We are often reminded how endless and exponential increases in computational power and complexity draw us ever closer to the possibility of creating artificial intelligence. Some argue it has already been achieved, given AI milestones such as computers passing the Turing test, beating human opponents at Jeopardy and summarily defeating the world's best human Chess and Go players. But I think we all know these are not the droids we are looking for. The identity and reciprocity we experience with other people and some of the higher animals? Maybe it's not intelligence we are waiting for, but something outside the domain of computer science, information retrieval and pattern recognition.

Bill Gates, Elon Musk and Stephen Hawking earlier in the year all said that the rapid advance of Artificial Intelligence is something that we should be worried about. Yet just a few months later Elon Musk was in the news for investing in a 1 billion venture with the single goal of rapidly advancing the research of Artificial Intelligence. The message seems to be that Artificial Intelligence has the potential to bring about enormous change, but there is also a need for vigilance so that we can minimize the risks and potential dangers of the technology. Reid Hoffman, co-founder of LinkedIn, told CNBC earlier in the week that "I think artificial intelligence is going to be transforming massive swaths of the area of work in the economy. Ten to twenty years from now if you're going to be an effective lawyer, doctor, or financial analyst, it will be in part your ability to use the technological implements, loosely going under the name of artificial intelligence."

Who's better, Lebron James or Stephen Curry? Which country is more powerful, the United States or China? How advanced is modern AI compared to humans? Of the three ridiculous questions above, which appears most underspecified? However misguidedly, we often discuss complex, multi-faceted issues as though they were easily reduced to single scalar quantities. In the past few years, modern AI techniques have made great strides, accomplishing a number of feats traditionally associated with human intelligence. In particular, machine learning systems using deep neural networks now perform human-level speech recognition and transcription.

Key players in machine learning include big cloud players like Amazon (NASDAQ:AMZN), Microsoft (NASDAQ:MSFT), and IBM. A recent study by AI language company Narrative Science found that 80% of executives believed that AI solutions boosted worker performance and created new jobs. Nuance developed the technology that powers Apple's (NASDAQ:AAPL) Siri, which preceded other voice assistants like Alphabet's (NASDAQ:GOOG) (NASDAQ:GOOGL) Google Now, Microsoft's Cortana, and Amazon's Alexa. The Motley Fool owns shares of and recommends Alphabet (A shares), Alphabet (C shares), Amazon.com, The Motley Fool owns shares of Microsoft and has the following options: long January 2018 90 calls on Apple and short January 2018 95 calls on Apple.

Another problem that the other answerers haven't mentioned is interpretability. After you've trained a neural net, it is very difficult to understand what it's actually doing. You can visualize what units in the network respond to using techniques like this: Jason Yosinski, but fundamentally, it's much harder to interpret what a CNN is doing than a simple linear model in some hand-picked feature space. This can make it difficult to use CNNs in science. Even if you have a predictive model, in some situations it's not very useful if you don't have insight into what the parameters in the model mean.

Eyal Grayevsky talks a lot about black holes, but he's not referring to the ones in outer space. The cofounder and CEO of FirstJob, an HR technology company, means the place where job applications go. One survey found that 75% of workers never heard back from a potential employer after applying. That hole turns into a vortex, according to Grayevsky, when candidates start applying to any job they're remotely qualified for. "It becomes a numbers game," he says.

Unless you've been hiding under a rock, you've no doubt heard about chatbots. However, what's not commonly known is that chatbots have been around for years. What differentiates today's bots is the integration of back-end artificial intelligence, which enables them to do more than simply respond with the basic logic of yesterday. I find that it's important to make distinctions between a bot and today's A.I.-powered intelligent assistants. Chatbots just happen to be conversational.

Quality Assurance (QA) gets baked into every aspect of the implementation by leveraging technologies such as Cognitive Process Automation (CPA) - an integration of Robotic Process Automation (RPA), Artificial Intelligence and Machine Learning, and Data Analytics.

Scientists in the Netherlands are looking to pair artificial intelligence (AI), or machine learning, with MRI techniques that measure blood perfusion in the brain. This approach, said the researchers -- diagnoses early forms of dementia and predicts the onset of Alzheimer's disease with between 82 and 90 percent accuracy. Though there is no cure for Alzheimer's, experts believe that early diagnosis could improve patient outcomes and alleviate the healthcare system's financial burden associated with the disease. According to the Alzheimer's Association, only 45 percent of patients and their caregivers dealing with the disease are aware of the diagnosis. Recent Alzheimer's research suggests that it may be possible to isolate biomarkers in the blood to diagnose the disease, demonstrated by scientists at Rowan University.

The devastating neurodegenerative condition Alzheimer's disease is incurable, but with early detection, patients can seek treatments to slow the disease's progression, before some major symptoms appear. Now, by applying artificial intelligence algorithms to MRI brain scans, researchers have developed a way to automatically distinguish between patients with Alzheimer's and two early forms of dementia that can be precursors to the memory-robbing disease. The researchers, from the VU University Medical Center in Amsterdam, suggest the approach could eventually allow automated screening and assisted diagnosis of various forms of dementia, particularly in centers that lack experienced neuroradiologists. Additionally, the results, published online July 6 in the journal Radiology, show that the new system was able to classify the form of dementia that patients were suffering from, using previously unseen scans, with up to 90 percent accuracy. "The potential is the possibility of screening with these techniques so people at risk can be intercepted before the disease becomes apparent," said Alle Meije Wink, a senior investigator in the center's radiology and nuclear medicine department. "I think very few patients at the moment will trust an outcome predicted by a machine," Wink told Live Science.