hype


How To Separate The AI Hype From Reality

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For some time, AI has been the "hot" topic among marketers, technologists and nearly everyone else, receiving an out-sized amount of media attention and buzz. In a discussion with Kipp Bodnar, CMO of HubSpot, a leading growth platform, he indicates that it's hard for businesses to distinguish between hype and reality. The result is that a lot of companies throw resources at an opportunity that doesn't materialize. Below are Bodnar's thoughts on how marketers can destinguish between what's possible and what's not. Kimberly A. Whitler: You indicated that a lot of the buzz around AI is just hype--exaggerated promotion of the concept that can't deliver on the promise…yet.


Five questions you can use to cut through AI hype

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In my opinion, a company with a quality machine-learning product should check off all the boxes: it should be tackling a problem fit for machine learning, have robust data acquisition and auditing processes, have highly accurate algorithms or a plan to improve them, and be grappling head-on with ethical questions. Oftentimes, companies pass the first four tests but not the last. For me, that is a major red flag. It demonstrates that the company isn't thinking holistically about how its technology can affect people's lives and has a high chance of pulling a Facebook later down the line. If you're an executive looking for machine-learning solutions for your firm, this should warn you against partnering with a particular vendor.


AI in business: looking beyond the hype towards success

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A couple of years ago, there was a joke doing the rounds at technology conferences that AI in business is like teenagers and sex: everyone talks about it, but few actually get it. Is the ribald witticism outdated in 2019? Or has the increased hype enveloping AI that it will magically solve most business problems only further confused executives? So much so they are not engaging with AI's myriad technologies or are left clumsily fumbling with algorithms that fail to perform, while cannier rivals score big. Moreover, has the crucial point that AI in business is best utilised as a means of achieving very specific, narrow-focused objectives, and is not an end point in itself, been obscured by the sheer volume of misleading buzz?


Small business owners: Don't rush into using AI

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Artificial intelligence (AI) is here to stay, and the tricky question for small business owners is not whether to jump on board, but when. Daniel Faggella, AI strategist and founder and CEO of Emerj, writes, "Given the inevitability of AI's applications across sectors, it would seem a good idea for small businesses to jump on the AI bandwagon sooner than later to be more competitive... Right?" In his Emerj article Is Artificial Intelligence for Small Business? Factors to Consider for Technology Adoption, he encourages caution. "Contrary to what might be hyped on social media, in nearly all application areas AI is an expensive and complex solution without evidence of direct ROI (return on investment)," writes Faggella.


Why Culture Is so Important to AI Adoption GovLoop

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We all see the potential of artificial intelligence (AI). After all, this is brand new territory. It's easy to get caught up in the hype and to forget all the groundwork and tactical steps it takes to effectively establish and use AI in an organization. Having witnessed adoption by many clients, I've developed a short checklist of what's needed to be successful, and I plan to devote a blog to each one. These are big buckets holding lots of detail.


Hype and reality in Chinese artificial intelligence Business, Technology, and Politics SupChina

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In MIT Technology Review, Jeff Ding shares five takeaways from his experience writing about and translating Chinese-language writing about artificial intelligence (AI) research in China. Ding is a researcher at the University of Oxford who has now published 48 issues of his insightful ChinAI newsletter. Four out of Ding's five points are likely to remain true through at least 2019. The odd one out is number four: AI research, in the near future, may no longer be an area of active China-U.S. collaboration. For more discussion of U.S.-China technology connections, listen to this recent Sinica Podcast with Samm Sacks.


Artificial intelligence and medicine: Is it overhyped? Medical Design and Outsourcing

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Artificial intelligence raises exciting possibilities for healthcare, but are companies promising more than they can deliver? But artificial intelligence's potential also comes with an incredible level of hype. "AI has the most transformative potential of anything I've seen in my life, and I graduated medical school 40 years ago. It's the biggest thing I've ever seen by far," prominent cardiologist and author Dr. Eric Topol told Medical Design & Outsourcing. "But it's more in promise than it is in reality."


#Blockchain Artificial Intelligence and Cryptocurrency: Separating Hype from Reality

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Pick an industry – any industry – and you can virtually guarantee that AI will have been hailed as its next big thing. The cryptocurrency sector is no different, with many of 2017's ICOs shoehorning the concept into their whitepapers somewhere in a bid to appear "cutting edge" and in touch with the zeitgeist. But beyond all the hype, what impact will artificial intelligence have on the crypto industry, and could its rise ultimately render human traders obsolete? AI is to tech what "blockchain" is to the cryptocurrency industry: a concept whose genuine applications are significantly outnumbered by the projects interested solely in latching onto the buzzword and surfing it for all it's worth. Given that startups described as being involved with AI attract 15-50% more funding than other tech firms, it's understandable why companies are so keen to cash in on the hype.


Machine Learning Applications in the Internet of Things (IoT) IoT For All

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If you just include "machine learning" in your pitch you can add a zero on to the end of your valuation. Machine Learning (ML) and the Internet of Things (IoT) have been huge buzzwords in the past few years, much of which has been hype and much of which reflects their profound potential. The above quote came somewhat jokingly from an investor, but it has some truth to it too. Given the hype around machine learning and IoT and the broad range of application to which they can be brought to bear, it can be difficult to cut through the noise and understand where the actual value lies. In this post, I'll explain how machine learning can be valuable for IoT, when it's appropriate to use, and some machine learning applications and use cases currently out in the world today.


Artificial Intelligence and Cryptocurrency: Separating Hype from Reality - Bitcoin News

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Pick an industry – any industry – and you can virtually guarantee that AI will have been hailed as its next big thing. The cryptocurrency sector is no different, with many of 2017's ICOs shoehorning the concept into their whitepapers somewhere in a bid to appear "cutting edge" and in touch with the zeitgeist. But beyond all the hype, what impact will artificial intelligence have on the crypto industry, and could its rise ultimately render human traders obsolete? AI is to tech what "blockchain" is to the cryptocurrency industry: a concept whose genuine applications are significantly outnumbered by the projects interested solely in latching onto the buzzword and surfing it for all it's worth. Given that startups described as being involved with AI attract 15-50% more funding than other tech firms, it's understandable why companies are so keen to cash in on the hype.