Ismail Salim @IssySalim
Co-founder/CEO @RunLocalAI (YC S24). Making it easier to ship better on-device AI. Also into house/techno from early 90's/00's, runlocal.ai Joined June 2020-
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Amazing video from @juliarturc 🙌 The best explanation you'll find for legacy, K & I quants in GGUF/llama.cpp: youtube.com/watch?v=vW30o4… Also nice to hear a nod to why we exist: “The challenge is choosing the right quant settings. This depends on your model, target hardware…
I can't wait to try more local models 🤠
🔥 VLMs on mobile devices with world-facing cameras key for proactive, intelligent computing. Local/on-device inference key for real-time, private experiences. Great to see an emphasis on smaller VLMs. Excited to see where @huggingface, @moondreamai, etc. take things 🚀
🔥 VLMs on mobile devices with world-facing cameras key for proactive, intelligent computing. Local/on-device inference key for real-time, private experiences. Great to see an emphasis on smaller VLMs. Excited to see where @huggingface, @moondreamai, etc. take things 🚀
Snap's announcement about their on-device text-to-image model seems to have slipped under the radar… Apparently, it generates 1024x1024 images with quality that's comparable to cloud-oriented models like Stable Diffusion XL. But it can do that locally on an iPhone 16 Pro Max…
Short but sweet talk about the WebNN API: youtube.com/watch?v=FoYBWz… Def worth checking out the YouTube playlist from @jason_mayes WebAI Summit last year. It's packed with great talks! Looking forward to the next summit!
Awesome work from @soldni and team at @allen_ai! If you're interested in shipping on-device AI language features in your app, I highly recommend checking out their demo app to get a sense of what's possible these days on an iPhone: apps.apple.com/us/app/ai2-olm…
Awesome work from @soldni and team at @allen_ai! If you're interested in shipping on-device AI language features in your app, I highly recommend checking out their demo app to get a sense of what's possible these days on an iPhone: apps.apple.com/us/app/ai2-olm…
creativestrategies.com/research/white… Stable Diffusion power consumption between M3 and X Elite: "M3 MacBook Air, 8-core CPU 10-core GPU with 16GB RAM spec, we see averages of 87.63 Joules used per image generated. On the Snapdragon X Elite system, we used a prototype Surface Laptop 15-inch…
“An old Asian man” Stable Diffusion 1.5 with ControlNet. Used 6.94 bit mixed-bit palletization to get the model size down to <1gb. Results are decent (around 1 it/s)
Benchmarked @bria_ai_'s RMBG CoreML model across almost every iPhone with an NPU yday. Latest iPhones 5x quicker for this model than XS/XR (from 2018).
Bitesize Benchmark (iPhone 15 Pro Max) WhisperKit (v0.6) vs Whisper.cpp (v1.6): - Accuracy: Both perfect for this short clip - Speed: WhisperKit at 45 w/s. Whisper.cpp at 30 w/s. (average over 3 runs) - Peak RAM (note: physical footprint only): WhisperKit at 180Mb, Whisper.cpp…
Always benchmark your on-device models! Tried to run whisper-tiny on MacOS, using computeUnits.all in CoreML. Produced worse inference/load times than only using ANE, which is surprising because you'd expect CoreML to pick the optimal config. Why CoreML did this 👇
Just converted @bria_ai_’s awesome background removal model to CoreML for inference on iOS/MacOS. There's a 3x inference speedup when using the NPU (ANE) vs CPU/GPU on an iPhone 15 Pro Max. Shout out to @YairAdato and team for their work (HF repo: briaai/RMBG-1.4).
Thought I'd unnecessarily add to the noise about Intel. This post is about what I've learnt in the past month on the company's rise (and fall?) from its annual reports as well as the opinions of those in the know basecase.substack.com/p/semiconducto… Thanks for this one goes to...
I’ve hopped onto Substack and my first post is on semiconductor foundries… oops it’s pretty crowded on this bandwagon 🤷♂️ basecase.substack.com/p/semiconducto…
#ADC20 is a go! Shouts out to all the lovely reps from @Ableton @WeAreFocusrite @NI_News @Avid @iZotopeInc @sonnoxplugins ... and many more! 🚀
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