aurareturn

They are. They are using ASML DUV machines for memory. Samsung, SK, and Micron have moved onto EUV machines for memory because they are better. So CXMT not only has to rely on ASML, they have to rely on a worse machine to make modern memory chips.

Everyone, and I mean everyone, is gated by ASML machines. They can't make nearly enough EUV machines to satisfy the demand. ASML has also not scaled their production nearly as much because they're quite far away from the AGI-pilled companies in the supply chain.

From an investment perspective, I think chip fabs TSMC, Intel, and Samsung will benefit from better AI chip design tools.

If AI made it 100x faster and cheaper to build software, you suddenly have an explosion of software that need to be hosted. So companies like AWS/iOS App Store/cloud companies benefit.

If AI makes designing chips 100x faster and cheaper, you will have an explosion of custom chips for all sorts of applications. These chips still need to be physically made at TSMC, Intel, or Samsung.

Apple says it takes 3-4 years to design each Apple Silicon generation.[0] So the M6 was being designed in 2022-2023 already. Reports are that it costs hundreds of millions to a billion to design a cutting edge chip from scratch to finish.[0]

The cool thing is that we'll have niche ASIC chips for accelerating special applications that previously didn't have big of a market for someone to make a profit on. This is the same thing with software today. It's much easier to build custom software for a small niche and be profitable today than in 2022.

Maybe some day, a kid in his garage can just tell an AI to design a custom chip, send it to TSMC, and get the chip in the mail in a few weeks.

And given that Moore's Law is essentially dead in terms of density scaling, having an AI to automatically optimize the hell out of design and squeeze as much performance as possible out of the transistors could help us have a few more years of nice performance increase.

[0]https://fireflies.ai/blog/johny-srouji-and-john-ternus-inter...

[1]https://www.granitefirm.com/blog/us/2023/04/29/cost-of-chip-...

Models are likely already doing this inside AI labs because it can be hundreds of millions of dollars for every percentage point increase in hardware inference efficiency.

At some point, models will be so smart, hardware will be so cheap that it makes sense for the LLM agent to just write code as low level as possible to optimize for performance and efficiency.

These things are hard for a human to do, but easy for a machine to do.

We are not there yet, not in 2026. Maybe in 2030?

It’s just reality when all the internet virtue signaling is turned off.

I’m not blaming anyone. I think all parties are behaving as they should.

Maybe part of the solution for any country dealing with low marriage rate is to ban all private dating apps and only government issued apps are allowed.

Private ones will always prioritize profit which means they want you to keep using the app which means they don’t want you to find a partner.

Modern dating apps makes it so that an average woman will have unlimited choices but the average man will have next to none. Before dating apps, they could have been a good match. But with dating apps, the woman has unlimited higher value men. How could these average women marry an average man if she’s being taken on dates constantly by top 5% men?

The problem is that these higher value men will not commit because they also have unlimited options.

Even if she marries an average man later in life, she will feel resentment towards him. Therefore, these women just choose to stay single. This is especially viable now because women often are more educated and have good income.

Now we can see why young men are increasingly becoming far right and longing for far more conservative world.

Modern dating apps are just manifesting natural instincts on steroids. I don’t blame either party. Just an observation.

It is too early to declare that there is no moat. I think there is and we will eventually arrive at a monopoly or duopoly at the frontier.

Don't think so unless all moderate actions are public.

Site overall. Mobile app makes it easy to type a few words and hit send and hard to write well thought out posts.

The subreddits that I frequent have turned into a low effort meme fest.

No original OP posts are allowed, only URLs from the same old websites.

I think it's the latter. People don't want to waste their time.

Echo chambers have gotten stronger.

I don't think so. I've been a Reddit user for 12+ years or so. Obviously when you make the platform easy to use for anyone, you also invite more casual users who just want to meme.

Reddit doesn't even make any attempt to control quality since user engagement numbers matter more than quality.

Reminds me of Quora which over optimized the site for engagement growth but eventually became completely useless for this reason.

My biggest problem with Reddit is that trolls, memes, unintelligent posts have taken over the platform. Go to any semi-popular subreddit and most upvoted posts are just low effort memes. Posts that are long and well thought out don't win over memes and trolls. One of the reasons is that posting a few short words wins in upvotes because they get posted first while it takes much longer to write something thoughtful.

Reddit's system rewards these low effort posts for some reason. Over time, the platform becomes less and less trustworthy until it becomes something like Quora.

We should measure cost per standard task. This is falling fast.

Yea but this model wasn’t trained to play Pokémon but it can. It’s general.

That's actually amazing. I think we can use it for our product.

What's very weird is that this study was published by two people working professionally at Okta. Yes, the auth tech company.

This is the title they chose for the study:

  Beyond the Hype: The Efficiency-Throughput Gap with GitHub Copilot

How can you possibly have a title like that when the study was done in 2024? I'm guessing even their own engineers at Okta would roll the eyes at this study.

Note the timelines of this study:

4/2024: Baseline metrics

8/2024: Participants given Github Copilot licenses

11/2024: Conducted surveys, 261 people invited and 97 responded in survey

9/2026: Study published

Then just call it Substack.

Are they doing to do something about authors using Arxiv to publish propaganda/opinion pieces but presented as research?

ArXiv gives the appearance of scientific credibility that a blog post wouldn't have so I'm seeing the platform get abused.

Example: https://news.ycombinator.com/item?id=49580164

I'm not sure if that's relevant. For all we know, Google's system also flagged the same person and at least 1 human being looked at it.

  British Columbia has sued OpenAI, saying a mass shooting at a school in the Canadian province could have been prevented if the company had warned local  law enforcement that the shooter  had used ChatGPT to  plan the attack.

Does Google notify the police if someone searches for phrases related to planning gun violence? Does Meta notify the police if someone sends messages via Instagram, WhatsApp, Messenger to their friends about planning gun violence? More importantly, is any platform, online or offline, responsible for contacting the police if it thinks someone might be planning a shooting? For example, if someone on Hacker News posts something, is Dang responsible for contacting the police? What is the threshold for ignore, delete post, or contacting local authorities?

The shooting is horrible, like all shootings. I'm just wondering if there is already a precedence for this stuff.

Also, are police departments around the world prepared to handle the likely big influx of automated ChatGPT notifications? How will they investigate them? Use an LLM to decide if they should investigate them?

I'm not blaming anyone but I think these questions need to be answered, thought through.

There is nothing like for like. We're comparing a fanless phone chip to machines that might have water cooling and nearly unlimited power.

Sustained performance is usually based on cooling, not the chip. There is no reason the iPhone chip can't sustain its performance if you give it a small fan.

So whatever your argument is, it doesn't make much sense.

The M6 is based on A20 Pro and it sustains its performance in a Mac Mini indefinitely - likely longer than Ryzens.

No. They make server CPUs which is predicted/expected to be the next bottleneck after memory.

It's not actually 2 years. It is 4 years of progress.

Zen 3: 2020 release

Zen 4: 2022 release

Zen 5: 2024 release

The author is disingenuous by looking at only the X3D variants. The Zen 3 X3D variant came out late.

For comparison, in the same time frame, the M4 is 52% faster in ST and 72% faster in MT than M1.[0] If you go by what you can physically buy in stores since Zen 3 was released to now, Apple's chips have gotten 83% faster in ST and 143% faster in MT.[1]

[0]https://browser.geekbench.com/v7/cpu/compare/433673?baseline...

[1]https://browser.geekbench.com/v7/cpu/compare/435139?baseline...

I found myself going back to Fable over and over again. At this point, I’m not sure if I’m just used to its style or it is truly more capable.

I tried Opus 5 and Astra.

If they can't afford to live there, then the rich people living there won't be happy and they'll pay a higher wage to those people.

M6 got another prompt processing boost. Likely no M6 Ultra though because Apple is reportedly going all in on AI performance in M7 generation.