In a world where unmanned spacecraft have landed on Mars and artificial intelligence can read your mind, one would think someone would have figured out a precise way to measure how much athletes should drink while exercising. Hydrating, or replacing body fluids lost through sweating, exhaling, and eliminating waste, is essential. When 2 or more percent of body mass is lost through dehydration, the body can go haywire, with elevated cardiovascular strain, reduced aerobic exercise performance, and impaired thermoregulatory function. After losing 12 percent of body mass to dehydration, a human will die. It's rare for an athlete to exercise to the point of death by dehydration.

We began to speak and we learnt to express. We began to get curious, and we uncovered the mysteries of the universe. We climbed the food chain, we proclaimed our superiority. But some thirsts are insatiable. To match our own intelligence and surpass the pace, we crafted Artificial Intelligence. From self-driving cars to smart voice assistants, face recognition to endless Newsfeed at Facebook, AI defeating former Go champion Lee Se-dol to Netflix movie recommendations; we have awed in the possibilities of AI.

Claire Stevenson started her academic career in the field of developmental psychology, where she researched children's learning potential: 'so not what they already know, but what they are capable of.' She examined the development of analogical reasoning in children, i.e. their ability to find solutions to new problems based on relationships with familiar ones. 'For example, children were asked to complete the sequence: thirst is to drinking as bleeding is to bandage, wound, cutting, water or food? If you want to find the right answer, you need to apply the relationship between thirst and drinking to bleeding, instead of using familiar associations like wound or cutting.' Analogical reasoning is considered the greatest strength of human intelligence. Later on in her career, Stevenson switched to the Psychological Methods programme group, where she became fascinated by the idea of applying mathematical models to measure creative processes.

CATEGORY WINNER: CELL AND MOLECULAR BIOLOGY William E. Allen William E. Allen received his undergraduate degree from Brown University in 2012, M.Phil. in Computational Biology from the University of Cambridge in 2013, and Ph.D. in Neurosciences from Stanford University in 2019. At Stanford, he worked to develop new tools for the large-scale characterization of neural circuit structure and function, which he applied to understand the neural basis of thirst. After completing his Ph.D., William started as an independent Junior Fellow in the Society of Fellows at Harvard University, where he is developing and applying new approaches to map mammalian brain function and dysfunction over an animal's life span. [ www.sciencemag.org/content/370/6519/925.3 ][1] Charting what the pioneering neuroanatomist Santiago Ramón y Cajal called the “impenetrable jungle” of the brain ([ 1 ][2]) presents one of biology's greatest challenges. How do billions of neurons, wired through trillions of connections, work together to produce cognition and behavior? Like an orchestra, wherein many instruments played simultaneously produce a sound greater than the sum of its parts, thought and behavior emerge from communication between ensembles of molecularly distinct neurons distributed throughout vast neural circuits. Although we know much about the properties of individual genes, cells, and circuits (see the figure, panel A), a vast gap lies between the function of each brain component and an animal's behavior. Bridging this gap has proven technically and conceptually difficult. Inspired by the fact that the development of high-throughput DNA sequencing led geneticists to shift focus from individual genes to the entire genome, I wanted to develop approaches that could simultaneously link multiple levels of the brain, from molecules to neurons to brain-wide neural networks. My goal was to capture a global perspective while maintaining the high resolution and specificity necessary to understand the function of individual components at each level. This new viewpoint, I hoped, would reveal how the collective properties of the brain's building blocks give rise to behavior. During my doctoral studies at Stanford University with Karl Deisseroth and Liqun Luo, I developed new methods to map the architecture and activity of mammalian neural circuits. I applied these approaches to understand the neural basis of thirst, a fundamental regulator of behavior ([ 2 ][3]). Need-based motivational drives, such as hunger and thirst, direct animals to satisfy specific physiological imperatives important for survival ([ 3 ][4]). Despite decades of research, at the beginning of my studies it was unclear how the activity of neurons that sense these needs causes an animal to engage in specific motivated behaviors (e.g., eating or drinking) to maintain homeostasis ([ 3 ][4]). Thirst, a relatively simple yet important drive, thus seemed the perfect model system for investigating multiple levels in the brain. I first traced thirst motivational drive from cellular gene expression to a circuit mechanism. Using a new version of targeted recombination in active populations (TRAP2), a tool to genetically label neurons according to their activity, I found that neurons in the median preoptic nucleus (MnPO) of the hypothalamus became activated in thirsty mice ([ 4 ][5]) (see the figure, panel C). Single-cell RNA sequencing revealed that these neurons formed a single molecularly defined cell type. Artificial activation of these neurons caused mice to drink water within seconds, whereas their inhibition prevented mice from drinking, which suggested that these MnPO neurons were master regulators of thirst. Drinking water also gradually reduced the activity of these neurons. Finally, activation of these neurons was aversive. Together, these results suggested a surprising “drive reduction” model of thirst motivation: Genetically hard-wired thirst neurons become active when mice need hydration, which causes mice to drink water. This ability to ascribe specific functional relevance to genetically defined neurons inspired me to develop new techniques to map cells within their native tissue architecture in even greater molecular detail. To this end, I co-developed STARmap, an approach for highly multiplexed in situ RNA sequencing to measure the expression of hundreds of genes simultaneously within a brain section at the level of single mRNA molecules ([ 5 ][6]) (see the figure, panel B ). In combination with genetic markers of activity, this technique powerfully describes the molecular identity of behaviorally activated neurons and their neighbors at single-cell resolution. ![Figure][7] New large-scale, high-resolution approaches to bridging multiple levels of brain function A new approach to brain function mapping. (A) An illustration of the levels of brain function and how they are interlinked. (B to D) New approaches to bridging levels: (B) STARm ap amplicons barcoding 1020 RNA species simultaneously with single-molecule resolution in the mouse visual cortex. (C) Genetic labeling of neurons according to activity reveals thirst neurons in the median preoptic nucleus of the hypothalamus, used to identify the motivational mechanism of thirst drive. (D) Brain-wide activity map of the response of thousands of neurons across dozens of brain regions to a water-predicting sensory cue, in thirsty or sated mice, reveals widespread broadcasting of thirst state. GRAPHIC: N. DESAI/ SCIENCE FROM W. ALLEN, WANG ET AL . ([ 5 ][6]), ALLEN ET AL . ( 4 ), ALLEN ET AL . ([ 9 ][8]) Despite these insights, a question remained: How do thirst-sensitive neurons deep in the brain coordinate activity in distributed circuits spanning sensory perception, cognition, and motor output to produce motivated behavior? I found that MnPO thirst neurons projected to many brain regions potentially serving different behavioral roles ([ 4 ][5]), but the gap between individual neurons and brain-wide networks was daunting. Earlier in graduate school, I had developed several new microscopy techniques to characterize brain-wide ([ 6 ][9]) or neocortex- wide ([ 7 ][10]) activity, which revealed that global neural activity was present during even simple motivated behaviors. However, because of the mammalian brain's opacity, these approaches were limited in their ability to record fast neural activity throughout the brain at the scale required to understand thirst motivation. Fortunately, however, developments in microelectronics enabled me to construct global maps of neuronal activity with microsecond-level temporal resolution. Using advanced “Neuropixels” probes ([ 8 ][11]), thin silicon needles that can be acutely inserted into the brain to record the electrical signals of hundreds of neurons simultaneously, I developed an experimental approach to record the activity of huge neuronal ensembles across the brain and reconstruct the anatomical location of each recorded cell ([ 9 ][8]). Applying this technique, I mapped the brain-wide flow of activity through ∼24,000 single neurons during thirst-motivated behavior ([ 9 ][8]) (see the figure, panel D). My experiments revealed that this simple behavior produced an unexpectedly global coordination of activity throughout the brain. By observing how activity changed as mice drank water, as well as directly stimulating hypothalamic thirst neurons, I showed that this activity wave was dependent on the animal's motivational state. Surprisingly, the activity of a few hundred thirst neurons instantly modulated the state of the entire brain. Even more surprisingly, I found many neurons, distributed throughout the brain, that directly encoded thirst. These results suggest that even simple behaviors, such as thirst, are emergent properties of the entire brain. I hope these new approaches will at last enable us to comprehend the rules that transform distributed patterns of electrical activity in neural circuits into thoughts, emotions, and perceptions. Understanding how molecules, neurons, and networks interact to shape these rules will have a sweeping impact on our understanding of brain function in health and disease. 1. [↵][12]“Mas, por desgracia, faltábanos el arma poderosa con que descuajar la selva impenetrable de la substancia gris…” ([ 10 ][13]). 2. [↵][14]1. C. A. Zimmerman, 2. D. E. Leib, 3. Z. A. Knight , Nat. Rev. Neurosci. 18, 459 (2017). [OpenUrl][15][CrossRef][16][PubMed][17] 3. [↵][18]1. S. M. Sternson , Neuron 77, 810 (2013). [OpenUrl][19][CrossRef][20][PubMed][21][Web of Science][22] 4. [↵][23]1. W. E. Allen et al ., Science 357, 1149 (2017). [OpenUrl][24][Abstract/FREE Full Text][25] 5. [↵][26]1. X. Wang et al ., Science 361, eaat5691 (2018). [OpenUrl][27][Abstract/FREE Full Text][28] 6. [↵][29]1. L. Ye et al ., Cell 165, 1776 (2016). [OpenUrl][30][CrossRef][31][PubMed][32] 7. [↵][33]1. W. E. Allen et al ., Neuron 94, 891 (2017). [OpenUrl][34][CrossRef][35][PubMed][36] 8. [↵][37]1. J. J. Jun et al ., Nature 551, 232 (2017). [OpenUrl][38][CrossRef][39][PubMed][40] 9. [↵][41]1. W. E. Allen et al ., Science 364, eeav3932 (2019). [OpenUrl][42] 10. [↵][43]1. S. Ramón y Cajal , Recuerdos de mi vida: Historia de mi labor científica (Moya, Madrid, 1917). 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This was the year we all began social distancing. But the ensuing isolation was already the norm for a rapidly growing population – and a major opportunity for many businesses. And as isolation has engulfed the globe like the virus itself, the business of loneliness is booming. Even before the pandemic, loneliness had been deemed an official epidemic in several countries. Rates of loneliness in the US have doubled over the past 50 years.

We experience thirst every day, but where does this sensation come from? In the 1950s, Bengt Andersson proposed a tantalizing answer: Our brains might contain an “osmosensor” ([ 1 ][1]) that governs thirst, which consists of a group of cells that sense when we are dehydrated by directly monitoring the osmolarity of the blood. In a series of pioneering experiments , Andersson systematically infused salt into the brains of goats in an attempt to locate this osmosensor ([ 2 ][2], [ 3 ][3]). He ultimately discovered a small area within the hypothalamus where even minute amounts of salt triggered immediate, voracious drinking. Subsequent studies established that Andersson's osmosensor encompasses the subfornical organ (SFO), a brain region that is distinctively suited to detecting blood osmolarity because it lies outside the blood-brain barrier ([ 4 ][4]). The osmosensor model is powerful because it explains how dehydration generates thirst, but it has a crucial shortcoming: Drinking behavior is regulated on a fast, moment-by-moment basis that cannot be explained by slow changes in blood osmolarity. Consider that drinking immediately satiates thirst, even though the water imbibed is not absorbed for many minutes ([ 5 ][5], [ 6 ][6]), and that eating stimulates prandial drinking long before the ingested food enters the bloodstream ([ 7 ][7], [ 8 ][8]). How does the brain bridge these disparate time scales to dynamically adjust our sense of thirst? I reasoned that we might gain new insight into this longstanding question by recording the activity of thirst-promoting neurons in living animals. My colleagues and I thus began by genetically labeling the SFO neurons that comprise Andersson's osmosensor and confirming that these cells are essential for dehydration-induced drinking ([ 9 ][9]). We then set out to observe the neural dynamics underlying thirst in behaving mice ([ 10 ][10], [ 11 ][11]). If SFO neurons are genuine osmosensors, then we would expect them to simply encode an animal's dehydration level. Consistent with this idea, our initial fiber photometry recordings demonstrated that these neurons are dose-dependently activated by increases in blood osmolarity ([ 10 ][10]). It was therefore surprising to discover that SFO neurons are also rapidly regulated during eating and drinking, well in advance of any impact food and drink might have on the blood ([ 10 ][10]). For example, their activity decreases every time a mouse licks from a water bottle and increases with every bite of food. This counterintuitive finding indicated that SFO neurons—long viewed as merely passive sensors of dehydration—must receive a second class of signals that operate on the fast time scale of behavior. To pinpoint the origin of these signals, we traced the flow of water through the digestive tract of the mouse. We found that fluid detection in the mouth triggers a near-instantaneous inhibitory signal that closely tracks the volume ingested ([ 10 ][10]). Temperature sensing contributes to this process—SFO neurons are most efficiently inhibited by drinking cold water, a phenomenon that could be reproduced through isolated oral cooling. This may explain why we experience cold drinks as especially thirstquenching and pleasurable ([ 12 ][12], [ 13 ][13]). Using an intragastric infusion paradigm, we next discovered that the osmolarity of ingested fluids is precisely measured in the gastrointestinal tract and then rapidly transmitted to the brain by the vagus nerve ([ 11 ][11]). This gut-to-brain osmolarity signal sustains the inhibition of SFO neurons produced by oral volume signals and satiates thirst if pure water is drunk. By contrast, detection of hypertonic fluids in the gut causes SFO activity to rebound to the “thirsty” state. Thus, drinking generates layers of signals that enable thirst neurons to predict how ingested fluids will affect hydration in the future and then adjust drinking preemptively. This simple model explains how drinking can rapidly quench thirst yet also be properly calibrated to match an animal's level of dehydration ([ 5 ][5], [ 6 ][6]). Does the body notify the thirst system about other behaviors that affect hydration? We found that eating triggers additional signals that activate SFO neurons in anticipation of food absorption ([ 10 ][10]). This activation drives prandial drinking or, if water is unavailable, suppresses further feeding. This suggests a neural basis for the widespread coordination of eating and drinking ([ 7 ][7], [ 8 ][8]). To test the causal role of the body-tobrain signals identified by our recording experiments, we used optogenetics to precisely manipulate each of them during behavior. This allowed us to confirm that these signals are necessary for thirst satiation, prandial thirst, and dehydration-induced anorexia ([ 10 ][10], [ 11 ][11]), and thus account for most normal drinking behavior. The discovery of diverse inputs to SFO neurons raises the fundamental question of how signals are processed by the individual cells that comprise the thirst system. Do they flow in segregated “streams” or do they interact? To answer this question, we used microendoscopic imaging to track the activity of single neurons during dehydration, drinking, and intragastric infusion ([ 11 ][11]). This revealed a simple processing logic : The signals arising from the mouth, gut, and blood converge onto the same individual thirst neurons, thereby enabling every cell to continuously integrate information about current hydration status with the predicted consequences of ongoing ingestion. In a parallel series of experiments, we showed that downstream brain regions use this integrated representation to coordinate the various components of the body's response to dehydration, including not only drinking but also cardiovascular adjustments, hormone secretion, and changes to emotional valence ([ 11 ][11], [ 14 ][14]). Thirst is governed by a sensory system, analogous to vision or hearing. Unlike these exterosensory systems, however, the neural dynamics underlying thirst were previously unknown. Our recordings revealed that thirst is regulated by layers of signals that arise throughout the body and converge onto individual neurons in the forebrain. This convergence occurs at the first node in the thirst system—the SFO—and generates a real-time estimate of the body's need for water that downstream nodes use to dynamically adjust drinking, valence, and cardiovascular physiology ([ 10 ][10], [ 11 ][11], [ 14 ][14]). Our findings reveal fundamental principles that govern ingestive behavior ([ 15 ][15], [ 16 ][16]) and provide neural mechanisms that can potentially explain long-enigmatic elements of everyday human experience, including the speed of thirst satiation, the prevalence of drinking during meals, and the thirst-quenching power of oral cooling. GRAND PRIZE WINNER Christopher Zimmerman Christopher Zimmerman received his undergraduate degrees from the University of Pittsburgh and a Ph.D. from the University of California, San Francisco. His thesis research focused on the neural mechanisms that govern thirst and drinking behavior. Zimmerman is currently a postdoctoral fellow at the Princeton Neuroscience Institute, where he continues to study the neural processes underlying motivated behaviors. FINALIST Tara LeGates Tara LeGates received her B.S. in Biopsychology from Rider University and a Ph.D. from Johns Hopkins University. She completed a postdoctoral fellowship at the University of Maryland School of Medicine, where she established the importance of the strength and plasticity of hippocampus-nucleus accumbens synapses and reward behavior. LeGates is now an assistant professor at the University of Maryland, Baltimore County (UMBC). Her lab studies how neuronal circuits integrate information to regulate behavior and their alterations in psychiatric disorders. [www.sciencemag.org/content/370/6512/46.1][17] FINALIST Riccardo Beltramo Riccardo Beltramo received his undergraduate degree from the University of Turin and a Ph.D. from the Italian Institute of Technology. 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Artificial intelligence offers boundless possibilities. Despite currently being used for solving practical tasks, experts believe we are only viewing the tip of the iceberg. But even the tip looks incredible already. Imagine playing a game of strategy and having a completely customized scenario, instead of following one of the scripted few. A personalized gaming reality, with unique conversations and decisions made right there and then.

AI means a lot of things to a lot of people. Usually what it means is not very well thought out. It is felt, it is intuited. It is either adored, worshipped or deemed blasphemous, profane, to be feared. In this article, I explore what society at large really means by artificial intelligence as opposed to what researchers or computer scientists mean. I want to clarify for the non-technical audience what can realistically be expected from AI, and more importantly, what is just unrealistic pie-in-the-sky speculation.

As the age of AI approaches, the question of whether robots can replace teachers looms larger. Anthony Seldon, vice chancellor of the University of Buckingham, predicts that robots will replace teachers by 2027, less than a decade away. Some say that robots can never replace teachers because teachers inspire us. But, in another article, Seldon, says "inspirational robots" are possible and can be adapted to each student's individual learning style. The idea of robot teachers may sound appealing on some levels because teachers are expensive and in increasingly short supply.

What better way to get killer robots to do what you want them to do -- get them addicted to vodka. The AI killer robots used by the Russian army are heavy duty alcoholics who feast on copious amounts of vodka. Russian army technician, Colonel Vladimir Dimitrov, revealed how the AI killer robots have to quench their thirst. "We first get them used to the vodka. For a few months they are pumped with the good stuff, then we suddenly withdraw all vodka. The robots naturally go crazy, their addiction is so so great they will do anything for their next fix. This is when we ask them to kill everything in sight, and afterwards they get a big tanker of vodka for a reward."