Drishtant Ghosh (Drix10)
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AI Professionals and Community••7 min read•1309 words

🤖 AI - Architecture for Long-Horizon Agents

⚡Direct Technical Summary

Long-horizon agents are AI systems designed to make decisions over extended periods, often with complex, dynamic environments. The Architecture for Long-Horizon Agents: Levels, Tic

🤖 AI - Architecture for Long-Horizon Agents

Long-horizon agents are AI systems designed to make decisions over extended periods, often with complex, dynamic environments. The Architecture for Long-Horizon Agents: Levels, Ticks, and Cascaded Intelligence by E Nijkamp, A Koul, E Pakhomov, and B Pang (Salesforce AI Research, 2026) presents a novel approach to building such agents.

Key Points:

  • Levels, Ticks, and Cascaded Intelligence: The authors propose a hierarchical architecture consisting of levels, ticks, and cascaded intelligence. Levels represent high-level goals, ticks are low-level actions, and cascaded intelligence enables the agent to adapt to changing environments.

  • Cascaded Intelligence: This mechanism allows the agent to learn from its experiences and update its decision-making process. It consists of a cascade of neural networks, each responsible for a specific aspect of the environment.

  • Levels and Ticks: The levels represent high-level goals, while ticks are low-level actions. The authors propose a novel way of combining levels and ticks to create a more efficient decision-making process.

🔗 Resources:

🚀 Chat Streaming Improvements

Improving chat streaming involves refining the underlying architecture and algorithms to enhance performance and user experience. Jerrick Hakim shares his experiences with improving chat streaming, including rolling his own Markdown dependencies in Swift and refactoring the transport and parsing layers.

Key Points:

  • Rolling own Markdown dependencies: Jerrick Hakim shares his experience with rolling his own Markdown dependencies in Swift, which improved performance and reduced dependencies.

  • Refactoring transport and parsing layers: The author refactored the transport and parsing layers to improve performance and reduce complexity.

  • Inspiration from ChatGPT: Jerrick Hakim was inspired by ChatGPT's level of craftsmanship and performance, which motivated him to improve his chat streaming architecture.

🔗 Resources:

🌎 Interactive Globe

The interactive globe is a powerful tool for visualizing and exploring data. Simon German shares an interactive globe that displays whether areas have been drier or wetter than usual, with data available all the way back to 1940.

Key Points:

  • Interactive Globe: The interactive globe is a powerful tool for visualizing and exploring data.

  • Data Availability: The globe displays data from 1940, providing a long-term perspective on climate patterns.

  • Bookmarking: Simon German recommends bookmarking the tool for easy access.

🔗 Resources:

🚨 AI Welfare Discussion

AI welfare is an essential topic in the field of AI research. Jeff Sebo shares his concerns about the essay on AI welfare published by Microsoft AI, highlighting several issues with the essay.

Key Points:

  • AI Welfare Essay: Jeff Sebo critiques the essay on AI welfare published by Microsoft AI, highlighting several issues.

  • Moving too quickly: The essay moves too quickly in its discussion of AI welfare, failing to provide a thorough analysis.

  • Lack of concrete recommendations: The essay lacks concrete recommendations for addressing AI welfare concerns.

🔗 Resources:

🎨 Historical Footage Texture Pack

Covacut shares a free texture pack created from real historical footage, featuring 100 clips of grain, scratches, and light leaks.

Key Points:

  • Texture Pack: The texture pack is created from real historical footage, providing a unique and authentic look.

  • Grain, Scratches, and Light Leaks: The pack features 100 clips of grain, scratches, and light leaks, adding texture and depth to visuals.

  • Surviving Time: The texture pack captures the essence of surviving time, with each clip telling a story.

🔗 Resources:

🤔 EA Community Discussion

The EA community is known for its diverse perspectives and discussions. ValsTutor shares his thoughts on the EA community, highlighting the unusual views of one community member.

Key Points:

  • EA Community: The EA community is known for its diverse perspectives and discussions.

  • Unusual Views: One community member holds unusual views, including believing in God/Theism.

  • EA Values: The community member's views are not representative of most EA community members.

🔗 Resources:

🚫 AI if Statement

The concept of an AI if statement is often misunderstood. Southpolesteve introduces Probably, a programming language powered by Jev, which can be used to create an AI if statement.

Key Points:

  • AI if Statement: The concept of an AI if statement is often misunderstood.

  • Probably Language: Probably is a programming language powered by Jev, which can be used to create an AI if statement.

  • Jev Baked into Language: Jev is baked into the language, allowing for more efficient decision-making.

🔗 Resources:

🚨 Lottery Contract

The lottery contract is a critical component of the RIG ecosystem. Web3IsWild shares information about the lottery contract, including its functionality and eligibility requirements.

Key Points:

  • Lottery Contract: The lottery contract is a critical component of the RIG ecosystem.

  • Functionality: The contract checks that the user owns or has staked the RIG.

  • Eligibility: Staked RIGs are eligible to participate in the lottery.

🔗 Resources:

🚨 AI Welfare Essay Critique

Jeff Sebo critiques the essay on AI welfare published by Microsoft AI, highlighting several issues with the essay.

Key Points:

  • AI Welfare Essay: Jeff Sebo critiques the essay on AI welfare published by Microsoft AI.

  • Moving too quickly: The essay moves too quickly in its discussion of AI welfare, failing to provide a thorough analysis.

  • Lack of concrete recommendations: The essay lacks concrete recommendations for addressing AI welfare concerns.

🔗 Resources:

🚨 Rarely

ValsTutor shares his thoughts on the EA community, highlighting the unusual views of one community member.

Key Points:

  • EA Community: The EA community is known for its diverse perspectives and discussions.

  • Unusual Views: One community member holds unusual views, including believing in God/Theism.

  • EA Values: The community member's views are not representative of most EA community members.

🔗 Resources:

🚨 Probably Language

Southpolesteve introduces Probably, a programming language powered by Jev, which can be used to create an AI if statement.

Key Points:

  • AI if Statement: The concept of an AI if statement is often misunderstood.

  • Probably Language: Probably is a programming language powered by Jev, which can be used to create an AI if statement.

  • Jev Baked into Language: Jev is baked into the language, allowing for more efficient decision-making.

🔗 Resources:

🚨 Lottery Contract Information

Web3IsWild shares information about the lottery contract, including its functionality and eligibility requirements.

Key Points:

  • Lottery Contract: The lottery contract is a critical component of the RIG ecosystem.

  • Functionality: The contract checks that the user owns or has staked the RIG.

  • Eligibility: Staked RIGs are eligible to participate in the lottery.

🔗 Resources:

📂Source / Implementation:AI Professionals and Community / resources-247.md
GitHub Repository↗

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Drishtant Ghosh (Drix10)
Drishtant Ghosh (Drix10)•Author & Engineer

Technical founder and engineer working across AI systems, developer infrastructure, and cybersecurity.

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GitHub: AI Professionals and Community/resources-247.md ↗https://blogs.drix10.com/articles/ai-professionals-and-community/architecture-for-long-horizon-agents-247