SHK

Dense models like Qwen 3.5 27B & Gemma 4 31B on unified memory are a bad idea Simple rule: Lower memory bandwidth works best w/ fewer active parameters per token MoE like Gemma 4 26B-A4B would work much faster on Unified Memory

99% of Ramp uses ai daily. but we noticed most people were stuck — not because the models weren't good enough, but because the setup was too painful and unintuitive for most. terminal configs, mcp servers, everyone figuring it out alone. so we built Glass. every employee gets a fully configured ai workspace on day one — integrations connected via sso, a marketplace of 350+ reusable skills built by colleagues, persistent memory, scheduled automations. when one person on a team figures out a better workflow, everyone on that team gets it and gets more productive. the companies that make every employee effective with ai will compound advantages their competitors can't match. most are waiting for vendors to solve this. we decided to own it.

What’s harder to build Chest or shoulders?

جس کو خود 72 سال کی عمر تک جرنیلوں اور اسٹیبشلمنٹ کا کردار ہی پتہ نہیں تھا۔۔۔ اخے اُس نے ہمیں شعور دیا ہے۔