August 19, 2023 - Hey folks, I’m thrilled to share the remarkable progress we’ve made with the OpenAI API as a client for our app School Hack. In just 5 months, we’ve seen an incredible surge in usage, with a staggering 1 million queries per day. Our ability ...

March 31, 2025 - Regular readers of the Cloud Database Report shouldn’t be surprised that OpenAI is shopping for storage. We’ve seen this coming. “I’m curious about how much new data will be generated by AI systems and applications, and I believe it’s going to be a big multiple,” I wrote last August.

March 25, 2024 - Training a large language model like the one that fuels OpenAI’s ChatGPT takes a lot of data. It took approximately 570 gigabytes of text data–about 300 billion words—to train ChatGPT.

November 28, 2023 - Identity is long past the days of logging into systems. Security teams must now manage SaaS apps, AI agents and machine-to-machine interactions across distributed environments. By Dave Shackleford ... Data integration in big data systems is even more complex now because of AI.

September 8, 2023 - I’m having difficulty finding the size of the data used to train GPT-3. Searches return wildly divergent answers, anywhere from 570GB to 45TB. Language Models are Few-shot Learners would seem to be the definitive source.

March 4, 2026 - OpenAI’s internal AI data agent searches 600 petabytes across 70,000 datasets, saving hours per query and offering a blueprint for enterprise AI agents.

April 20, 2023 - In AI development, the dominant paradigm is that the more training data, the better. OpenAI’s GPT-2 model had a data set consisting of 40 gigabytes of text. GPT-3, which ChatGPT is based on, was trained on 570 GB of data.

In this post, we’ll break down ... than 3.5k internal users working across Engineering, Product, and Research, spanning over 600 petabytes of data across 70k datasets....

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August 23, 2024 - I’m curious about how much new data will be generated by AI systems and applications, and I believe it’s going to be a big multiple. Maybe 10, 100, or even 1,000 times more data within the next few years.

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March 17, 2025 - Discover the challenges and benefits of big data in AI, downsampling, and smart sampling techniques to reduce data size without losing accuracy.

June 7, 2023 - I’m trying to build a chatbot that interacts with my own data by translating natural language questions into SQL queries and then querying the database to get the final answer. I’m using langchain to get the work done. Does the size (volume) of the database and the OpenAI API costs have ...

May 7, 2024 - Unlike larger companies in the AI field, we do not have a large corpus of data collected over decades. We primarily rely on publicly available information to teach our models how to be helpful.

1 week ago - Including a live demo of GitLab ... just your repo. Virtual, free, and just days away. ... OpenAI’s data platform stores 1.5 exabytes across 90,000 datasets and serves ~4,000 internal users as of May 2026....

October 16, 2025 - Each AI model has unique data requirements, and factors like the model’s complexity, error margins, and more impact the amount of data an AI model may need.

April 6, 2023 - They may share aggregated information like general user statistics with third parties, publish such aggregated information or make such aggregated information generally available. ... “As between the parties and to the extent permitted by applicable law, you own all Input” that you provide to the services, such as what you type in as the prompt and its context. With regards to the output that is generated by the service, OpenAI assigns you all its rights, which means that you can use it for any purpose including commercial purposes.

February 6, 2022 - Worried you don't have enough data to train your machine learning models? Well, there are ways around it. This article explains how much data is needed for different AI applications and highlights tips on how to develop data strategy for your business and how to benefit from data augmentation ...

May 30, 2024 - The type of machine learning problem: Supervised learning models need labeled training data. Supervised learning models need more data than unsupervised models. Unsupervised models do not use labels. Image recognition or natural language processing (NLP) projects will need larger AI training data sets.

2 weeks ago - AI can streamline operations by optimizing resource use, automating repetitive tasks, and predicting issues before they occur. This not only reduces downtime and costs but also ensures smoother, more efficient processes. Who wouldn’t want their operations to run like a well-oiled machine?