frolicking in the garden of technology @rox_ai
SF
Joined March 2021
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~/mehul/ retweeted
what is this thing on bart?? percy uses public transit too.
Ride BART to explore the city while playing Pursuit.
sfpursuit.org
🎬
Revenue agents are the main course. Data enrichment is on the house.
B2B orgs spend $3.1B a year for employees to find contact and company data. Now agents need it too.
So we made a call: enrichment is a cost of doing agentic work, not a product to mark up. It's infrastructure that revenue agents need to run.
Today, we’re opening up our in-house data collection and enrichment infrastructure to all.
No extra contracts. No credits to count.
Just revenue, served.
~/mehul/ retweeted
“don’t train your own model” is common ai advice. it's wrong. your token bill's the proof.
today, we’re excited to launch castform into open preview. castform is the easiest way for you to train your own model, on your own data.
open-weights models are performant and much cheaper. when trained on your task & proprietary data, they beat closed models. the thing standing between you and that was weeks of plumbing & years of ml expertise.
with castform, model training is as simple as prompt engineering. @castformai
bring your agent traces or raw corpora. castform turns it into training data, picks the right algorithmic recipes, manages gpus, and gives you an ide to watch and chat with your model as it learns.
see what you can build with castform👇
~/mehul/ retweeted
@joininteract has opened applications for the 2026 class. Interact was and is meaningful for me; if you resonate with the "young technologist" label, you should consider applying.
I'm very excited to share that @joininteract 2026 fellowship applications are now open!
This has been a wonderful community of peers and mentors for me - if you're a young aspiring technologist, I can't recommend it highly enough.
apps close Feb 9th
joininteract.com/
Many implementations of agent memory follow similar approaches, but they're missing pieces to be useful.
After spending the last few months exploring the memory space @spc and talking to people building across the stack, I wrote about common patterns, design decisions, and what still needs to be built 👇
~/mehul/ retweeted
1/ The future of general-purpose robotics will be decided by one major question: which flavor of data scales reasoning? Every major lab represents a different bet.
Over the past 3 months, @adam_patni, @vriishin, and I read the core research papers, spoke with staff at the major labs, and mapped the talent pool. This has completely changed how we think about general-purpose robotics.
Our paper builds intuition, step-by step, across the 2025 frontier: from architectures → evals → data → industry dynamics. Each layer reveals a different bottleneck, but they all converge on one truth—data decides everything.
Our takeaways + process below👇
If you want access to our graph (sound on), comment or DM me
~/mehul/ retweeted
There’s been a lot of work on unlearning in LLMs, trying to erase memorization without hurting capabilities — but we haven’t seen much success.
❓What if unlearning is actually doomed from the start?
👇This thread explains why and how *memorization sinks* offer a new way forward.
