Eden AI offers a unified API for accessing large language models and specialist AI models, including OCR, speech, translation and vision. It standardizes requests, responses, authentication, billing and monitoring across providers, and supports routing requests by cost, performance and region.
LifeArchitect.ai hosts a Models Table of large language model data, including parameters, tokens trained, and benchmark scores such as MMLU, MMLU-Pro, GPQA and HLE. The page also presents rankings, a data dictionary and visualization snapshots of frontier models.
LiteLLM is an open-source library that provides a single, unified interface to call over 100 LLMs using the OpenAI format. It includes a Python SDK whose completion() function uses the same arguments across providers and returns responses in the OpenAI Chat Completions format, plus a self-hosted gateway with virtual keys, cost tracking and an admin UI.
An article by Cavin on Deep Markets discussing machine-generated content and creativity. It describes technology as leverage over creation: writing, the printing press, the internet, digital tools and machine learning. It also covers synthetic text from large language models such as OpenAI's GPT-3, published in summer 2020.
Text Mining with R: A Tidy Approach is a website for a guide to text analysis within the tidy data framework, using the tidytext package and other tidy tools. It is written by Julia Silge and David Robinson and licensed under Creative Commons Attribution-NonCommercial-ShareAlike 3.0 United States License.
Vellum is a personal AI assistant available locally or in the cloud, with long-term memory across conversations. It can send emails, manage calendars, browse the web, create slides, write code, run research, and execute recurring background tasks. It offers fine-grained permissions requiring approval for high-stakes actions until marked trusted. Two plans exist: Base (free) and Pro packages Mighty, Super, and Ultra.
Feast is an end-to-end open source feature store for machine learning. It allows teams to define, manage, discover, and serve features, delivering structured data to AI and LLM applications during training and inference. Documented use cases include real-time recommendations, fraud detection, risk scoring, and customer segmentation.
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LifeArchitect.ai hosts a Models Table of large language model data, including parameters, tokens trained, and benchmark scores such as MMLU, MMLU-Pro, GPQA and HLE. The page also presents rankings, a data dictionary and visualization snapshots of frontier models.
LiteLLM is an open-source library that provides a single, unified interface to call over 100 LLMs using the OpenAI format. It includes a Python SDK whose completion() function uses the same arguments across providers and returns responses in the OpenAI Chat Completions format, plus a self-hosted gateway with virtual keys, cost tracking and an admin UI.
An article by Cavin on Deep Markets discussing machine-generated content and creativity. It describes technology as leverage over creation: writing, the printing press, the internet, digital tools and machine learning. It also covers synthetic text from large language models such as OpenAI's GPT-3, published in summer 2020.
Text Mining with R: A Tidy Approach is a website for a guide to text analysis within the tidy data framework, using the tidytext package and other tidy tools. It is written by Julia Silge and David Robinson and licensed under Creative Commons Attribution-NonCommercial-ShareAlike 3.0 United States License.
Vellum is a personal AI assistant available locally or in the cloud, with long-term memory across conversations. It can send emails, manage calendars, browse the web, create slides, write code, run research, and execute recurring background tasks. It offers fine-grained permissions requiring approval for high-stakes actions until marked trusted. Two plans exist: Base (free) and Pro packages Mighty, Super, and Ultra.
Feast is an end-to-end open source feature store for machine learning. It allows teams to define, manage, discover, and serve features, delivering structured data to AI and LLM applications during training and inference. Documented use cases include real-time recommendations, fraud detection, risk scoring, and customer segmentation.
