Artificial intelligence hinges on using broad datasets, drawing from global internet resources like social media, news outlets, and more, to power algorithms that shape many facets of modern life. The training of generative models, such as GPT-4, Gemini, Cluade, and others, relies on often insufficiently documented and vetted data. This unstructured and obscure data collection…
In computational linguistics, the interface between human language and machine understanding of databases is a critical research area. The core challenge lies in enabling machines to interpret natural language and convert these inputs into SQL queries executable by database systems. This translation process is vital for making database interaction accessible to users without deep technical…
Methods like Molecular Dynamics simulations, Quantitative Structure-Property Relationships (QSPR), and First-Principles calculations are based on scientific principles and complex mathematical models. They require expensive computational resources, have limited accuracy with complex models, and heavily depend on the quality and quantity of available data. These methods for material development rely on physical synthesis and testing, which…
Transformers are at the forefront of modern artificial intelligence, powering systems that understand and generate human language. They form the backbone of several influential AI models, such as Gemini, Claude, Llama, GPT-4, and Codex, which have been instrumental in various technological advances. However, as these models grow in size & complexity, they often exhibit unexpected…
In traffic management and urban planning, the ability to learn optimal routes from demonstrations conditioned on contextual features holds significant promise. As underscored by previous research endeavors, this methodology rests on the assumption that agents seek to optimize a latent cost when navigating from one point to another. Factors such as trip duration, comfort, toll…
The evolving field of aerial robotics has seen considerable advancements, particularly in the autonomous operation of Micro Aerial Vehicles (MAVs) during nighttime. Despite significant progress, night operations remain a complex challenge due to the inherent limitations of low-light environments. Let’s explore the integration of advanced sensing technologies and vision-based algorithms to enable robust autonomous navigation…
In the vast world of data science, countless tools are available to help analysts and researchers make sense of data and build powerful machine-learning models. While some tools are widely known and used, others might not be as familiar to many. Here are the ten great Python packages that can significantly enhance your workflow. 1.…
Recently, the UK government-backed AI Safety Institute has introduced Inspect, an Artificial Intelligence (AI) safety review tool, as a major step towards improving the safety and accountability of AI technologies. This unique instrument has the potential to strengthen AI safety assessments worldwide and promote cooperation amongst various parties involved in AI R&D. With Inspect, a…
Knowledge Distillation has gained popularity for transferring the expertise of a “teacher” model to a smaller “student” model. Initially, an iterative learning process involving a high-capacity model is employed. The student, with equal or greater capacity, is trained with extensive augmentation. Subsequently, the trained student expands the dataset through pseudo-labeling new data. Notably, the student…