Lead Developer Advocate
About
Philip Kiely is a software developer and author based out of Chicago. Originally from Clive, Iowa, he graduated from Grinnell College with honors in Computer Science. Philip joined Baseten in January 2022 and works across documentation, technical content, and developer experience. Outside of work, he's a lifelong martial artist, voracious reader, and, unfortunately, a Bears fan.
Integrate Chroma’s open-source vector database with Baseten’s fast inference engine for efficient, real-time embedding inference in your AI-native apps.
Discover the best open-source embedding models for search, RAG, and recommendations—curated picks for performance, speed, and cost-efficiency.
Discover how we optimized embedding, reranker, and classifier inference using TensorRT-LLM, doubling throughput and achieving ultra-low latency at scale.
Running DeepSeek-R1 on H100 GPUs requires multi-node inference to connect the 16 H100s needed to hold the model weights.
The NVIDIA GH200 Superchip combines an NVIDIA Hopper GPU with an ARM CPU via high-bandwidth interconnect
Dedicated deployments of DeepSeek-R1 and DeepSeek-V3 offer private, secure, high-performance inference that's cheaper than OpenAI
Our TensorRT-LLM Engine Builder now supports speculative decoding, which can improve LLM inference speeds.
Speculative decoding improves LLM inference latency by using a smaller model to generate draft tokens that the larger target model can accept during inference.
