ilker

i made myself a lifeos in 45 minutes which is connected to my whoop band. it's powered by @fal (great way to spend credits is to use openrouter endpoint on fal) i also used @hasaneyldrm 's repo for library of excersizes. what this can do: - pulls recovery, sleep, strain & hrv from whoop - log meals by photo, text or voice (wizper) — describe a meal in natural language and it figures out the kcal + macros, web search included - generates training programs from goal + days + equipment, with 1324 exercise gifs hosted locally - inline edit programs: swap moves, change sets/reps in place - tdee from real whoop kilojoules, not a guess currently only whoop band but can be extended to other fitness trackers as well should i opensource it? would you use it? yet, would you contribute it?

made the sports fan cam trend into @fal workflow. just add your photos and type something like “lakers vs celtics finals game 7” or “wimbledon final center court”

fal Meetup is back in Istanbul! ​It is going to be an evening of learning, creating, and chatting about generative media. As always, drinks and @fal credits are on us. If you are a founder, developer, creative professional, or just genuinely curious about generative media, join us at this special event! (All the fal Türkiye team is going to be there) I know it is hard to keep up with this industry when there is a new model every week, sometimes even every day. That’s why @gokayfem will inform us about the latest news and developments in the generative media space, and @ailker will share tricks to get the best out of fal Workflows so that you can make the most of these models. It's gonna be a great evening at @QNBEYOND! Apply through the link in the replies

Announcing World Model Accelerator, fal's new product: fal.ai/wma We've spent years building the inference layer for generative media. In 2023, we shipped 30 FPS, low-latency, action-controlled diffusion APIs, years before anyone else. Fast forward to today and we've been powering foundational model companies across image, video, real-time speech-to-speech and action-controlled world models. Now we're opening it up. World Model Accelerator is the system behind it all. Our in-house inference engine hits SOTA performance on Hopper and Blackwell for Diffusion Transformer workloads, both causal and bi-directional. Built on fal Serverless, it scales seamlessly from 1 GPU to 1,000+. This is the same platform that's been running real workloads, at scale, for years. A new WebRTC gateway optimizes latency between users and GPUs (routing requests to the closest region), built on the same infra that powers our real-time speech workloads. And direct access to the fal Marketplace puts your model in front of enterprises spending hundreds of millions on generative media, with a real co-selling motion behind it. This is the infrastructure layer for world models.