Causal effect estimation is crucial for understanding the impact of interventions in various domains, such as healthcare, social sciences, and economics. This area of research focuses on determining how changes in one variable cause changes in another, which is essential for informed decision-making. Traditional methods often involve extensive data collection and structured experiments, which can…
Competition significantly shapes human societies, influencing economics, social structures, and technology. Traditional research on competition, relying on empirical studies, is limited by data accessibility and lacks micro-level insights. Agent-based modeling (ABM) emerged to overcome these limitations, progressing from rule-based to machine learning-based agents. However, these approaches still struggle to accurately simulate complex human behavior. The…
Evaluating model performance is essential in the significantly advancing fields of Artificial Intelligence and Machine Learning, especially with the introduction of Large Language Models (LLMs). This review procedure helps understand these models’ capabilities and create dependable systems based on them. However, what is referred to as Questionable Research Practices (QRPs) frequently jeopardize the integrity of…
Autonomous web navigation focuses on developing AI agents capable of performing complex online tasks. These tasks range from data retrieval and form submissions to more intricate activities like finding the cheapest flights or booking accommodations. By leveraging large language models (LLMs) and other AI methodologies, autonomous web navigation aims to enhance productivity in both consumer…
Generative Artificial Intelligence (GenAI), particularly large language models (LLMs) like ChatGPT, has revolutionized the field of natural language processing (NLP). These models can produce coherent and contextually relevant text, enhancing applications in customer service, virtual assistance, and content creation. Their ability to generate human-like text stems from training on vast datasets and leveraging deep learning…
Aligning models with human preferences poses significant challenges in AI research, particularly in high-dimensional and sequential decision-making tasks. Traditional Reinforcement Learning from Human Feedback (RLHF) methods require learning a reward function from human feedback and then optimizing this reward using RL algorithms. This two-phase approach is computationally complex, often leading to high variance in policy…
The landscape of artificial intelligence has seen significant advancements with the introduction of state-of-the-art language models. Among the leading models are Llama 3.1, GPT-4o, and Claude 3.5. Each model brings unique capabilities and improvements, reflecting the ongoing evolution of AI technology. Let’s analyze these three prominent models, examining their strengths, architectures, and use cases. Llama…
Large Language Models (LLMs) can improve their final answers by dedicating additional computer power to intermediate thought generation during inference. System 2 strategies are used in this procedure to mimic intentional and conscious reasoning. Many more System 2 strategies, such as Rephrase and Respond, System 2 Attention, and Branch-Solve-Merge, have been proposed since the introduction…
Large language models (LLMs) are used in various applications, such as machine translation, summarization, and content creation. However, a significant challenge with LLMs is their tendency to produce hallucinations—statements that sound plausible but are not grounded in factual information. This issue affects the reliability of AI-generated content, especially in domains requiring high accuracy, such as…
In a groundbreaking achievement, AI systems developed by Google DeepMind have attained a silver medal-level score in the 2024 International Mathematical Olympiad (IMO), a prestigious global competition for young mathematicians. The AI models, named AlphaProof and AlphaGeometry 2, successfully solved four out of six complex math problems, scoring 28 out of 42 points. This places…