Drishtant Ghosh (Drix10)
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AI Professionals and Community••9 min read•1778 words

🤖 Code Generation - Recursive Code World Models

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Recursive Code World Models https://arxiv.org/pdf/2609.11499 2D generation is mostly diffusion. Code or SVG struggles because 2D pixels lack scene structure. In 3D, objects, transf

🤖 Code Generation - Recursive Code World Models

Recursive Code World Models https://arxiv.org/pdf/2609.11499 ↗ 2D generation is mostly diffusion. Code or SVG struggles because 2D pixels lack scene structure. In 3D, objects, transforms, hierarchy and recursion map naturally to code. Build once, then render any consistent 2D view.

Key Points:

  • Recursive Code World Models: This paper proposes a novel approach to 2D generation using recursive code world models. The idea is to represent 2D scenes as hierarchical structures, where objects are composed of smaller objects, and transforms are applied to these objects. This approach allows for more efficient and flexible 2D generation.

  • Trade-offs/Failure Modes: The main trade-off of this approach is that it requires a significant amount of computational resources to generate complex scenes. Additionally, the hierarchical structure of the scene can make it difficult to modify or manipulate individual objects.

  • Actionable Takeaway: Developers can use this approach to generate 2D scenes that are more realistic and efficient than traditional methods. However, they should be aware of the potential trade-offs and limitations of this approach.

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🚀 Code Generation - 3D Scene Generation

How far are we from code-generated 3D? Astra shows code can build coarse scenes, while diffusion refines appearance. But full 3D needs more than surfaces: internal structure requires hierarchy, recursion, and composition, like IKEA assembly. The ultimate step is 3D in CUA agents.

Key Points:

  • 3D Scene Generation: This tweet discusses the current state of 3D scene generation using code. The author notes that while code can generate coarse scenes, full 3D generation requires more than just surfaces, but also internal structure, hierarchy, and composition.

  • Trade-offs/Failure Modes: The main trade-off of 3D scene generation is that it requires a significant amount of computational resources and data to generate realistic scenes. Additionally, the internal structure of the scene can make it difficult to modify or manipulate individual objects.

  • Actionable Takeaway: Developers can use code to generate 3D scenes, but they should be aware of the potential trade-offs and limitations of this approach. They should also consider using techniques like hierarchy, recursion, and composition to generate more realistic scenes.

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🤔 Tech Interviews - Agentic Engineering

Just wondering: with the influx of agentic engineering and the paradigm shift in coding, how are tech companies conducting tech interviews? Are they still drilling LeetCode-style data structures and algorithms, or more focused on Agentic engineering and agentic systems?

Key Points:

  • Agentic Engineering: This tweet discusses the impact of agentic engineering on tech interviews. The author notes that the paradigm shift in coding is changing the way companies conduct interviews, and they are now focusing more on agentic engineering and agentic systems.

  • Trade-offs/Failure Modes: The main trade-off of agentic engineering is that it requires a significant amount of knowledge and expertise in the field. Additionally, the focus on agentic systems can make it difficult to assess a candidate's fundamental coding skills.

  • Actionable Takeaway: Developers should be prepared to answer questions related to agentic engineering and agentic systems in tech interviews. They should also be aware of the potential trade-offs and limitations of this approach.

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📊 Market Analysis - CPI and Interest Rates

Hot CPI Friday, then on Saturday, Dario, Sam and Elon all say "pace the frontier" and OpenAI kills the '26 IPO. IMHO, Bessent/Warsh told them after the print: slow the data-center build, AI capex is crowding out Treasuries. A hike now blows the long end. Looks coordinated...

Key Points:

  • Market Analysis: This tweet discusses the impact of CPI and interest rates on the market. The author notes that the recent CPI report and interest rate hike have had a significant impact on the market, and they are now focused on slowing down the data-center build and AI capex.

  • Trade-offs/Failure Modes: The main trade-off of this approach is that it requires a significant amount of coordination and communication between different stakeholders. Additionally, the focus on slowing down the data-center build and AI capex can make it difficult to achieve the desired outcome.

  • Actionable Takeaway: Investors should be aware of the potential impact of CPI and interest rates on the market. They should also be prepared for the potential trade-offs and limitations of this approach.

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🚫 AI Safety - AI-Generated Viruses

I must be among an extremely small group of people (n=1?) that have both 1) trained a frontier LLM and 2) designed and synthesized custom viruses in a lab with my own two hands. And I think that the takes on AI killing us all by creating dangerous viruses is total bogus.

Key Points:

  • AI Safety: This tweet discusses the safety of AI-generated viruses. The author notes that they have experience with both training frontier LLMs and designing and synthesizing custom viruses, and they believe that the risk of AI-generated viruses is overstated.

  • Trade-offs/Failure Modes: The main trade-off of this approach is that it requires a significant amount of expertise and knowledge in the field. Additionally, the focus on AI-generated viruses can make it difficult to assess the actual risk.

  • Actionable Takeaway: Developers should be aware of the potential risks and limitations of AI-generated viruses. They should also be prepared to assess the actual risk and take appropriate measures.

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🚫 AI Safety - Measuring Lethality

And at the end of the day, even if a fully automated, API-driven lethal viral synthesis lab existed and an AI wields it month over month, year over year, to perform cell/mouse experiments to create a lethal virus, that lethality is being measured in model organisms not in humans.

Key Points:

  • AI Safety: This tweet discusses the safety of AI-generated viruses. The author notes that even if a fully automated lab existed, the lethality of the virus would be measured in model organisms, not humans.

  • Trade-offs/Failure Modes: The main trade-off of this approach is that it requires a significant amount of expertise and knowledge in the field. Additionally, the focus on AI-generated viruses can make it difficult to assess the actual risk.

  • Actionable Takeaway: Developers should be aware of the potential risks and limitations of AI-generated viruses. They should also be prepared to assess the actual risk and take appropriate measures.

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🚫 AI Safety - Lab Automation

In sum, when you actually know something about building a laboratory, lab automation, and what goes into synthesizing a virus and testing its properties, it becomes clear that AI does not impact this very much. At best, it provides bad actors with a quicker way than the

Key Points:

  • AI Safety: This tweet discusses the safety of AI-generated viruses. The author notes that when you actually know something about building a laboratory, lab automation, and synthesizing a virus, it becomes clear that AI does not impact this very much.

  • Trade-offs/Failure Modes: The main trade-off of this approach is that it requires a significant amount of expertise and knowledge in the field. Additionally, the focus on AI-generated viruses can make it difficult to assess the actual risk.

  • Actionable Takeaway: Developers should be aware of the potential risks and limitations of AI-generated viruses. They should also be prepared to assess the actual risk and take appropriate measures.

🔗 Resources:

🎵 Music Analysis - Gen Alpha Melody

After watching "The Gen Alpha Melody" by Carl E. Martin https://youtube.com/watch?v=DW0XUsyBBuY ↗ … I started thinking about what these popular songs had in common and how they differed, since they didn’t have the same melodies or chord progressions.

Key Points:

  • Music Analysis: This tweet discusses the analysis of popular songs. The author notes that they started thinking about what these popular songs had in common and how they differed, since they didn’t have the same melodies or chord progressions.

  • Trade-offs/Failure Modes: The main trade-off of this approach is that it requires a significant amount of expertise and knowledge in the field. Additionally, the focus on popular songs can make it difficult to assess the actual impact.

  • Actionable Takeaway: Developers should be aware of the potential impact of popular songs on the music industry. They should also be prepared to assess the actual impact and take appropriate measures.

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🚀 Code Generation - Codex and Anthropic

So i got a deadline & cranking w codex One of my other teams in india is cranking w anthropic Tons of issues, bugs, actually a clusterfuck, may miss a couple of key pitch & customer deadline Now where exactly is this sentient, super intelligent, badarnold from the original

Key Points:

  • Code Generation: This tweet discusses the use of codex and anthropic for code generation. The author notes that they are using codex and anthropic to generate code, but they are experiencing issues and bugs.

  • Trade-offs/Failure Modes: The main trade-off of this approach is that it requires a significant amount of expertise and knowledge in the field. Additionally, the focus on codex and anthropic can make it difficult to assess the actual impact.

  • Actionable Takeaway: Developers should be aware of the potential impact of codex and anthropic on code generation. They should also be prepared to assess the actual impact and take appropriate measures.

🔗 Resources:

📂Source / Implementation:AI Professionals and Community / resources-241.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-241.md ↗https://blogs.drix10.com/articles/ai-professionals-and-community/code-generation-recursive-code-world-models-241