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I’d like to draw your attention to this magnificent description of the current state of AI development. Lay accessible but also accurate and deep.
Finally had a chance to listen through this pod with Sutton, which was interesting and amusing. As background, Sutton's "The Bitter Lesson" has become a bit of biblical text in frontier LLM circles. Researchers routinely talk about and ask whether this or that approach or idea…
The opposite of bespoke, this image screams SCALE as modularity improves everything about deploying a charging network. This box design will help make vehicle charging inexpensive, ubiquitous, fast, and reliable. Everything Tesla Energy makes is beautiful inside.
It might be odd to get so excited about a white box, but the V4 cabinet is a charging masterpiece: AC in, 16 trays of power electronics, DC out. This is the tech that will make 1.2MW charging for Semi, and 0.5 MW charging for cars, ubiquitous around the world.

In the late 90’s we talked about “internet time”- things advanced at a pace one could hardly believe. “AI time” is already orders of magnitude faster. And it’s accelerating so quickly that you can see the speed change from month-to-month.

As you approach the event horizon you see the universe around you accelerate.
Datacenter power will change to solar+batteries.

We aren't going to have nuclear powered AI datacenters. We're going to have solar+battery powered AI datacenters running flexible loads. They'll be built in sunny places with cheap land and friendly regulations. No grid or utilities required if Starlink is used for network…
If Tesla’s Robotaxi efforts continue to go well we could see both US road accidents and US road emissions halved in less than 10 years.
You can fit more total RAM on the board if you use “normal” memory than high-bandwidth memory and it is super cheap. Maybe high-bandwidth memory is still the right choice, but using HBM isn’t the slam dunk many people think it is.
The Samsung fab in Texas will make AI6, not AI5, and the decision regarding using HBM has not been made yet. As the ratio of total parameters to active (frequently used) parameters increases, the cost per unit of useful compute and compute per Watt may favor relatively…
While hype is a real thing, it’s also true that deep learning continues to outperform simple extrapolations of existing trends, often by orders of magnitude.
reminded of this paragraph from gsm8k paper, 2021 :)

Nice. Glad to see more people thinking through this carefully. Some comments: 1) The functional TOPS of the silicon is dominated by the NNU, and (conceptually) modest architectural changes to the NNU have a big impact on TOPS without much power or area change. For example -…
TLDR: I estimate the AI5 computer will deliver 3-4x more compute than AI4. I predict Tesla will use AI5 chips which fail QC, cut them down to become an 'AI5 lite' and underclock them to fit the power budget of the HW3 harness while still delivering much more performance than AI4.…

Robotaxi waiting list is open for business!
OK folks, the @robotaxi app (downloaded yesterday using my own account, not @jamesdouma’s) is already letting me book rides in SF this morning. I didn’t get a message—I just happened to open the app and saw that it was live. @SawyerMerritt @WholeMarsBlog

Yes. More please. More for everyone.
😲
View of Starship landing burn and splashdown on Flight 10, made possible by SpaceX’s recovery team. Starship made it through reentry with intentionally missing tiles, completed maneuvers to intentionally stress its flaps, had visible damage to its aft skirt and flaps, and still…


MSM headlines about starship are like the intro to 2001 - but with the primates throwing fecal matter at the monolith.
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