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Deep Reinforcement Learning Methods for Automated Chip Layout: Evidence and Impact

I've been reviewing this response paper to recent skepticism about AI/ML approaches for chip design. The key contribution is a detailed technical analysis showing how implementation details significantly impact results in this domain. Main technica…

Guidelines for Accurate Performance Benchmarking of Quantum Computers

I found this paper to be a worthwhile commentary on benchmarking practices in quantum computing. The key contribution is drawing parallels between current quantum computing marketing practices and historical issues in parallel computing benchmarking fr…

Decomposing and Reconstructing Prompts for More Effective LLM Jailbreak Attacks

DrAttack: Using Prompt Decomposition to Jailbreak LLMs I've been studying this new paper on LLM jailbreaking techniques. The key contribution is a systematic approach called DrAttack that decomposes malicious prompts into fragments, then reconstruc…

Decomposing and Reconstructing Prompts for More Effective LLM Jailbreak Attacks

DrAttack: Using Prompt Decomposition to Jailbreak LLMs I've been studying this new paper on LLM jailbreaking techniques. The key contribution is a systematic approach called DrAttack that decomposes malicious prompts into fragments, then reconstruc…

Snapchat used AI agents to build a sound-aware video captioning system

Training AI to understand and describe video content requires datasets which are expensive for humans to annotate manually. Now researchers from Snap, UC Merced, and the University of Trento have put together a new dataset called Panda-70M that aims to…

Google DeepMind uses AI to discover 2.2 million new materials – equivalent to nearly 800 years’ worth of knowledge. Shares they’ve already validated 736 in laboratories.

Materials discovery is critical but tough. New materials enable big innovations like batteries or LEDs. But there are ~infinitely many combinations to try. Testing for them experimentally is slow and expensive. So scientists and engineers want to simul…

Researchers present SuGaR: Surface-Aligned Gaussian Splatting for Speedy 3D Mesh Reconstruction

Computer vision researchers developed a way to create detailed 3D models from images in just minutes on a single GPU. Their method, called SuGaR, works by optimizing millions of tiny particles to match images of a scene. The key innovation is getting t…

You can predict disease progression by modeling health data in latent space

Many complex diseases like autoimmune disorders have highly variable progression between patients, making them difficult to understand and predict. A new paper shows that visualizing health data in the latent space helps find hidden patterns in clinica…

They found a new NeRF technique to turn videos into controllable 3D models

The key challenge is that NeRFs typically require multiple view images to reconstruct a scene in 3D, whereas videos provide only a single view over time. But that means we have to capture a lot of data to create a NeRF. What if there was a way to creat…

Telling GPT-4 you’re scared or under pressure improves performance

In a recent paper, researchers have discovered that LLMs show enhanced performance when provided with prompts infused with emotional context, which they call "EmotionPrompts." These prompts incorporate sentiments of urgency or importance, suc…