A group of researchers recently developed an AI program to assist them in a complex procedure for an experiment involving finely optimized conditions. But rather than simply assist, the AI showed enough proficiency to run the experiment on its own and faster than humans or previous programs designed for the experiment. "I didn't expect the machine could learn to do the experiment itself, from scratch, in under an hour," co-lead researcher Paul Wigley, a doctoral student at the Australian National University Research School of Physics and Engineering, said in a statement. The physicists from the ANU, University of Adelaide, and the University of New South Wales Australian Defence Force Academy, were attempting to recreate an experiment that won the 2001 Nobel Prize – creating a Bose-Einstein condensate, a super chilled gas trapped in between laser beams. Bose-Einstein condensates are able to reach temperatures so low that they are some of the coldest areas of the universe, in some cases less than a billionth of a degree above absolute zero, the temperature where all atoms stop moving.

According to SciFi canon, AI and Big Data might not be a good idea. In recent years, big data and artificial intelligence (AI) have received overwhelming attention, however the interesting – even obvious – connection between the two hasn't often been explored. It is the combination of big data and AI working together that is now enabling business leaders to deliver new insights, efficiencies and even new functions that haven't been possible before. This is evident in the increasingly useful role big data and AI are playing in a broad spectrum of traditionally outsourced functions such as recruitment, HR, finance and supply chain, through to security and IT. The combination has already had a major impact on how the stock market works, synthesising more and more data to the point at which some people believe it will eventually be able to accurately predict both market trends and human influences on the market.

A team of Australian physicists has employed a new research assistant in the form of an artificial intelligence (AI) algorithm to help set up experiments in quantum mechanics. For its first task, the algorithm took control of a delicate experiment to create a Bose-Einstein condensate – a weird state of matter that can form in certain atoms at ultracold temperatures. The algorithm didn't need specific training and was able to learn on the job. It developed its own model of the process and tweaking the parameters to get them just right. "I didn't expect the machine could learn to do the experiment itself, from scratch, in under an hour," said co-lead researcher Paul Wigley from the Australian National University in Canberra.

Paging HAL: What Will Happen When Artificial Intelligence Comes to Radiology? The myth of Hephaestus' golden handmaidens illustrates mankind's centuries-long fascination with artificial intelligence (AI). The god of the forge created his handmaidens, who could talk and perform even the most difficult tasks, to assist him in his labors, and many people have since speculated about the possible uses of AI and the forms it might take. More recently, noted scientists and futurists, such as Ray Kurzweil; Stephen Hawking, CH, CBE, FRS, FRSA; and Elon Musk, have discussed, debated, and dissected the possibilities and pitfalls of AI. With many AI advances coming in the past few years, some people are beginning to wonder whether it will eventually replace radiologists.

Australian physicists, perhaps searching for a way to shorten the work week, have created an AI that can run and even improve a complex physics experiment with little oversight. The research could eventually allow human scientists to focus on high-level problems and research design, leaving the nuts and bolts to a robotic lab assistant. The experiment the AI performed was the creation of a Bose-Einstein condensate, a hyper-cold gas, the process for which won three physicists the Nobel Prize in 2001. It involves using directed radiation to slow a group of atoms nearly to a standstill, producing all manner of interesting effects. "It did things a person wouldn't guess, such as changing one laser's power up and down, and compensating with another," said ANU's Paul Wigley, co-lead researcher, in a news release.

When I returned to university to do a graduate degree, I was interested to discover how certain terms are subject to "intellectual interpretation." A word that I was asked to explain during one of my earliest classes was "ontology." Since this term was absent from my dictionary, I originally confused it with "oncology." I faintly recall that oncology involves the study of tumors. After consulting a few sources, I said that ontology is the study of how things come to exist or into being. I came across another perspective although I don't recall the source: ontology is the study of how things gain relevance or become recognized, indicating that existence can be regarded as a matter of recognition. Perhaps there is no monopoly on the exact meaning. However, I would say of ontology in relation to data science, it explains how meaning is attached to data and therefore how that data gains and retains meaning. For example, if I were asked to count the number of trucks in a parking lot, it isn't obvious what should be included: small pick-ups, tow-trucks, commercial hauling vehicles, dump trucks, and maybe heavy construction trucks.

Artificial intelligence isn't likely to replace doctors, says a researcher, but it's likely their role will change as more artificial intelligence is developed. A study by Whangarei doctors William Diprose and Nicholas Buist has highlighted rapid progress of machine learning and artificial intelligence (AI) in the health sector. They say a safe and sustainable healthcare system needs to look beyond human potential towards solutions such as AI. Q: Could artificial intelligence spell the end of doctors as we know them? Diprose and Buist are right to highlight the prospects of artificial intelligence in healthcare.

Artificial intelligence isn't likely to replace doctors, says a researcher, but it's likely their role will change as more artificial intelligence is developed. A study by Whangarei doctors William Diprose and Nicholas Buist has highlighted rapid progress of machine learning and artificial intelligence (AI) in the health sector. They say a safe and sustainable healthcare system needs to look beyond human potential towards solutions such as AI. Q: Could artificial intelligence spell the end of doctors as we know them? Diprose and Buist are right to highlight the prospects of artificial intelligence in healthcare.

In a world of smart machines that can drive cars, beat humans at chess, advise on medical diagnoses and perform a host of other tasks, imagine the next likely step as a smart machine as a people manager. As business investment in smart machines grows, "robobosses" will increasingly make workplace decisions that previously could only have been made by human managers. By 2018, more than three million workers globally will be supervised by robobosses, according to Frances Karamouzis, vice president and distinguished analyst at Gartner. These smart machine managers will look at data derived from worker performance in new ways because of their ability to dispassionately discover previously undetected relationships and correlations, test their hypotheses, and then elevate them to production status. "Supervisor duties are increasingly shifting toward monitoring worker accomplishments through measurements of performance that are directly tied to output and customer evaluation," explained Ms. Karamouzis.

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