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Who Feeds the GPUs? Inside AI’s Hidden $30B Layer | Renen Hallak, VAST Data
The MAD Podcast with Matt Turck · 2026-09-24
Speaker 1 | 00:00 - 00:17
Sometimes it scares me. We had a customer, one of these AI clouds, they said we’re probably going to need about 500 petabytes over the next three years. Last week, came back to us and said, we’re gonna need an extra two exabytes on top of that 500 petabytes. I think in the next ten years, we’ll see more difference than we did in the last thousand years.
Speaker 2 | 00:17 - 00:30
Hi. I’m Matt Turk. Welcome to the MAD podcast. We talk a lot about AI models on this show, and we talk a lot about compute. But today is about the layer in between, the crucial software infra…
🐦 X/Twitter 热点
Thibault Sottiaux (@thsottiaux)
- All right, we’re locking in. Only things being worked on are simplifications, more efficiency for more usage, groundbreaking features or new models.
Sometimes you have to invest ahead of the curve, but feedback is clear that you all want things to get simpler. On it. [6762 ❤️ 167 🔄]
What it did
delete all categories of email that were not needed for me to keep, validating them in batch
identify labels for types of work that I do and label all the emails appropriately
walked me through emails that needed a reply, searching for relevant context in the background to help get things right
and in the process I was able to go through a lot of feedback and requests people send me directly through email. It was a good Saturday. [254 ❤️ 7 🔄]
- I have never in my life achieved inbox zero until I just made it an active goal for my dot to help get it done. Let’s see how long it lasts, but it’s a great feeling. [1352 ❤️ 34 🔄]
Peter Yang (@petergyang)
- I’m watching Foundation now season 1 episode 3 and can’t decide if I really love it or not.
Does it get much better? The emperor plot is good the rest seems meh so far. [86 ❤️]
- Google CEO actually uses this app and replies to feedback while YouTube CEO only uses this as a comms channel to post announcements [1311 ❤️ 15 🔄]
- Was talking to my agents at the park then got scratched by a squirrel
nature is telling me something [57 ❤️]
Nan Yu (@thenanyu)
- The man has spoken [37 ❤️ 1 🔄]
Madhu Guru (@realmadhuguru)
- AI adoption is largely a product problem today.
Even among the 2% that are paying for AI today, the depth of usage is shallow.
The main reason : most AI products look like airplane cockpits with 100 levers - connectors, permissions, model selection, token usage etc.
This has started to change. Things will look materially different in the next 12 months as product teams come into their own and make AI products easier to use. [145 ❤️ 13 🔄]
Amjad Masad (@amasad)
- Who’s building this? [470 ❤️ 19 🔄]
- We go really deep and somewhat technical here with the brilliant @alexatallah of OpenRouter. Enjoy! [217 ❤️ 13 🔄]
- Replit Drift [316 ❤️ 9 🔄]
Guillermo Rauch (@rauchg)
- Summer is finally here! 🌞⛱️ [868 ❤️ 7 🔄]
- Security will become a larger and larger function in software companies. Security is verification engineering (eg: “my code is probably memory-safe”), as well as capital allocation (“what surface should I throw most tokens at?”)
For startups, it’s a challenge and opportunity. As the world’s paranoia grows given ever-more-sophisticated AI adversaries, how can you trust a 2-person-and-a-dog company?
But conversely, given the dire state of global cybersecurity and increasing reliance on centralization, as always, there’re vast areas that small teams can now disrupt that I’m excited to invest in. [587 ❤️ 32 🔄]
- AI will make everything free, including itself. The last domino to fall will be free energy, which is humanity’s final frontier. [3229 ❤️ 193 🔄]
Aaron Levie (@levie)
- AI agent adoption is still very bimodal right now. You have coding and coding adjacent tasks which have taken off, and then everything else.
And even within coding, you have a very wide continuum of adoption patterns, with some likely a small percentage of developers deploying background agents working on projects in parallel, and the rest of everyone else still working with agents 1:1.
Then, there’s the entire rest of knowledge work where real agentic adoption is still very early. The reason for this is that most of the workflows still need to reengineered to work with agents.
This isn’t the same as deploying a chat system for better research efficiency, but instead requires workflows to be rebuilt, data to be wired up in new ways, new practices for accountability and liability of decisions when agents are in the mix, governance and compliance paradigm changes, security upgrades, and more.
We’re still so unbelievably early in what this is going to look like outside of a few categories of work right now. This is why you can basically expect 100X more agent adoption from what we’ve seen so far. [187 ❤️ 15 🔄]
Ryo Lu (@ryolu_)
- [124 ❤️ 5 🔄]
- convergence to the mean
when everyone looks at everyone else to decide what to make, we eventually stop making anything of our own.
we copy what works. borrow the language, the aesthetic, the features. we call it learning from the market, following best practices, staying competitive. together, everything starts to feel familiar. polished, interchangeable. nothing wrong. nothing alive.
the mean isn’t necessarily bad. it’s where everything lands when we remove the reasons for it to be different.
numbers are easier to compare than feelings, so we make things that produce numbers. we study what gets attention, then shape ourselves around it. eventually the feedback stops informing the work and starts authoring it. we’re no longer asking what we want to say. we’re asking what will be rewarded for saying.
ai makes this loop frictionless. it can draw from more references than we could see in a lifetime. but access to every perspective isn’t the same as having one. it hasn’t lived a particular life that makes one detail unbearable and another beautiful. when we ask it to choose for us without bringing any intention of our own, we get something plausible, easy to approve.
then we ship it, measure it, copy it, and feed it back into the next round. a tidal wave of mid.
this changes not just the work, but the people making it.
we describe ourselves in categories platforms can distribute and markets understand. designer. founder. creator. pick a niche. build a brand. be consistent. the parts that don’t fit become inconvenient, even when those contradictions might produce our most interesting work. we become easier to classify and harder to tell apart.
i think we need to approach making things more like artists.
an artist develops a perspective through the work. making, noticing, choosing, failing, returning. learning what matters even when nobody else cares. craft gives that perspective a form precise enough for someone else to experience.
the life outside the work matters too. the places you’ve lived, the people you’ve loved, the things you’re embarrassed to care about. these aren’t distractions from having something to say. they’re how you come to have something to say.
we understand this with music, paintings, photographs, movies. we expect a person to be present in the choices. we want to experience something we wouldn’t have encountered without them.
software can do this too.
a piece of software expresses beliefs about how life should feel. what deserves your attention. what you should be free to change. whether a task should feel like paperwork or play. even a small interaction can carry someone’s care, humor, or curiosity.
but we rarely talk about software as a medium. we talk about it as an industry. markets to capture, workflows to optimize, competitors to catch up with. we add a feature because someone else has it, without asking whether it belongs. products accumulate the same parts and lose what made them worth choosing.
underneath the branding, it’s all the same thing.
artists learn from others too. the question is whether you’re absorbing those influences into a point of view, or using them to avoid developing one.
what are you trying to let someone feel, understand, or do? why this particular shape? what have you noticed that the existing tools don’t seem to notice?
those questions don’t have answers you can borrow from a competitor’s roadmap.
if we can make almost anything, deciding what deserves to exist becomes more important, not less. speed gives us more chances to exercise judgment. it doesn’t remove the responsibility.
i don’t want a world where every person becomes a more efficient distributor of the same ideas. i want people to use these tools to go further into what they actually care about. to make things specific enough that we can feel someone behind them.
what is the point of everyone being able to make something, if we all end up making the same thing? [1776 ❤️ 224 🔄]
Zara Zhang (@zarazhangrui)
- How will the world change if coding agents get 10x better? [96 ❤️ 3 🔄]
Nikunj Kothari (@nikunj)
- Me: Enjoying the warm weekend..
Me: Also refreshing that El Nino forecast 🤯 [10 ❤️]
- It’ll be interesting to see how this innovator’s dilemma plays out in the next few years as personal agents become inevitable..
Amazon is protecting it’s “ads” cash cow and cough the brand.
Doordash, albeit smaller, is opening the gates (slowly) with their CLIs and allowing to order via text. [23 ❤️]
- Again do it for a bit to explore the edges and maybe find the right purpose.
But tokenmaxxing for the sake of doing it is not honestly useful in this era. [1 ❤️]
Peter Steinberger (@steipete)
- laughing about how we all are building the same thing. [609 ❤️ 14 🔄]
- Do I know anyone at Google who could help? We’re now over a week in review limbo for OpenClaw’s Android app. [6315 ❤️ 106 🔄]
Aditya Agarwal (@adityaag)
- A common misconception is that if you are super rich, you can get unlimited access to the world’s best doctor/lawyer/creative-professional etc.
The reality is that the world’s leading cancer doctor will still see you for 20-30min if you have cancer no matter how much money you have.
This is why AI is so crazy.
It both democratizes access AND it makes the amount of time available unlimited for every individual.
This is the practical effect of intelligence too cheap to meter. [335 ❤️ 18 🔄]
Sam Altman (@sama)
- I am very uncomfortable about people trying to ascribe religious force or a surrender of human judgment to AI models, and think it is a real safety issue. [24293 ❤️ 1650 🔄]
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由 Follow Builders 自动生成 · 2026-10-04