marsten (u/marsten) - Readit News

marsten commented on Uncle Sam shouldn't own Intel stock wsj.com/opinion/uncle-sam... · Posted by u/aspenmayer

dismalaf · 6 days ago

So should the government give bailouts without getting any equity back? Only deal in loans?

Intel is strategically important. As nice as it is to pretend that the whole world plays by the same rules, that the free market exists everywhere and that we'll never to to war, there are bad actors and the US (rest of the collective West as well) need to ensure that we won't be completely crippled if China attacks a single island off their coast...

marsten · 6 days ago

> Intel is strategically important.

Fab capability on US soil is strategically important. Intel is one of many possible routes to that.

marsten commented on Uncle Sam shouldn't own Intel stock wsj.com/opinion/uncle-sam... · Posted by u/aspenmayer

x0x0 · 6 days ago

From my pov, it looks more like intel shit the bed repeatedly.

Missed on: mobile, custom chips in the data center, graphics cards, ai, and building out fab services they can sell.

Meanwhile, they took at least 5 years off of making their chips faster, and we're treated to the absurdity that the m-series chips are as performant in single core as anything Intel can build on a power budget 1/10th of Intel's.

I'm not sure what that has to do with outsourcing? It looks more like a comprehensive lack of execution.

marsten · 6 days ago

Intel should have spun out their fab in 2009-2010 when the signs were clear: Mobile was taking off, AMD spun out their fab, Intel had missed the boat on mobile CPUs, and Apple had acquired PA Semi and was investing heavily in custom silicon.

High-end fab is a volume game and that was the time frame when Intel was still process competitive and could have competed for Apple's business (and Nvidia's, ...). But that would never happen as a division of Intel, nobody wants to send their designs to a competitor.

marsten commented on GPT-5 openai.com/gpt-5/... · Posted by u/rd

gf000 · 23 days ago

I get your point, but even whole ass countries routinely fail at developing nukes.

"Just" enrichment is so complicated and requires basically every tech and manufacturing knowledge humanity has created up until the mid 20th century that an evil idiot would be much better off with just a bunch of fireworks.

marsten · 23 days ago

Biological weapons are probably the more worrisome case for AI. The equipment is less exotic than for nuclear weapon development, and more obtainable by everyday people.

marsten commented on Why MIT switched from Scheme to Python (2009) wisdomandwonder.com/link/... · Posted by u/borski

darksaints · a month ago

Colleges becoming more vocational is a consequence of colleges becoming more expensive for students. If you are paying all of that money for college, you better get a good job out of it. I don't see that as a bad thing necessarily, but it would definitely be nice if we had better paths for those who want to end up in research.

I'd argue that SML (or derivative thereof) would make for a better teaching language, for both the lambda calculus aspect and the type theory aspect.

marsten · a month ago

I attribute the curriculum shift to something slightly different, which is the changing perception of CS as a career.

When I was in college in the late 1980s, CS was not perceived as the moneymaking career it is today. Accordingly the kids who went into CS were typically the nerds and hackers who truly loved the field.

Many kids now perceive CS as a safe, lucrative career option akin to becoming a doctor or lawyer. It attracts many students who are smart but perhaps not as intrinsically excited about the field. The universities adjusted their curricula to what these students care about: Less beautiful theory, and more practical training.

A similar thing happened in statistics. At one time it was hardcore stats nerds. Now "data science" has brought a ton more people into the field and the teaching methods have changed dramatically.

marsten commented on Nobody has a personality anymore: we are products with labels freyaindia.co.uk/p/nobody... · Posted by u/drankl

Walf · 2 months ago

I'm sure there are those who self-diagnose without really suffering from a condition, but you do realise time blindness is a real issue, right?

https://www.simplypsychology.org/adhd-time-blindness.html

I don't watch TikTok videos, I don't use Instagram, but I have been plagued by these symptoms my entire life, and don't really care about others opinions on it. You probably don't have it if those symptoms don't resonate with you, but there are plenty of people who genuinely struggle, and there's likely some overlap with those who have undiagnosed ADHD.

marsten · 2 months ago

The problem isn't that time blindness is a fake issue.

The problem is that many people incorrectly self-diagnose as suffering from conditions like time blindness. Which they do for a variety of reasons: To externalize accountability for why they're late, to feel special, and so on.

A comparison is the large number of people who claim "gluten sensitivity" and maintain special diets. Now there are serious medical conditions like celiac disease that require one to avoid gluten. But the vast majority of self-diagnosed "gluten sensitives" do not have such conditions. Researchers conclude that for many of them there is no physical basis for their self-diagnosis.

Among other things this phenomenon makes it harder for people with actual conditions to be taken seriously, because there are so many impostors.

marsten commented on The Gentle Singularity blog.samaltman.com/the-ge... · Posted by u/firloop

flessner · 3 months ago

> Already we live with incredible digital intelligence, and after some initial shock, most of us are pretty used to it. Very quickly we go from being amazed that AI can generate a beautifully-written paragraph to wondering when it can generate a beautifully-written novel;

It was probably around 7 years ago when I first got interested in machine learning. Back then I followed a crude YouTube tutorial which consisted of downloading a Reddit comment dump and training an ML model on it to predict the next character for a given input. It was magical.

I always see LLMs as an evolution of that. Instead of the next character, it's now the next token. Instead of GBs of Reddit comments, it's now TBs of "everything". Instead of millions of parameters, it's now billions of parameters.

Over the years, the magic was never lost on me. However, I can never see LLMs as more than a "token prediction machine". Maybe throwing more compute and data at it will at some point make it so great that it's worthy to be called "AGI" anyway? I don't know.

Well anyway, thanks for the nostalgia trip on my birthday! I don't entirely share the same optimism - but I guess optimism is a necessary trait for a CEO, isn't it?

marsten · 3 months ago

> Over the years, the magic was never lost on me. However, I can never see LLMs as more than a "token prediction machine".

The "mere token prediction machine" criticism, like Pearl's "deep learning amounts to just curve fitting", is true but it also misses the point. AI in the end turns a mirror on humanity and will force us to accept that intelligence and consciousness can emerge from some pretty simple building blocks. That in some deep sense, all we are is curve fitting.

It reminds me of the lines from T.S. Eliot, “...And the end of all our exploring, Will be to arrive where we started, And know the place for the first time."

marsten commented on OpenAI dropped the price of o3 by 80% twitter.com/sama/status/1... · Posted by u/mfiguiere

bitpush · 3 months ago

The problem is your costs also scale with revenue. Ideally you want to have control costs as you scale (the first you build is expensive, but as you make more your costs come down).

For OpenAI, the more people use the product, the same you spend on compute unless they can supplement it with another ways of generating revenue.

I dont unfortunately think OpenAI will be able to hit sustained profitability (see Netflix for another example)

marsten · 3 months ago

You raise a good point that this isn't a low marginal cost business like software, telecom, or (most of) the web. Efficiency will be a big advantage for companies that can achieve it, in part because it will let them scale to new AI use cases.

With the race to get new models out the door, I doubt any of these companies have done much to optimize cost so far. Google is a partial exception – they began developing the TPU ten years ago and the rest of their infrastructure has been optimized over the years to serve computationally expensive products (search, gmail, youtube, etc.).

marsten commented on Sandia turns on brain-like storage-free supercomputer blocksandfiles.com/2025/0... · Posted by u/rbanffy

marsten · 3 months ago

Interesting that they converged on a memory/network architecture similar to a rack of GPUs.

- 152 cores per chip, equivalent to ~128 CUDA cores per SM

- per-chip SRAM (20 MB) equivalent to SM high-speed shared memory

- per-board DRAM (96 GB across 48 chips) equivalent to GPU global memory

- boards networked together with something akin to NVLink

I wonder if they use HBM for the DRAM, or do anything like coalescing memory accesses.

marsten commented on See how a dollar would have grown over the past 94 years [pdf] newyorklifeinvestments.co... · Posted by u/mooreds

fasthands9 · 3 months ago

When I was born in 1990 my grandparents spent like 5k on government bonds that my dad didn't tell me about until I was 30.

It was a very nice treat, but when I did the math to see how much more it would have been if just invested in the market I gasped.

marsten · 3 months ago

A surprising number of 401(k) plans default to a money market fund for invested assets. Imagine retiring after a decades-long career and realizing what could have been.

marsten commented on See how a dollar would have grown over the past 94 years [pdf] newyorklifeinvestments.co... · Posted by u/mooreds

jihadjihad · 3 months ago

Rule of 72: time for an investment to double is roughly 72 / the interest rate [0].

  Annual return on small-cap stocks: ~12%
  Time to double: 72/12 ~= 6 years
  Number of doubling periods: 99/6 ~= 16
  Final investment value: ~2**16 ~= $65k ~= $64,417

Math checks out.

0: https://en.wikipedia.org/wiki/Rule_of_72

marsten · 3 months ago

I've always found it amusing that mathematically it should be the rule of 70, but it's commonly rounded to 72 because the latter has more convenient divisors.

70 is divisible by 1, 2, 5, 7, 10, 14, 35, 70

72 is divisible by 1, 2, 3, 4, 6, 8, 9, 12, 18, 24, 36, 72