suspect is going to take most people by surprise when they are rapidly able to perform a huge number of tasks that currently require an unskilled (or even skilled) human worker (e.g., doing laundry ... I've always said that the real test for humanoid AI is folding laundry, because it's an…
Even if DeepSeek has figured out how to do more (or at least as much) with less, doesn't the Jevons Paradox come into play? GPU sales would actually increase because even smaller companies would get the idea that they can compete in a space that only 6 months ago we assumed would be the realm of the large mega tech companies (the Metas, Googles, OpenAIs) since the small players couldn't afford to compete. Now that st…
Jevons paradox isn't some iron law like gravity.
Great article. I still feel like very few people are viewing the Deepseek effects in the right light. If we are 10x more efficient it's not that we use 1/10th the resources we did before, we expand to have 10x the usage we did before. All technology products have moved this direction. Where there is capacity, we will use it. This argument would not work if we were close to AGI or something and didn't need more, but I…
Yep. I’ve been harping on this. DeepSeek is bullish for Nvidia.
DeepSeek is bullish for the semiconductor industry as a whole. Whether it is for Nvidia remains to be seen. Intel was in Nvidia position in 2007 and they didn't want to trade margins for volumes in the phone market. And there they are today.
The description of DeepSeek reminds me of my experience in networking in the late 80s - early 90s. 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-q…
Another aspect that reinforces your point is that the ATM push (and subsequent downfall) was not just bandwidth-motivated but also motivated by a belief that ATM's QoS guarantees were necessary. But it turned out that software improvements, notably MPLS to handle QoS, were all that was needed.
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.
Earlier quoted context omitted.
>> Plus the cell phone industry paved the way for VOIP by getting everyone used to really, really crappy voice quality 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 00…
Because at some point, someone decided that 8 kbps makes for an acceptable audio stream per subscriber. And at first, the novelty of being able to call anyone anywhere, even with this awful quality, was novel enough that people would accept it. And most people did until the carriers decided they could allocate a little more with VoLTE, if it works on your phone in your area.
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 description of DeepSeek reminds me of my experience in networking in the late 80s - early 90s. 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-q…
The description of DeepSeek reminds me of my experience in networking in the late 80s - early 90s. 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-q…
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.
This story could be applied to every tech breakthrough. We start where the breakthrough is moated by hardware, access to knowledge, and IP. Over time: - Competition gets crucial features into cheaper hardware - Work-arounds for most IP are discovered - Knowledge finds a way out of the castle This leads to a "Cambrian explosion" of new devices and software that usually gives rise to some game-changing new ways to use…
It's still wild to me that toasters have always been $20 but extremely expensive lasers, digital chips, amps, motors, LCD screens worked their way down to $20 CD players.
Great article. > Now, you still want to train the best model you can by cleverly leveraging as much compute as you can and as many trillion tokens of high quality training data as possible, but that's just the beginning of the story in this new world; now, you could easily use incredibly huge amounts of compute just to do inference from these models at a very high level of confidence or when trying to solve extremely…
> NVIDIAs moat Offtopic, but your comment finally pushed me over the edge to semantic satiation [1] regarding the word "moat". It is incredible how this word turned up a short while ago and now it seems to be a key ingredient of every second comment. [1] https://en.wikipedia.org/wiki/Semantic_satiation