Vector Embeddings Explained
Get an intuitive understanding of what exactly vector embeddings are, how they’re generated, and how they’re used in semantic search.
concepts
data-science, deep-learning, Machine Learning
Training an XGBoost Classifier Using Cloud GPUs Without Worrying About Infrastructure
Imagine you want to quickly train a few machine learning or deep learning models on the cloud but don’t want to deal with cloud infrastructure. This short…
Safety & Alignment
Forecasting potential misuses of language models for disinformation campaigns and how to reduce risk
OpenAI researchers collaborated with Georgetown University’s Center for Security and Emerging Technology and the Stanford Internet Observatory to investigate how large language models might be misused for disinformation purposes. The collaboration incl…
Uncategorised
Large Transformer Model Inference Optimization
[Updated on 2023-01-24: add a small section on Distillation.]
Large transformer models are mainstream nowadays, creating SoTA results for a variety of tasks. They are powerful but very expensive to train and use. The extremely high inference cost, in b…
concepts, integrations
Pulling back the curtains on text2vec
Ever wonder how Weaviate turns objects into vectors, behind-the-scenes? Find out in this post!
data-science, deep-learning, Machine Learning
Open Source Highlights 2022 for Machine Learning & AI
Recently, I shared the top 10 papers that I read in 2022. As a follow-up, I am compiling a list of my favorite 10 open-source releases that I discovered…
Uncategorised
How the AI Bill of Rights Impacts You
The AI Bill of Rights is a landmark document for the fair and ethical use of AI. ML teams must understand its impact and principles.
Story
Delivering nuanced insights from customer feedback
Using GPT-3 to deliver fast, nuanced insights from customer feedback.