I’m excited to announce the @brickxbrickpod! @arpanpunyani and I will be sitting down with early employees, founders and investors to talk about the (often untold) crazy stories that help lay the foundation for future startup success 🧱
@taps and I @GarudaVC hosted our annual meeting in SF a few weeks ago for our LPs and invited guests, followed by our community-wide Spring Celebration right after.
It's always a fun opportunity to share where we're investing and what we're learning, having a few founders and leaders share insights on where their markets are going, and bringing our growing community together for some fun!
Special thanks to portfolio founders @adarshkulkarni from @FoundryRobotics, @shaneehrhardt from @ExScienceAI , and Derek Ben and Michael at Vardera - who were busy closing deals the morning of our event! - for joining us. And thank you to the inimitable @rodriscoll from @scalevp and Jonathan Roosevelt from Goldman Sachs for sharing their perspectives and wisdom.
Thanks to our amazing sponsors Burkland, Neutech, Inc., Fenwick, and Citizens!
@erikbryn That is absolutely true. Not enough house for a screen big enough to do it justice!
I just hope there are mostly “fans” in the audience, vs. those that are going to see and be seen at arguably the hottest event (and hardest ticket) in NYC
Mirai Tech is now Mirai Labs (@trymirai)
A full-stack frontier lab for on-device AI.
Models, inference engine, quantization, and application layer, all co-designed from the hardware constraint up.
Interactive AI is a continuous loop: parsing, validating, tool calls, rendering. That only works when latency disappears.
Cloud models can't get you there as they're built for large batches, abundant memory, throughput as the metric. On-device inverts every assumption, requiring the architecture that was built from the hardware constraint up.
The silicon is shipped. The software stack to match the chip doesn't exist yet. That's ours to build.
“@arenaphysica’s bet is that the same idea works as a foundation model rather than a one-off demo: faster inference, trained on roughly 10 million geometries plus decades of simulation data, with lab measurements added as a third data leg to help close the sim-to-reality gap.”
Thanks to the @hardwarefyi team for highlighting @m__frei’s CDFAM talk in this week’s newsletter. Read the full piece here: https://t.co/9RPCEdpV2A.
Welcome to Episode 1 of The New Feynman Lectures. No one better to kick off this series than Shaun Donovan, Head of Electrical and Mechnical Engineering at @anduriltech.
Ever wonder about Triplex Redundancies in Autonomous Aircraft? Watch the full episode here: https://t.co/SsrGhk9MTA
Next up: @JLopas with @basepowerco!