Gartner: The emerging technologies on the Gartner Inc. Hype Cycle for Emerging Technologies, 2017 reveal three distinct megatrends that will enable businesses to survive and thrive in the digital economy over the next five to 10 years.
Artificial intelligence (AI) everywhere, transparently immersive experiences and digital platforms are the trends that will provide unrivaled intelligence, create profoundly new experiences and offer platforms that allow organizations to connect with new business ecosystems.
Gartner Hype Cycle for Emerging Technologies 2016: Deep Learning Still Missing
Most Hyped Technologies: Self-Driving Cars, Self-Service Analytics, IoT; No More Big Data Buzz
Brookings: “…the map makes clear that while industrial robots are by no means everywhere, they are clustered heavily in a short list of Midwestern and Southern manufacturing states, especially the upper Midwest… It is telling that the robot incidence in red states that voted for President Trump in November is more than twice that in the blue states that voted for Hillary Clinton… This is not to say robots determined the outcome of the 2016 election. However, the red-state robot concentration does suggest that to the extent industrial automation brings difficult labor market transitions and anxiety, it will visit those difficulties most heavily on a particular swath of red-leaning America—specifically, the most robot-exposed locations in the industrial Midwest. To be sure, the disruption that will come with the continued adoption of broader “office” technologies like artificial intelligence will likely be felt on a wider national scale. But for its part, the robot portion of the automation fear is, and should continue to be, more confined.
In that sense, robots appear to be playing a special role in the specific unease of at least one region.”
Question: Since industrial robots have been present in large quantities in Michigan and other states with heavy industries for quite some time, why have the same people who tolerated them for such a long time (and as a result, according to the Brookings paper logic, voted for the Democrats’ presidential candidate), all of a sudden became “anxious” about robots (and as a result, voted for the Republicans’ presidential candidate)?
Posted in AI, robots
Textio: These phrases appear to be following the pattern of big data before them. As AI language has become more common in job ads, the less interesting it has become to potential job applicants. No surprise: when everyone is using the same language, no one stands out…
Textio looked at a bunch of tech terms that appear to be trending based on their recent usage growth. While all of these phrases still occur much less often than AI or ML, they’re all on the rise in a statistically unexpected way…
Enjoy your 15 minutes of fame, chatbots. Everyone knows what happens next.
Recent translation from Italian to English on Facebook:
The Flea market of square has no longer existed for a few years in its original place in square square. It has been moved against the will and protests of the owners of the stands, in in, cemetificato, less central and assolatissimo. It seemed that the city couldn’t wait for a minute so much was the rush that had to “retrain the area” (and I still didn’t understand what to do next). About two years after eviction (month plus, month less), space remains boarded, covered with weeds and holes, with a digger in between. A space like this is waiting for him in Mosul. Not in the middle of Florence. He follows pictures, as soon as the sun sets and me me on the outside.
Facebook recently switched its backend translation systems entirely to neural networks, which handle more than 2,000 translation directions and 4.5 billion translations every day. They say that these translations are more accurate than Facebook’s previous system, which used phrase-based machine translation models.
Sources: SiliconAngle, Facebook
Imperial College London professor Erol Gelenbe says artificial neural networks can ease language translation by executing a three-step process. The process includes word translations, syntax mapping, and contextual translation, which Gelenbe, recipient of the 2008 ACM SIGMETRICS Achievement Award, says the neural networks can achieve by storing and matching patterns. A key element of the translation process is long short-term memories (LSTMs), which support machine learning and can learn from experience. Swiss Dalle Molle Institute for Artificial Intelligence president Jurgen Schmidhuber expects LSTM recurrent neural networks to eventually enable “end-to-end video-based speech recognition and translation, including lip-reading and face animation.” Meanwhile, Google Brain recently announced its researchers are using neural networks to improve speech-to-text translation. Microsoft Research’s Rick Rashid says the creation and deployment of deep-learning neural networks by his company’s researchers has significantly reduced word error rates in transcribed translations, which he notes could be useful to international business dealings, and have a major effect on cross-industry learning.
…Microsoft Form 10K 2017: Vision: “Our strategy is to build best-in-class platforms and productivity services for an intelligent cloud and an intelligent edge infused with artificial intelligence (“AI”).”
……# Mentions AI or artificial intelligence: 7
…Microsoft Form 10K 2016: Vision: “Our strategy is to build best-in-class platforms and productivity services for a mobile-first, cloud-first world.”
……# Mentions AI or artificial intelligence: 0
Source: AI Import