Expect a broad range of AI-enabled significant advancements in 2019.
From Google searches to handling complex jobs like big data analysis, artificial intelligence (AI) has already started shaping many areas of modern life. In 2018, there were many breakthroughs that turned futuristic fiction into reality with the application of AI.
In 2019, AI will expand to cover new dimensions such as media, healthcare, retail, manufacturing, communication, research – in fact, almost every area of modern life has the potential to be influenced by AI applications.
Though most of us think of the future of AI in the form of robots, market intelligence firm Tractica predicts less fanciful use cases of AI.
Industry watchers expect the following new advancements in AI this year to be:
AI-enabled chips
AI operations heavily rely on specialised processors that complement the CPU. Even the most advanced CPU may fail to support the speed requirements of training an AI model.
In 2019, expect to see chip manufacturers with new, specialized chips that can cope with the speed required for the execution of AI-enabled applications. Qualcomm’s A12 chip could be an example of the rise of AI-enabled chips in 2019. Chip manufacturers will optimize these specialized chips for specific use cases, such as those related to computer vision, speech recognition and natural language processing.
Companies like Amazon, Google, Facebook and more will invest in custom AI-enabled chips based on field programmable gate arrays (FPGA) and application specific integrated circuits (ASIC). These chips will be able to run modern workloads based on AI and high-performance computing (HPC) as well as speeding up query processing and predictive analytics with next-generation databases.
Automated machine learning
AI is in a constant process of change, and it’s important to the industry to be able to automate learning experiences without requiring overwriting algorithms every time. This year will bring even further change by bringing automated machine learning (AutoML) algorithms.
These algorithms will be able to address complex scenarios without requiring the typical process of training machine learning models. It will bridge the gap between the actual technology potential and its existing use.
Business analysts with AutoML focus on the business problem rather than on the process and workflow – AutoML helps developers obtain the right level of customization without requiring them to go through the elaborate workflow.
The rise of AI regulations
Facial recognition is one of the fastest growing and most widely adopted AI applications. It has become ubiquitous in smartphones, online media, and smart cameras. At the same time, industry experts are predicting more AI–based regulations.
In 2019, many countries will regulate facial recognition and focus on bias and privacy issues. Many of these regulations will give customers the right to opt out of its uses. They will be able to examine how these regulations are used to target them and receive a full accounting of how their facial data is being managed.
Some of these regulations will be used across all applications of facial recognition, while some will be incrementally applied according to existing regulations in various sectors such as social media, healthcare, and law enforcement.
AIOps will automate DevOps
Log data generated by model applications and infrastructure is captured for indexing, searching, and analytics. Data obtained from hardware, software and operating systems are aggregated and correlated for insights and patterns. When machine learning models are used for these data sets, IT operations become predictive instead of reactive.
In 2019, AI will redefine the way data and infrastructures are managed. Use of ML and AI in IT and DevOps will deliver intelligence to companies and help the ops teams perform accurate root cause analysis.
AIOps will become mainstream this year, and public cloud vendors and enterprise will benefit from the convergence of AI and DevOps.
Improved cybersecurity
Cybercriminals today strategically target organizations to hack data and invade systems. AI algorithms will be soon smart enough to recognize usual activity patterns faster than ever before. It will set standards set for regular activities and ways to identify actions that are different from the standard patterns. It will also eliminate the requirement of supervising systems to detect a data breach. AI-enabled cybersecurity systems will offer supervised monitoring of malware that may be new or a mutated version of a previous one.
In 2019, AI will integrate into our everyday world like never before. The future holds a huge variety of AI applications, both anticipated and unexpected, along with the benefits and concerns that come along with any new technology. This year will bring us a world full of technology that is more advanced, more useful – and more intelligent.
