Comments URL: https://news.ycombinator.com/item?id=47792023

Points: 5

# Comments: 0

Unless the rich somehow manage to completely stifle the progress of consumer-level computing advancement (all chip manufacturers would just collude to quit selling to consumers?) and exert an iron-fisted control over the dissemination of software (when has this ever worked?), I'm not sure how they could control the democratization of AI.

— in the 1960/1970s, when compilers came out. "We don't need so many programmers hand-writing assembly anymore." Remember, COBOL (COmmon Business-Oriented Language) and FORTRAN (FORmula TRANslator) were marketed as human-readable languages that would let business professionals/scientists no longer be reliant on dedicated specialist programmers.

— in the 1980s/1990s, when higher-level languages came out. "C++ and Java mean we don't need an army of low-level C developers spending most of their effort manually managing memory, and rich standard libraries mean they don't have to continuously reimplement common data structures from scratch."

— in the 1990s/2000s, when frameworks came out. "These things are basically plug-and-play, now one full-stack developer can replace a dedicated sysadmin, backend engineer, database engineer, and frontend engineer."

While all of these statements are superficially true, the result was that the world produced more software (and developer jobs) than ever, as each level of abstraction freed developers from having to worry about lower-level problems and instead focus on higher-level solutions. Mel's intellect was freed from having to optimize the position of the memory drum [0] to allow him to focus on optimizing the higher-level logic/algorithms of the problem he's solving. As a result, software has become both more complex but also much more capable, and thus much more common.

While this time with AI may truly be different, I'm not holding my breath.

[0] http://catb.org/jargon/html/story-of-mel.html

I'm not sure this moat is inevitably perpetual. It's likely computing technology evolves to the point of being able to run frontier-level models on our phones and laptops. It's also likely that with diminishing marginal returns, future datacenter-level models will not be dramatically more capable than future local models. In that case, the power of AI would be (almost) fully democratized, obviating any oligarchic concentration of power. Everyone would have equal access to the ultimate means of production.

Why do we watch Olympic runners, when cars on your average city street easily exceed Usain Bolt's top speed on their morning drive to Starbucks? Why do we watch the Tour de France, when we can watch Uber Eats drivers on their 150cc scooters easily outpace top cyclists? I'm sure within a couple years a Boston Dynamics robot will be able to out-gymnast Simone Biles or out-skate Surya Bonaly. Would anyone watch these robots in competition? I doubt it. We watch Bolt, Biles, and Bonaly compete because their performance represents a profound confluence of human effort and talent. It is a celebration of human achievement, even though that achievement objectively pales in comparison to what our machines can accomplish.

I think the same is true for other aspects of human creativity and labor. As we are able to automate more and more, we will place increasing importance on what inherently cannot be automated: celebration of our fellow humanity. Another poster wrote that "bullshit jobs" [0] exist primarily because we value human contact [1]. I am inclined to agree.

[0] https://en.wikipedia.org/wiki/Bullshit_Jobs

[1] https://news.ycombinator.com/item?id=47738865

The two biggest labor displacements in human history were the agricultural and industrial revolutions, both of which resulted in enormous gains in human living standards. Can you think of a mass labor displacement that resulted in an overall erosion of living standards? I cannot.

That's true for any NFS setup, not just EFS. The benefit of local NFS caching is to speed up reads of large, immutable files, where latency is relatively negligible. I'm not sure why AWS specifically dissuades users from enabling caching, since it's not like bandwidth to an EFS volume is even in the ballpark of EBS/NVMe bandwidth.

Would

   mkfs.ext4 /dev/nvme0n1 && \
   mount /dev/nvme0n1 /var/cache/fscache && \
   mount -t s3files -o fsc fs-0aa860d05df9afdfe:/ /home/ec2-user/s3files

— All writes cost $0.06/GB, since everything is first written to the EFS cache. For write-heavy applications, this could be a dealbreaker.

— Reads hitting the cache get billed at $0.03/GB. Large reads (>128kB) get directly streamed from the underlying S3 bucket, which is free.

— Cache is charged at $0.30/GB/month. Even though everything is written to the cache (for consistency purposes), it seems like it's only used for persistent storage of small files (<128kB), so this shouldn't cost too much.

(Of course, the ideal scenario is not that rising carbon emissions from increased cooling get offset by lower emissions from decreased heating, but rather that we transition to abundant carbon-free energy from solar, wind, nuclear, etc. and are able to keep our houses as cool as we want in the summer and as warm as we want in the winter without any environmental consequences.)

[0] https://ourworldindata.org/grapher/co2-heating-cooling

   Ubuntu base      ~29 MB compressed
   PyTorch + CUDA   7 – 13 GB
   NVIDIA NGC       4.5+ GB compressed

Comments URL: https://news.ycombinator.com/item?id=47157120

Points: 3

# Comments: 0

I use Claude Code almost every day [1], and when used properly (i.e. with manual oversight), it's an amazing productivity booster. The issue is when it's used to produce far more code than can be rigorously reviewed.

[0] https://www.reddit.com/r/ClaudeAI/comments/1px44q0/claude_co...

[1] https://news.ycombinator.com/item?id=45511128