We asked @davidpstout (Co-Founder & CEO, webAI) about the advantages of running AI on devices.
"There's no free lunch, but there are things cloud players can't do. It's RAM intensive, yes, but by distributing across devices, we can unlock more accuracy and context. But if you're…
On the latest TinyLlama 1.1B benchmarks (MacBook Pro M4):
Unquantized: ~8× faster than llama.cpp
8-bit & 4-bit quantized: still leading — and getting faster month over month
From July → August, every variant of webframe-cpp improved its speed.
GPT-5 isn’t what we expected.
On public benchmarks, 25–35% of failures weren’t random — they came from ambiguous, context-heavy tasks that monolithic models just can’t nail.
This vision of “one giant brain for everything” is ending.
The future? Networks of highly contextual…
Privacy by policy fails. Current AI lawsuits exposes it: user chats, even deleted ones, ordered for discovery despite “privacy” claims.
Only privacy by design—data staying on your device protects you.
Wow this is such a brilliant idea for running AI models locally. 🎯
webFrame is @thewebAI 's backend that slices a huge language model into smaller shards, sends each shard to a different computer on your own network, then stitches the answers back together on the fly.
Because…
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