The next chapter of our Gemini era

Early warning earthquake systems have changed the way people perceive earthquake threats, providing valuable seconds to minutes of warning to prepare for potential damage. Scientists are increasingly open to the possibility of earthquake prediction, exploring phenomena…

MIT and Meta AI researchers developed a real-time object reorientation controller using a depth camera. This AI system efficiently manipulates diverse objects and generalizes to new shapes, indicating promising future applications in robotics. The controller is…

Generative AI has rapidly developed since going mainstream, with new models emerging regularly. Evaluating generative models is more complex than discriminative models due to the challenge of assessing quality, coherence, diversity, and usefulness. Evaluation methods include…

Theory of Mind: How GPT-4 and LLaMA-2 Stack Up Against Human Intelligence A recent study by a team of psychologists and researchers from various institutions compares the theory of mind abilities of large language models (LLMs)…

Advancements in AI Communication for Multi-Agent Environments Understanding the Challenge Artificial intelligence (AI) has made great progress in multi-agent environments, especially in reinforcement learning. A major challenge is enabling AI agents to communicate effectively using natural…

IBM researchers have introduced LAB (Large-scale Alignment for chatbots) to address scalability challenges in instruction-tuning for large language models (LLMs). LAB leverages a taxonomy-guided synthetic data generation process and a multi-phase training framework to enhance LLM…

Vision models, foundational in computer vision tasks, serves as starting points for specific and complex models. Their adaptability in handling various tasks makes them integral to modern AI applications. Researchers at Kyung Hee University resolve image…

The blog describes TruEra’s collaboration in co-writing with Josh Reini, Shayak Sen, and Anupam Datta from TruEra. It highlights Amazon SageMaker JumpStart’s provision of pretrained foundation models, outlines the need for adapting foundation models to new…

Large language models (LLMs) are being used more frequently as conversational systems, leading to increased reliance on them for answers. To understand how these models respond to questions about ongoing debates, we need datasets with human-annotated…

Understanding the Importance of Quality in AI Training A strong link exists between the quality of an LLM’s training data and its performance. Researchers are focusing on gathering high-quality datasets, which currently require detailed human input.…

Enhancing Spiking Neural Networks with CPG-PE Addressing Challenges in Sequential Task Processing Spiking Neural Networks (SNNs) offer energy-efficient and biologically plausible artificial neural networks. However, they face limitations in handling sequential tasks like text classification and…

Tech giant Meta has disbanded its Responsible AI (RAI) team, as part of a strategic shift towards generative artificial intelligence. The RAI team, established in 2019, focused on ethical development and accountability in AI. Most members…

AI web scraping operations that collect online artworks without consent or compensation of the creators have become a major concern for artists. Existing solutions have been limited, but researchers have developed a tool that subtly manipulates…

Studying scaling laws in large language models is crucial for optimizing their performance in tasks like translation. Challenges include determining the impact of pretraining data size on downstream tasks and developing strategies to enhance model performance.…

AI-Generated Content: Opportunities and Challenges AI content creation is growing rapidly. This brings both new opportunities and challenges, especially when it comes to identifying what is generated by machines versus humans. As AI-generated text becomes more…

Practical AI Solutions for Your Business Automating Red-Teaming of Large Language Models Large Language Models (LLMs) have proven to be highly effective in various fields, but they can be vulnerable to jailbreaking attacks, leading to the…

The text discusses the significance of natural language generation in AI, focusing on recent advancements in large language models like GPT-4 and the challenges in evaluating the reliability of generated text. It presents a new method,…

Understanding RNA 3D Structure Prediction Predicting the 3D structures of RNA is essential for grasping its biological roles, enhancing drug discovery, and advancing synthetic biology. However, RNA’s flexible nature and the scarcity of experimental data create…

Protein Annotation-Improved Representations (PAIR): Enhancing Protein Function Prediction Enhancing Protein Models with Text Annotations Protein language models (PLMs) are trained on large protein databases to predict amino acid sequences and generate feature vectors representing proteins. These…