Look at the first image with the people in the field.
That looks to me like a very poorly generated image, not a real image of people, and not even a high-quality AI generated image.
Is this what we can expect of the new apple?
I'm not against AI generated imagery, but I expect them to be of equal quality to a real photo.
Or am I wrong, and it isn't AI generated?
The things that make me think it is just poorly made are
1) the angles of the laptop on the black case,
2) the lack of any lighting on the back panel,
3) the size of the hand on the woman in the back, and the squareness of what she is holding (if it is even supposed to be another mac).
Almost certainly not AI gen, it's shot with a 35mm lens (quality looks like the 1.4 L to me), probably around f8 given how the DOF falloff happens, heavy forward flood (flash or otherwise, but whatever it was it's defused) and then what's I think giving you the sense it's AI is it looks like they've over used a double S curve to bump the contrast and sharpness. https://www.youtube.com/watch?v=XZh_9HnO_4w&t=640s
That was my first thought, is that guy's face AI? The angle of the laptop looks off. Then I decided I don't care and moved on, but yeah, you're not the only one who thought it looked off.
I'm wondering if we could create one-off phone numbers similar to one-off credit cards when we have to give a number to a service we don't want to be regularly receiving messages from.
I wonder if the entire thing would be better if the first step was for the LLM to try to understand the final goal of the user, rather than just the simple instruction.
For instance, the LLM may have an understanding that the ball is easier for it to pick-up than the elephant (which it seemed to struggle with, which also made it a strange choice for the demo).
How much of an LLM understanding the physical limitations of the robot would help the task be accomplished in a way that satisfies the goal, without following the exact directions.
I think data centers and power are the dark-fiber of this current "bubble".
Inference is 2/3rds of the power used in AI, and I expect the majority of inference to go local in the next 2-3 years, about the time these data centers will come online.
The other 3rd is training, and the major labs are training 6-7 times a year right now. But I suspect we will see a few things.
1) training iterations will slow as the improvements between training runs gets lower and lower. Is it worth spending an extra $500M(ish) for the small improvement in quality? Who is paying for that?
2) Training improvements and improvements in GPUs will require less power. Along with fewer training runs, as we add more and more tokens, the amount of power needed for a training run will likely asymptote at some point.
The dark fiber comparison is very close. I remember contracting bandwidth with Global Crossing in the late 90s/early 2000s when they were HOT and two years later they were bankrupt.
I work in neurotech and specifically with EEG, some would find it surprising that I 100% agree with this take.
When we understood the world of fluid-dynamics, we looked at the body as blood going through a pump delivering materials (oxygen, minerals, etc) to different parts of the body. We though to ourselves "we know how this works!".
Then we discovered electricity, slapped our collective foreheads and said "oh! It's electrical!" now I get it.
We still don't.
Let's learn what we can from what we can and use this knowledge to our benefit, but let's not assume we understand the underlying mechanisms just because we can find correlations.
We were not wrong, though. Major functional component of the body is the pump pushing around a fluid that distributes materials around the body. Electricity is another functional layer. And on top of the fluidic layer, it turned out many of the disributed material aren't inert building block, but chemical signals and machines, too.
I think the main error is in people trying to explain a complex machine through one mode of "how it works". The second error is people trying to accuse other people of doing that.
Today, anyone with half a brain and an ounce of interest could look at any of the large machines that operate in their environment - buses, trains, construction equipment - and quickly discover that such machines have fluids being pumped, air being pumped, mechanical linkages and electric circuits used for both power delivery and control, many or all of these things having - at a higher level - feedback loops designed in for autonomous control/self-balancing, and of course there's a whole economic and social layer on top, that's key to explaining why the machine works the way it does.
Why wouldn't it be any different with the human body?
We’re finding out though that the brain is, yes, a fluid dynamic system, an electromagnetic system (though we know way less about the magnetism that we’d like), AND a mechanical system. Wonder how many more ands we’d have to add by the time we figure it out.
I'd add that we've seen how the leadership/reputation of different AI leaders, and with 2 decades of history with Larry and Sergey, they seem to come up on top as the most respectable.
Did they ever really abuse the power Google could have wielded?
I could be missing something, but for the most part they seem to just get down to building and pushing technology/science forward and avoid drama rather than welcome it.
> Did they ever really abuse the power Google could have wielded?
Plenty of times. Perhaps the worse is pushing Manifest v3 with no support for real ad blockers in Chrome. Not to mention no support for ad blockers in Chrome mobile.
Also, their stealing of newspaper content.
Their new push for AI summaries instead of actual search in their search product, stealing even more clicks from sites that actually produce information.
YouTube pushing Shorts to everyone, and now the weird text posts that you can't hide.
In general their gigantic push for ads everywhere all of the time.
Google, with the help of Facebook, destroyed the independent online publishing business. They made it impossible to maintain an honest publication and tunneled users to low quality websites until there's not much left of respect.
> Did they ever really abuse the power Google could have wielded?
The "Do no evil" never being an official slogan and people saying it's no longer true for the last 10 years or so, they're just really massive. They do mess up a lot, but when you're Microsoft, Apple or Google sized, its nearly impossible to get everything right all at once.
There are pictures of Sergey in the files, but they are rather milquetoast. He's just sitting next to David Brooks of the NYTimes. I don't think there's any evidence he's engaged in sex abuse.
The alternative would have been paywalls galore with subscription tiers for everything. Only rich people would be able to afford having subs for everything, while the poor would just get the most dirt tier scraps and wouldn't be able to afford many platforms.
Nothing would be "free", so google sub, news source subs, reddit sub, youtube sub, discord sub, instagram sub, FB sub, app stores are full of paid only apps, podcasts are all paywalled, all the ad supported stuff is subscription supported. Everything would feel like constant nickle and dime'ing you.
On the bright side, there would be no ads, and relatively robust privacy.
Ehh, the internet was worse before Google. Google actually became popular for having a nice blank page with only the search bar. Even the ads they had later were much cleaner compared to yahoo, altavista, lycos, aol and other firms of that time.
Let's not ignore the economy where the agent is the buyer.
Video editing and website design being the example here. If the video is an ad, or the website is a sales site, if an agent is a buyer these change considerably. That is an entirely new economy, similar to how we did not understand the knowledge economy until it was fairly well developed in the mid 1900s (someone smarter than me might have better info here).
I have no doubt the economy will change, but we as humans operating in the world will still have needs that need to be met.
In addition, with a shrinking population in all developed nations, we may well still have a shortage of workers in 30 years, not an oversupply.
really good feedback. I made it for her for her 12th birthday as a surprise, and I can update the blog to make that more clear.
Since then, I have asked her for feedback and we made some tweaks. She is more excited to market/sell it, than build. I mentioned that at the end of the post and got her permission to open source it. She really wants to try to sell these which I am not as excited about due to being a full time parent & professional.
An interesting thought experiment, but I'm not sure I follow the reasoning of these two statements, which is the crux of why open software fits this mold.
1. Reproducible, meaning executable, as well as modifiable, and
2. Reliable, meaning that the results are consistently trustworthy
Why does modifiable fit reproducible. Modifiable fits the open source theme, but not the science theme. Can someone set me straight on this if I am missing something?
Number 2 is something I've been thinking about more recently, and the definition of science from the post being "testable hypothesis and predictable".
Medicine is testable and predictable, but not reliable. To me reliability is the job of engineering. To take what is known in science and make it reliable.
I used to work at CSIRO (Australia's science and technology org) and I remember my boss telling me that researchers always think their work is ready to go from the lab into the real world, but it is our job as engineers to make that translation so that the work outside of the lab. That's what I think about when I think of reliable.
I was hoping to see something like this, though I didn't know what form it would take.
A few months ago I was at a demo night in SF and 4 people demo'd essentially the same tool for managing PRs. At the time my thought was "are we really going to be dealing with PRs in 2 years.
I don't know if Delta is the right solution, but Zed is at least questioning the current paradigm, which I think is important.
Is this what we can expect of the new apple? I'm not against AI generated imagery, but I expect them to be of equal quality to a real photo.
Or am I wrong, and it isn't AI generated?
The things that make me think it is just poorly made are 1) the angles of the laptop on the black case, 2) the lack of any lighting on the back panel, 3) the size of the hand on the woman in the back, and the squareness of what she is holding (if it is even supposed to be another mac).
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