MacBook, every mention
16 scenes, the whole family · ← back to MacBook
tap a year for its mentions
every year anyone Felix Rieseberg 3Soumith Chintala 2Alessio Fanelli 2Yi Tay 1Paul Klein 1Justin Johnson 1Emmanuel Ameisen 1Dylan Patel 1Benedikt Jenik 1Ankur Goyal 1
Verbatim, from the transcripts: the passages where MacBook comes up
Faster Chips That Don't Melt — Anima Anandkumar & Benedikt Jenik, Accelerated Understanding
- ▶ 13:32 Benedikt Jenik We have done inference on, like, we can do small models with smaller context, or even medium big models with smaller context fit on a MacBook or Mac Studio.
Next 100x in AI: Inference, Networking, & Self-Optimizing Models — Philip Kiely & Ali Taha, Baseten
- ▶ 48:01 Alessio Fanelli How much of this applies to, say I have this MacBook, I want to run Gemma really efficiently, um, 2 times in the scene
⚡️ The best engineers don't write the most code. They delete the most code. — Stay Sassy
- ▶ 56:53 unnamed speaker You know, you, you make fun of the MacBook Neo, but actually it's a way better MacBook than you used to buy for 1300 dollars in 2016. 2 times in the scene
Anthropic’s Felix Rieseberg on AI Coworkers, Local-First Agents, and the Future of Knowledge Work
- ▶ 0:14 Felix Rieseberg Silicon Valley overall is undervaluing the local computer, and my default argument for that is always, how come you are using Macbooks and not like an iPad or a Chromebook?
- ▶ 17:43 Felix Rieseberg And my default argument for that is always, how come we're all using Mac books and not like an iPad or a Chromebook?
- ▶ 1:17:57 Felix Rieseberg You didn't buy the latest MacBook.
After LLMs: Spatial Intelligence and World Models — Fei-Fei Li & Justin Johnson, World Labs
- ▶ 38:27 Justin Johnson Um, but if you're allowed to, like, work on a recent, like, even this year's iPhone, or, like, a recent MacBook, or even if you have a local GPU,
How Zyphra went all-in on AMD + Why Devs feel faster with AI but are slower — with Quentin Anthony
- ▶ 27:08 unnamed speaker Oh, on like my, on my MacBook.
The Utility of Interpretability — Emmanuel Amiesen
- ▶ 29:21 Emmanuel Ameisen Sometimes you can load them, like, on your CPU, on your MacBook, and it's also a relatively new field, and so, you know, there's, as I'm sure we'll talk about, there's, like, some conceptual burdens and concepts that you just want to,…
Browserbase: Browser Infrastructure For Your AI Agents
- ▶ 13:46 Paul Klein It's barely running on my MacBook Air.
Production AI Engineering starts with Evals
- ▶ 1:46:34 Ankur Goyal C++ or Rust code on my MacBook Pro and like build a, you know, database or whatever.
The 10,000x Yolo Researcher Metagame — with Yi Tay of Reka
LLM Asia Paper Club Survey Round
- ▶ 30:15 unnamed speaker So let's say I want to do a question and answer, and then I, I get a probability of like, this is a Mac book. 2 times in the scene
Open Source AI is AI we can Trust — with Soumith Chintala of Meta AI
- ▶ 12:12 Soumith Chintala So, as, like, the MacBooks, uh, have GPUs, and as that stuff started getting increasingly interesting, we pushed Apple to push some engineers and work on the MPS support, and we spent significant time from, like, meta-funded engineers on… 2 times in the scene
The Four Wars of the AI Stack - Dec 2023 Recap
- ▶ 24:11 unnamed speaker So like, if you give me like a Postgres benchmark, I can run Postgres on my MacBook, you know, and run similar ones.
The State of Silicon and the GPU Poors - with Dylan Patel of SemiAnalysis
- ▶ 25:59 Dylan Patel Um, you know, I mentioned the ratio of flops to bandwidth on a GPU is actually really, really good compared to, like, a MacBook or, like, a phone.