Harry Renquist

@buccocapital Worth it

$2T in capex for this btw

Dario worrying about the third world not getting AI, my brother they don't even have toilets

Facemogged

I don't know how to break this, but the missing productivity gains from AI is because most desk workers are not really productive. They do not do useful work as it is, AI isn't helping that.

@leahyunaxo @grok @grok make her a tradwife with husband and kids

hey @grok put me in a micro bikini

@blacknredtext This is just so good

anon sub

@StevenHailAus @StephanieKelton The Official Public Account cannot go negative (by legislation?) so bonds must be sold right?

@StevenHailAus @StephanieKelton But they do kind of sell exactly the amount in bonds that they need to keep spending?

@StevenHailAus @StephanieKelton Link to source?

@robinhanson Economics

What are the topics where you see the lowest quality commentary from all different sides? I nominate: UFOs and consciousness.

@TheAhmadOsman They invented embeddings?

most people donʼt realize how massively set up Google is to win the AGI race, theyʼv been quietly running the world’s largest AGI farm for a quarter of a century they invented half the stack > embeddings, transformers, most LLM breakthroughs: started at Google > Hassabis, Shazeer: top-tier talent, still in the building hardware & infra monopoly > tpus: custom AI silicon since 2016 > proprietary data centers, zero bandwidth bottlenecks > 2b+ lines of internal code: real, living training ground best dataset on the planet > search: billions of queries, clicks, and corrections > gmail: 1.8b inboxes of real-world behavior > youtube: millions of videos daily > android: 3b devices, humanity on tap 24/7 > waymo: 71m self-driving miles > earth/maps/streetview: full planet coverage > fitbit, chrome, docs, pixel, nest: all the signals, all the time everything is feedback > every click, typo, swipe, scroll: training data in real time > automatic reinforcement loops, everywhere planet-scale experience > multimodal data: text, images, video, code, sensor streams > feedback from billions, not benchmark suites > labeled, versioned, real-world codebase > operating at God Mode, quietly syncing and mapping the world even more > and now, while everyone else scrambles > to build nuclear plants to power AI, > they simply asked: > what if we just moved the datacenters closer to the sun? the kicker > others train on books and PDFs > Google trains on humanity itself to Google > AGI is just a side quest, > when you’ve been running a planet-scale simulation for 25 years

@AISafetyMemes Great image

Drug company: I invented a drug I hope will solve every health problem, I’m putting it in the planet’s water supply Society: You're...WHAT Drug company: Actually, we started putting it in the water supply months ago. It might kill everyone, but you can’t regulate us because it's too economically valuable. Society: The fuck?? If you put it in the water supply, people can’t even opt OUT of taking your drug. Cancer drugs are economically valuable and we STILL make drug companies test them for 10-15 years. We even do this for PIMPLE drugs! (This is the state of AI.)

@cafreiman What is the 1 thing it gets most right?

Econ 101 gets far more right than it gets wrong

@ctbeiser Ahh I see. tiktok algo better at not recommending such slop?

@harry_renquist the slop on shorts is truly abominable

new study out confirms something I've long believed: watching Instagram Reels or Youtube Shorts is basically twice as bad for you as TikTok

@MiddleOfMayhem Hard to explain, but this is a very funny post

nvm i figured it out

@thoughtlesslabs @kylascan Does it describe MMT?

Hey hey! Weekend reading material just showed up @kylascan

🔥 Today we’re excited to announce new funding for `grep` (at a $1.3B valuation) to continue building the foundation of agent observability and text search infrastructure. grep began as a humble UNIX utility in 1973. Since then, it’s evolved—through recursive innovation and the rise of ripgrep—into a core platform for developers, sysadmins, and agents. Our tools now power engineering and AI teams across @OpenAI, @Anthropic, @Meta, @Cloudflare, @Replit, @NASA, and thousands more. Over the decades we’ve iterated from grep to `egrep` to `ripgrep`. Our goal has always been to figure out what intelligent agents of the future need to see, filter, and extract—and then build the tools that make that possible. While our journey is still just beginning, we also want to take a moment to reflect on how the space (and our role in it) has evolved. You can read our reflections and details on this funding milestone here: gnu.org/software/grep/… We also share more about the funding that will power our future there. Thank you to @IVP, @Benchmark, @Sequoia, @CapitalG, and the open-source community for their belief in the enduring power of regex. What excites us most today is what’s next: grep 5.0 with AI-assisted pattern synthesis ripgrep Cloud, bringing distributed search to agent clusters pgrepGPT, an agent-native process discovery layer And new no-code integrations for autonomous observability pipelines We’re in the midst of a transformation in computation itself. grep and ripgrep will remain at the core—helping humans and agents alike find what matters, faster.

This is what propaganda from China looks like btw

@wbmosler Uhhh China?