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Highlights💡 

LEGO-Net: Learning Regular Rearrangements of Objects in Rooms [Link],[GitHub]

Humans universally dislike the task of cleaning up a messy room. If machines were to help us with this task, they must understand human criteria for regular arrangements, such as several types of symmetry, co-linearity or co-circularity, spacing uniformity in linear or circular patterns, and further inter-object relationships that relate to style and functionality. Previous approaches for this task relied on human input to explicitly specify goal state, or synthesized scenes from scratch – but such methods do not address the rearrangement of existing messy scenes without providing a goal state. In this paper, we present LEGO-Net, a data-driven transformer-based iterative method for LEarning reGular rearrangement of Objects in messy rooms. LEGO-Net is partly inspired by diffusion models--it starts with an initial messy state and iteratively “denoises” the position and orientation of objects to a regular state while reducing distance traveled. Given randomly perturbed object positions and orientations in an existing dataset of professionally-arranged scenes, our method is trained to recover a regular re-arrangement. Results demonstrate that our method is able to reliably rearrange room scenes and outperform other methods. We additionally propose a metric for evaluating regularity in room arrangements using number-theoretic machinery.

Augment AI - Imagine ChatGPT, but it knows you and works across all your apps [Link]

• Compose messages in your own tone & style, in the apps you already use (Slack, iMessage, GMail, GDocs, Notion... literally anywhere).

• Automatically summarize Zoom/GMeet meetings.

• Stop copy-pasting into ChatGPT. Just reference anything you’ve come across.

Augment AI is briefly re-opening its early access exclusively to Superpower readers. Sign up for Augment AI.

AI at Work: What People Are Saying [Link]

How do nearly 13,000 people in the workforce—from executive suite leaders to frontline employees—in 18 countries feel about AI?

• Survey respondents are more optimistic than concerned about AI.

• But there are vast differences in perceptions of AI between leaders and frontline employees, and companies need to address them.

• Employees recognize the need for training and upskilling that this new era will require, but few have actually received it.

• Almost everyone sees the need for responsible AI and regulation.

Tutorial: Creative QR Codes with ControlNet [Link]

Tools & Links 🛠️

Empower Your AI Journey: Key Resources, Software, and Innovations

Unclassified 🌀 

• Morning Brew - Get smarter in 5 minutes (it's free) [Link]

• Fiverr - Find the right freelance service, right away [Link]

• WFH.Team - Work from anywhere in the world [Link]

• Add your link here ➜

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