As the promise of artificial intelligence (AI) captivates biomedicine, few people are riding the wave like Priscilla Chan--because few people have her resources. Trained as a pediatrician, Chan and her husband, Facebook creator Mark Zuckerberg, co-run a philanthropy that launched in 2015 with the wildly ambitious--some would say quixotic--goal of curing, preventing, or managing every disease by the end of the century. The couple pledged nearly their entire fortune-- 45 billion then and more than 200 billion today--to the Chan Zuckerberg Initiative (CZI), which would also support their education and progressive causes. Recently, however, the foundation has wound down support for almost everything but science. And this week, CZI announced it is increasing its research spending, doubling down on AI, and vowing to meet Chan and Zuckerberg's biomedical goal even earlier--although CZI won't set a specific target.

The Chan Zuckerberg Initiative (CZI), the philanthropic organization created in 2015 by Priscilla Chan and her husband Mark Zuckerberg, announced a bold new generative AI initiative today. The group is funding and building a high-end GPU cluster that will use AI to create predictive models of healthy and diseased cells; it hopes they'll help researchers better understand the human body's cells and cellular reactions. The group believes the collection of computers will help it achieve its incredibly lofty goal of helping to "cure, prevent, or manage all diseases by the end of this century." "Researchers are gathering more data than ever before about the trillions of cells within our bodies, and it's too complex for our brains to grapple with," Jeff MacGregor, CZI vice president of communications, wrote in an emailed statement to Engadget. He lists an example of imaging one cell at nanometer resolution, which would use the same amount of data as 83,000 photos on a smartphone.

Priscilla Chan and Mark Zuckerberg are cofounders and co-CEOs of the Chan Zuckerberg Initiative. Cells are key to understanding disease--yet so much about them remains unknown. We do not know, for example, how billions of biomolecules come together to act as one cell. Nor do we know how our many types of cells interact within our bodies. We have limited understanding of how cells, tissues, and organs become diseased and what it takes for them to be healthy.

TileDB, the database for any complex data and compute, announced the launch of TileDB-SOMA, the first collection of software libraries that implement the open-source SOMA API specification. SOMA and TileDB-SOMA are the result of a collaboration between the Chan Zuckerberg Initiative and TileDB to accelerate single-cell research by eliminating data silos and enable large-scale computations that are otherwise too challenging to execute on commodity hardware. "By streamlining access to enormous datasets, powerful new tools like TileDB-SOMA will accelerate the research efforts of single-cell biologists" New technologies and analysis tools have led to the exponential growth of single-cell RNA sequencing (scRNA-seq) data, requiring new solutions that can accommodate datasets at scale. Advancements in genomics technologies have also enabled researchers to combine multiple modalities of data collected from the same cell samples, increasing the complexity and impact of single-cell analysis. "The unsaid assumption in single-cell research is that dataset size is bound by RAM, but instead of asking researchers to change their computational tools, we're rethinking how the data model itself could do more heavy lifting for scientists," said Stavros Papadopoulos, Founder & CEO, TileDB, Inc. "With TileDB-SOMA for R and Python, computational biologists can work across programming languages and combine data that was previously formatted specifically for Seurat, Anndata/Scanpy or Bioconductor. This breaks down data silos, and allows scientists to collaborate without the hassle of converting or duplicating data. Everyone can access the dataset, stored locally or in the cloud, at any scale."

Chan Zuckerberg Initiative co-founders and co-CEOs Mark Zuckerberg '06, L.L.D. '17 and Priscilla Chan '07, announced today a gift to establish the Kempner Institute for the Study of Natural and Artificial Intelligence at Harvard. The new institute, which will have dedicated space in the recently completed Science and Engineering Complex in Allston (see "A 500-Year Building"), is named after Karen Kempner Zuckerberg, the mother of the Meta CEO and founder (Facebook, Instagram, and WhatsApp are Meta Platforms Inc.'s best-known apps) and her parents. According to Jeff MacGregor, vice president of science communications for the Chan Zuckerberg Initiative (CZI), the Kempner Institute will receive $500 million in funding during the next 15 years. The gift will support 10 new faculty appointments, new computing infrastructure, and resources for students--from undergraduates to post-doctoral fellows--that will allow them to pursue knowledge in an uninhibited way across labs and disciplines. Zuckerberg and Chan, a pediatrician, will donate an additional $2.9 billion to support biomedical research focused on improving human health, with the aim of ultimately ending all human disease.

This story about Summit Learning was produced by The Hechinger Report, a nonprofit, independent news organization focused on inequality and innovation in education. Logan Dubin is good with computers. The 14-year-old speeds ahead when asked to use them to complete assignments. He finds it easy to teach himself with online content as his guide. "I just don't like doing work on an online platform," said Logan, an eighth grader at Rhodes Junior High in Mesa, Arizona. "It's better to have a teacher guiding you."

In a briefing on Monday, research leaders across tech, academia and the government joined the White House to announce an open data set full of scientific literature on the novel coronavirus. The COVID-19 Open Research Dataset, known as CORD-19, will also add relevant new research moving forward, compiling it into one centralized hub. The new data set is machine readable, making it easily parsed for machine learning purposes -- a key advantage according to researchers involved in the ambitious project. In a press conference, U.S. CTO Michael Kratsios called the new data set the "most extensive collection of machine readable coronavirus literature to date." Kratsios characterized the project as a "call to action" for the AI community, which can employ machine learning techniques to surface unique insights in the body of data.

U.S. health and technology specialists on Monday said they had launched a new collaborative venture to assemble a dataset of tens of thousands of scientific papers and literature on the coronavirus, which would then be analyzed by artificial intelligence programs to find patterns and answer questions raised by the World Health Organization about the pandemic. The dataset includes 29,000 articles, including 13,000 full-text pieces of medical literature, which will be made available on a special website allowing data scientists and artificial intelligence programmers to propose tools and software code that can unearth insights from the articles, White House officials and experts told reporters in a conference call. The venture came together after the White House Office of Science and Technology Policy issued a call to tech companies and research groups to figure out how artificial intelligence tools could be used to sift through thousands of research articles being published worldwide on the pandemic, said Lynn Parker, deputy chief technology officer at the White House office. With data scientists and machine language experts mining the literature compilation known as COVID-19 Open Research Dataset, experts and White House officials expect to get help developing vaccines, forming new guidelines on how long social distancing should be maintained and other insights, Michael Kratsios, the U.S. chief technology officer said. The venture includes the National Library of Medicine, which is part of the National Institutes of Health, Microsoft, Allen Institute of AI, Georgetown University's Center for Security and Emerging Technology, the Chan Zuckerberg Initiative (named for Mark Zuckerberg, Facebook's founder, and his wife Priscilla Chan), and Kaggle, which is a unit of Google.

Today, researchers and leaders from the Allen Institute for AI, Chan Zuckerberg Initiative (CZI), Georgetown University's Center for Security and Emerging Technology (CSET), Microsoft, and the National Library of Medicine (NLM) at the National Institutes of Health released the COVID-19 Open Research Dataset (CORD-19) of scholarly literature about COVID-19, SARS-CoV-2, and the Coronavirus group. Requested by The White House Office of Science and Technology Policy, the dataset represents the most extensive machine-readable Coronavirus literature collection available for data and text mining to date, with over 29,000 articles, more than 13,000 of which have full text. Now, The White House joins these institutions in issuing a call to action to the Nation's artificial intelligence experts to develop new text and data mining techniques that can help the science community answer high-priority scientific questions related to COVID-19. The collection was constructed via a unique collaboration between Microsoft, NLM, CZI, and the Allen Institute for AI, coordinated by Georgetown University. Microsoft's web-scale literature curation tools were used to identify and bring together worldwide scientific efforts and results, CZI provided access to pre-publication content, NLM provided access to literature content, and the Allen AI team transformed the content into machine-readable form, making the corpus ready for analysis and study.

Prime Minister Justin Trudeau reaffirmed his nerd-in-chief reputation and outlined his government's vision to capitalize on Canada's early lead in artificial intelligence, or AI, during an appearance today at the University of Toronto's Rotman School of Management. Trudeau, a self-professed "geek," was a special guest at an annual business of AI conference hosted by Rotman's Creative Destruction Lab (CDL), a seed stage accelerator that specializes in building AI-powered startups. Quizzed on his AI knowledge, Trudeau compared the technology to playing chess against a computer that not only made moves based on cold hard calculations, but "leaps of instinct" that mimic how the human brain works. "I think we all understand, certainly in this room, the way the world is going," Trudeau said during a 20-minute conversation with Shivon Zilis of Tesla, Bloomberg Beta and Open AI. "So let's be part of it and help shape it, and let's make sure we're benefiting from the innovations – in both the designing of them and the applications and the jobs." In recent years, Canada – and Toronto in particular – has emerged as a hotbed of AI activity thanks in part to fundamental research performed by people like U of T's University Professor Emeritus Geoffrey Hinton, who is known as the "godfather of deep learning" and works for Google, and U of T Associate Professor Raquel Urtasun, who is heading up Uber's self-driving car lab in Toronto.