Source: Deep Learning on Medium
5 Artificial Intelligence Trends to Watch This Year
Expect a wide range of AI-enabled significant breakthroughs in 2019.
From Google searches to managing complex jobs such as big data analysis, Artificial Intelligence (AI) has already begun to shape many areas of modern life. In 2018, there have been many advances that have made futuristic fiction a reality with the application of AI.
In 2019, AI services will expand to cover new aspects of media, healthcare, retail, manufacturing, communication, and research — in fact, almost every area of modern life is likely to be impacted by AI applications.
Although most of us are thinking about the future of AI in the form of robots, market intelligence firm Tractica has to address the less fan-friendly use cases of AI.
Industry observers expect the following new advances in AI this year:
AI operations rely heavily on specialized processors that complete the CPU. Even the most advanced CPU may fail to support the speed requirements that the AI model can train.
In 2019, chip makers expect to see new and specialized chips that can accelerate the pace of AI-enabled applications. Qualcomm’s A12 chip could be an example of the growth of AI-enabled chips in 2019. Chip manufacturers optimize these unique chips for specific use cases such as computer vision, speech recognition, and natural language processing.
Amazon, Google, Facebook, and more companies are investing in custom AI-enabled chips based on field-programmable gate arrays (FPGAs) and application-specific integrated circuits (ASICs). These chips can implement advanced workloads based on AI and high-performance computing (HPC), as well as accelerate query processing and predictive analytics with next-generation databases.
Automated Machine Learning
AI solutions are in the process of sustainable change and the industry needs to be able to automate learning experiences without the need for overwriting algorithms every time. This year will bring further change by bringing in automated machine learning (AutoML) algorithms.
These algorithms can solve complex scenarios without requiring the typical process of training machine learning models. This reduces the gap between actual technical capacity and its current use.
Business analysts with AutoML focus on the business problem rather than the process and workflow — AutoML helps developers get the right level of customization without the need to go through the extensive workflow.
The rise of AI regulations
Facial recognition is one of the fastest-growing and widely adopted AI applications. It is ubiquitous in smartphones, online media, and smart cameras. At the same time, industry experts are predicting more AI-based regulations. In 2019, most countries will regulate facial recognition and focus on bias and privacy issues. These Terms give most users the right to discontinue its use. You will be able to observe how these terms are used to target them and get a full accounting of how their facial data is handled.
Some of these terms are used in all applications of facial recognition, while others are developed under different types of regulations such as social media, healthcare and law enforcement.
AIOps automates DevOps
Log data generated by model applications and infrastructure can be summarized for data indexing, search and analysis. Data from hardware, software, and operating systems are comprehensive and interconnected for insights and models. When machine learning models are used for these data sets, IT activities can be iced instead of reactive.
In 2019, AI is going to redefine data and infrastructure management. The use of ML and AI in IT and DevOps provides intelligence to organizations and helps ops teams to perform accurate root cause analysis.
AIOps will become mainstream this year, and public cloud vendors and enterprises will benefit from a combination of AI and DevOps.
Cybercriminals today strategically target organizations to hack data and attack systems. AI algorithms will soon be smart to detect simple operational patterns faster than the previous ones. It sets the criteria set for normal operations and the ways to identify actions that are different from the standard models. It also eliminates the need for monitoring systems to detect data breaches. AI-enabled cybersecurity systems provide monitoring of malware, which may be new or a modified version of the previous one.
In 2019, AI services will unite into our everyday world like never before. In addition to the benefits and concerns that come with any new technology in the future, there are many types of AI applications that are unexpected. This year brings us a world filled with more modern, more useful and more intelligent technologies.
Marketing Team, SEO Executive
USM SYSTEMS 8–2–293/82/A/270E, Road No — 10, Jubilee Hills, Hyderabad-500034