Hormesis Management in Agriculture: Leveraging AI for Crop Improvement: Plant stress negatively impacts crop productivity but can also be beneficial when controlled, a phenomenon known as hormesis. Hormesis management involves exposing crops to low doses of stressors to enhance traits like stress tolerance and metabolite production. However, the complexity of plant responses to stress limits… →
State-of-the-art large language models (LLMs) are increasingly conceived as autonomous agents that can interact with the real world using perception, decision-making, and action. An important topic in this arena is whether or not these models can effectively use external tools. Tool use in LLMs will involve: Recognizing when a tool is needed. Choosing the correct… →
The integration of language models into biological research represents a significant challenge due to the inherent differences between natural language and biological sequences. Biological data, such as DNA, RNA, and protein sequences, are fundamentally different from natural language text, yet they share sequential characteristics that make them amenable to similar processing techniques. The primary challenge… →
INTRODUCTION: Insomnia is a prevalent sleep disorder that negatively impacts daytime functioning and quality of life. Breast cancer patients report higher rates of insomnia and more circadian disruption than other cancer groups. Approximately 50% of patients experience acute insomnia following breast cancer diagnosis, which often persists during cancer treatment and rehabilitation. Sleep Restriction Therapy (SRT)… →
Artificial intelligence (AI) has evolved into a powerful tool beyond simple automation, becoming a critical asset in scientific research. Integrating AI in scientific discovery is reshaping the landscape by enabling machines to perform tasks that traditionally require human intelligence. This evolution marks a shift towards a future where AI assists and autonomously drives scientific innovation.… →
The rapid advancement of AI and machine learning has transformed industries, yet deploying complex models at scale remains challenging. This is particularly true for multimodal applications integrating diverse data types like vision, audio, and language. As AI applications grow more sophisticated, transitioning from prototypes to production-ready systems becomes increasingly complex. There is a pressing need… →
Sarvam AI has recently unveiled its cutting-edge language model, Sarvam-2B. This powerful model, boasting 2 billion parameters, represents a significant stride in Indic language processing. With a focus on inclusivity and cultural representation, Sarvam-2B is pre-trained from scratch on a massive dataset of 4 trillion high-quality tokens, with an impressive 50% dedicated to Indic languages.… →
Large Language Models (LLMs) have demonstrated remarkable effectiveness in addressing generic questions. An LLM can be fine-tuned using the company’s proprietary documents to utilize it for a company’s specific needs. However, this process is computationally intensive and has several limitations. Fine-tuning may lead to issues such as the Reversal Curse, where the model’s ability to… →