在 英语 中使用 Cognitive technologies 的示例及其翻译为 中文
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Not all cognitive technologies are seeing such rapid improvement.
In 2018, respondents remain enthusiastic about the value cognitive technologies bring.
It applies cognitive technologies to security, end-user productivity, mobile app management and administration.
Sberbank will have a 30% share in the company, while Cognitive Technologies will take 70%.
The good news is that new cognitive technologies will help to solve many important business and societal problems.
Russia's biggest lenderwill have a 30% share in the company, while Cognitive Technologies will take 70%.
Cognitive technologies can find meaning in this data in ways that, until now, only the human brain could comprehend.
When asked about perceived benefits of AI and cognitive technologies, workforce reduction was ranked the lowest(22 percent).
Her creativity and vision will help organizations transform themselves totake fuller advantage of emerging data and cognitive technologies.".
Perhaps one day those cognitive technologies will, in turn, speed up the development of AI, in a virtuous feedback cycle.
For the second year in a row,we have seen that early adopters are using cognitive technologies to effect positive change for their companies.
The CEO should make cognitive technologies an executive-level responsibility, increasing the scale of available resources.
Wall Street staffing reductions thus far have come largely from traditional automation technologies, but new cognitive technologies are likely to accelerate them.
Forrester predicts that cognitive technologies(ML, automation, robots etc) will replace the 7% of US jobs by 2025.
When exposed to that work,other people can internalize those new cognitive technologies, and so expand the range of their own visual thinking.
For instance, cognitive technologies are being used in the banking industry to detect and combat fraud- consistently a top industry pain point.
Through cloud services and enterprise software,companies can try cognitive technologies and even deploy them widely, with low initial cost and minimal risk.
Cognitive technologies, such as machine learning and artificial intelligence, are increasingly used to reduce complexity and personalize experiences across multiple sectors.
Today IBM is theonly vendor that helps companies infuse cognitive technologies seamlessly into their marketing, commerce and supply chain capabilities.
As mentioned, RPA and cognitive technologies such as AI remain distinctly different, yet they can create immense value when used together.
Seventy-three percent of early adopters are exploring mature cognitive technologies such as robotic process automation and 70 percent statistical machine learning.
By 2021, operational cognitive technologies are expected to become core competencies and major operational tools throughout the life sciences industry.
We believe executives are acknowledging the complexity of using cognitive technologies to drive change across lines of business, without despairing of attaining that goal.
This is where AI and other cognitive technologies have played a big role and helped ensure rapid access to insights and intelligence.
In our 2018 survey,56 percent of respondents said cognitive technologies would transform their companies within three years, down from 76 percent last year.
Roughly 56 percent of them said cognitive technologies would transform their companies within three years, down from 76 percent last year.
Roughly 56 percent of them said cognitive technologies would transform their companies within three years, down from 76 percent last year.
Below we describe some of the most important cognitive technologies- those that are seeing wide adoption, making rapid progress, or receiving significant investment.
Below we describe some of the most important cognitive technologies- those that are seeing wide adoption, making rapid progress, or receiving significant investment.
About three quarters of the early adopters are exploring mature cognitive technologies such as robotic process automation(RPA) and 70 percent statistical machine learning.