aurareturn

If this is true, then you can just hire them and beat out the businesses that erroneously laid off valuable workers.

Why are people such big opponents of the AI buildout?

I generally don't see many cons to it.

1. Big tech was just using profits to buy back shares before AI build out. Would you rather they buy back shares with their profits or finance the AI build out?

2. If there is an AI bubble, great, when it pops, we'll all have ultra cheap tokens and we'll have all these amazing AI infrastructure built for the next wave of innovation.

3. Even if AI progress stops here and models hit a wall in intelligence, we'll still have AI good enough to solve millennium problems.

My theories on why people are so anti-AI:

1. It threatens their jobs.

2. They want AI stocks to drop so they can buy the dip.

3. Their identity is being challenged because AI makes what they do easier.

Super useful. Any open source tools like this?

Incorrect.

  Leaked prior to announcement - Leaked Benchmarks Confirm M2 Chip is Up to 20% Faster Than M1 https://www.macrumors.com/2022/06/15/m2-geekbench-benchmark/

Date of article: June 15, 2022 10:32 am PDT. M2 announcement was June 6.[0]

I don't feel like doing it for your other sources. They follow the same pattern. You can check official announcement dates vs "leaked" dates yourself.

[0]https://www.apple.com/newsroom/2022/06/apple-unveils-m2-with...

No, not the same. Those are review samples who got sent the product early. Those "leaks" happen AFTER the products have been officially announced by Apple.

Apple has not mentioned M6 Pro anywhere.

Yea but they aren't going to be talking about consciousness.

Wait. What?

This is actually the M6 Pro and not the M6. It has 18 CPU cores to the M6's 12. The scores line up as well.

Reports have said all along that Apple is skipping M6 Pro/Max to focus on M7 generation.

I can't remember the last time an Apple chip got leaked like this.

They're not conscious in the same way humans and animals are.

  Critically, nobody trained Claude to do anything like this; the behavior emerged on its own.

They clearly are trained to do so even if Anthropic didn't deliberately optimize for it. These models were trained on human text and knowledge. Of course they will talk about consciousness. If cats trained the models, all they'll talk about is sleeping, catching mice, and not on consciousness.

No, arguably, software engineers are in more demand than ever. I predict that in 2027, more software engineers will be employed than in 2026.

I'm seeing many small companies who are hiring the first software engineer. In the past, one software engineer could build next to nothing in a year. Nowadays, one software engineer can build a lot in a matter of weeks.

The phone that I'm still looking for is an iPhone Mini Pro. I miss my 13 Mini a lot. I'll take an iPhone clamshell fold if Apple ever makes one.

That said, I understand why small screen phones don't sell well worldwide. For many people, especially younger generation or less wealthy countries, the phone is the person's only computer. It's their entertainment and their work.

Been seeing Waymo test cars in Tokyo.

They are extremely reliable.

This is exactly why Cerebras wafer chips aren’t even on N3. They stayed on N5. It is also why they are now stacking HBM onto the chip.

A16 is a half node. It is a derivative of N2 family.

Yes but it takes 8 years to have the same scaling as 2 years before.

Yes, 5 years seems like an eternity in AI world.

We also don't know how small of nm chips they can manufacture. If it's 20nm, it's practically useless for advanced AI chips.

The compute part must have been made in Taiwan because it uses TSMC N2. TSMC N2 is only available in Taiwan right now due to a law restricting the latest node to Taiwan for 1-2 years.

A simple ChatGPT can explain it to you.

Intel being up 100% has nothing to do with China market being restricted. They could be up 200% instead if the China market is free.

I'm well aware of how good China is at manufacturing. However, DUV/EUV machine manufacturing is unproven.

What is the timeline like? 1 year? 5 years? 10 years?

Not being able to have unrestricted access to the world's second biggest market does not relate to Intel being up over 100%.

Just logic.

Yes, but we don't know how well they work or what nm can they print or how machines they can make.

Because having unrestricted access to both American and Chinese hardware is better than only Chinese hardware. Long term or short term. More suppliers the better.

China is gated by not having EUV machine access. They're also bottlenecked by ASML's DUV machine production like everyone else. There are already talks of banning China from even purchasing DUV machines from ASML.

So until China solves the ASML problem, there won't be any flooding.

US chip export winners and losers:

Winners: Huawei, SMIC, CXMT,Chinese ASML-competitors, OpenAI, Anthropic, Amazon, Microsoft, Google, Meta.

Losers: Chinese AI labs, Nvidia, AMD, TSMC, Micron, SK Hynix, Samsung, Intel.

Any company that depends on Nvidia hardware such as OpenAI, Anthropic, AWS are winners. It means less competition for Nvidia chips and services. If you think Nvidia chips are expensive now, imagine if Chinese companies can buy them freely. Also for American AI labs, it also means they can stay ahead of Chinese AI labs in compute capacity.

The American hardware makers lost the lobby fight in Washington.

Do we know that AI can't invent a conceptual framework?

If we give it a real problem to solve, it may just have to invent a new form of math to solve.

Making paperclips:

https://waitbutwhy.com/2015/01/artificial-intelligence-revol...

https://waitbutwhy.com/2015/01/artificial-intelligence-revol...

I first read these articles in 2015. These remain the most profound things I read.

That depends on the solution, right?

Question:

Did the theoretical math lead to the invention of GPS, cryptography, lasers, etc? Or did we encounter a real physical problem, then we found that someone had done some theoretical math before that would be useful for this application? If we run into a real physical problem today, can we just have AI invent the math on the spot to solve the problem without a human having done the theoretical math in the past?

So my question is this:

Would this slow technological progress? Or make it go faster?

That math problems are found and solved as we run into real physical problems.

Humans only invest in solving problems that matter one way or another.

I also disagree that none of them solve "real" problems. They clearly do. Solving them have implications on real world problems.