In some ways, it already has - Experts highlight American role in Ukraine's unbelievable AI military development - Baltimore union denies school principal went on'ungrateful Black kids' rant, calls it an AI fraud ROBOT IQ: The rapid development of artificial intelligence has led some to fear dangerous scenarios where the technology is smarter than the humans who created it, but some experts believe AI has already reached that point in certain ways. FORMIDABLE WARRIORS: Ukraine's artificial intelligence (AI) development continues at a frightening pace beyond that of even tech giants in the U.S. and China as the war with Russia lurches toward a third year, but experts highlighted America's critical role in helping that rapid advance. RUSH TO JUDGMENT?: A Baltimore, Maryland school district has launched an investigation after a high school principal was allegedly recorded making racist comments to students and staff. And AI is being blamed. Baltimore County Public Schools said it launched an internal investigation after an audio recording claiming to capture the principal of Pikesville High School making offensive comments circulated online.

A Baltimore, Maryland school district has launched an investigation after a high school principal was allegedly recorded making racist comments to students and staff. In a Wednesday email to parents, Baltimore County Schools superintendent Myriam Rogers said that while the statements were "deeply disturbing," the district could not "confirm the veracity of this recording at this time." "I understand how upsetting this recording is for many members of the Team BCPS community," Rogers said, according to a report in WMAR2 News. "We will not tolerate disparaging remarks about any member of the Team BCPS community." Things became more perplexing after The Council of Administrative & Supervising Employees (CASE), the union representing Pikesville High School Principal Eric Eiswert, claimed the recording was fraudulent and generated using artificial intelligence (AI).

In 1918, the American chemist Irving Langmuir published a paper examining the behavior of gas molecules sticking to a solid surface. Guided by the results of careful experiments, as well as his theory that solids offer discrete sites for the gas molecules to fill, he worked out a series of equations that describe how much gas will stick, given the pressure. Now, about a hundred years later, an "AI scientist" developed by researchers at IBM Research, Samsung AI, and the University of Maryland, Baltimore County (UMBC) has reproduced a key part of Langmuir's Nobel Prize-winning work. The system--artificial intelligence (AI) functioning as a scientist--also rediscovered Kepler's third law of planetary motion, which can calculate the time it takes one space object to orbit another given the distance separating them, and produced a good approximation of Einstein's relativistic time-dilation law, which shows that time slows down for fast-moving objects. A paper describing the results is published in Nature Communications on April 12.

Cyber Threat Intelligence (CTI) is information describing threat vectors, vulnerabilities, and attacks and is often used as training data for AI-based cyber defense systems such as Cybersecurity Knowledge Graphs (CKG). There is a strong need to develop community-accessible datasets to train existing AI-based cybersecurity pipelines to efficiently and accurately extract meaningful insights from CTI. We have created an initial unstructured CTI corpus from a variety of open sources that we are using to train and test cybersecurity entity models using the spaCy framework and exploring self-learning methods to automatically recognize cybersecurity entities. We also describe methods to apply cybersecurity domain entity linking with existing world knowledge from Wikidata. Our future work will survey and test spaCy NLP tools and create methods for continuous integration of new information extracted from text.

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][1] Rewards are powerful stimuli that drive and reinforce goal-directed behaviors. There are a variety of factors that contribute to this process—such as motivation, anticipation, and contextual information—that are encoded in different brain regions. As a result, normal reward-related behaviors require proper functional integration of signals from multiple brain regions, but the essential pathways and underlying mechanisms of integration remain elusive. We have found that a critical mediator of this behavior is the connection between the hippocampus and nucleus accumbens (NAc) ([ 1 ][2]). The NAc receives information from multiple brain regions and must integrate it to process rewarding stimuli and modulate hedonic responses ([ 2 ][3]–[ 4 ][4]). We were particularly interested in examining the excitatory input from the hippocampus because this region is involved in mediating contextual learning and memory, which are critical to an organism's ability to return to the location of a previous reward to obtain that reward again. Previous work provided evidence that the hippocampus and NAc are linked, implicating the potential importance of this connection in reward signaling ([ 4 ][4]–[ 8 ][5]). Hippocampal input to the NAc drives neuronal activity ([ 4 ][4], [ 9 ][6]), and rewarding stimuli such as cocaine strengthen the connectivity between these two nuclei ([ 10 ][7]). Thus, we hypothesized that plasticity of these excitatory synapses is a critical regulator of reward-related behaviors. Using whole-cell electrophysiology in mouse brain slices, we demonstrated that hippocampus-NAc synapses can be strengthened in an activity-dependent manner through long-term potentiation (LTP). We dissected the molecular mechanisms underlying this potentiation and found that it requires canonical N -methyl-d-aspartate receptor–dependent pathways in the hippocampus ([ 11 ][8]) but is independent of dopamine receptor signaling. This was surprising because activity of the dopamine-1 receptor (D1) is required for the induction of LTP at other excitatory synapses in the NAc ([ 12 ][9]–[ 15 ][10]). Although these slice experiments were informative for establishing plasticity and its underlying mechanisms, the question remained as to whether LTP can be induced at the hippocampus-NAc synapse in vivo. Using high-frequency optogenetic stimulation of these synapses, we demonstrated that they are capable of undergoing LTP in vivo. To determine the relevance of this potentiation in regulating reward-related behaviors, we combined our optogenetic approach with the conditioned place preference (CPP) paradigm. This task uses a two-chamber arena connected by a corridor, and mice are alternatively confined to each chamber—one containing a reward, one containing no reward—over multiple days. When the mice are later allowed free access to the arena, they spend more time in the chamber that had been previously paired with the reward, showing CPP. Rather than presenting a reward during conditioning, we optogenetically induced LTP while mice were confined to one of the chambers. Potentiation of these synapses in the absence of any external rewarding stimuli was sufficient to induce CPP. (The brief, highfrequency stimulation during the conditioning phase occurred at least 24 hours before testing CPP, showing that potentiation of this synapse produces long-lasting effects on reward behavior.) Our results clearly demonstrated that excitatory input from the hippocampus, which we know is important for driving NAc activity, regulates reward-related behaviors, and that potentiation of this synapse is itself rewarding. Maintaining excitatory drive in the NAc is crucial for maintaining a normal hedonic state ([ 16 ][11], [ 17 ][12]), and dysfunction of excitatory synapses in reward pathways both within and outside the NAc contributes to the genesis of depression ([ 17 ][12]). The validity of this assertion is further supported by studies showing that environmental stress, a common precipitator of depression in humans and related behaviors in animal models, weakens excitatory synapses in specific, stress-sensitive regions, including the hippocampus ([ 18 ][13], [ 19 ][14]). Antidepressants exert opposing effects to restore the normal function of these synapses ([ 20 ][15]–[ 24 ][16]). The clear bidirectional effect on these synapses occurs in parallel with many depression-related behavioral changes, such as anhedonia (loss of pleasure seeking) and social avoidance, suggesting that these changes may be causative. However, the exact nature of the stress-induced neuronal changes that promote depression in susceptible individuals remains unknown. We therefore sought to investigate how hippocampus-NAc synapses change in stress states related to depression. We used a well-validated chronic stress paradigm to induce depression-like changes in mice. The key reward-related effect of this paradigm is anhedonia, a core symptom of depression, which manifests as a loss of sucrose preference. Using whole-cell electrophysiology, we found that chronic stress weakens hippocampus-NAc synapses and impairs their plasticity. This effect was specific to the subtype of NAc neurons expressing the D1 receptor, a subpopulation of cells that has classically been associated with positive reward ([ 25 ][17]–[ 28 ][18]). This suggests that the weakening of excitatory drive at hippocampus-D1 NAc neurons contributes to stressinduced anhedonia. We also observed that chronic stress interferes with contextual reward learning, manifesting as a loss of CPP. These stress-induced changes in physiology and behavior were restored with antidepressant treatment, suggesting that restoration of excitatory synaptic strength and plasticity at the hippocampus-NAc synapse coincides with the reinstatement of normal reward behavior. 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Forests are having their moment. Because trees can vacuum carbon from the atmosphere and lock it away in wood, governments and businesses are embracing efforts to fight climate change by reforesting cleared areas and planting trees on a massive scale. But scientists have warned that the enthusiasm and money flowing to forest-based climate solutions threaten to outpace the science. Two papers published this week seek to put such efforts on a firmer footing. One study quantifies how much carbon might be absorbed globally by allowing forests cleared for farming or other purposes to regrow. The other calculates how much carbon could be sequestered by forests in the United States if they were fully “stocked” with newly planted trees. Each strategy has promise, the studies suggest, but also faces perils. To get a worldwide perspective on the potential of second-growth forests, an international team led by ecologist Susan Cook-Patton of the Nature Conservancy (TNC) assembled data from more than 13,000 previously deforested sites where researchers had measured regrowth rates of young trees. The team then trained a machine-learning algorithm on those data and dozens of variables, such as climate and soil type, to predict and map how fast trees could grow on other cleared sites where it didn't have data. > Can the forest regenerate naturally, or can we do something to help? > > Susan Cook-Patton , the Nature Conservancy A TNC-led team had previously calculated that some 678 million hectares, an area nearly the size of Australia, could support second-growth forests. (The total doesn't include land where trees might not be desirable, such as farmland and ecologically valuable grasslands.) If trees were allowed to take over that entire area, new forests could soak up one-quarter of the world's fossil fuel emissions over the next 30 years, Cook-Patton and colleagues report in Nature . That absorption rate is 32% higher than a previous estimate, based on coarser data, produced by the Intergovernmental Panel on Climate Change. But the total carbon drawdown is 11% lower than a TNC-led team estimated in 2017. The study highlights “what nature can do all on its own,” Cook-Patton says. And it represents “a lightning step forward” in precision compared with earlier studies, says geographer Matthew Fagan of the University of Maryland, Baltimore County, who was not involved in the work. But, Fagan adds, “Natural regrowth is not going to save the planet.” One problem: There is often little economic incentive for private landowners to allow forests to bounce back. Under current policies and market pricing, “nobody will abandon cattle ranching or agriculture for growing carbon,” says Pedro Brancalion, a forest expert at the University of São Paulo in Piracicaba, Brazil. And even when forests get a second life, they often don't last long enough to store much carbon before being cleared again. Fagan notes that even in Costa Rica, renowned as a reforestation champion for doubling its forest cover in recent decades, studies have found that half of second-growth forests fall within 20 years. Given such realities, some advocates are pushing to expand tree planting in existing forests. To boost that concept, a team of researchers at the U.S. Forest Service (USFS) quantified how many additional trees U.S. forests could hold. Drawing on a federal inventory, they found that more than 16% of forests in the continental United States are “understocked”—holding fewer than 35% of the trees they could support. Fully stocking these 33 million hectares of forest would ultimately enable U.S. forests to sequester about 18% of national carbon emissions each year, up from 15% today, the team reports in the Proceedings of the National Academy of Sciences . But for that to happen, the United States would have to “massively” expand its annual tree-planting efforts, from about 1 billion to 16 billion trees, says lead author Grant Domke, a USFS research forester in St. Paul, Minnesota. Cook-Patton says planting trees might make sense in some places, but natural regeneration, where possible, provides more bang for the buck. “For any given site,” she says, “we should always ask ourselves first: ‘Can the forest regenerate naturally, or can we do something to help?’”

The meetup will take place in Baltimore and will start at 6 pm with 30 minutes of networking -- join us for beer & pizza -- followed by a program featuring Philip Resnik speaking on the state of NLP -- on mainstream and emerging natural language understanding techniques -- and mapped to startup and AI research opportunities.

MIAMI – Two people were killed and 11 others wounded Sunday when a video game tournament competitor went on a shooting rampage before turning the gun on himself in the northern Florida city of Jacksonville, local police said. Sheriff Mike Williams named the suspect of the shooting at a Madden 19 American football eSports tournament as 24-year-old David Katz from Baltimore, Maryland. "There were three deceased individuals at the scene, one of those being the suspect, who took his own life," Williams told reporters. He said local fire and rescue transported nine victims -- seven of whom had gunshot wounds -- to local hospitals, while another two people who were shot took their own transportation to hospital. Williams said Katz was a competitor in the eSports tournament and used "at least one handgun" to carry out the shooting.

Computer programs can, in some cases, predict chemical toxicity as well as tests done on rats and other animals.Credit: Coneyl Jay/SPL Machine-learning software trained on masses of chemical-safety data is so good at predicting some kinds of toxicity that it now rivals -- and sometimes outperforms -- expensive animal studies, researchers report. Computer models could replace some standard safety studies conducted on millions of animals each year, such as dropping compounds into rabbits' eyes to check if they are irritants, or feeding chemicals to rats to work out lethal doses, says Thomas Hartung, a toxicologist at Johns Hopkins University in Baltimore, Maryland. "The power of big data means we can produce a tool more predictive than many animal tests." In a paper published in Toxicological Sciences1 on 11 July, Hartung's team reports that its algorithm can accurately predict toxicity for tens of thousands of chemicals -- a range much broader than other published models achieve -- across nine kinds of test, from inhalation damage to harm to aquatic ecosystems. The paper "draws attention to the new possibilities of big data", says Bennard van Ravenzwaay, a toxicologist at the chemicals firm BASF in Ludwigshafen, Germany.

Last week I attended the 2018 INFORMS Conference on Business Analytics & Operations Research in Baltimore, MD. Among the activities of the conference, several teams of researchers from universities and industries were competing in challenges to show how their work is influencing the world. I had the honor to be among the finalist teams for the 2018 Syngenta Crop Challenge in Analytics. The Syngenta Crop Challenge in Analytics was established in 2015 with funding provided by prize winnings awarded to Syngenta in connection with its receipt of the 2015 Franz Edelman Award for Achievement in Operations Research and the Management Sciences. This year's Challenge asked participants to develop a quantitative framework for predicting corn hybrids performance in new, untested locations.