PostgresML vs OpenAI Academy：怎么选？

关于 PostgresML

Hear from our communityThis is why I’m bullish on@postgresml- devs will always prefer to do things in data stores they already use in productionJames yu@jamesyuGreat article by PostgresML, running@huggingfacemodels INSIDE@PostgreSQLnice tidbit on scalability: "Our example data is based on 5 million DVD reviews from Amazon ... that's more data than fits in a Pinecone Pod at the time of writing"Paul Copplestone@kiwicoppleLove the fact that@postgresmlcan run various algorithms to find the optimum one for model creationRebataurAI@rebataurYou can look at PostgresML. Its based on Postgres, not specifically a vector database but they've got a pleasantly full featured eco-system for the whole training process, fetching datasets, huggingface integration, training etc. of course they also have vector related functionsDushyant (e/acc)@DevDminGodIf you want to seamlessly integrate machine learning models into your#PostgreSQLdatabase, use PostgresML.Khuyen Tran@KhuyenTran16? there's also PostgresML if you wanna get a little more full featured - supports embedding in-database as well as CUBE / pgvectorMartin McFly@martinmarkTons of capability in that Postgres extension. It's an important part of the ML Stack atcloud.tembo.ioas well.Adam Hendel@adamhendelA game-changer indeed! By integrating ML and AI directly at the database level with@postgresml, we're not just streamlining processes but revolutionizing data handling and insights generation in one fell swoop.Pranay Suyash@pranaysuyashThis is why I’m bullish on@postgresml- devs will always prefer to do things in data stores they already use in productionJames yu@jamesyuGreat article by PostgresML, running@huggingfacemodels INSIDE@PostgreSQLnice tidbit on scalability: "Our example data is based on 5 million DVD reviews from Amazon ... that's more data than fits in a Pinecone Pod at the time of writing"Paul Copplestone@kiwicoppleLove the fact that@postgresmlcan run various algorithms to find the optimum one for model creationRebataurAI@rebataurYou can look at PostgresML. Its based on Postgres, not specifically a vector database but they've got a pleasantly full featured eco-system for the whole training process, fetching datasets, huggingface integration, training etc. of course they also have vector related functionsDushyant (e/acc)@DevDminGodIf you want to seamlessly integrate machine learning models into your#PostgreSQLdatabase, use PostgresML.Khuyen Tran@KhuyenTran16? there's also PostgresML if you wanna get a little more full featured - supports embedding in-database as well as CUBE / pgvectorMartin McFly@martinmarkTons of capability in that Postgres extension. It's an important part of the ML Stack atcloud.tembo.ioas well.Adam Hendel@adamhendelA game-changer indeed! By integrating ML and AI directly at the database level with@postgresml, we're not just streamlining processes but revolutionizing data handling and insights generation in one fell swoop.Pranay Suyash@pranaysuyash

What makes PostgresMLso powerfulIndex, filter and re-rank vector embeddings10x faster vector operationsPerform fast KNN and ANN searchIndex embeddings with HNSW or IVFFlatLearn Morearrow_forwardGenerate embeddingsChoose from state-of-the-art modelsBuilt-in data preprocessors for splitting and chunkingConvert text to vector embeddingsLearn Morearrow_forwardColocate data and computeEmbed, serve and store all in one processTerabytes of data on a single machineBuilt-in data privacy & securityTrain, tune and deployRegression, classification and clusteringFine-tune LLMs on your own dataMonitor model deployments over timeLearn Morearrow_forwardGet the most of LLMsUse open-source models (Mistral, LLama, etc.)Perform a range of NLP tasksServe with the same infrastructureLearn Morearrow_forwardComprehensive platformMultiple deployment optionsPerform several AI & machine learning tasksUse SQL or SDKs in JS and PythonIndex, filter and re-rank vector embeddings10x faster vector operationsPerform fast KNN and ANN searchIndex embeddings with HNSW or IVFFlatLearn Morearrow_forwardGenerate embeddingsChoose from state-of-the-art modelsBuilt-in data preprocessors for splitting and chunkingConvert text to vector embeddingsLearn Morearrow_forwardColocate data and computeEmbed, serve and store all in one processTerabytes of data on a single machineBuilt-in data privacy & securityTrain, tune and deployRegression, classification and clusteringFine-tune LLMs on your own dataMonitor model deployments over timeLearn Morearrow_forwardGet the most of LLMsUse open-source models (Mistral, LLama, etc.)Perform a range of NLP tasksServe with the same infrastructureLearn Morearrow_forwardComprehensive platformMultiple deployment optionsPerform several AI & machine learning tasksUse SQL or SDKs in JS and Python

This is why I’m bullish on@postgresml- devs will always prefer to do things in data stores they already use in productionJames yu@jamesyuGreat article by PostgresML, running@huggingfacemodels INSIDE@PostgreSQLnice tidbit on scalability: "Our example data is based on 5 million DVD reviews from Amazon ... that's more data than fits in a Pinecone Pod at the time of writing"Paul Copplestone@kiwicoppleLove the fact that@postgresmlcan run various algorithms to find the optimum one for model creationRebataurAI@rebataurYou can look at PostgresML. Its based on Postgres, not specifically a vector database but they've got a pleasantly full featured eco-system for the whole training process, fetching datasets, huggingface integration, training etc. of course they also have vector related functionsDushyant (e/acc)@DevDminGodIf you want to seamlessly integrate machine learning models into your#PostgreSQLdatabase, use PostgresML.Khuyen Tran@KhuyenTran16? there's also PostgresML if you wanna get a little more full featured - supports embedding in-database as well as CUBE / pgvectorMartin McFly@martinmarkTons of capability in that Postgres extension. It's an important part of the ML Stack atcloud.tembo.ioas well.Adam Hendel@adamhendelA game-changer indeed! By integrating ML and AI directly at the database level with@postgresml, we're not just streamlining processes but revolutionizing data handling and insights generation in one fell swoop.Pranay Suyash@pranaysuyash

核心功能

• filter_dramaPostgresML Cloud（自动优化版）
• vpn_keyVPC（自动优化版）
• descriptionLLMs（自动优化版）
• subtitlesEmbeddings（自动优化版）
• open_withVector Database（自动优化版）
• model_trainingSupervised Learning（自动优化版）
• manage_searchRAG（自动优化版）
• feature_searchSearch（自动优化版）

关于 OpenAI Academy

OpenAI Academy是OpenAI推出的免费AI学习平台，提供免费的AI课程帮助普通人掌握AI技能。OpenAI Academy提供丰富多样的课程，包括《ChatGPT Edu学术助手指南》《提示词大师课》等，内容短小精悍，适合碎片化学习。平台设有每周多场线上活动，如《老年人AI入门》等，方便用户与专家实时互动。OpenAI Academy的让AI真正落地应用，提升工作效率、解决公益难题，致力于让AI造福全人类。目前平台仅支持英文。

AI工具集导航关于我们免责声明最新AI项目AI应用商店果核剥壳CakeGrowthVipCheap攻壳智能体映技派豆包讯飞绘文绘蛙即梦蛙蛙写作白日梦咔片PPT办公小浣熊TRAE码上飞堆友AILiblibAI星流AI秒哒DuMateAstronClawLibTV

核心功能

• 免费AI课程：提供海量的视频课程，如《ChatGPT Edu学术助手指南》《提示词大师课》等。
• 直播互动：每周举办多场线上活动，邀请专家讲解和互动，如《老年人AI入门》等课程。
• 社群交流：用户在社群中随时提问，与其他学员和专家交流。