If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Havelock Ellis said it is not the attainment of the goal that matters, it is the things met with by the way. He was speaking of philosophy. In business AI is all about goal attainment. The things met along the way are decisions. Decisions constitute a focus of the recent survey by Signal AI of 1,000 C-suite executives in an attempt to estimate the impact of AI on the U.S. economy.
The Boston area has long been home to innovation that leads to impactful new drugs. But manufacturing those drugs for clinical trials often involves international partners and supply chains. The vulnerabilities of that system have become all too apparent during the Covid-19 pandemic. Now Snapdragon Chemistry, co-founded by MIT Professor and Associate Provost Tim Jamison, is helping pharmaceutical companies manufacture drugs locally to shorten the time it takes for new drugs to get to patients. Snapdragon essentially starts as a chemistry lab, running experiments on behalf of pharmaceutical customers to create molecules of interest.
To experimentally test hypotheses about the emergence of living systems from abiotic chemistry, researchers need to be able to run intelligent, automated, and long-term experiments to explore chemical space. Here we report a robotic prebiotic chemist equipped with an automatic sensor system designed for long-term chemical experiments exploring unconstrained multicomponent reactions, which can run autonomously over long periods. The system collects mass spectrometry data from over 10 experiments, with 60 to 150 algorithmically controlled cycles per experiment, running continuously for over 4 weeks. We show that the robot can discover the production of high complexity molecules from simple precursors, as well as deal with the vast amount of data produced by a recursive and unconstrained experiment. This approach represents what we believe to be a necessary step towards the design of new types of Origin of Life experiments that allow testable hypotheses for the emergence of life from prebiotic chemistry. The transition of prebiotic chemistry to present-day chemistry lasted a very long period of time, but the current laboratory investigations of this process are mostly limited to a couple of days. Here, the authors develop a fully automated robotic prebiotic chemist designed for long-term chemical experiments exploring unconstrained multicomponent reactions, which can run autonomously and uses simple chemical inputs.
MIT engineers have discovered a new way of generating electricity using tiny carbon particles that can create a current simply by interacting with liquid surrounding them. The liquid, an organic solvent, draws electrons out of the particles, generating a current that could be used to drive chemical reactions or to power micro- or nanoscale robots, the researchers say. "This mechanism is new, and this way of generating energy is completely new," says Michael Strano, the Carbon P. Dubbs Professor of Chemical Engineering at MIT. "This technology is intriguing because all you have to do is flow a solvent through a bed of these particles. This allows you to do electrochemistry, but with no wires." In a new study describing this phenomenon, the researchers showed that they could use this electric current to drive a reaction known as alcohol oxidation -- an organic chemical reaction that is important in the chemical industry.
Its machine learning systems predict the best ways to synthesize potentially valuable molecules, a crucial part of creating new drugs and treatments. The company's system enters play when you have some exotic new compound you want to make in order to test it in real life, but don't know how to make it. After all, these molecules are brand new to science -- no one has created them before, so why should anyone know? The company leverages machine learning and a large body of knowledge about chemical reactions to create these processes, though as CSO Stanisław Jastrzębski explained, they do it backwards. "Synthesis planning can be characterized as a game," he said.
People who have an extreme reaction to certain noises, specifically loud chewing and breathing, may have a'supersensitized' brain connection, a new study reveals. Scientists at Newcastle University discovered an increased connectivity between the auditory cortex and the motor control areas related to the face, mouth and throat in those suffering with misophonia. Misophonia, which means'hatred of sound', is a condition in which people experience intense and involuntary reactions to certain sounds made by others, referred to as'trigger' sounds. The findings suggest that misophonia is not an abreaction of sounds, but'manifestation of activity in parts of the motor system involved in producing those sounds,' according to the study published in the Journal of Neuroscience. Dr Sukhbinder Kumar, Newcastle University Research Fellow in the Biosciences Institute said: 'Our findings indicate that for people with misophonia there is abnormal communication between the auditory and motor brain regions - you could describe it as a'supersensitized connection'.
Thirty-five years after the Chernobyl Nuclear Power Plant in Ukraine exploded in the world's worst nuclear accident, fission reactions are smoldering again in uranium fuel masses deep inside a mangled reactor hall. “It's like the embers in a barbecue pit,” says Neil Hyatt, a nuclear materials chemist at the University of Sheffield. Now, Ukrainian scientists are scrambling to learn whether the reactions will wink out—or require extraordinary steps to avert another accident. Sensors are tracking a rising number of neutrons, a signal of fission, streaming from one inaccessible room, Anatolii Doroshenko of the Institute for Safety Problems of Nuclear Power Plants (ISPNPP) in Kyiv, Ukraine, reported last month during discussions about dismantling the reactor. “There are many uncertainties,” says ISPNPP's Maxim Saveliev. “But we can't rule out the possibility of [an] accident.” The neutron counts are rising slowly, Saveliev says, suggesting managers still have a few years to figure out how to stifle the threat. Any remedy will be of keen interest to Japan, which is coping with the aftermath of its own nuclear disaster 10 years ago at Fukushima, Hyatt notes. “It's a similar magnitude of hazard.” The specter of self-sustaining fission, or criticality, in the nuclear ruins has long haunted Chernobyl. When part of the Unit Four reactor's core melted down on 26 April 1986, uranium fuel rods and their zirconium cladding, graphite blocks, and sand dumped on the core to try to extinguish the fire melted together into a lava. It flowed into basement rooms and hardened into formations called fuel-containing materials (FCMs), laden with about 170 tons of irradiated uranium—95% of the original fuel. The concrete-and-steel sarcophagus called the Shelter, erected 1 year after the accident to house Unit Four's remains, allowed rainwater to seep in. Because water slows, or moderates, neutrons and thus enhances their odds of striking and splitting uranium nuclei, heavy rains sometimes sent neutron counts soaring. After a downpour in June 1990, a “stalker”—a scientist at Chernobyl who risks radiation exposure to venture into the damaged reactor hall—dashed in and sprayed gadolinium nitrate solution, which absorbs neutrons, on an FCM that scientists feared might go critical. Several years later, the Shelter was equipped with gadolinium nitrate sprinklers. But the spray can't effectively penetrate some basement rooms. Chernobyl officials presumed any criticality risk would fade when the massive New Safe Confinement (NSC) was slid over the Shelter in November 2016. The €1.5 billion structure was meant to seal off the Shelter so it could be stabilized and eventually dismantled. It also keeps out the rain, and since its emplacement, neutron counts in much of the Shelter have been stable or are declining. But they began to edge up in a few spots, nearly doubling over 4 years in room 305/2, which contains tons of FCMs buried under debris. ISPNPP modeling suggests the drying of the fuel is somehow making neutrons ricocheting through it more, rather than less, effective at splitting uranium nuclei. “It's believable and plausible data,” Hyatt says. “It's just not clear what the mechanism might be.” The threat can't be ignored. As water continues to recede, the fear is that “the fission reaction accelerates exponentially,” Hyatt says, leading to “an uncontrolled release of nuclear energy.” There's no chance of a repeat of 1986, when the explosion and fire sent a radioactive cloud over Europe. A runaway fission reaction in an FCM could sputter out after heat from fission boils off the remaining water. Still, Saveliev notes, although any explosive reaction would be contained, it could threaten to bring down unstable parts of the rickety Shelter, filling the NSC with radioactive dust. Addressing the newly unmasked threat is a daunting challenge. Radiation levels in 305/2 preclude installing sensors. And spraying gadolinium nitrate on the nuclear debris there is not an option, as it's entombed under concrete. One idea is to develop a robot that can withstand the intense radiation for long enough to drill holes in the FCMs and insert boron cylinders, which would function like reactor control rods and sop up neutrons. In the meantime, ISPNPP intends to step up monitoring of two other areas where FCMs have the potential to go critical. The resurgent fission reactions are not the only challenge facing Chernobyl's keepers. Besieged by intense radiation and high humidity, the FCMs are disintegrating—spawning even more radioactive dust that complicates plans to dismantle the Shelter. Early on, an FCM formation called the Elephant's Foot was so hard scientists had to use a Kalashnikov rifle to shear off a chunk for analysis. “Now it more or less has the consistency of sand,” Saveliev says. Ukraine has long intended to remove the FCMs and store them in a geological repository. By September, with help from European Bank for Reconstruction and Development, it aims to have a comprehensive plan for doing so. But with life still flickering within the Shelter, it may be harder than ever to bury the reactor's restless remains.
Scientists monitoring the ruins of the Chernobyl nuclear power plant in Ukraine have seen a surge in fission reactions in an inaccessible chamber within the complex. They are now investigating whether the problem will stabilise or require a dangerous and difficult intervention to prevent a runaway nuclear reaction. The explosion at Chernobyl in 1986 brought down walls and sealed off many rooms and corridors. Tonnes of fissile material from the interior of a reactor were strewn throughout the facility and the heat it generated melted sand from the reactor walls with concrete and steel to form lava-like and intensely radioactive substances that oozed into lower floors. One chamber, known as subreactor room 305/2, is thought to contain large amounts of this material, but it is inaccessible and hasn't been seen by human or robotic eyes since the disaster.
To understand the long-run behavior of Markov population models, the computation of the stationary distribution is often a crucial part. We propose a truncation-based approximation that employs a state-space lumping scheme, aggregating states in a grid structure. The resulting approximate stationary distribution is used to iteratively refine relevant and truncate irrelevant parts of the state-space. This way, the algorithm learns a well-justified finite-state projection tailored to the stationary behavior. We demonstrate the method's applicability to a wide range of non-linear problems with complex stationary behaviors.
Can you imagine machines having emotions? The future is not far where devices around you will understand your emotions and change their responses to match your behavior. Sounds like something that's straight out of a sci-fi movie, this is the latest technology in machine learning. Emotional AI is used by machine developers to make the system capable of reading, interpreting, and responding to human behavior and even affect it, just like how we experience varied emotions every day. All this is to make machines interact with humans more naturally.