5 Notable Artificial Intelligence Trends in 2019

With every passing year, the evolution of artificial intelligence is heralding greater business value and purpose. Leading industrialists and data analysts are capitalizing on the latest artificial intelligence trends to accelerate business production and growth. Today, dynamic AI development services are unlocking new business opportunities with cloud computing, conversational interfaces, AutoML, AI accelerators, and other advancements.

This blog post explores some ground-breaking artificial intelligence trends that reigned 2019-

1) Automated Machine Learning

The process of building machine learning models involves the identification and labeling of large datasets. It is followed by rigorously training the model with rich algorithms. It is, therefore, challenging for small and medium enterprises to train machine learning models in a time and cost-effective manner.

Automated machine learning or AutoML is the next big advancement under ML-based model training. It automates ML processes which involve data pre-processing, feature engineering, extraction and selection, algorithmic selection, and hyperparameter optimization.

Typically, AutoML technologies channelize data in the following manner-

The business benefits of AutoMl includes-

a) Cost reduction

b) Increased productivity of data analysts 

c) Accurate predictions and insights

d) Democratize machine learning processes

Related- Optimizing the Code with Machine Learning for Software Development

2) Deep Neural Network

Unlike machine learning that requires pre-defined datasets, deep learning uses artificial neural networks (ANN) that divide data classification among different network layers. Therefore, deep learning is considered as a subset of machine learning as it involves hierarchal classification of data and images. 

Here are two most recent advancements sprouting under deep learning technology-

a) AI-augmented analytics powered by deep learning is the latest disruptive technology that is propelling business growth with in-depth organizational data analysis. It can replace data scientists by deploying deep neural networks to analyze business models and generate effective marketing strategies, insights, and more.

b) Open Neural Network Exchange (ONNX) is only a year old deep learning mechanism yet rapidly gaining momentum. It is an open-source artificial intelligence ecosystem supported by deep learning tools. It streamlines data training and deployment of ML models over industrial PCs, smartphones, and web for better portability and implementation.

Related- Strengthening Artificial Intelligence with Raspberry Pi for Global Businesses

3) AI Accelerators

Technological advancement in computer hardware is leaping beyond the dominant Graphic Processing Units (GPUs). Today, industrial systems are powering deep neural networks and ML models with AI-optimized chipset architecture.

This new generation of GPUs includes Neural Network Processing Units (NNPUs), Field Programmable Gate Arrays (FPGAs), and Application-specific Integrated Circuits (ASICs). These AI accelerators enable greater autonomy for mobile and the Internet of Things (IoT) devices. Today, leading industrialists are investing in various AI accelerators for more efficient and accurate AI processing.

4) AI Cloud services

The computational power of cloud-based solutions has grown rapidly during the past decade. Low-cost data storage, easy access, and algorithmic advancements have led businesses to adopt cloud-first strategies for their offerings and revenue growth.

Gartner predicts a $331.5 billion market growth of the cloud service industry by 2022, with Sid Nag, research vice president at Gartner, illustrating,

“Cloud services are definitely shaking up the industry.”

The advent of artificial intelligence has further added to the data generating and processing capabilities of cloud-based services models across enterprises. Here’s how businesses across industries can harness the transformative powers of cloud-based AI engines-

a) AI can decode large and complex cloud data streams to analyze consumer demands and market scenarios with greater efficiency and support.

b) AI’s machine learning capabilities are fast replacing rule-based processes with automated and self-monitoring cloud-based business applications.

5) Conversational Chatbots

Customer services and engagement are essential marketing strategies for diverse businesses from eCommerce to automobile and healthcare. Artificial intelligence has already entered this space with considerable success in managing customer interactions.

However, 2019 has witnessed significant improvement in AI’s conversational abilities from being a mere recommendation engine to assisting the following vectors-

a) With instant human-like responses, timely product notifications, sentiment analysis, and emotional recognition, chatbots effectively boost advertisement efforts and customer loyalty.

b) Financial institutions can deploy AI chatbots for smart wealth management, treasury services, online transactions, and customer support.

c) Also, healthcare businesses can benefit from custom chatbot development services to facilitate preliminary diagnosis, remote assessment, health plan selection, etc.

Also Read- Custom Chatbot Development | Business Uses Cases and Benefits

Capitalizing on Artificial Intelligence Trends with Oodles AI

We, at Oodles AI, empower businesses with diverse AI solutions that use deep neural networks and machine learning algorithms to generate key business insights. We have experiential knowledge in building AI-powered business applications with specialized cloud-based frameworks such as AWS, Google Cloud, IBM Watson, and Microsoft Azure.

Talk to our Artificial Intelligence team to know more about our AI development services.