Hugging Face was founded in 2016 and has grown to become one of the most prominent ML platforms. It’s commonly used to develop and disseminate state-of-the-art ML models and is a central hub for researchers and developers. Sayak Paul is a Machine Learning Engineer at Hugging Face and a Google Developer Expert. He joins the

Hugging Face with Sayak Paul

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Vercel provides a cloud platform to rapidly deploy web projects, and they develop the highly successful Next.js framework. The company recently made headlines when they announced v0 which is a generative AI tool to create React code from text prompts. The generated code uses open-source tools like Tailwind CSS and shadcn/ui. Lee Robinson is the

Vercel AI with Lee Robinson

Algolia is a platform that provides search as a service. The company was founded in 2012, was part of Y Combinator’s Winter 2014 class, and has become highly popular for integrating modern search functionality into web-facing services. Sean Mullaney is the CTO of Algolia and has worked at Google X, Stripe, and Zolando. He joins

Algolia with Sean Mullaney

Jodie Burchell is the Data Science Developer Advocate at JetBrains, which makes integrated development environments or, IDEs, for many major languages. After observing the rapid growth of the AI coding assistant landscape, the company recently announced integration of an AI assistant into their IDEs. Jodie joins the show today to talk about why the company

JetBrains AI with Jodie Burchell

This episode of Software Engineering Daily is part of our on-site coverage of AWS re:Invent 2023, which took place from November 27th through December 1st in Las Vegas. In today’s interview, host Jordi Mon Companys speaks with Ankur Mehrotra who is the Director and GM of Amazon SageMaker. Jordi Mon Companys is a product manager

AWS re:Invent Special: Sagemaker with Ankur Mehrotra

An embedding is a concept in machine learning that refers to a particular representation of text, images, audio, or other information. Embeddings are designed to make data consumable by ML models. However, storing embeddings presents a challenge to traditional databases. Vector databases are designed to solve this problem. Pinecone has developed one of the most

Hugging Face with Sayak Paul

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