The possibility of autonomous computers raises many social and ethical issues including job displacement and decisions involving human lives.
Elon Musk has accused Mark Zuckerberg of failing to understand artificial intelligence. It comes after the Facebook boss said that the doomsday scenario put forward by Mr Musk was unhelpful. Mr Musk tweeted: "I've talked to Mark about this. Mr Musk began warning AI could destroy humans three years ago, when, during a talk at the Massachusetts Institute of Technology, the billionaire Space X founder called it humanity's "biggest existential threat".
Everyone's favorite eccentric billionaire Elon Musk is the latest example of this, publicly slamming Mark Zuckerberg with a tweet stating that the Facebook CEO's understanding of AI "is limited." Musk hasn't exactly been shy on the topic, previously proclaiming that artificial intelligence is "the biggest risk we face as a civilization." Meeting with US governors earlier in the year, he went on to say that "AI is a rare case where we need to be proactive in regulation instead of reactive because if we're reactive in AI regulation it's too late." Rodney Brooks, the founding director of MIT's Computer Science and Artificial Intelligence recently questioned Musk's AI knowledge in much the same way Elon did about Zuckerberg.
However, development of an artificial general intelligence, or AGI, opens up potential risks. There are fundamental differences between today's AIs and AGIs, the primary difference being based on how computers and humans operate. Perhaps the world's most famous scientist, Stephen Hawking, expressed similar concerns, stating that artificial intelligence could "spell the end of the human race." One positioned is shared by many in the computer science field: AGI systems that could pose a threat to mankind are so far from being developed they're not worth worrying about.
Artificial Intelligence – Neil Jacobstein recently gave an information-packed talk at the Exponential Manufacturing conference on how artificial intelligence is redefining the future of work, production, supply chain, and design. At the Summit, Neil Jacobstein chairs the Artificial Intelligence and Robotics Track at Singularity University, explored how exponential technologies including artificial intelligence, additive manufacturing, exponential energy, and bio manufacturing are continually redefining the future of work, production, supply chain, and design. Hardware is a key component of the AI revolution, and Jacobstein introduces the Tensor Processing unit, that Google only recently introduced and deployed. Neil Jacobstein recently gave an information-packed talk at the Exponential Manufacturing conference on how artificial intelligence is redefining the future of work, production, supply chain, and design.
Conversation has been the most powerful way humans communicate with each other for thousands of years. AI visionaries believe that in just three to five years, computer conversational abilities will advance significantly, paving the way for a bevy of life-changing AI applications. How will conversation advance and what are the possible applications?
Artificial intelligence today is making progress exponentially and opening new horizons as to the possibilities it provides us. While some view it as a chance at eradicating hunger and solving illiteracy and poverty, others are concerned about a future where machines surpass human intelligence and make decisions that endanger our safety and survival. The singularity, therefore, is a hypothetical moment in time where artificial intelligence will surpass human intelligence and result in unthinkable changes to the human civilization. So, our fear here is the development of something that surpasses humans, as the artificially intelligent machine would then proceed to redesign and improve itself at an alarming rate, even perceive actions against it and defend itself.
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Instead, we should focus on the challenges and opportunities presented by new technology trends, including artificial intelligence, machine learning, and Big Data analytics. He added: "The development of automation enabled by technologies, including robotics and artificial intelligence, brings the promise of higher productivity (and with productivity, economic growth), increased efficiencies, safety, and convenience, but these technologies also raise difficult questions about the broader impact of automation on jobs, skills, wages, and the nature of work itself." It's tempting to view machine learning's evolution as a slam dunk for the robots As machine learning-based skills approach those of human beings, it's tempting to view their evolution as a slam dunk for the robots. And over time machine learning and other advanced technologies will create new growth opportunities and jobs for workers with updated skills.
Artificial intelligence already plays a major role in human economies and societies and it will play an even bigger role in the coming years. Beyond these innovations, we can expect to see countless more examples of what were once called "expert systems": Artificial intelligence applications that aid, or even replace, human professionals in various specialties. Given this trend, it is not surprising that some people foresee a point known as the "Singularity," when artificial intelligence systems will exceed human intelligence, by intelligently improving themselves. Ultimately, the future of artificial intelligence -- our artificial intelligence future -- is bright.
IoT promises that field-service reps will be able to talk to machines to quickly identify issues; AI promises to make reps aware of problems before they even appear. AI will use image recognition to streamline the service process, whether that's break-fix, preventative maintenance, or installations. As field service is closely involved in fixing or replacing parts at the customer's home or office, image recognition has huge potential to increase the field rep's accuracy throughout the asset service lifecycle. This disparate information -- weather, traffic, skillsets, customer needs -- will, when crunched by AI, improve field-service scheduling.