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Applying Deutsch's concept of good explanations to artificial intelligence and neuroscience -- an initial exploration

arXiv.org Artificial Intelligence

Artificial intelligence has made great strides since the deep learning revolution, but AI systems still struggle to extrapolate outside of their training data and adapt to new situations. For inspiration we look to the domain of science, where scientists have been able to develop theories which show remarkable ability to extrapolate and sometimes predict the existence of phenomena which have never been observed before. According to David Deutsch, this type of extrapolation, which he calls "reach", is due to scientific theories being hard to vary. In this work we investigate Deutsch's hard-to-vary principle and how it relates to more formalized principles in deep learning such as the bias-variance trade-off and Occam's razor. We distinguish internal variability, how much a model/theory can be varied internally while still yielding the same predictions, with external variability, which is how much a model must be varied to accurately predict new, out-of-distribution data. We discuss how to measure internal variability using the size of the Rashomon set and how to measure external variability using Kolmogorov complexity. We explore what role hard-to-vary explanations play in intelligence by looking at the human brain and distinguish two learning systems in the brain. The first system operates similar to deep learning and likely underlies most of perception and motor control while the second is a more creative system capable of generating hard-to-vary explanations of the world. We argue that figuring out how replicate this second system, which is capable of generating hard-to-vary explanations, is a key challenge which needs to be solved in order to realize artificial general intelligence. We make contact with the framework of Popperian epistemology which rejects induction and asserts that knowledge generation is an evolutionary process which proceeds through conjecture and refutation.


Council Post: Artificial Intelligence, Real Medicine

#artificialintelligence

Today, AI is used with increasing regularity across nearly every industry, with AI-based systems and technologies introducing new efficiencies, unlocking extraordinary opportunities and delivering powerful new insights and capabilities that were previously unattainable -- perhaps even unthinkable. Not only are health care and pharmaceuticals no exception to that rule, but life sciences actually represents one of the most innovative and exciting new frontiers for AI technology and machine learning. In recent years, AI usage has exploded in pharma, health care and biotech. Life sciences companies and institutions have used AI to develop and test new drugs, advance new therapeutics and treatment protocols, and, in some cases, completely transform the drug development and distribution process. The power and potential of AI-based technology in life sciences has arguably never been more important.


Council Post: Artificial Intelligence, Real Medicine

#artificialintelligence

Today, AI is used with increasing regularity across nearly every industry, with AI-based systems and technologies introducing new efficiencies, unlocking extraordinary opportunities and delivering powerful new insights and capabilities that were previously unattainable -- perhaps even unthinkable. Not only are health care and pharmaceuticals no exception to that rule, but life sciences actually represents one of the most innovative and exciting new frontiers for AI technology and machine learning. In recent years, AI usage has exploded in pharma, health care and biotech. Life sciences companies and institutions have used AI to develop and test new drugs, advance new therapeutics and treatment protocols, and, in some cases, completely transform the drug development and distribution process. The power and potential of AI-based technology in life sciences has arguably never been more important.


The Three Ghosts of Medical AI: Can the Black-Box Present Deliver?

arXiv.org Artificial Intelligence

Our title alludes to the three Christmas ghosts encountered by Ebenezer Scrooge in \textit{A Christmas Carol}, who guide Ebenezer through the past, present, and future of Christmas holiday events. Similarly, our article will take readers through a journey of the past, present, and future of medical AI. In doing so, we focus on the crux of modern machine learning: the reliance on powerful but intrinsically opaque models. When applied to the healthcare domain, these models fail to meet the needs for transparency that their clinician and patient end-users require. We review the implications of this failure, and argue that opaque models (1) lack quality assurance, (2) fail to elicit trust, and (3) restrict physician-patient dialogue. We then discuss how upholding transparency in all aspects of model design and model validation can help ensure the reliability of medical AI.


How The Department Of Veterans Affairs Uses AI To Help Vets

#artificialintelligence

Over the past decade, there's been no doubt that AI is positively impacting a number of industries, with medicine and healthcare being no exception. The use of AI and machine learning is already transforming many areas of the healthcare industry, ranging from patient-facing and customer service activities to improvements in overall care, diagnosis, and treatment. With the global pandemic being front-and-center in the minds of healthcare workers, pharmaceutical companies, and life sciences organizations around the world, AI has been applied to help physicians evaluate COVID-19-associated prognosis and needs. In particular, the US federal government has focused on AI in a variety of ways to address pressing needs. The Department of Veterans Affairs, a US Federal agency that provides healthcare services to eligible military veterans, and is the largest integrated health care system in the United States, is adopting AI to help address the wide ranging impacts of the global pandemic on the lives of patients and their families.


New experimental AI platform matches tumor to best drug combo

#artificialintelligence

Only 4 percent of all cancer therapeutic drugs under development earn final approval by the U.S. Food and Drug Administration (FDA). "That's because right now we can't match the right combination of drugs to the right patients in a smart way," said Trey Ideker, Ph.D., professor at University of California San Diego School of Medicine and Moores Cancer Center. "And especially for cancer, where we can't always predict which drugs will work best given the unique, complex inner workings of a person's tumor cells." In a paper published October 20, 2020 in Cancer Cell, Ideker and Brent Kuenzi, Ph.D., and Jisoo Park, Ph.D., postdoctoral researchers in his lab, describe DrugCell, a new artificial intelligence (AI) system they created that not only matches tumors to the best drug combinations, but does so in a way that makes sense to humans. "Most AI systems are'black boxes'--they can be very predictive, but we don't actually know all that much about how they work," said Ideker, who is also co-director of the Cancer Cell Map Initiative and the National Resource for Network Biology.


AI Weekly: AI-driven optimism about the pandemic's end is a health hazard

#artificialintelligence

As the pandemic reaches new heights, with nearly 12 million cases and 260,000 deaths recorded in the U.S. to date, a glimmer of hope is on the horizon. Moderna and pharmaceutical giant Pfizer, which are developing vaccines to fight the virus, have released preliminary data suggesting their vaccines are around 95% effective. Manufacturing and distribution is expected to ramp up as soon as the companies seek and receive approval from the U.S. Food and Drug Administration. Representatives from Moderna and Pfizer say the first doses could be available as early as December. But even if the majority of Americans agree to vaccination, the pandemic won't come to a sudden end.


Scientists Employing 'Chemputers' in Efforts to Digitize Chemistry

#artificialintelligence

A "chemputer" is a robotic method of producing drug molecules that uses downloadable blueprints to synthesize organic chemicals via programming. Originated in the University of Glasgow lab of chemist Lee Cronin, the method has produced several blueprints available on the GitHub software repository, including blueprints for Remdesivir, the FDA-approved drug for antiviral treatment of COVID-19. Cronin, who designed the "bird's nest" of tubing, pumps, and flasks that make up the chemputer, spent years thinking of a way researchers could distribute and produce molecules as easily as they email and print PDFs, according to a recent account from CNBC. "If we have a standard way of discovering molecules, making molecules, and then manufacturing them, suddenly nothing goes out of print," Cronin stated. Beyond creating the chemputer, Cronin's team recently took a second major step towards digitizing chemistry with an accessible way to program the machine.


New Products

Science

![Figure][1] AMS Biotechnology announces two chemically defined, cryopreservation excipient solutions: STEM-CELLBANKER and HSC-BANKER. Available in both dimethyl sulfoxide (DMSO)-containing and DMSO-free formulations, STEM-CELLBANKER is a chemically defined freezing media optimized for stem-cell and induced pluripotent stem-cell storage as well as fragile primary cell storage. Published data supports its ability to cryopreserve organoids and tissues to allow the recovery of viable cells. Free from animal-derived components, this popular medium contains only chemically defined U.S. Pharmacopeia (USP)-, European Pharmacopeia (EP)-, and Japanese Pharmacopeia (JP)-grade ingredients. Manufactured to be completely free of serum and animal-derived components, HSC-BANKER contains only EP- or USP-grade ingredients, making it highly suitable for storage of hematopoietic stem cells developed for cell-therapy applications. Recently the master files of HSC-BANKER were accepted by the Center for Biologics Evaluation and Research within the U.S. Food and Drug Administration. HSC-BANKER is supplied ready-to-use and requires no special devices, such as a controlled-rate freezer, to achieve consistently high viabilities following resuscitation from cryopreservation, even over extended long-term storage. HSC-BANKER significantly increases cell viability while maintaining cell pluripotency, normal karyotype, and proliferation ability after freeze-thaw. It is evaluated for endotoxins, pH, osmolarity, and mycoplasma contaminants to ensure GMP equivalent quality. The EAF2000 series from Postnova Analytics is a powerful and field-proven 2D field-flow fractionation (FFF) system, which can be applied as either traditional asymmetric flow FFF or alternatively as a hybrid FFF system utilizing both separation forces in the same channel simultaneously. This allows particle size and molar mass separations induced by the crossflow field as well as charge separations by electrophoretic mobility. As particle and molecule charge play a primary role in many applications, such as protein aggregation, polymer flocculation, particle agglomeration, and pharmaceutical formulations, the EAF2000 enables significantly better understanding of these phenomena and will help to establish more efficient product development and QC processes. TESTA Analytical Solutions has developed a new flowmeter that enables continuous measurement of flow rate without interference in chromatography systems. Flow rate is one of the most important parameters in any liquid chromatography system; it determines retention time or volume and has a major influence on reproducibility. Compatible with all high-performance liquid chromatography (HPLC) and gel permeation chromatography/size-exclusion chromatography (GPC/SEC) solvents, the TESTA flowmeter is conveniently sized and powers itself from a USB connection. A PC-based app allows continuous recording and storage of the measured flow rates. The current flow rate is also displayed on the flowmeter's integral high-resolution organic LED display, allowing easy control of current flow value. Extraordinary high resolution and wide dynamic range make the TESTA flowmeter the perfect flow-monitoring tool for the most demanding HPLC and GPC/SEC systems. Resolve Optics offers a service to design, develop, and supply application-optimized machine vision lenses for any industrial and robotic image-processing application. High-quality construction, coupled with precision engineering, results in outstanding machine vision lenses that deliver sharp, high-resolution, optically precise images. Our lenses provide wide fields of view with little or no distortion, optical designs and coatings that are balanced to give best performance at a desired wavelength or waveband, and compact lens designs where the target application is space-limited. Lonza Bioscience announces the release of the PyroCell Monocyte Activation Test (MAT) System, a sustainable, reliable solution for in vitro pyrogen testing. The new offering ensures the safety of parenteral pharmaceuticals during development, manufacture, and product release. It provides sensitive pyrogen detection without the use of experimental animals, thereby supporting sustainability objectives while helping to deliver safe products to the market. Through a collaboration with Sanquin Reagents B.V., the PyroCell MAT System consists of pooled, cryopreserved peripheral blood mononuclear cells (PBMCs) specifically developed for use with the MAT. These PyroCell Kit PBMCs eliminate the need to qualify blood donors and undertake cell isolation for each test run. With the PyroCell MAT System, the cells can be available whenever the need arises. The Atik VS series of scientific cooled charge-coupled device (CCD) cameras is flexible enough to meet the needs of both scientific OEMs and microscopy users. It provides a versatile solution for any low-light application, which simplifies the designer's task of integration and has an optional five-position integrated filter wheel allowing filters to be loaded without opening the camera. The VS series delivers the highest-quality images under low-light conditions, thanks to 16-bit digitization that offers 65,536 gray levels, plus high-performance thermoelectric cooling to –35°C below ambient. At 6 MP/s, the VS series offers the fastest digitization of any Atik camera. This range supports a wide variety of Sony CCD sensors, including ICX285, ICX274, ICX674, ICX655, ICX694, and ICX814. The VS255 and VS825 cameras are specifically for use with quantitative PCR instruments for accurate, reliable COVID-19 testing. [1]: pending:yes


FDA-approved Apple Watch NightWare app treats PTSD-linked nightmares

Daily Mail - Science & tech

An app designed for Apple Watch has received approval from the Food and Drug Administration (FDA) for an effective treatment for nightmares caused by post-traumatic stress disorder (PTSD). Called NightWare, the application is now marketed as an aid for the'temporary reduction of sleep disturbances related to nightmares in adults.' The app uses Apple Watch sensors to monitor body movement and sleep and when it detects the user is experiencing a nightmare, the device will vibrate to disturb their sleep. NightWare is currently only available with a prescription and the company stresses it is not a standalone treatment for PTSD. Approximately eight million Americans suffer from PTSD and up to 96 percent of them have nightmares as a result.