“Peter is extremely sharp and great programmer. He has a huge amount of pride in his work, and will always pitch in and make sure a project he's involved in is a success. Peter is also super enthusiastic, and just a fun guy to work with, easily one of the very top people I've ever worked with.”
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It was a great honor to keynote at PyData Paris to talk about building with Mistral AI! Love and appreciate my PyData community and thankful for the…
It was a great honor to keynote at PyData Paris to talk about building with Mistral AI! Love and appreciate my PyData community and thankful for the…
Liked by Peter Wang
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Heading to PyCon Japan, where I’ll be keynoting on the first day, and (if they let me) presenting a lightning talk on `bwrap`! 2024.pycon.jp cc…
Heading to PyCon Japan, where I’ll be keynoting on the first day, and (if they let me) presenting a lightning talk on `bwrap`! 2024.pycon.jp cc…
Liked by Peter Wang
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I am pleased to announce I am doing a keynote address on applying AI to cybersecurity at the 3CS (Cybersecurity Capabilities and Careers Symposia) on…
I am pleased to announce I am doing a keynote address on applying AI to cybersecurity at the 3CS (Cybersecurity Capabilities and Careers Symposia) on…
Liked by Peter Wang
Projects
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BokehJS
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BokehJS is a library for interactive visualizations targeting the browser.
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SciPy2013 Conference
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A scientific computing conference consisting of two days of tutorials followed by two days of presentations, and concludes with two days of developer sprints on projects of interest to the attendees.
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Languages
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Chinese
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Qdrant
Using Qdrant with Apache Airflow can revolutionize how you automate and manage complex workflows for semantic querying. It makes handling large-scale vector data much simpler, and Airflow's monitoring features ensure everything runs smoothly. In this tutorial, you'll learn to use the Qdrant Airflow provider to write a DAG that generates embeddings in parallel and performs semantic retrieval based on user input. Explore the guide here: https://lnkd.in/eMpqD2tN P.S. How are you using Airflow in your data workflows? Comment below! 🚀
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Baobab Tech
In this Technical Deep Dive, we share our approaches in using Large Language Models (#LLMs) to make numerical-type data(sets) like DHS, JMP, HDX more accessible with the example of WASH data. In this 15 min. video Olivier Mills and team cover: 1️⃣ Basic scripting to extract core data from datasets from API endpoints 2️⃣ How to use LLMs to generate LLM-friendly schema definitions 3️⃣ How to structure a AI-friendly database store that can scale to thousands of datasets and millions of data indicators 4️⃣ How to use vector querying to retrieve relevant indicators from the store based off of a natural language (english) query 5️⃣ How to build a prompt that generates valid SQL query using LLMs with the above retrieved data schema. The various components form a single AI system combining data ingestion and data exploration using a software layer, a data layer and multiple LLM layers. ⏭️ Next steps will be to expand the datasets, automate other data source ingestion and further test the system with more complex plain english queries. We plan to incorporate this as a new feature for WASH AI after testing. Feel free to reach out if you would like a copy of the Notebooks, sample prompts and data schema definitions. We are #opensource The initial work was done in collaboration with Data for Good YYC (see https://lnkd.in/g3AijS93)
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Twelve Labs
~ New Webinar ~ The recording of #MultimodalWeekly 57 is up! Watch here: https://lnkd.in/gwfVPq8P 📺 They discussed: 1️⃣ Automatic Data Construction for Composed Video Retrieval (Lucas Ventura) 2️⃣ The Rapid Decline of the AI Data Commons + Multimodal Implications (Shayne Longpre) 3️⃣ Prompting LLMs to Transform Video Annotations at Scale (Nina Shvetsova Anna Kukleva) Enjoy!
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Quansight
🚀 Want to employ the power of #PyTorch for your scientific models without a steep learning curve? 👀 Check out our latest blog, where Travis Oliphant discusses how PyTorch's integration with the Array API makes it easy to use with familiar libraries like NumPy and scikit-learn.🔥 https://lnkd.in/dDRkEY3v #Innovation
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