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catalyst.ai

#artificialintelligence

Health Catalyst believes machine learning is the life-saving technology that will transform healthcare. Machine learning challenges the traditional, reactive approach to healthcare. In fact, it's the exact opposite: predictive, proactive, and preventative--life-saving qualities that make it a critically essential capability in every health system. Health Catalyst is on a mission to help health systems save lives by making machine learning routine, actionable, and pervasive through catalyst.ai Some may ask whether machine learning is just a technology fad or whether it will provide true value in healthcare.


Data Mining vs. Machine Learning: What's The Difference? - Import.io

@machinelearnbot

Data mining isn't a new invention that came with the digital age. The concept has been around for over a century, but came into greater public focus in the 1930s. According to Hacker Bits, one of the first modern moments of data mining occurred in 1936, when Alan Turing introduced the idea of a universal machine that could perform computations similar to those of modern-day computers. Forbes also reported on Turing's development of the "Turing Test" in 1950 to determine if a computer has real intelligence or not. To pass his test, a computer needed to fool a human into believing it was also human.


Low Cost Gold In The Age Of QE, AI, Trump and War - GoldCore Gold Bullion Dealer

#artificialintelligence

'Fear and Loathing In the Age of QE โ€ฆ AI' is a presentation given at Mining Investment London earlier this week. Stephen Flood, CEO of GoldCore presentation (28 minutes) was well received at the conference which is a strategic mining and investment conference for leaders in the mining and investment sectors, bringing together attendees from 20 countries. 'Fear and Loathing In the Age of QE โ€ฆ AI' can be watched on Youtube here Why Silver Bullion Is Set To Soar โ€“ GoldCore Interview Gold Bullion Stored In Singapore Is Safest โ€“ Marc Faber Russia Seen More Likely to Sell Dollar Rather Than Gold Talking Gold with CNN's Richard Quest Gold holds near one-week low as dollar firms (Reuters.com) Goldman Says the Bitcoin Haters Just Don't Get It (Bloomberg.com) Goldman Warns That Market Valuations Are at Their Highest Since 1900 (Bloomberg.com)


Data Mining vs. Machine Learning: What's The Difference? - Import.io

@machinelearnbot

Data mining isn't a new invention that came with the digital age. The concept has been around for over a century, but came into greater public focus in the 1930s. According to Hacker Bits, one of the first modern moments of data mining occurred in 1936, when Alan Turing introduced the idea of a universal machine that could perform computations similar to those of modern-day computers. Forbes also reported on Turing's development of the "Turing Test" in 1950 to determine if a computer has real intelligence or not. To pass his test, a computer needed to fool a human into believing it was also human.


Russia unveils SKYF heavy lift drones

Daily Mail - Science & tech

A new drone designed by Russian researchers is the hulk of the quadcopter world - and can carry a 400-pound (181-kg) payload and fly for up to eight hours. The multi-rotor, autonomous drone, called SKYF, was designed with logistics and agribusinesses companies in mind to create a air freight platform to help business carry out tasks. The vertical take-off and landing drone has applications in areas such as the aerial application of pesticides and fertilizers, seed planting for forest restoration and emergency situations for food and medicine delivery. The drone, designed by Russian company ARDN technology, has a maximum flight speed of 70 kilometers per hour (43.5 miles per hour) at a maximum height of 3,000 meters (9,843 feet) and has a positional accuracy of 30 centimeters (11.8 inches) The drone, designed by Russian company ARDN technology, has a maximum flight speed of 70 kilometers per hour (43.5 miles per hour) and is 5.2 meters (17 feet) by 2.2 meters (7.2 feet). It can fly at a maximum height of 3,000 meters (9,843 feet) and has a positional accuracy of 30 centimeters (11.8 inches).


Tech-savvy Chinese farmers use drones to spray pesticide

Daily Mail - Science & tech

Farmers in China have caught up with the country's booming drone trend and started using unmanned aircraft to spray pesticide onto the fields. Not only that, a team of villagers in central China recently bought 30 of these bug-zapping vehicles in hope of turning it into a new business. Zhu Xiwang and his neighbours said they hoped their squad of agri-drones to could help them start a pest-killing service, according to Huanqiu.com, an affiliation to People's Daily Online. This ยฃ24.8K flat pack folding home takes just SIX HOURS to build Pictures show the 30 drones lining up on a field, ready to take off. The unmanned aircraft, known by its model name MG-1S, is produced by Shenzhen-based Da Jiang Innovation, one of the largest drone manufacturers in China.


Artificial Intelligence: A Catalyst for a Better Worldโ€ฆwith Great Music

#artificialintelligence

Do you believe that artificial intelligence is poised to significantly improve our societies, or do you imagine extreme dangers resulting from this technology in the future? Tech moguls Elon Musk and Mark Zuckerberg have been publicly debating this issue recently, with Musk claiming that Zuckerberg's knowledge about AI is "limited". The Tesla CEO and outspoken innovator has been pushing for the proactive regulation of artificial intelligence based on his belief that the technology is a "fundamental existential risk for human civilization." On the other side, Zuckerberg has denounced Musk's warnings, calling his statements "pretty irresponsible." While many academics, such as Pedro Domingos, a professor who works on machine learning at the University of Michigan, believe that Musk's nightmare scenarios could eventually happen, but his perspective is entirely wrong.


Comparison of data mining techniques and tools for data classification (PDF Download Available)

#artificialintelligence

The datasets used in the test were saved in Weka's standardized All tools are able to read this format natively. It was not used any preprocessing widget. Bayes', the data has not been subjected to preprocessing as these'RProp MLP Learner', the real class and the predicted class were Tests were exhaustive, i.e. all the algorithms were RapidMiner has some operators (e.g. 'LibSVMLearner'), that only work with numeric attributes; for


How AI-driven Search Empowers the Digital Workplace

#artificialintelligence

If finding information in the workplace is a manual hunt-and-peck exercise, and you keep adding more digital information to the mix, your employees are getting frustrated, and even worse, disengaged. After all, they are used to easy, intuitive search experiences in their personal lives with tools like Google, Alexa, and Siri. Yet when it comes to the workplace, the systems don't deliver that ease of use. Get the eBook How AI-driven Search Empowers the Digital Workplace to learn how AI technologies and cognitive search deliver a personalized, highly relevant experience for information access in the enterprise, and help you engage a modern workforce.


"Found in Translation": Predicting Outcomes of Complex Organic Chemistry Reactions using Neural Sequence-to-Sequence Models

arXiv.org Machine Learning

There is an intuitive analogy of an organic chemist's understanding of a compound and a language speaker's understanding of a word. Consequently, it is possible to introduce the basic concepts and analyze potential impacts of linguistic analysis to the world of organic chemistry. In this work, we cast the reaction prediction task as a translation problem by introducing a template-free sequence-to-sequence model, trained end-to-end and fully data-driven. We propose a novel way of tokenization, which is arbitrarily extensible with reaction information. With this approach, we demonstrate results superior to the state-of-the-art solution by a significant margin on the top-1 accuracy. Specifically, our approach achieves an accuracy of 80.1% without relying on auxiliary knowledge such as reaction templates. Also, 66.4% accuracy is reached on a larger and noisier dataset.