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We live in a golden age for research.<\/p>\n
Never before have we had the opportunity to make such rapid advances in computer science, and apply them so quickly to global-scale challenges, in a way that can help people in their daily lives. Since the start of my career, I\u2019ve been excited by the \u201cmagic cycle\u201d of research, where real-world challenges motivate new foundational and applied research, which in turn has a positive impact in the real world. Today, with the right infrastructure, talent and approach, we\u2019re able not only to make rapid breakthroughs in everything from AI to algorithms to computing infrastructure, but to put those technologies to work to improve people\u2019s daily lives and have societal impact faster than ever before, sometimes in a matter of months.<\/p>\n
I\u2019m seeing this firsthand as I\u2019ve recently stepped up to lead Google Research, so I wanted to share a perspective on the incredible progress we\u2019re seeing \u2014 and how important research is in driving helpful innovation.<\/p>\n
Google itself in fact began with research. \u201cThe anatomy of a large-scale hypertextual Web search engine,\u201d published in 1998, explored how PageRank could provide a fundamentally better way to find info on the web, But it didn\u2019t stop with a research paper \u2014 it was applying that research that produced Google. Over the past 26 years, that approach to implementing research \u2014 quickly \u2014 has transformed not only our company, but also how people can interact with the world\u2019s information. Indeed, much of the rapid progress in AI we see all around us today grew from Google Research\u2019s invention of the Transformer.<\/p>\n
In all of our research, we ask ourselves: How can we make a step change, not just incremental? What\u2019s impossible today, that we could make possible? And what is the greatest impact we can have \u2014 how can this make a real difference in the world?<\/p>\n
Google Research today includes fundamental and applied work in foundational machine learning and algorithms, computing systems and quantum AI, and science, AI & societal impact. And across all these domains, we run initiatives on efficiency in machine learning, factuality & grounding in AI systems, and new data techniques.<\/p>\n
We motivate our research by going after the biggest questions that matter to advance science and make a difference to people and to communities globally. What are the most effective ways to mitigate climate change? How can we help make billions of people healthier? How can we enable new experiences? And to do all this, can we break through limitations in computing and AI systems? Each of those becomes an inspiring research challenge \u2014 and in so many cases we\u2019ve already translated research into solutions.<\/p>\n
For example, to address climate change, in a trial with American Airlines we used AI to help reduce contrails by 54%, demonstrating that airlines can verifiably avoid contrails and thereby reduce their climate impact. To help address the growing wildfire crisis, we partnered with leading wildfire authorities to develop FireSat, an upcoming AI-powered global satellite constellation to detect and track wildfires the size of a classroom \u2014 within 20 minutes. And consider flood forecasting \u2014 when our team at Google Research began the project in 2018, experts I met with said it was likely impossible to forecast riverine floods. But by developing AI that can build a global hydrologic model, we\u2019ve not only proven it\u2019s possible, but applied it to provide communities accurate early warnings and help save lives.<\/p>\n
Meanwhile, to support health and wellbeing, we\u2019ve developed AI that can help screen for breast cancer and colorectal cancer, help prevent blindness at scale, spot potential skin conditions and detect diseases based on the sound of coughs. We\u2019re still in the earliest days of AI breakthroughs and genomics research, and yet we\u2019ve made progress with Large Language Models for the medical domain and we\u2019re already poised to improve the health care for hundreds of millions of people.<\/p>\n
But perhaps one of the biggest undertakings involves advancing computing itself, and how it can fundamentally alter the scope of problem-solving. We\u2019ve developed state-of-the-art attention models and use graph mining to improve retrieval quality. We\u2019re also working on approaches to grounding large language models, such as by training models to rely on source documents for summarization and evaluating factual consistency. This research has led to improvements like the double-check feature in the Gemini app. We\u2019ve made AI more efficient with research on speculative decoding, efficient inference techniques, and cascades, and we\u2019ve helped improve privacy with federated learning and differential privacy. And our quantum computing team just published new results in Nature<\/i> affirming that as we reduce the error rate in our quantum processors, we reach levels of computation that can\u2019t be matched by even the world\u2019s most powerful classical computers \u2014 putting us on track to crack open an entirely new computational capability for the world.<\/p>\n
These are just a few examples of the type of work done across Google Research.<\/p>\n
Of course, as we turn research towards impact, we\u2019re acutely aware that technology is not automatically beneficial \u2014 you can’t “invent it and forget it,” simply releasing powerful technologies on the naive assumption that they will be helpful. It requires careful stewardship, partnership and a fundamentally human-centric view of how to design and guide emerging technologies. That\u2019s one reason we do our research in partnership with a multitude of researchers in academia and many others, while creating tools and best practices that support a truly global research ecosystem with the aim of steering new technologies towards beneficial outcomes. We actively engage in advancing socio-technical research to bolster our AI principles \u2014 including on equitable datasets, interpretability, and algorithmic fairness \u2014 and there\u2019s important work ahead to make our AI models even more efficient, factual, robust and safe.<\/p>\n
We have the greatest impact when we\u2019re working with research partners. Since 2005, Google has worked with more than 1,000 research institutions and invested over $400 million dollars in academic research worldwide, much of this led by Google Research. We find experts across disciplines, roll up our sleeves, dive into the research, and make scientific advances together. In our connectomics research, we\u2019ve partnered with Harvard to use AI to make the most detailed mapping yet of neurons in the human brain, revealing newly discovered structures \u2014 all towards helping scientists understand fundamental processes such as thought, learning and memory. Google Research also engaged in a first-of-its-kind collaboration with Howard University and other HBCUs to build a high-quality African-American English (AAE) speech dataset that Google \u2014\u00a0and others \u2014\u00a0will use to improve speech products. This is related to our overall effort to reduce barriers and better serve communities by enabling technology to work in many more languages.<\/p>\n
With our partners, and through Google\u2019s own products, we use our research advances to benefit billions of people. For example, as populations swell and shift in the Global South, millions of people\u2019s buildings aren\u2019t represented on any map, and they risk missing out on essentials like electricity, healthcare and mail delivery. So Google Research in Africa has used AI to make big improvements to the Open Buildings dataset \u2014 transforming blurry, low-res satellite imagery into useful, high-res building outlines so partners like the World Bank, the World Resources Institute, UN Habitat, WorldPop and Sunbird AI can use it to ensure global development includes everyone. Along with our SKAI effort, this has helped our partnership with the UN to boost damage assessment.<\/p>\n
In another sphere, our Operations Research team recently showed how cargo shippers could double their profit, deliver 13% more containers and use 15% fewer ships. This is not only helpful for businesses, but good for supply chains globally.<\/p>\n
Finally, we of course partner extensively with product teams to drive innovation across Google \u2014 and our responsibility also includes keeping an eye on the horizon, exploring the art of the possible, and imagining how we can apply our breakthrough technologies for maximum benefit in years to come.<\/p>\n
We feel great urgency given the scope of problems facing humanity \u2014 but also great optimism because of what we\u2019ve been able to do already. Our multi-decade track record shows that Google Research is second-to-none in delivering helpful advances. We\u2019ve delivered breakthroughs that have shaped Google’s identity as a company, helped inaugurate new fields in computer science, and advanced the frontiers of innovation and technology with thousands of publications. The advances we\u2019ve shared are already assisting people \u2013 from their everyday tasks, to their most ambitious and imaginative endeavors \u2014 and addressing society\u2019s most pressing challenges, from healthcare to education to climate change and climate science.<\/p>\n
We’ll keep sharing our breakthroughs on our Google Research blog, at conferences and at other events. We’re eager to explore \u2014 and invent \u2014 the future alongside all the partners and communities we work with.<\/p>\n<\/div>\n