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Excited to be talking at the AI Engineer World's Fair next week in SF. I'll be sharing the playbook we've developed at Anterior for making your LLM application a domain expert and solving the "last mile" problem of applying LLMs to vertical industries. Let me know if

AI development isn't engineering. It's applied research. Stop asking "Why isn't accuracy improving?" Start asking "How can we run more experiments?" Embrace uncertainty. Focus on learning, not just shipping. jxnl.co/writing/2024/1…

If you're attending AI Engineer on wed, june 4th, check out the recsys track. I'll be hosting talks from Pinterest, LinkedIn, Netflix, Instacart, Youtube. I'll also share 3 ideas that'll likely drive the next few years in recsys: semantic IDs, llm-augmentation, unified models

I'm in SF until Friday for the AI Engineer conference Hit me up if you're around and want to talk about: - scalable evaluation of AI systems - AI product management - systems for incorporating domain expertise

great end to the 2nd day at AI Engineer conference hearing swyx 📍 @aiDotEngineer and Greg Brockman talk about AI engineering! (with special feature from Jensen)

AI development progress is driven by quality of hypotheses x speed of experiments You get better quality hypotheses by better understanding your data (including your outputs - eg clustering and finding trends) Great talk by jeff and jason liu