A major step forward in mathematical reasoning is the use of computer-verifiable formal languages such as Lean to prove mathematical theorems. These formal languages make it possible to rigorously verify proofs, guaranteeing accuracy and consistency in mathematical outcomes. Using Large Language Models (LLMs) trained on Natural Language (NL) proofs to produce comprehensive formal proofs is… →
The world’s cultural heritage faces mounting peril from escalating conflicts and natural disasters, jeopardizing ancient sites and artifacts worldwide. Wars, earthquakes, and floods pose existential threats, imperiling invaluable pieces of history. Urgent action is needed to protect these sites. Artificial intelligence (AI) presents a potent solution, providing sophisticated tools to document, analyze, and safeguard cultural… →
Managing, analyzing, and extracting data from large volumes of documents is a crucial yet challenging task. Traditionally, this has required expensive proprietary software solutions. Introducing Open Contracts, a free and open-source platform designed to democratize document analytics. Open Contracts is a fully open-source, AI-powered document analytics tool licensed under Apache-2. This platform empowers users to… →
CONCLUSION: The AI assisted diagnosis system is a valuable tool for training junior radiology residents and medical imaging students to perform pulmonary nodules detection and diagnosis. →
CONCLUSIONS: Vitamin D deficiency is prevalent in EPTB patients, in whom, vitamin D supplementation is a useful adjunctive therapy to anti-TB drugs and improves treatment course. →
Product insights & monitoring, testing, end-to-end analytics, and errors are four of the most difficult LLMs to monitor and test. Teams mostly waste weeks of dev time building internal tools to solve these problems. Most product analytics efforts have concentrated on numerical metrics like CTR and conversion rates. This information is critical, yet it is… →
Few-shot Generative Domain Adaptation (GDA) is a machine learning and domain adaptation concept that addresses the challenge of adapting a model trained on a source domain to perform well on a target domain, using only a few examples from the target domain. Such a technique is particularly useful when obtaining a large amount of labeled… →
Traditional protein design, often relying on physics-based methods like Rosetta, faces challenges in creating functional proteins with complex structures due to the need for parametric and symmetric restraints. Recent advances in deep learning, particularly with tools like AlphaFold2, have transformed protein design by enabling accurate prediction and exploration of vast sequence spaces. This has led… →