Maurício Maia (@mmaia) profile picture

Software & Data Engineer building: 🌎 https://teapawt.org/t.co/mXsKJ361fq 👩‍💻 https://teapawt.org/t.co/ZpkD4tYqkG

Joined July 2007
Photo by Maurício Maia (@mmaia)Photo by Maurício Maia (@mmaia)Photo by Maurício Maia (@mmaia)Photo by Maurício Maia (@mmaia)Photo by Maurício Maia (@mmaia)Photo by Maurício Maia (@mmaia)Photo by Maurício Maia (@mmaia)Photo by Maurício Maia (@mmaia)Photo by Maurício Maia (@mmaia)Photo by Maurício Maia (@mmaia)
Maurício Maia retweeted
1/ 🤖 You don’t need a specialized vector database. You just need PostgreSQL. Introducing Timescale Vector: PostgreSQL++ for AI Applications - 📈 3x ANN search performance vs Weaviate, 40%-1,500% boost for pgvector. - ⚙️ No need to learn and manage a separate vector database.
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Interesting new position spotted at @sourcegraph: LLM Interaction Engineer aijobnetwork.com/jobs/source… #jobs #remotejobs
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📈 And the number o jobs published keep growing like crazy.
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🗂️ Data from AIJobNetwork.com where I track jobs from selected AI companies. Analysis inspired by the amazing work of @AznWeng
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Excellent analysis of the market for AI talent at big companies.
Companies are hiring like crazy for Generative AI talent. In this 🧵 I’ll dive into: - Companies leading the hiring surge (+1 that stands out) - Technologies/cloud services most mentioned in these jobs - How much $$$ companies are paying for GenAI talent - Common use cases
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At AIJobNetwork.com we currently have 1300+ careers at 100+ AI startups #jobs #aijobs
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Jonathan Katz (@jkatz05): pgvector 0.5.0 Feature Highlights and HOWTOs postgr.es/p/68a
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Maurício Maia retweeted
Here goes: viberary.pizza is a side project I've been working on over the past few months. It gives you book recommendations based on ✨vibes✨. You enter a search query like "funny scifi" and it returns a list of good recommendations (still working on the good part).
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Maurício Maia retweeted
Today, we are taking your AI and LLM apps to the next level🚀 Introducing pg_embedding. A new extension for @Postgres and @langchain for scalable AI apps. Learn how #pg_embedding outperforms #pgvector by 20x in speed with HNSW index 🎉⬇️ bit.ly/46HykGF
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At some point, anyone building production-grade apps will realize this. Understand your data and optimize splitting it.
Replying to @activeloop
(6/14) The first attempt was to naively split the custom knowledge base into equal-length chunks. The idea was to pass relevant excerpts to LLM. Good in theory, but it led to mismatched advice and objections. We needed to maintain semantic boundaries.
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Maurício Maia retweeted
GPT-4 and GPT-3.5 Turbo models in the API now support calling your custom functions, allowing the model to use tools you design for it. Also — reduced pricing & new model versions (including 16k context for 3.5 Turbo): openai.com/blog/function-cal…
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