The Chan Zuckerberg Initiative (CZI) has announced it is building the largest open-source computer system for non-profit life science research.
The computing cluster will comprise of over 1000 GPUs and allow AI and large language models (LLMs) to be used within widescale biomedical research.
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The AI leveraged by this computer will create predictive models of healthy and sick cells, allowing researchers to better understand disease cure and prevention.
Large AI systems could better automate and understand greater amounts of scientific data in less time.
Whilst current AI infrastructure to analyse such data is costly, the CZI has pledged to make its AI and LLM software open source. This would allow the CZI’s software to be openly available to researchers, something that CZI believes will enable closer collaboration between healthcare researchers.
CZI co-founder and co-CEO Priscilla Chan explains how this AI can benefit biomedical research.
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By GlobalData“AI models could predict how an immune cell responds to an infection, what happens at the cellular level when a child is born with a rare disease, or even how a patient’s body will respond to a new medication,” Chan explained.
The CZI’s predictive AI will be trained on datasets of information of over 50 million cells.
This training data will also be made publicly available.
CZI head of science, Stephen Quake, described the adoption of AI into healthcare as a “natural evolution” to its work.
“CZ Science has employed many AI tools in its research for years, and this focus will unify our collective efforts to create a field-wide resource for better understanding cells and cell systems,” Quake said.
Surveys conducted by research analyst GlobalData have consistently shown AI to be the most attractive investment target for businesses since 2018.
Global Data states that AI can be used to save the time and labour costs that accompany time consuming drug research and discovery processes.
As of May 2023, 22.4% of pharmaceutical companies surveyed by GlobalData reported that they were currently using generative AI in their daily work, whilst a further 20% answered that they were actively investigating the technology.
However, some industry scepticism towards the integration of AI into healthcare remains.
Despite having the power to speed up drug research and development, GlobalData research also analysed what pharma companies believed the be the biggest barriers in adopting AI.
Over 30% of respondents answered that AI also brought with it a high risk of misuse within the pharma sector, and a further 17% of businesses believed AI could pose ethical complications within healthcare.
In August 2023, the Australian Medical Association called for clearer and stricter AI regulation that is healthcare-specific. The demand was in response to hospital reports that doctors were using ChatGPT to write medical notes.
Despite this, the CZI has already used ChatGPT in its online encyclopedia CellGuide, which uses ChatGPT generated definitions.
By 2030, GlobalData predicts the global market of specialised AI applications to be worth around $505bn.
