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Chris von Csefalvay
12 quotes
“This is what coding agents are actually good for: not replacing programmers, but replacing the programmer-as-bureaucrat.”
Chris von Csefalvay first seen 2025 wikiquote, CC BY-SA 4.0 source
Recorded in: Dorkestration, 15 December 2025
“To me, agentic AI has always been about large scale emergence and self-organisation. This isn’t a matter of degree but qualitatively different. If you can draw it on a whiteboard, it may well be useful, possibly make decent dinner reservations, but it will not ever exhibit meaningful emergence (if you don’t believe me, try to draw every neuron of a modern convolutional neural network). It may be useful, but it’s not what I mean when I talk about agentic AI.”
Chris von Csefalvay first seen 2025 wikiquote, CC BY-SA 4.0 source
Recorded in: What I talk about when I talk about agentic AI, 01 November 2025
“I do think that the future of LLMs is not in the direction of the ‘big’ LLMs that are currently in vogue, but in the direction of smaller, more specialised LLMs that can interact with us, and with each other, in the role-defined and goal-directed agentic manner in which we as humans have interacted for our history.”
Chris von Csefalvay first seen 2023 wikiquote, CC BY-SA 4.0 source
Recorded in: Teams of Rivals, 30 October 2023
“Somewhere — perhaps in a tropical rainforest, perhaps in the thawing permafrost soil or maybe in one of our own cities — the next pathogen to try humanity’s resilience and resourcefulness is slowly emerging.”
Chris von Csefalvay first seen 2023 wikiquote, CC BY-SA 4.0 source
Recorded in: Data for the Next Pandemic, 7 March 2023
“Despite the advances of modern medicine, the challenges of global epidemics have only become greater. Habitat loss of viral reservoir species increases the likelihood of zoonotic spillover events. Our global trade and transportation networks enable pathogens to make their way around the world in 24 hours. Climate change is disrupting fragile ecosystems and global poverty, especially urban poverty, exacerbates the problem.”
Chris von Csefalvay first seen 2023 wikiquote, CC BY-SA 4.0 source
Recorded in: Data for the Next Pandemic, 7 March 2023
“It often takes years to create a viable antibody test as accurate as PCR-based testing. But in less than six weeks, biotech companies—approached by the U.S. government through the White House-created public-private partnership—have already seen their efforts bear fruit. This is a tribute to the incredible creative potential of the biotech sector, but it also shows the power of free enterprise, unshackled by government bureaucracy. It took more than America’s best scientists to rise to the occasion: it took a regulatory regime to let them do so.”
Chris von Csefalvay first seen 2020 wikiquote, CC BY-SA 4.0 source
Recorded in: A Remarkable Leap Forward, City Journal, April 21 2020
“Today, the efforts waged to curb the COVID-19 pandemic may be the first example of a large-scale, global data-driven response to a worldwide crisis, and as such perhaps the first war of data science.”
Chris von Csefalvay first seen 2020 wikiquote, CC BY-SA 4.0 source
Recorded in: COVID-19 and the First War of Data Science, 18 March 2020
“The term 'natural immunity' has been often used to express post-infectious immunity and differentiate it from vaccine-induced immunity. In practice, this is not necessarily helpful. There is nothing fundamentally "unnatural" in vaccine-induced immunity, and while the minutiae of natural infection and vaccine-induced immunity might differ, this is a quintessentially unhelpful notion.”
Chris von Csefalvay first seen 2023 wikiquote, CC BY-SA 4.0 source
Recorded in: Chris von Csefalvay, Modeling the control of infectious disease: Pharmacological and nonpharmacological interventions, in: Computational Modeling of Infectious Disease, Elsevier, 2023.
“Computational models of infectious disease can make all the difference in our response to pandemics. As habitat loss and climate change make zoonotic spillover events increasingly more likely, COVID-19 is almost certainly not the last major pan- demic of the 21st century. In fact, it is reasonable to assume that such outbreaks will become increasingly frequent. Computational models can be powerful weapons in our fight against pandemics.”
Chris von Csefalvay first seen 2023 wikiquote, CC BY-SA 4.0 source
Recorded in: Chris von Csefalvay, Preface, in: Computational Modeling of Infectious Disease, Elsevier, 2023.
“Hesiod’s description of Pandora’s box reminds us that though we live in a world of danger, where infectious diseases continue to maim and kill millions, especially across the developing world, we are not without hope. Part of that hope is our ability as humans to bring mathematics, genomics, data science, statistics, and computational science to bear on this problem and call these altogether rather disparate disciplines into humanity’s service against disease. Infectious disease modeling is part of that wider story of hope.”
Chris von Csefalvay first seen 2023 wikiquote, CC BY-SA 4.0 source
Recorded in: Chris von Csefalvay, Introduction: Why and how we model infectious disease, in: Computational Modeling of Infectious Disease, Elsevier, 2023.
“Some pathogens live exciting double lives, with entirely separate life cycles and be- haviors in different animals.”
Chris von Csefalvay first seen 2023 wikiquote, CC BY-SA 4.0 source
Recorded in: Chris von Csefalvay, Host-vector and multihost systems: Dynamics of host-vector transmission, in: Computational Modeling of Infectious Disease, Elsevier, 2023.
“The same dynamics that keep us safe in a pack, herd or society, and comfortable in our family, friends or neighbours also serves as a way for pathogenic transmissions. The warmth of a human dwelling or the immense complexity of a bee hive is also an opportunity for a pathogen to tap into a susceptible population. Network interdiction is a comprehensive name for algorithms intended to disrupt such connections.”
Chris von Csefalvay first seen 2023 wikiquote, CC BY-SA 4.0 source
Recorded in: Chris von Csefalvay, Spatial dynamics of epidemics: Epidemics in discrete and continuous space, in: Computational Modeling of Infectious Disease, Elsevier, 2023.