Technologies that underpin modern society, such as smartphones and automobiles, rely on a diverse range of functional ...

Google Cloud’s lead engineer for databases discusses the challenges of integrating databases and LLMs, the tools needed to ...

By applying machine learning to experimental data in materials science, it may be possible to replicate such intuition ...

As for the AI bubble, it is coming up for conversation because it is now having a material effect on the economy at large.

Increased use of organoids in cancer research: The Würzburg lighthouse project "Preclinical Models" is working towards this ...

Joe Root had 17 Test 100s in his first 9 years. He has 24 in the last 4. How did he do it? This data-centric long-read ...

No code automation platforms let you build workflows and connect apps without writing any code, making them accessible to ...

However, it is important to note that nearly 90 percent of India’s tea production comprises CTC tea. This highlights the need for greater initiatives and focused efforts to increase the share of ...

Organizations have a wealth of unstructured data that most AI models can’t yet read. Preparing and contextualizing this data is essential for moving from AI experiments to measurable results.

Right now, AI technologies are not just enhancing existing technology portfolios-they are reshaping how organizations think about modern data architecture, elevating modernization from a competitive ...

According to TII’s technical report, the hybrid approach allows Falcon H1R 7B to maintain high throughput even as response ...

This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...