Artificial Intelligence and Machine Learning have a wide range of applications. For example, IBM's Chef Watson could make a quintillion different combinations with just four components. In addition, AI-powered virtual nurses like "Molly" and "Angel" are already saving lives and lowering costs, and robots are aiding with a variety of treatments, from less invasive procedures to open-heart surgery.
1. The Future of Machine Learning-
- Increasing Use of AI and Machine
Many firms that use AI and Machine Learning, however, do not properly comprehend these technologies. In fact, according to a recent survey, 64% of respondents believe their staff does not fully trust or understand AI.
While the advantages of AI and machine learning are becoming more apparent, businesses will need to step up and hire individuals with the necessary abilities to put these technologies into practice. Some have already made significant progress. According to a recent KPMG poll of Global 500 firms, most anticipate expanding their investment in AI-related skills by 50-100 percent over the next three years.
- Transparency Trends
As a result, in 2021, there will be a stronger push for AI deployment that is transparent and well-defined. While businesses will struggle to grasp how AI models and algorithms work, AI/ML software providers will have to make complex ML solutions more understandable to users.
The roles of experts who work in the trenches of programming and algorithm development will become increasingly crucial as transparency becomes a significant conversation in the AI area.
- Rising Emphasis on Data Security and Regulations-
GDPR and, more recently, the California Consumer Privacy Act — both of which went into force in 2020 — have made privacy violations extremely costly. The Information Commissioner's Office (ICO) fined British Airways and Marriott International nearly $300 million in 2019 for GDPR violations.
Companies will need data scientists and analysts on hand to stay compliant and ahead of AI and Machine Learning trends as the need to meet these standards grows.
- The Overlap Between AI and IoT-
So, why do these two technologies complement one other so well? IoT can be compared to the digital nervous system and AI to the decision-making brain. IoT systems become more sophisticated thanks to AI's capacity to quickly extract insights from data. According to Gartner, by 2022, more than 80% of enterprise IoT projects will use AI in some form, up from just 10% currently.
This AI and Machine Learning revolution provide software developers and embedded engineers with yet another opportunity.
- Augmented Intelligence is on the Rise-
Gartner expects that by 2023, 40% of big enterprise infrastructure and operations teams would employ AI-augmented automation, resulting in increased efficiency. To get optimal results, their staff should be skilled in data science and analytics or have the option to upskill on the latest AI and ML technologies.
- Hyper Automation-
The Future of AI and Machine Learning-
The New Year has here, and we're excited to see what the future holds for AI and Machine Learning, as well as the advances they will bring. Despite their age, these technologies are still in their infancy. If you're a tech professional trying to keep up with the latest technological advances, now is the time to do so. Our comprehensive AI Courses will teach you everything you need to know about how AI can help you succeed in your profession, as well as keep you up to date on machine learning's future. Geoffrey Everest Hinton CC FRS
Geoffrey Everest Hinton CC FRS FRSC (born 6 December 1947) is a British-Canadian cognitive psychologist and computer scientist, most noted for his work on artificial neural networks.
What are the 3 types of machine learning?
These are three types of machine learning: supervised learning, unsupervised learning, and reinforcement learning.
Why is machine learning used?
Simply defined, machine learning allows a user to submit massive amounts of data to a computer algorithm, which then analyses and makes data-driven suggestions and decisions based only on the supplied data.
What is AI vs machine learning?
While machine learning is founded on the idea that robots should be able to learn and adapt via experience, AI is a larger concept that refers to machines that can perform jobs "smartly." Machine learning, deep learning, and other approaches are used in artificial intelligence to tackle real-world problems.