I’m rebuilding this account around what I actually do now:
I build AI + robotics systems for the physical world.
PCB design. Embedded C. Robotics control. ML/computer vision. Mobile apps. Medical-device engineering. Mechanical prototypes. The messy stuff where software has to survive contact with hardware.
I’ve founded and built projects across pathology imaging, automated agriculture, medical devices, AI training tools, PCB automation, and robotics. I’m currently building PromptPCB and leading engineering on AutoTQ.
This account is going to be build logs, technical notes, failures, fixes, prototypes, AI hardware workflows, and lessons learned the hard way.
No guru content. No fake founder theater.
Just engineering, product building, and the grind of making difficult systems work.
The way I would automate PCB design is spending a year or so doing electrical engineering classes to learn how to make a simulator and then training models in those simulators as verifiers
anyone know of any projects doigngLLM memory management inspired by os memory paging techniques
but maybe semantically aware
seems like an extremely similiar problem
If you move past using google flow to make clips with people or animals where its squarely in uncanny valley
its actually insane for general B-Roll, promo video, static shots
Introducing Claude Fable 5: a Mythos-class model that we’ve made safe for general use.
Its capabilities exceed those of any model we’ve ever made generally available.
current pulse on AI PCB design seems like its still in a stage where it lacks grounding and is prone to hallucination or misses complex interactions and behaviors
i'm confident this is a solvable problem
I've seen some thoughts that there isn't enough data or there wasn't enough training data in this domain
but i think all the data thats needed is present in datasheets and in simulation data that can be gathered from the circuit and it just needs to be collected and structured in a way that allows for AI based reasoning
for humans that involves reading datasheets and looking at schematic files, and drc tools, etc
for AI to be capable I think the input data needs to go beyond dropping in a netlist, or schematic, or footprints etc and needs to use deterministic tools in order to help pull out signal from noise on behalf of the AI in order to unlock its reasoning ability in a grounded way
still unreal that I got the chance to briefly talk about the work i'm doing at https://t.co/i8HqfmRRg3 with @alexwg thanks to @EwillieP for making the whole thing happen
https://t.co/hR24jsuI22