Twitter

The Adversarial Path to the Personal Assistant: Sumit Agarwal

Feb 15, 2025 · 18:46

Sumit Agarwal, founder of Ario AI, discusses building a personal AI assistant that uses adversarial ETL to extract users' data from services like Google, Amazon, and Doordash, enabling immediate personalization without manual input. He announces $16M in funding and demonstrates how the assistant generates data portraits, recommends travel and routines based on personal history, and manages schedules by detecting conflicts. Agarwal shares RAG insights: avoid LLMs for trivial math, use search and pre-processed profiles, and present the right data at the right time. Ario Boost, a browser extension, lets users download their data locally in developer mode without creating an account.

Moondream: how does a tiny vision model slap so hard? — Vikhyat Korrapati

Nov 14, 2024 · 19:26

Vikhyat Korrapati built Moondream, a tiny open-source vision language model under 2 billion parameters that matches LLaVA 1.5, a model four times its size, on VQA v2 and GQA benchmarks. He attributes this to focusing on image understanding over world knowledge and investing heavily in synthetic training data—a pipeline that generated 35 million images and used two orders of magnitude more compute on data than training. Key lessons: community engagement was critical, open-source builds trust, and safety guardrails should be application-layer, not baked in. He argues tiny models will dominate production due to cost and privacy advantages, and that prompting will replace custom model training for most vision tasks. Moondream raised a seed round from FullySysAscent and the GitHub Fund.