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Latest AI news and updates from around the world
Enveda draws inspiration from nature and combines AI technology to develop drugs from natural products (plants, microorganisms).

Google proposed PDFM, which uses machine learning to integrate available geospatial data worldwide and expand the capabilities of geospatial models.

Shanghai Jiao Tong University, Shanghai AI Lab and others have jointly developed a new protein mutant design model PRIME, which has better prediction effects in protein mutations and other aspects.

Tsinghua University, in collaboration with several universities in China and abroad, has proposed an active learning framework that can more efficiently identify high-entropy oxides.

The tutorial "Evo: Prediction and Generation from Molecular to Genome Scale" is now online. You can quickly experience it with one-click cloning!

The fifth episode of the Meet AI4S live series will be launched on time at 19:00 on December 10, come and make an appointment!

Professor Hong Liang from Shanghai Jiao Tong University comprehensively sorted out the challenges and approaches for implementing AI4S, as well as how to organically combine AI and Science.

The tutorial section of HyperAI's official website has launched the "InkSight Demo to Digitize Handwritten Text", which can be cloned with one click to experience.

Lu Feng's team from Huazhong University of Science and Technology proposed CGS-Mask, which can not only improve the prediction accuracy of the model, but also increase the interpretability of the results.

With AI godfather Hinton in charge, startup CuspAI is committed to using AI to explore carbon capture materials to combat global warming.

David Baker's team developed a diffusion model-based technology, RFpeptides, to design macrocyclic binders for a variety of protein targets.

Highlights of the speech by Qi Jin, a researcher in earth science at Zhejiang University, at the COSCon'24 AI for Science forum.

A team from the Institute of Automation, Chinese Academy of Sciences, designed a multimodal integration framework that can solve the problem of visual reconstruction of brain activity.

The fifth episode of the Meet AI4S live series has invited Dr. Wang Zeyuan from Zhejiang University’s Knowledge Engine Laboratory. Come and make an appointment to watch the live broadcast!

Shanghai AI Lab, in collaboration with several scientific research institutions, proposed the GMAI-MMBench benchmark, which includes 284 downstream task datasets.

Shanghai Jiao Tong University, in collaboration with Shanghai AI Lab, has successfully developed a pre-trained protein language model ProSST with structure-aware capabilities.

Meta FAIR Laboratory released the material generation model FlowLLM, which improves the efficiency of generating stable materials by more than 300% compared with previous models.

Enveda draws inspiration from nature and combines AI technology to develop drugs from natural products (plants, microorganisms).

Google proposed PDFM, which uses machine learning to integrate available geospatial data worldwide and expand the capabilities of geospatial models.

Shanghai Jiao Tong University, Shanghai AI Lab and others have jointly developed a new protein mutant design model PRIME, which has better prediction effects in protein mutations and other aspects.

Tsinghua University, in collaboration with several universities in China and abroad, has proposed an active learning framework that can more efficiently identify high-entropy oxides.

The tutorial "Evo: Prediction and Generation from Molecular to Genome Scale" is now online. You can quickly experience it with one-click cloning!

The fifth episode of the Meet AI4S live series will be launched on time at 19:00 on December 10, come and make an appointment!

Professor Hong Liang from Shanghai Jiao Tong University comprehensively sorted out the challenges and approaches for implementing AI4S, as well as how to organically combine AI and Science.

The tutorial section of HyperAI's official website has launched the "InkSight Demo to Digitize Handwritten Text", which can be cloned with one click to experience.

Lu Feng's team from Huazhong University of Science and Technology proposed CGS-Mask, which can not only improve the prediction accuracy of the model, but also increase the interpretability of the results.

With AI godfather Hinton in charge, startup CuspAI is committed to using AI to explore carbon capture materials to combat global warming.

David Baker's team developed a diffusion model-based technology, RFpeptides, to design macrocyclic binders for a variety of protein targets.

Highlights of the speech by Qi Jin, a researcher in earth science at Zhejiang University, at the COSCon'24 AI for Science forum.

A team from the Institute of Automation, Chinese Academy of Sciences, designed a multimodal integration framework that can solve the problem of visual reconstruction of brain activity.

The fifth episode of the Meet AI4S live series has invited Dr. Wang Zeyuan from Zhejiang University’s Knowledge Engine Laboratory. Come and make an appointment to watch the live broadcast!

Shanghai AI Lab, in collaboration with several scientific research institutions, proposed the GMAI-MMBench benchmark, which includes 284 downstream task datasets.

Shanghai Jiao Tong University, in collaboration with Shanghai AI Lab, has successfully developed a pre-trained protein language model ProSST with structure-aware capabilities.

Meta FAIR Laboratory released the material generation model FlowLLM, which improves the efficiency of generating stable materials by more than 300% compared with previous models.
