Vinci4D.ai

The engineers who know how to run complex physics simulation workflows are a small and specialized population. They always have been. For most of the history of hardware development, that was manageable — the number of programs, the complexity of the systems, and the pace of iteration were constrained enough that a small group of specialists could keep up. That balance has broken. Hardware programs are multiplying. Systems are becoming more complex. Design cycles are accelerating. But access to physics expertise has not scaled with them. Hiring more specialists will not solve a structural bottleneck. At Vinci, we are building the physics infrastructure that will — making solver-accurate physical reasoning available at the speed and scale modern hardware development demands.

The hardest physics problems in semiconductor design are no longer at the chip level. Chiplet architectures, 3D integration, and HBM-class systems have pushed thermal, mechanical, and electrical behavior into the critical path across the full system — and the simulation workflows built to handle it weren't designed for this level of complexity or this pace of iteration. Hardik Kabaria is joining a panel of industry and academic experts at DAC, The Chips to Systems Conference 2026 on Monday, July 27, to examine what it takes to make physics-based AI trustworthy in production engineering environments — what breaks under real conditions, what validates, and what becomes possible when physics reasoning runs continuously at machine scale. Learn more: https://lnkd.in/eBenwGfn

For most of the history of semiconductor engineering, physics has entered the design process at the end. A candidate design gets frozen, handed to a specialist, and checked against physical reality after the decisions that shaped it have already been made. Thermoelastic warpage prediction has been one of the clearest examples of that constraint. Understanding how heat and mechanical stress cause a real design to deform—at manufacturing resolution and on native geometry—has historically required so much time and specialist effort that it became a late-stage activity by necessity. Vinci runs thermoelastic analysis directly on native design geometry, while there is still time to change the outcome. That changes the order of operations. Physics stops being a verification step and starts shaping the design from the beginning. See how it works: https://lnkd.in/eKeCGhr4

For decades, physics simulation in hardware development has been gated by a small population of specialists — the engineers with the expertise and the time to run the tools. A chip reaches tape-out—and a thermal issue surfaces too late to fix without millions in cost and months of delay. The analysis that could have caught it was still waiting in a queue. Hardik Kabaria joined the Built This Week podcast to make the case that this is a structural problem, not a resourcing one, and how a foundation model for physics is what breaks it open. When physics reasoning becomes accessible to every engineer on the design team, what hardware teams can build and how fast they can build it changes fundamentally. Watch the full episode here: https://lnkd.in/dE_MbeQ7

DAC, The Chips to Systems Conference brings together the engineers, researchers, and technology leaders defining the next generation of semiconductor and electronic systems design. At this year’s conference, Vinci will be on stage discussing how deterministic, solver-grade physics reasoning is changing what's possible in hardware development — and meeting with the engineering teams experiencing that shift firsthand. If you're attending and want to connect with the team, join our recruitment happy hour at the Marriott Long Beach Vinci suite on Tuesday, July 28. Register here: https://luma.com/80je2lej Hardik Kabaria Satish Radhakrishnan, Ph.D JOHN BRUGGEMAN

Physics has been a checkpoint in engineering workflows for decades — run by a handful of specialists after the architecture is frozen. Hardik Kabaria sat down with CDFAM - Computational Design Symposium to explain why that model is hitting a structural limit and what replaces it. Vinci's foundation model computes thermal and thermo-elastic behavior directly on manufacturing geometry — without simplification, manual meshing, or per-customer training — and generalizes to new designs out of the box. Semiconductors are the proving ground. The same approach extends across automotive, aerospace, energy, and medical devices. When physics stops being a gate and becomes always-on design infrastructure, what engineering teams can build changes fundamentally. Read the full article here: https://cdfam.com/vinci4d/ 𝗛𝗮𝗿𝗱𝗶𝗸 𝘄𝗶𝗹𝗹 𝗽𝗿𝗲𝘀𝗲𝗻𝘁 𝗮𝘁 𝘁𝗵𝗲 𝗖𝗗𝗙𝗔𝗠 𝗖𝗼𝗺𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗗𝗲𝘀𝗶𝗴𝗻 𝗦𝘆𝗺𝗽𝗼𝘀𝗶𝘂𝗺 𝗶𝗻 𝗪𝗮𝘀𝗵𝗶𝗻𝗴𝘁𝗼𝗻 𝗗.𝗖. 𝘁𝗵𝗶𝘀 𝘄𝗲𝗲𝗸. 𝗜𝗳 𝘆𝗼𝘂'𝗿𝗲 𝗮𝘁𝘁𝗲𝗻𝗱𝗶𝗻𝗴, 𝘄𝗲'𝗱 𝗹𝗼𝘃𝗲 𝘁𝗼 𝗰𝗼𝗻𝗻𝗲𝗰𝘁.

This week we sat down with Hardik Kabaria, co-founder and CEO of Vinci4D.ai, to demo the AI platform making physics simulation accessible to any engineer building hardware. Thermal analysis that used to take days now takes seconds. No PhD required. No waiting for a specialist. We also got into why AI image and video generation still has not produced a single Netflix movie and what has to change before it does. Full episode here: https://lnkd.in/dE_MbeQ7

World models are reshaping how industries think about simulation, autonomy, and physical intelligence. The more important question isn't whether AI can simulate reality — it's whether it can do so deterministically, at manufacturing resolution, with the fidelity that engineering decisions actually require. Join us at Ai4 - Artificial Intelligence Conferences 2026, where Hardik Kabaria will make that case alongside industry leaders who are pushing the boundaries of what physical reasoning can do on the 𝙎𝙞𝙢𝙪𝙡𝙖𝙩𝙞𝙣𝙜 𝙍𝙚𝙖𝙡𝙞𝙩𝙮: 𝙏𝙝𝙚 𝘽𝙪𝙨𝙞𝙣𝙚𝙨𝙨 𝙑𝙖𝙡𝙪𝙚 𝙤𝙛 𝙒𝙤𝙧𝙡𝙙 𝙈𝙤𝙙𝙚𝙡𝙨 panel.

In semiconductor packaging, warpage has quietly derailed some of the industry's most advanced programs — not because the engineering was wrong, but because the physics arrived too late to act on it. When deformation exceeds tolerance by even a few microns, the impact can cascade from assembly problems to redesigns, qualification risk, and delayed product shipments. For decades, teams had to choose between physical experiments that took months and simplified simulations that abstracted away the very layout and stress detail responsible for real warpage behavior. Vinci is bringing thermo-mechanical analysis into the design workflow earlier, with thermoelastic warpage prediction that runs at manufacturing resolution directly on native package geometry. In plain terms: predicting how heat and process-induced stresses cause a package to deform, before that deformation becomes a late-stage failure. This is what continuous physics reasoning looks like in production. Learn more: https://lnkd.in/eKeCGhr4

The design cycle for a modern PCB or vehicle system can span months. Physics validation typically happens near the end of it — after the architecture is set, the components are chosen, and the options for changing anything have narrowed considerably. Vinci changes where in that process physics insight becomes available. The same foundation model that runs final validation can run at the earliest stages of design — on full-fidelity geometry, deterministically, in seconds. Engineering teams working on boards, enclosures, and vehicle subsystems are using it to surface heat and reliability constraints at the point where acting on them is still straightforward.