Google, every mention
752 scenes, the whole family · ← back to Google
tap a year for its mentions
every year anyone Shawn Wang 216Alessio Fanelli 62Dylan Patel 56Yi Tay 42Will Bryk 24Bret Taylor 19Jeremy Howard 18Omar Sanseviero 16Anjney Midha 16Varun Mohan 15
Verbatim, from the transcripts: the passages where Google comes up
Anthropic’s Felix Rieseberg on AI Coworkers, Local-First Agents, and the Future of Knowledge Work
- ▶ 1:18:48 Felix Rieseberg Um, you can enter chrome, colon, whack, whack, GPU. 3 times in the scene
- ▶ 1:21:08 Felix Rieseberg Like for, for a long time, the Chrome ads would like sort of reinvent all the tools because none of them are capable of ending Chrome. 2 times in the scene
⚡️Monty: the ultrafast Python interpreter by Agents for Agents — Samuel Colvin, Pydantic
- ▶ 19:11 Samuel Colvin So someone said to me, which makes sense, like the single biggest private code base in the world is Google and supposedly Gemini is trained on it. 3 times in the scene
Retrieval After RAG: Hybrid Search, Agents, and Database Design — Simon Eskildsen of Turbopuffer
- ▶ 0:57 Shawn Wang Where, like, there's a lot of legendary programmers that have come out of it, like, uh, Bjorn Stolstrup, Rasmus Lerdorf, Anders Heilsberg, and the V-A team, and Google Maps team.
- ▶ 19:11 Simon Eskildsen It wasn't available in S III until late, but it was available in GCP. 5 times in the scene
- ▶ 21:27 Simon Eskildsen East, the Google, like the GCP and, and AWS data centers are like within a millisecond on each other on the public exchanges.
- ▶ 21:27 Simon Eskildsen East, the Google, like the GCP and, and AWS data centers are like within a millisecond on each other on the public exchanges. 4 times in the scene
- ▶ 35:32 Simon Eskildsen I just saw that my GCP bill was, was high, was a lot higher than the Cursor bill.
- ▶ 46:50 Simon Eskildsen I'm sure Google and others have done this, but we haven't seen anyone, um, at least not in like a public consumable SaaS that can do this.
Agent Inference at the "Speed of Light" — How NVIDIA moves like a $4.3 Trillion Startup
- ▶ 20:56 Kyle Kranen Uh, the common models like deep learning recommendation model, which came out of meta and the wide and deep model, which was used, uh, or it was released by Google were very accelerated by GPUs using, you know, the fast HBM on the chips,… 3 times in the scene
- ▶ 26:46 unnamed speaker And when you think the scale of companies deploying these, right, Amazon recommendations, Google Web Search, like, it's, it's huge scale, and you want fast.
- ▶ 36:22 unnamed speaker I think it's a paper from Google if I'm not mistaken, right?
- ▶ 55:07 Shawn Wang Google it, yeah.
- ▶ 1:03:39 Shawn Wang Then the cool thing became for Chrome hackathon. 2 times in the scene
⚡️ Polsia: Solo Founder Tiny Team from 0 to 1m ARR in 1 month & the future of Self-Running Companies
- ▶ 19:43 unnamed speaker It's like right now it's just UGC content for meta, but it should allow you to manage Google, uh, Google ads, TikTok ads, and every other network that exists, and it should be able to manage your spend.
- ▶ 19:43 unnamed speaker It's like right now it's just UGC content for meta, but it should allow you to manage Google, uh, Google ads, TikTok ads, and every other network that exists, and it should be able to manage your spend.
Measuring Exponential Trends Rising (in AI) — Joel Becker, METR
- ▶ 30:38 Shawn Wang I did a podcast with, um, Yitay from Gemini, who is also like, basically he's plugging his own training logs into Gemini to like improve his, his own code. 2 times in the scene
- ▶ 39:49 Shawn Wang But I will also say like, uh, you know, don't discount Meta compute spend, don't discount XAI compute spend, and don't discount DeepMind compute spend, uh, all of which you have
- ▶ 43:18 Joel Becker I think it's, it's not the case that a DeepMind model was, was at the frontier of Time Horizon at any point in twenty-twenty-five.
- ▶ 48:50 Alessio Fanelli It's like some people, people, people at Google already know.
- ▶ 53:39 Shawn Wang On the DeepMind side, the way they phrase it is literally having open-endedness team, which I think, uh, is, is a, is a topic that re-emerges once a year.
Dylan Patel Explains the AI War While Cooking | In-Context Cooking
- ▶ 15:41 Dylan Patel Um, if we start looking at like, Hey, um, this year Google spending, uh, Amazon spending two hundred billion dollars, Google spending one hundred eighty billion dollars. 2 times in the scene
- ▶ 24:27 Dylan Patel Um, Google announced a hundred and eighty billion of capex.
- ▶ 29:18 Dylan Patel Whether it's meta through ads, uh, whether it's, um, Google through search, uh, whether it's Amazon through AWS and Amazon.com, um, so on and so forth, right? 6 times in the scene
- ▶ 44:11 Dylan Patel Google, Amazon, they get to vertically integrate, integrate, and vertical integration always saves tons of money.
- ▶ 49:51 Dylan Patel And, and so now we've entered an age in, especially in 26, but as we go into 27, 28, um, you know, when we look in 26, Google would buy a lot more TPUs, but they can't ramp production fast enough, right? 4 times in the scene
Claude Code for Finance + The Global Memory Shortage: Doug O'Laughlin, SemiAnalysis
- ▶ 1:20:18 Doug O'Laughlin Like they're not quite a google.com in terms of having so much ability to like siphon off users off.
- ▶ 1:25:17 Shawn Wang So it's just like Google Yahoo again. 2 times in the scene
- ▶ 1:34:16 Shawn Wang Externally, and now you can, and Google's open as a, as a, as a supplier, I guess. 6 times in the scene
- ▶ 1:34:29 Shawn Wang A part of the whole DeepMind story was, we will hoard all the TPUs, because we were first, you know, and so, like, why sell?
Inside AI’s $10B+ Capital Flywheel — Martin Casado & Sarah Wang of a16z
- ▶ 11:18 Shawn Wang I mean, the actual post-mortem is he wanted to go back to Google. 2 times in the scene
- ▶ 16:44 Alessio Fanelli 800 K a million at Google, but if I'm getting paid five, six million, that's different.
- ▶ 40:12 Shawn Wang Like, I would say that the one data point I recently had against it is the DeepMind IMO goals, where, so typically, the typical answer is that this is where you start going down the neuro-symbolic path, right? 2 times in the scene
- ▶ 46:07 Sarah Wang Like if that were true, OpenAI or, or actually just DeepMind would be,
The AI Frontier: from Gemini 3 Deep Think distilling to Flash — Jeff Dean
- ▶ 0:11 Shawn Wang We're here in the studio with Jeff Dean, chief AI scientist of Google. 3 times in the scene
- ▶ 8:02 Jeff Dean We're using it more in our search products of various AI mode and AI overviews.
- ▶ 13:46 Shawn Wang I think Google's still the leader. 2 times in the scene
- ▶ 20:12 Alessio Fanelli Has there been any discussion inside of Google of like, you mentioned tending to the whole internet, right?
- ▶ 20:31 Alessio Fanelli Five, six links in a Google search versus for an LLM, should you expect to have 20 links that are highly relevant? 4 times in the scene
- ▶ 28:39 Jeff Dean But, you know, as you said, in the early days of Google, we were growing the index, uh, quite extensively. 3 times in the scene
- ▶ 29:16 Jeff Dean We launched a Google News product, but you also want news-related queries that people type into the main index to also be sort of updated, so.
- ▶ 30:24 Shawn Wang Or is it, is that because of Chrome?
- ▶ 42:07 Alessio Fanelli Um, any other interesting research ideas that you've seen or, like, maybe things that you cannot pursue at Google that you would be interested in seeing researchers take a step at?
- ▶ 1:00:13 Jeff Dean Um, and so, um, when I started working on neural nets at Google in, in late 2011, um, you know, I really just felt like we should scale up the 6 times in the scene
- ▶ 1:04:32 Shawn Wang Uh, so by the way, I found out from, uh, the recent, uh, I mean, you've probably told this story a few times, but apparently Google brain was also started in a micro kitchen. 4 times in the scene
- ▶ 1:07:56 Jeff Dean Um, so in particular at the time we had, uh, you know, uh, efforts within Google research on, uh, and in the brain team in particular on large language models. 2 times in the scene
- ▶ 1:16:07 Shawn Wang I think, uh, one thing that, uh, anti-gravity from, from Google also did was like, just come out the gate, very, very strong multimodal, including videos.
- ▶ 1:16:07 Shawn Wang I think, uh, one thing that, uh, anti-gravity from, from Google also did was like, just come out the gate, very, very strong multimodal, including videos.
🔬Generating Molecules, Not Just Models
- ▶ 39:16 Gabriele Corso AlphaFold Free for, you know, commercial reasons that, you know, um, did mine since spinoff isomorphic lab that is now trying to become sort of like a new pharmaceutical company, uh, had decided to keep this model internal and, and only…
Goodfire AI’s Bet: Interpretability as the Next Frontier of Model Design — Myra Deng & Mark Bissell
- ▶ 46:10 unnamed speaker Um, DeepMind has opened a lot of essays on, um, Gemma.
🔬 From Red Teaming GPT-4 to Automating Drug Discovery: The Future of AI in Science — Andrew White
- ▶ 0:58 Andrew White And when AlphaFold came out, and it's like, you can do it in Google CoLab, you know, or on a GPU or desktop, it was so mind-blowing.
- ▶ 22:35 Andrew White You know, I think when the co-scientist paper came out from Google, I think it was a really interesting idea to do this, like, tournament style or just pairwise ranking of hypotheses, right?
- ▶ 22:35 Andrew White You know, I think when the co-scientist paper came out from Google, I think it was a really interesting idea to do this, like, tournament style or just pairwise ranking of hypotheses, right? 4 times in the scene
- ▶ 44:21 Andrew White And when AlphaFold came out and it's like, you can do it in Google CoLab, you know, or on a GPU or desktop, it was so mind blowing.
Captaining IMO Gold, Deep Think, On-Policy RL, Feeling the AGI in Singapore — Yi Tay
- ▶ 0:47 unnamed speaker And then you joined GDM again, working for Cork again. 4 times in the scene
- ▶ 1:57 unnamed speaker Okay, so you rejoined GDM. 3 times in the scene
- ▶ 2:05 unnamed speaker You were talking about how it's like externally, you were in BRAIN and came out, and now you're back in GDM. 2 times in the scene
- ▶ 2:11 unnamed speaker I wonder what's your general reflections, just plugging back into the Google infrastructure. 3 times in the scene
- ▶ 13:30 Yi Tay Last year they got, like, I was not back at Google at that time.
- ▶ 26:24 unnamed speaker We have other sort of researchy topics, but beyond, before I go into sort of researchy topics, I did want to maybe leave the floor to cover what else should people know about the reasoning effort that's going on at GDM?
- ▶ 31:30 unnamed speaker Google has done stuff there, which I don't, you're probably not that close to those teams that has done AI scientist work.
- ▶ 38:48 Yi Tay I think, I think also because these tools were not like that in Google infrastructure, it's not that easy to, you don't, I'm not that familiar with what is available outside.
- ▶ 1:00:03 unnamed speaker and I've seen the talk from the DeepMind guy recently. 2 times in the scene
- ▶ 1:06:21 unnamed speaker I don't, nobody said anything about DeepMind.
- ▶ 1:12:07 Yi Tay So over time, I also left Google and stuff like, so over time, this thing evolved a little bit here and there. 2 times in the scene
Artificial Analysis: The Independent LLM Analysis House — with George Cameron and Micah Hill-Smith
- ▶ 7:21 Shawn Wang Or a Google sheet where you just like copy and paste the numbers from every paper and just post it up there.
- ▶ 8:36 Micah Hill-Smith That in the extreme and like you get crazy cases, like back when I'm Googled a Gemini one when I ultra and needed a number that would say it was better than GPT four.
- ▶ 32:11 George Cameron So we saw a big jump in, this is accuracy, so this is just percent that they get, uh, correct, and Gemini three pro knew a lot more than the other models, and so big jump in accuracy, but relatively no change between the Google Gemini…
- ▶ 47:36 Micah Hill-Smith So for me, like Google drive, one drive, um, and our super best databases, if we need to do some analysis or some data or something,
[State of Research Funding] Beyond NSF, Slingshots, Open Frontiers — Andy Konwinski, Laude Institute
- ▶ 5:02 Andy Konwinski The Google co-founders, Larry and Sergey, obviously took research, NSF funded research, by the way, and, uh, turned it into one of the most iconic companies in the history of humanity.
- ▶ 13:51 Andy Konwinski I mentioned Google earlier, Databricks, all these researchers came from NSF funding, and it's just been
[State of Code Evals] After SWE-bench, Code Clash & SOTA Coding Benchmarks recap — John Yang
- ▶ 17:21 unnamed speaker Yeah, with, uh, Google actually just, uh, came out their own version.
[State of MechInterp] SAEs in Production, Circuit Tracing, AI4Science, "Pragmatic" Interp — Goodfire
- ▶ 15:51 unnamed speaker I don't like celebrity culture, but it's hard to avoid Neil's impact, and he basically said he's pivoting his team at DeepMind, uh, to no longer focus on whatever, and now it's, like, pragmatic retributability. 2 times in the scene
[State of AI Papers 2025] Fixing Research with Social Signals, OCR & Implementation — Team AlphaXiv
- ▶ 13:50 unnamed speaker I saw this paper, it was earlier this year, called Agent Laboratory, um, from Sam Schmidt Go from DeepMind, and the idea is like, hey, like, what if we basically automate the scientific process itself, you know, like, basically it would…
[State of Context Engineering] Agentic RAG, Context Rot, MCP, Subagents — Nina Lopatina, Contextual
- ▶ 2:32 unnamed speaker Gemini launched, uh, Gemini Nano in Chrome this year.
[State of Evals] LMArena's $1.7B Vision — Anastasios Angelopoulos, LMArena
- ▶ 13:20 Anastasios Angelopoulos I mean, that moment alone changed Google's like roadmap. 2 times in the scene
[State of Post-Training] From GPT-4.1 to 5.1: RLVR, Agent & Token Efficiency — Josh McGrath, OpenAI
- ▶ 10:43 unnamed speaker Like, what are, what are, you meet your, your peer at Anthropic and DeepMind and, like, what, what are you talking about? 2 times in the scene
One Year of MCP — with David Soria Parria and AAIF leads from OpenAI, Goose, Linux Foundation
- ▶ 1:44 David Soria Parra And then like, you had this like inflection point around April with like Sam Altman and Satya and Sundar and all, um, posting about like MCP and that they're going to adopt MCP at Microsoft, at Google.
- ▶ 9:50 David Soria Parra All they know is like, oh, in the morning, I'm going to go log in with Google for, and then get access to all my work stuff.
- ▶ 12:00 David Soria Parra We literally just spent the last two days at the Google offices with a bunch of, like, scene engineers from Google, Microsoft, AWS, Anthropic, OpenAI. 3 times in the scene
- ▶ 16:32 David Soria Parra You know, Google has a different set of problems, like Microsoft and, and a lot of it comes from like just the ways of building things.
- ▶ 52:13 Alessio Fanelli But I thought Chrome developer, uh, tool, the new Chrome one is like the new, right?
- ▶ 1:32:52 Jim Zemlin So when we started CNCF, I got a call from, I think it was Urs Holzl and Brian Stevens, who were over at Google. 2 times in the scene
- ▶ 1:35:53 David Soria Parra Like if I really take a neutral look at like what just happened in the industry with creating this, it's like you have Google, Microsoft, Amazon, um, uh, Block, Bloomberg, Cloudflare, OpenAI, Anthropic.
Steve Yegge's Vibe Coding Manifesto: Why Claude Code Isn't It & What Comes After the IDE
- ▶ 11:26 unnamed speaker And just to pre-warm you, I also want to talk about just Google in general and how this Gemini revolution has kind of changed Google's image. 3 times in the scene
- ▶ 14:39 unnamed speaker I don't know if you saw anti-gravity from Google the other day, uh, we shot two days ago.
- ▶ 15:37 Steve Yegge And, uh, but there's, there will be more coming, I guess, uh, Google's as well, right?
- ▶ 28:00 Steve Yegge And then, of course, I've done platforms and Google and ads and this and that. 2 times in the scene
- ▶ 28:20 unnamed speaker One thing I wanted to get you to comment on is Google. 10 times in the scene
- ▶ 28:23 unnamed speaker One of my favorite memories, which is like just before you retired, was talking about how Google still doesn't get it, Google Cloud in particular, how they shut down the deprecation policy.
SAM 3: The Eyes for AI — Nikhila & Pengchuan (Meta Superintelligence), ft. Joseph Nelson (Roboflow)
- ▶ 35:16 Joseph Nelson And maybe the Google team taking some notes to improve a Gemini and other series of models based on what SAM-III demonstrates here.
⚡️Jailbreaking AGI: Pliny the Liberator & John V on Red Teaming, BT6, and the Future of AI Security
AI to AE's: Grit, Glean, and Kleiner Perkins' next Enterprise AI hit — Joubin Mirzadegan, Roadrunner
- ▶ 16:31 Joubin Mirzadegan Where everybody has promised, Google included, like the best companies in the world, that they're going to solve enterprise search once and for all.
- ▶ 27:10 Joubin Mirzadegan That they want to both build Google class product and Salesforce class distribution.
The Future of Email: Superhuman CTO on Your Inbox As the Real AI Agent (Not ChatGPT) — Loïc Houssier
- ▶ 29:57 Loïc Houssier Um, we are a GCP shop.
- ▶ 49:28 Shawn Wang So I, based on the different emails I have, logins I have, I switch between Atlas and Chrome and Arc. 2 times in the scene
- ▶ 58:11 Shawn Wang Obviously has privileged access to all of Google.
The Great Evals Debate — Ankur Goyal & Malte Ubl
- ▶ 1:05 Malte Ubl Like, I think the, like, one maybe important background on me is also that I worked on Google search just before leaving for Vercel. 2 times in the scene
- ▶ 8:51 Shawn Wang This is not like, this sounds like a made up term, but it's a real team at Google that is actually exploring open-endedness.
World Models & General Intuition: Khosla's largest bet since LLMs & OpenAI
- ▶ 1:52 unnamed speaker DeepMind has been working on this with Genie one two and three and SEMA one and two, and this year, Okon AI seemed to finally agree