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Artificial intelligence has become the driving force of enterprise development

Date:2018-08-29




 
When a new concept becomes a viable business tool, many companies will actively adopt this technology to join the market trend. These include artificial intelligence (AI) and machine learning (ML). From high-tech giants with a history of more than 100 years to start-ups dedicated to innovation, organizations of all sizes are actively investing time and resources to accelerate technology development and use it for business development.

But AI is not just a popular fashion. Tractica, the analytical body, estimates that the global spending on artificial intelligence will increase from $644 million in 2016 to nearly $39 billion in 2025, and will become a driving force for the development of efficient sales platforms and virtual digital receptionists, children's toys, autopilot cars, products or services.

Artificial intelligence (AI) and machine learning (ML) will ultimately provide the driving force for most enterprises. What driving forces do AI have? That's powerful data and processing power.

Great potential, great limitations

The potential impact of AI on vertical industry and every enterprise should not be underestimated. With the development of non-assisted machine learning, natural language processing (NLP) and in-depth learning, the application of each skill will continue to grow and expand to new use cases.

Many companies are already studying how to use artificial intelligence (AI) and machine learning (ML) technologies for object recognition and tracking, localizing geographic data, preventing fraud, improving marketing outcomes, and many other applications. Although manufacturers in these fields hope to use this technology to achieve this commitment, other companies have applied these innovations to the practical applications of autopilot, call center, customer service and network security.

Enterprises that have adopted AI technology have been systematically and strategically aggregating data for many years. They have taken the lead in organizations that are just beginning to focus on data collection and organization. But they also face the biggest limitation of artificial intelligence (AI) and machine learning (ML) technology: capacity.

Power, capacity and speed are very important for intelligent technology.

The artificial neural network (ANN), which drives the development of artificial intelligence (AI) and machine learning (ML), aims to model and process the relationship between input and output in parallel. To do this, they need to store a large amount of input data, and large-scale computations to understand these relationships and provide the appropriate output.

Consider deploying chat robots to provide customer self-service and assist the customer service agent team in the contact center. Ideally, robots can answer questions accurately, direct customers to appropriate resources, and usually interact with customers in a natural way.


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