Aravind Srinivas

AI Founder

Sources checked
ABOUT

Co-founder and CEO of Perplexity AI. Former research scientist at OpenAI focusing on language models and contrastive learning, and research intern at DeepMind and Google Brain. Completed Ph.D. in Computer Science at UC Berkeley under Pieter Abbeel, pioneering unsupervised visual representation and sub-quadratic attention systems.

Areas of focus

Professional niches

THE WORK BEHIND THE PROFILE

Proof of Work

researchChecked Sep 20, 2026

Bottleneck Transformers for Visual Recognition (BoTNet)

Co-authored BoTNet, an architecture that replaces the final spatial convolutions in ResNet with Multi-Head Self-Attention, achieving 84.7% Top-1 accuracy on ImageNet while substantially improving instance segmentation and object detection on COCO.

Scope & limitations

Quadratic memory complexity in early spatial layers restricts attention blocks to deeper, downsampled feature maps in the network.

Context: ResNet backbone with Multi-Head Self-Attention bottleneck blocks, TPU v3 accelerators, 2D relative position encodings.

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implementationChecked Sep 20, 2026

Perplexity Sonar and Real-Time Agentic Search Pipeline

Architected Perplexity's conversational search engine and Sonar API, synthesizing real-time multi-source web crawling, dense vector retrieval, dynamic citation parsing, and fine-tuned LLM response generation with strict anti-hallucination attribution.

Scope & limitations

Subject to latency variance across heterogeneous external web APIs; adversarial or SEO-manipulated web sources require continuous algorithmic filtering.

Context: Llama-3-Sonar fine-tuned checkpoints, TensorRT-LLM, sub-second latency SLA, dynamic search grounding over live web indexes.

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