Drishtant Ghosh (Drix10)
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Computer Vision and AI Applications••7 min read•1245 words

📝 Task Scheduling and ADHD

⚡Direct Technical Summary

Task scheduling can be challenging, especially for individuals with ADHD. Some tasks inherently require a certain amount of time to complete. Breaking the afternoon into two blocks

📝 Task Scheduling and ADHD

Task scheduling can be challenging, especially for individuals with ADHD. Some tasks inherently require a certain amount of time to complete. Breaking the afternoon into two blocks of time can leave no block long enough to complete a task.

Key Points:

  • Task Scheduling Challenges: Understanding the inherent time requirements of tasks is crucial for effective scheduling.

  • ADHD and Task Scheduling: Individuals with ADHD may face unique challenges in task scheduling due to difficulties with time estimation and organization.

  • Block Scheduling: Breaking the day into blocks of time can help individuals with ADHD stay focused and complete tasks.

🔗 Resources:

📸 Depth Map Confidence Threshold

Tweaked the depth model to output a confidence map. Now you can set a confidence threshold and dubious pixels in the depth map come as nan (shown as pitch black in video). Useful in noisy scenes (e.g. poor lighting) when the downstream system doesn’t handle noise well.

Key Points:

  • Depth Map Confidence: Understanding the confidence of depth map pixels is crucial for accurate scene understanding.

  • Confidence Threshold: Setting a confidence threshold can help filter out noisy pixels and improve overall accuracy.

  • Noisy Scenes: In scenes with poor lighting or other noise sources, a confidence threshold can be particularly useful.

🔗 Resources:

🎮 3D Platformer Generation

Astra + Thrixel just built this 3D platformer from a single prompt. Astra mocks up the scene, then calls Thrixel to generate the editable 3D assets. Depending on the asset’s role (background prop, animation), Astra picks the best Thrixel creation pipeline. Play below

Key Points:

  • 3D Platformer Generation: Using AI to generate 3D platformers from a single prompt is a promising area of research.

  • Astra and Thrixel: Astra and Thrixel are two AI tools that can be used together to generate 3D platformers.

  • Pipeline Selection: Astra can select the best pipeline for generating 3D assets based on their role in the scene.

🔗 Resources:

🚫 Free Models and Market Competition

This is a strong argument as to why free models won't take over the market. No vendors, Chinese or otherwise, will give away their best agentic harness and full solution. So simple work will be cheap. For important work one will have to pay up.

Key Points:

  • Free Models and Market Competition: Free models may not be able to compete with paid models in the market.

  • Agentic Harness: The best agentic harnesses and full solutions are likely to be proprietary and not given away for free.

  • Simple Work vs. Important Work: Simple work may be cheap, but important work will likely require payment.

🔗 Resources:

📐 Platform Geometry and Navigation

Platform Geometry & Navigation 09 Pose = Position + Orientation Pose tells us two things about a platform at one instant: Position → Where is it? Orientation → How is it rotated? Together: Position + Orientation → Pose

Key Points:

  • Platform Geometry: Understanding the geometry of a platform is crucial for navigation and control.

  • Pose: The pose of a platform is determined by its position and orientation.

  • Position and Orientation: Position and orientation are two fundamental aspects of platform geometry.

🔗 Resources:

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🚀 Trajectory and Pose Estimation

And: One instant → Pose Many poses over time → Trajectory Why it matters in aerial systems: GNSS → position IMU → motion + orientation information Sensor fusion → pose estimate Pose → place Camera / LiDAR measurements correctly in 3D

Key Points:

  • Trajectory and Pose Estimation: Estimating the trajectory and pose of a platform is crucial for navigation and control.

  • Sensor Fusion: Sensor fusion is used to estimate the pose of a platform.

  • GNSS and IMU: GNSS and IMU provide position and motion information, respectively.

🔗 Resources:

🚨 Terminal Bench and Epoch

ok i kinda love @terminalbench folks, so sorry for being a little COI'd here, but was very surprised to see this because my knee-jerk interpretation of the post was "TB 4.0 is broken". Epoch indeed did not say broken, they found 30/66 have scoring defects, but I feel the way this

Key Points:

  • Terminal Bench and Epoch: Terminal Bench and Epoch are two tools used for benchmarking and scoring.

  • Scoring Defects: 30/66 of the benchmarks had scoring defects.

  • TB 4.0: TB 4.0 was not found to be broken, but rather had scoring defects.

🔗 Resources:

  • Original post ↗
  • Dimitris Papail
  • Wenhao Cha
  • Dimitris Papail
  • Dimitris Papail
  • Terminal Bench

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📊 PKC Forum and Chinese R1 Candidates

Even though the Chinese R1 candidates are not available, the names are: https:// list.niccs.org.cn/archives/list/ pkcforum@list.niccs.org.cn/ … Seeing (guessing): - 34 Signature schemes - 41 KEMs - 9 Key Exchange - 35 Hash (block ciphers later)

Key Points:

  • PKC Forum and Chinese R1 Candidates: The PKC forum has listed the names of Chinese R1 candidates.

  • Signature Schemes: 34 signature schemes are listed.

  • KEMs: 41 KEMs are listed.

  • Key Exchange: 9 key exchange algorithms are listed.

  • Hash: 35 hash algorithms are listed.

🔗 Resources:

Image

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🎉 ABC Release and CoRL 2026

Happy to announce the full ABC release! We’re also excited that ABC was accepted to CoRL 2026! Check out our website for code, 400+ hours of sim data on 24 tasks, and 5,850 labeled policy-evaluation episodes. @arthurallshire @Cinnabar233 @ritvik_singh9 @redstone_hong

Key Points:

  • ABC Release: The ABC release is now available.

  • CoRL 2026: ABC was accepted to CoRL 2026.

  • Code and Sim Data: The code and sim data are available on the website.

  • Policy-Evaluation Episodes: 5,850 labeled policy-evaluation episodes are available.

🔗 Resources:

  • Original post ↗
  • Jon Stephens
  • Adam Rasb
  • Adam Rasb
  • Adam Rasb
  • Arthur Allshire
  • Cinnabar233
  • Ritvik Singh
  • Redstone Hong

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🌐 SNAP3D and Physically Compatible 3D Part Generation

Introducing SNAP3D — physically compatible 3D part generation from a single image. Existing methods can generate visually appealing 3D parts, but the generated parts are often not physically compatible for assembly. With SNAP3D, the parts are designed to fit together in the

Key Points:

  • SNAP3D: SNAP3D is a tool for generating physically compatible 3D parts from a single image.

  • Physically Compatible Parts: The generated parts are designed to fit together in the real world.

  • Existing Methods: Existing methods can generate visually appealing 3D parts, but they are not physically compatible.

🔗 Resources:

📂Source / Implementation:Computer Vision and AI Applications / resources-238.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: Computer Vision and AI Applications/resources-238.md ↗https://blogs.drix10.com/articles/computer-vision-and-ai-applications/task-scheduling-and-adhd-238