If you want to use GLM 5.2 with the full 1M context on BYOK in Cursor, you need to enable Max mode *before* the first message is sent. Thanks @OnurGvnc
! @Zai_org
LLMS
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Enable Max mode before first message for GLM 5.2 1M context Cursor
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Create mobile apps instantly with one prompt, collect payments
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๐จ PROMPT TO MOBILE APP INSTANTLY – COLLECT PAYMENTS
— Abacus.AI (@abacusai) 18 juin 2026
Use top models like Claude Fable, Opus 4.8. GPT 5.5 and Gemini 3.5 to create iOS and Android apps
DEPLOY WITH ONE CLICK
With one prompt create an entire app
– comes with user auth & backend
– agent swarm can create bothโฆ pic.twitter.com/mYs3Y57GIePROMPT TO MOBILE APP INSTANTLY – COLLECT PAYMENTS
Use the best models like Claude Fable, Opus 4.8, GPT 5.5 and Gemini 3.5 to create iOS and Android apps
DEPLOY WITH A SINGLE CLICK
With a single prompt, create an app -
Clarification: unofficial MCP servers, but third-party plugins
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They were not official MCP servers. They were third-party plugins.
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AuroraGPT: generalizable foundation-scale LLM for scientific discovery
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AuroraGPT – Built by Scars of Frontline The theory is nothing. AuroraGPT advances scientific discovery by building generalizable, foundation-scale large-language models across multiple scientific domains, including physics, chemistry, mathematics, and material sciences. In a
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AI-Powered File Reader Using RAG and LLM
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RAG with LLM: Creating an AI-Powered File Reader! #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #IoT #IIoT #PyTorch #Python #RStats #TensorFlow #Java #JavaScript #ReactJS #GoLang #CloudComputing #Serverless #DataScientist #Linux #Programming #Coding
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Kimi, GLM, MiniMax recent releases are good
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Kimi, GLM, MiniMax all had recent releases and are good.
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Arctic-Text2SQL-R1-32B achieves 72.20 on Bird benchmark
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Bird (BIg Bench for LaRge-Scale Database Grounded Text-to-SQL Evaluation) 72.20!
Arctic-Text2SQL-R1-32B
Snowflake AI Research
Size: 32B
Self Consistency: Few
Dev: 72.20
Test: 73.84 #BigData #Analytics #DataScience #AI #MachineLearning #NLProc #LLM #IoT #IIoT #PyTorch #Python -
Learn MCP with Python for Agentic Systems
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Learn Model Context Protocol [MCP] with Python โ Build Agentic Systems in Python with the new standard for AI Capabilities: http://
amzn.to/4njfsVM by @chris_noring v/ @PacktDataML ๐ฆ๐ฑ๐ช๐ฝ ๐จ๐ธ๐พ ๐ฆ๐ฒ๐ต๐ต ๐๐ฎ๐ช๐ป๐ท:
Understand the MCP protocol and its core components -
30 Agents Every AI Engineer Must Build
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30 Agents Every AI Engineer Must Build โ Build production-ready agent systems using proven architectures and patterns: http://
amzn.to/41ckg6z v/ @PacktDataML โ
What you will learn:
Deploy production-ready agent systems that scale securely and reliably
Use LangChain and -
GitHub Action triggers codex to compare against VISION.MD and implement
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It's not! It trigger a GitHub Action, spins up codex, compares it against VISION.MD and if a fit, implements it.