HyperLab Blog - AI
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AI
ICML 2025 Preview
We've taken an early look at key ICML 2025 papers on drug discovery, bioinformatics, and molecular generation.
Sangyoun Hwang, AI Research 1 Team Lead2025.06.13

AI
Hyper-Binding Co-Folding: Innovations in Drug Development After AlphaFold 3
Hyper Binding Co-folding builds on AlphaFold3 to enhance precision and usability, boosting accuracy and efficiency in drug discovery.
Jaechang Lim, CTO2025.05.26

AI
HyperLab 2.0: Smarter, Faster AI Drug Discovery – Now Launched
"HyperLab 2.0," equipped with more advanced features and workflows, has been released.
HITS Hyper Lab TEAM2025.05.16

AI
HyperLab AI Assistant, The perfect Partner for Drug Discovery
The HyperLab AI assistant is an LLM-based tool specialized for drug development, automating tasks from literature review to data analysis to maximize research productivity.
Jaechang Lim, CTO2025.04.25

AI
Is AI the Future of Pharma? Why the U.S. Is Investing $700 Billion in Artificial Intelligence
The $500B “Stargate Project” — What’s behind President Trump’s bold move, and what does it really mean?
HITS Hyper Lab TEAM2025.04.13

AI
Google's Next-Gen Deep Learning Architecture, Titans Takes on the Transformer Dynasty
Introduces the concept of deep learning architecture and compares two representative models: Transformer and Titans.
Sunghan Bae, AI Researcher2025.04.04

AI
The Evolution of AI Drug Discovery: Past, Present, and Future
Here’s why AI drug development is gaining attention, along with its past, present, and future at a glance
히츠 하이퍼랩 팀2025.03.21

AI
Hyper Screening X : World's Largest Molecular Library Powers the Future of Drug Development
Hyper Screening X utilizes RxnFlow to efficiently explore a 7-trillion-compound ultra-large library, identifying innovative drug candidates with low binding energy and over 60% synthetic feasibility.
Jaechang Lim, CTO2025.03.14

AI
The First AI-Physics Hybrid Docking: Advancing Drug Development Accuracy
In this article, we introduce the development background and outstanding performance of PIGNet, which overcomes the limitations of traditional molecular docking by integrating deep learning with physical laws.
Jaechang Lim, CTO2025.03.07

AI
ICLR 2025 Preview
Introducing the AI-driven drug discovery research unveiled at ICLR 2025: RxnFlow, DynamicFlow, and NEXT-MOL
Sunghan Bae, AI Researcher2025.02.17