The speculation and concern surrounding artificial intelligence (AI) are prompting more and more software vendors to introduce AI into their product development strategy. Gartner also pointed out that this approach has also caused a huge market turmoil. The company analyzed that by 2020 AI technology will be introduced to almost every new software product and service. In January 2016, the term "artificial intelligence" was not yet able to enter the top 100 search terms on gartner.com, but its rankings have jumped to seventh place by May this year, which indicates that Gartner customers are paying close attention AI issues, and actively think about how to introduce it into its own digital business development strategy. According to Gartner's forecast, by 2020, AI will be one of the top ten CIO investment priorities. Jim Hare, research vice president at Gartner Inc., commented: "As AI technology rapidly moves into the speculation cycle, software vendors are starting to catch up with the gold rush that has emerged in recent years. While AI technology does offer exciting possibilities, Unfortunately, most vendors focus only on simply building and marketing AI-based products, rather than really looking at market needs, planning potential uses, and thinking about how to enhance their business value. " AI refers to those systems that can observe the current situation without explicitly programming and analyze the behavior adjustment conclusion alone. Although there is widespread concern that AI technology may eventually replace human beings, the reality is that the current AI and machine learning technologies are only greatly enhancing human beings' abilities. After training, machines can perform far beyond human performance in certain areas; in fact, the combination of machines and humans has made many of the impossible ever possible. To successfully capitalize on the opportunities offered by AI technology, technology providers need to understand how to address three key issues: 1) The lack of differentiation leads to buyers being frustrated and difficult to make purchasing decisions A growing number of start-ups and major vendors both claim to be offering AI-related products, but none of them differentiates to really help buyers sort out their needs. More than 1,000 applications and platform providers now claim to be AI providers, or at least claim to have used AI technology in their products. According to Gartner, this is a wave of emerging trends that resemble "green" products - declaring or exaggerating the environmental impact of their products, regardless of the actual situation. In fact, this widespread AI flaunting has had a negative impact on technology investments. In order to establish user trust, suppliers should focus on creating quantitative conclusions for AI and provide relevant case studies. Hare explained that "the word 'AI' should be used wisely in product sales and marketing, specifically differentiating the differentiated nature of AI solutions and what they can solve." 2) Satisfy end-user needs with proven, easy-to-learn machine learning capabilities The achievements of AI development, including deep learning, have been highly affirmed, but still appear vague in terms of the immediacy and maturity of relevant values. Gartner recommends that each vendor take the simplest approach to use, along with state-of-the-art AI technology to bridge this gap. 3) Businesses lack the ability to evaluate, build and deploy AI solutions According to the 2017 AI Development Strategy Survey released by Gartner, more than half of the respondents believe the lack of the talent and skill pool required is the single greatest challenge for AI adoption in the enterprise. The survey found that businesses are actively looking for AI solutions that improve decision-making processes and automate business. How is it possible that most businesses tend to buy embedded or packaged AI solutions instead of trying to build customized solutions. Hare explains, "Software vendors need to focus on providing solutions to business problems rather than merely delivering cutting-edge technological results, and the point is that suppliers should explain how their AI solutions can help their business customers solve their skills shortages while bringing Beyond the value of internal customizable AI solutions. " * This research report was completed April 5-21, 2017 and covers all members of the Gartner Research Circle, an ecosystem of IT and business leaders managed by Gartner. The research report collected a total of 83 respondents.
Relative density:1.335g/ml at 25C(lit)
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Product Description
WHAT IS DIESEL EXHAUST FLUID (DEF)
Diesel Exhaust Fluid (DEF) is a non-toxic, high purity solution comprised of 32.5% urea and 67.5% de-ionized
water for specific use in Selective Catalytic Reduction (SCR) systems. Using this fluid in diesel-powered vehicles, such as
trucks, buses, and tractors, helps to reduce the amount of nitrogen oxides (NOx) emitted into the air by 90%. It is not a fuel additive and must be filled into the dedicated Diesel Exhaust Fluid tank on your diesel vehicle.
Chemical SCR/DEF grade urea, Pure Urea automotive grade urea high purity
adblue grade urea
Nitrogen: 46.6%
Moisture: 0.35%
Biuret:0.7%
Granular Urea Particle size(0.85-2.80mm): 94%
Urea 46% or Urea N 46% or Urea prilled or Industry Urea
CAS:57-13-6
Molecular Formula:CH4N2Ol
Molecular Weight:60.06
Melting point:132-135C
