The Annual International Biocuration Conference (AIBC) was held for the first in India, at the Indian Biological Data Centre (IBDC), Regional Centre for Biotechnology (RCB), Faridabad and co-hosted by the Department of Plant Molecular Biology, University of Delhi South Campus. As usual, GigaDB had representation at the event (see write-ups of many previous meetings here), Mary Ann Tuli and Chris Hunter. Both of whom were wearing two hats!

Hot on the heals of the post on how to downsize microscopy movie files, let’s look at ways to shrink the size of a PDF file. There’s several ways to tackle this – suggestions came from this thread on Mastodon. Scenario: you have created a preprint/manuscript/proposal in PDF format.

Exploring the Boundaries of Creativity and Responsibility in the Age of AI-Driven Media Author Vaibhav Khobragade ( ORCID: 0009–0009–8807–5982) Introduction In 2024, the discipline of Generative AI takes a big step forward with the launch of revolutionary models that convert text into dynamic films, altering the landscape of digital content creation.

Prompt Engineering — Part 2 Using intelligence to use artificial Intelligence: A deep dive into Prompt Engineering Author Dhruv Gupta (ORCID: 0009–0004–7109–5403 ) Introduction In the previous article we discussed what prompt engineering and some of the techniques used for prompt engineering.

Understanding how RNNs work and its applications Author Wenyi Pi ( ORCID : 0009–0002–2884–2771) Introduction In the ever-evolving landscape of artificial intelligence (AI), bridging the gap between humans and machines has seen remarkable progress. Researchers and enthusiasts alike have tirelessly worked across numerous aspects of this field, bringing about amazing advancements.

Solutions to Enhance LLM Performance in Long Contexts Author · Qingqin Fang ( ORCID: 0009–0003–5348–4264) Introduction In the era of AI breakthroughs, large language models (LLMs) are not just advancements; they are revolutions, transforming how we interact with technology, from casual conversations with chatbots to the intricate mechanisms behind sophisticated data analysis tools.

Harvesting the Power and Knowledge of Large Language Models Author Amanda Kau (ORCID: 0009–0004–4949–9284 ) Introduction Knowledge Graphs are networks that represent data in a graphical format. The beauty of Knowledge Graphs lies in their representation of concepts, events and entities as nodes, and the relationships between them as edges.

Apologies for the long hiatus: we've had some health issues in the family, and startup life has been particularly overwhelming. With any luck, I'll be able to return to a more regular posting frequency soon. What’s the right relationship between theory, computation, and experiment? Much has been written on this.

Last week, I attended “AI” UK – which was organised by The Alan Turing Institute and where I served in a minor role on the program advisory committee – and a workshop on Responsible “AI” , co-organised by some fellow fellows of the Software Sustainability Institute.

Latest findings in multiple research directions for handling graph prediction and optimization Author · Xuzeng He ( ORCID: 0009–0005–7317–7426) A graph, in short, is a description of items linked by relations, where the items of a graph are called nodes (or vertices) and their relations are called edges (or links). Examples of graphs can include social networks (e.g. Instagram) or knowledge