Partner @CorrelationVC // Previously @Yext, Nomi, Buddy Media, WMA, Penn // TX native // ❤️ tacos, concerts, tennis

Brooklyn, Austin, Hudson
Wesley Barrow ⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝ retweeted
Introducing Quotient Analytics. Most marketing analytics starts after the work is done. You plan the campaign in one tool. Create the email and content in a few more. Publish social somewhere else. Then, once it is all live, you try to piece together what happened across GA4, email reports, social dashboards, and your CRM. That is backward. Marketing needs a tighter feedback loop: plan the work, ship it, see what it drove, and make the next campaign better. Quotient Analytics brings that loop into the same platform where the work happens. It connects email, social, and website activity to the campaigns that drove it, with automatic tagging and an agent you can ask for answers. The goal is not another dashboard. It is a marketing system that learns from the work you put into it. Go check it out: getquotient.ai/features/anal…
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Man RIP Mr. Belding. SBTB was part of my childhood routine.
"Saved by the Bell" star Dennis Haskins has died at 75 💔🕊️ tmz.com/2026/09/28/saved-by-…
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Wesley Barrow ⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝ retweeted
Here is official trailer, You Can See Everything
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Congrats on the launch Spencer!
AI is killing your company. It should be making you more revenue. Introducing BuildBetter: the first AI Head of Product. Here’s how it works 👇
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Wesley Barrow ⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝ retweeted
i know everyone is concerned so let me come and say it: there is a 0% chance Virtual Offices like @roam kill everyone
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Story of my life
crazy that on @united you either pay $0 for super fast @Starlink wifi or you pay $8 to spend the entire flight trying (and failing) to connect to network wifi
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This has to be the most exciting upcoming season for gamers in a very long time right? Zelda, GTA, Stage Tour, what else?
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Congrats on the launch @David_Reich and @fambotAI !! We are proud to be investors at @CorrelationVC
Today @fambotAI announced we’ve closed a $3.5M pre-seed co-led by @NextViewVC and @_baukunst , 1,000+ families, apps live on iOS + Android, and WhatsApp integration. Fambot is AI that exists to let parents put their phones down and be present with their kids - free in beta
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Wesley Barrow ⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝ retweeted
We've spent the last several years building what we believe is the best instrument for studying human skin. Real tissue, alive and measurable long enough to see skin change the way it does in the human body. Our goal is to meaningfully improve skin health. We hope you'll follow along. techcrunch.com/2026/08/21/mi…
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Wesley Barrow ⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝ retweeted
Build your band, hit the stage, and go on tour! 🤘 • 90+ officially licensed songs • 180+ authentic in-game @gibsonguitar guitars • 50+ bandmates • Official hardware • New ways to play and more! 👉️ Pre-order game & hardware now at StageTour.com.
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Wesley Barrow ⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝ retweeted
Humanoid robotics, physical AI, and a growing fleet already the largest independent one in the U.S. Our Oakland facility is a foothold in the Bay Area's physical AI corridor, and there's much more to come. Read more: businesswire.com/news/home/2…
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Wesley Barrow ⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝ retweeted
Presenting compute-optimal scaling laws for human motion generation!!! Human motion generation has historically been niche and difficult to scale. Animators, roboticists, motion analysts, and game developers all see the potential, but it rarely lives up to the rigor required in production. We have long believed this is because all prior systems have been fantastically data constrained. Until today, we haven't been able to prove that scaling would actually help. Today we present our flagship research paper: Compute-Optimal Scaling Laws for Human Motion Generation. (link: github.com/Cartwhl/scaling-l…) We are building the world's largest, high-quality human-motion dataset. We trained hundreds of models across varying scales. They match the Chinchilla scaling found in language. This places motion as the fifth data modality we understand how to scale. Text, images, audio, and video all have scaling laws. None of them really reflect the physical world. 3D human motion, across time, does. Both autoregressive and flow matching motion models scale predictably. We can now predict, before training a model, how good it will be. Motion is no longer data constrained. It is now a predictable and scalable frontier for physical and digital intelligence. Our largest models are training now, and the gap between generated motion and the real physical world is closing fast. paper: github.com/Cartwhl/scaling-l… blog: getcartwheel.com/blog/scalin…
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Wesley Barrow ⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝ retweeted
.@OuterBio emerged from stealth over the weekend with Yuna, a platform that makes it possible to study living, full-thickness human skin outside the body for weeks, not days. That longer window gives researchers time to observe slower biological processes like collagen remodeling, pigmentation, inflammation, and barrier repair. Yuna pairs those experiments with machine learning, using each one to sharpen the next prediction. We’re proud to support @michaelpolansky and his team alongside other investors Wing Venture Capital, @SozoVentures, Hawktail, @lightspeedvp, Third Kind Venture Capital, @Liquid2V, and @svangel. More from @cookie in @TechCrunch: techcrunch.com/2026/08/21/mi… + more from Michael on why they are building Outer Bio: outerbio.com/news/why-we-are…
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Wesley Barrow ⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝ retweeted
Pretty exciting for Andrew and the Cartwheel team. Cartwheel just discovered that 3D human motion has a scaling law. This puts them in the same league as the frontier AI labs, but in a totally new domain.
Presenting compute-optimal scaling laws for human motion generation!!! Human motion generation has historically been niche and difficult to scale. Animators, roboticists, motion analysts, and game developers all see the potential, but it rarely lives up to the rigor required in production. We have long believed this is because all prior systems have been fantastically data constrained. Until today, we haven't been able to prove that scaling would actually help. Today we present our flagship research paper: Compute-Optimal Scaling Laws for Human Motion Generation. (link: github.com/Cartwhl/scaling-l…) We are building the world's largest, high-quality human-motion dataset. We trained hundreds of models across varying scales. They match the Chinchilla scaling found in language. This places motion as the fifth data modality we understand how to scale. Text, images, audio, and video all have scaling laws. None of them really reflect the physical world. 3D human motion, across time, does. Both autoregressive and flow matching motion models scale predictably. We can now predict, before training a model, how good it will be. Motion is no longer data constrained. It is now a predictable and scalable frontier for physical and digital intelligence. Our largest models are training now, and the gap between generated motion and the real physical world is closing fast. paper: github.com/Cartwhl/scaling-l… blog: getcartwheel.com/blog/scalin…
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Wesley Barrow ⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝ retweeted
Last week we opened our first West Coast facility in Oakland. Hundreds showed up, including Oakland's mayor. We ran live humanoid demos alongside our existing fleet. Formic runs the largest independently owned robot fleet in the U.S., with 650,000+ production hours logged. More to come.
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Wesley Barrow ⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝꙰⃝ retweeted
I'm excited to introduce @OuterBio and Yuna, the ex vivo human skin platform our team has been building for the past several years. Yuna keeps living, full-thickness human skin viable and observable for four weeks, with native tissue architecture preserved. Innovation in skin health has been slow for decades, and part of the reason is that outside the body, human skin has only stayed usable for about a week. Yet key biological processes such as collagen rebuilding, inflammation resolution and damage accumulation take far longer than that. The field has been reading the opening days of a process that plays out over a month. Yuna extends that window and pairs it with machine learning in a closed loop, so every experiment sharpens the next prediction. Our bioRxiv preprint shows Yuna holding three distinct skin biologies across four weeks: psoriasis-like inflammation, senescence in aged donor tissue, and UVB stress response. In each case it returned the known answer when challenged with an established intervention. Thank you to KJ Jang, Chris Hinojosa, Stan King, and the rest of the incredible Outer Bio team. outerbio.com/news/why-we-are…
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