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This SQL query looks like it should fail immediately. Instead, it runs and quietly returns the wrong result. Why doesn’t the database complain?

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11,376 Aufrufe • vor 3 Monaten •via X (Twitter)

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This is a tool that used GPT that lets you connect to PostgresDB or MongoDB, lets users type in questions, and it generates the query code (even advanced table joins), runs the code and returns the answer instantly. Like a query co-pilot. Here are my thoughts 👇🏻
0:23

This is a tool that used GPT that lets you connect to PostgresDB or MongoDB, lets users type in questions, and it generates the query code (even advanced table joins), runs the code and returns the answer instantly. Like a query co-pilot. Here are my thoughts 👇🏻

Duy

68,792 Aufrufe • vor 3 Jahren

🤯🤯 That's insane! Hugging Face just shipped Data Studio on dataset pages... Ask a question about any dataset, the agent writes and runs a SQL query... then share the result or download as CSV... check it out! 👀 ⤵️ Wow GG Caleb 👏
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🤯🤯 That's insane! Hugging Face just shipped Data Studio on dataset pages... Ask a question about any dataset, the agent writes and runs a SQL query... then share the result or download as CSV... check it out! 👀 ⤵️ Wow GG Caleb 👏

Jeff Boudier 🤗

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using tools, Cursor Agent have the capability to reason about when it should - read & write code - search your codebase - call MCP servers - run terminal commands an example where it connects to a postgres database, runs a query and writes to file
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using tools, Cursor Agent have the capability to reason about when it should - read & write code - search your codebase - call MCP servers - run terminal commands an example where it connects to a postgres database, runs a query and writes to file

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It looks like she should take a shower immediately after doing this.
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It looks like she should take a shower immediately after doing this.

Ayu D. Palupi

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If this is wrong, why doesn’t it feel wrong?
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If this is wrong, why doesn’t it feel wrong?

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Looks like it runs in the family 😎
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Looks like it runs in the family 😎

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If Kyle was mad about the lesbian comment, she should have said something at the moment instead of laughing it off. This is why she comes across as so fake and a victim. Why complain about it at the reunion when she could have called Garcelle out? #RHOBH
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If Kyle was mad about the lesbian comment, she should have said something at the moment instead of laughing it off. This is why she comes across as so fake and a victim. Why complain about it at the reunion when she could have called Garcelle out? #RHOBH

Reality Roast

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You can now access AI directly from your database! Here is a step-by-step demo that uses GPT-4 to classify customer reviews from a MySQL dataset. And I'm only writing SQL instructions! You have to see it! The model acts as another table in the database. I can query it and join it with other tables. It's awesome! This is all thanks to mindshub. Here is their GitHub repository: They are sponsoring this post. Watch the video.
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You can now access AI directly from your database! Here is a step-by-step demo that uses GPT-4 to classify customer reviews from a MySQL dataset. And I'm only writing SQL instructions! You have to see it! The model acts as another table in the database. I can query it and join it with other tables. It's awesome! This is all thanks to mindshub. Here is their GitHub repository: They are sponsoring this post. Watch the video.

Santiago

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At first, it looks like Jinyoung is crying, but then it turns out that he changed into the wrong pants and wants to change back. Why is this man so funny?
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At first, it looks like Jinyoung is crying, but then it turns out that he changed into the wrong pants and wants to change back. Why is this man so funny?

Lavina

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English Is The New SQL LLMs have made it easy for everyone to create on-the-fly dashboards and plots. You can connect to your database and then use a SOTA LLM like 4o, Opus, or Gemini to generate SQL and Python code to create on-the-fly dashboards and plots. ChatLLM makes it possible across all state-of-the-art LLMs -
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English Is The New SQL LLMs have made it easy for everyone to create on-the-fly dashboards and plots. You can connect to your database and then use a SOTA LLM like 4o, Opus, or Gemini to generate SQL and Python code to create on-the-fly dashboards and plots. ChatLLM makes it possible across all state-of-the-art LLMs -

Bindu Reddy

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The Global American Cultural Victory doesn’t look like people wearing blue jeans and listening to rock and roll. It looks like this:
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The Global American Cultural Victory doesn’t look like people wearing blue jeans and listening to rock and roll. It looks like this:

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During one of my runs, this song started playing in my YouTube mix—I fell in love with it, and the result was this dance. I hope you like it.
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During one of my runs, this song started playing in my YouTube mix—I fell in love with it, and the result was this dance. I hope you like it.

ArianaRealTV

11,175 Aufrufe • vor 2 Monaten

PEOPLE OF THE EARTH. Figured out how to ask natural language questions of current financial data and get back a natural language response...with correct/relevant numbers! 🤯💰✨ So. Freaking. Cool. 1. Send database schema along with the question and relevant scope/parameters to GPT. 2. GPT returns SQL query. 3. Run SQL query on your data. 4. Take returned data and pass it in along with the original question. 5. GPT returns natural language answer with relevant data! Original Question: What was the highest price of Apple's stock over the past decade and how does it compare to Tesla's highest stock price? And on what date were those highest prices? Final Answer: The highest price of Apple's stock over the past decade was $182.94 on January 4, 2022, while Tesla's highest stock price was $414.50 on November 4, 2021.
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PEOPLE OF THE EARTH. Figured out how to ask natural language questions of current financial data and get back a natural language response...with correct/relevant numbers! 🤯💰✨ So. Freaking. Cool. 1. Send database schema along with the question and relevant scope/parameters to GPT. 2. GPT returns SQL query. 3. Run SQL query on your data. 4. Take returned data and pass it in along with the original question. 5. GPT returns natural language answer with relevant data! Original Question: What was the highest price of Apple's stock over the past decade and how does it compare to Tesla's highest stock price? And on what date were those highest prices? Final Answer: The highest price of Apple's stock over the past decade was $182.94 on January 4, 2022, while Tesla's highest stock price was $414.50 on November 4, 2021.

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Leave the range immediately if it’s absolutely filthy and it looks like a torture dungeon.
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Leave the range immediately if it’s absolutely filthy and it looks like a torture dungeon.

Weapons Daily

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"nooo you cant map government spending in a SQL database and allow everyone to use it, you dont have a degree" The beaver builds the dam regardless
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"nooo you cant map government spending in a SQL database and allow everyone to use it, you dont have a degree" The beaver builds the dam regardless

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it looks fun and it doesn’t at the same time
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it looks fun and it doesn’t at the same time

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Student runs a “race-based pricing” bake sale to spark convo on affirmative action. Different prices depending on race (higher for some groups, discounts for others). People immediately call it racist and wrong. So here’s the real question: If it’s wrong at a bake sale… why is it acceptable in college admissions or hiring? School shut it down instead of debating. Thoughts? #AffirmativeAction

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Your agents can't keep up with real-time data. Especially when it's scattered across dozens of sources. Most teams waste weeks building custom connectors for every database, API, and data warehouse. Then they build ETL pipelines to sync everything. By the time your agent retrieves the data, it's already outdated. Picture this: Your Postgres database updated 5 minutes ago. Your MongoDB collection changed 2 minutes ago. Your agent is still pulling from yesterday's snapshot. This is why most production RAG systems fail. There's a better approach: MindsDB is an open-source AI platform with a federated data engine that lets you query multiple data sources in real-time using SQL - without moving any data. Here's what makes it different: ↳ Your data stays in place. No ETL pipelines or data duplication ↳ Query Postgres, MongoDB, REST APIs, and more using consistent SQL ↳ JOIN across different sources in real-time with a unified interface ↳ Works with both structured and un-structured data And here's the best part: You don't even need to write SQL. Just describe what you want in plain English, and MindsDB converts it to SQL automatically. The system does all the heavy lifting. The breakthrough for AI agents is simple: When data updates at the source, your agent gets fresh results immediately. No sync delays. No stale embeddings. No custom code for each integration. You can literally write a SQL query that joins a Postgres table with a MongoDB collection and gets live results. This is what production AI applications need but rarely get. In this video, I give you a complete walkthrough of what we just discussed and how to actually do it. Make sure you watch this till the end. I've shared the link to MindsDB's GitHub repo in the next tweet!
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Your agents can't keep up with real-time data. Especially when it's scattered across dozens of sources. Most teams waste weeks building custom connectors for every database, API, and data warehouse. Then they build ETL pipelines to sync everything. By the time your agent retrieves the data, it's already outdated. Picture this: Your Postgres database updated 5 minutes ago. Your MongoDB collection changed 2 minutes ago. Your agent is still pulling from yesterday's snapshot. This is why most production RAG systems fail. There's a better approach: MindsDB is an open-source AI platform with a federated data engine that lets you query multiple data sources in real-time using SQL - without moving any data. Here's what makes it different: ↳ Your data stays in place. No ETL pipelines or data duplication ↳ Query Postgres, MongoDB, REST APIs, and more using consistent SQL ↳ JOIN across different sources in real-time with a unified interface ↳ Works with both structured and un-structured data And here's the best part: You don't even need to write SQL. Just describe what you want in plain English, and MindsDB converts it to SQL automatically. The system does all the heavy lifting. The breakthrough for AI agents is simple: When data updates at the source, your agent gets fresh results immediately. No sync delays. No stale embeddings. No custom code for each integration. You can literally write a SQL query that joins a Postgres table with a MongoDB collection and gets live results. This is what production AI applications need but rarely get. In this video, I give you a complete walkthrough of what we just discussed and how to actually do it. Make sure you watch this till the end. I've shared the link to MindsDB's GitHub repo in the next tweet!

Akshay 🚀

65,672 Aufrufe • vor 6 Monaten

Frankly, it doesn’t look like magic, it looks like shit. Like someone stuck trees in a warehouse and left for the day before finishing.
0:51

Frankly, it doesn’t look like magic, it looks like shit. Like someone stuck trees in a warehouse and left for the day before finishing.

Dr. Jebra Faushay

363,183 Aufrufe • vor 6 Monaten