Dorian

1/ Ever wonder why many VLA demos look smooth only after 5-10× video speed-up? Running VLAs in real time (or faster) is not one problem. It’s several tightly coupled ones. Here is a "mini literature survey" thread on recent papers (RTC, SAIL, VLASH) in this paradigm.

In 2026, Venture Capital will eat Private Equity It used to be that venture capital and private equity lived on two separate planets: VC = San Francisco PE = New York They targeted completely different universes of companies: --> PE - people heavy biz services, stable/low growth, predictable cashflows --> VC - tech-forward, high growth, high risk, massive TAM What was the playbook for B2B VC backed startups? --> Grow to unicorn scale by selling to other early adopter tech companies, then Fortune 500s XX> SMB and mid-market services - think field services, IT staffing, accounting, construction, recruiting - were always tough to sell into for startups Why? -->Thin margins, high labor costs, and small IT budgets >> But as AI eats labor, these businesses are in play << There are 3 ways where VC and PE are colliding: 1/ Private Equity funds will become channel partners for startups. PE funds are focused on financial engineering and cost optimization. Startups building AI products and services can sell across their portfolio to automate the backoffice and uplevel sales and marketing. PE funds have made AI their #1 strategic priority and have hired central leaders to oversee their portfolio adoption efforts 2/ PE portfolio pages are a startup idea menu Private equity will often buyout vertical software companies whose TAM didn’t allow venture scaled returns. As software evolves from data storage and collaboration to agents taking action and completing work, AI should massively expand the TAM for these categories. Founders will set their sights on unseating these legacy incumbents backed by private equity. All they have to do is look at their portfolio pages for category ideas 3/ AI Rollups This is one of the most direct ways that VC is eating PE VC backed AI platform businesses are not just selling software but acquiring legacy business services companies to own the value chain end to end. As an example, our @speedrun company AgentAstra is acquiring freight forwarding services businesses with mostly debt and integrating AI deeply into their operations These companies aim to increase margins by at least 2x and make them “AI native” tl;dr - While the west coast, Patagonia-wearing VCs and the east coast, PE suits used to live in different universes, in 2026 with AI, I believe, those worlds converge

I have met many students and young researchers lately who claim to be working on World Models or Embodied AI but do not even know the basics of 3D Vision or linked rigid body motions. When did we start to give students the illusion that they can *do* things right without *learning* anything right?

We release OpenReal2Sim, an open-source toolbox for real-to-sim reconstruction and robot simulation. A key difference from prior work is our focus on building an interactive digital twin from in-the-wild data — even Internet images or generated videos. Try it out: Interactive Demo: hesic73.github.io/OpenReal2S… Code: github.com/PointsCoder/OpenR…

It’s near impossible to beat someone who just doesn’t give up. I learned that racing marathons: you hit a wall, you feel awful, you may think you're done—and then somehow you find another gear. The same thing happens as a founder. And as an investor. You can believe something long before the rest of the world catches up. Sometimes it takes years, sometimes it shows up in a form you never imagined. But if you stick with it, the payoff is real. Stamina compounds.

FT Exclusive: Jensen Huang has warned that China will beat the US in the artificial intelligence race, thanks to lower energy costs and looser regulations. Read more from his interview with the Financial Times: on.ft.com/4oZUXyB