The artificial intelligence and machine learning fields have seen an increase in demand recently. Reliance on intelligent systems is becoming increasingly common. From smart devices to smart homes, people are enjoying the era of intelligent systems. Computer scientists and engineers have done a lot of work in the area. Still, the world expects the future to follow the same trajectory of growth. As IT companies work to offer seamless experiences to their customers, data analytics, AI, and ML become increasingly important.
Current State of AI and ML
Despite the current pandemic, the AI and ML industry has continued to flourish. In fact, the reliance on smart technologies has gone up since the beginning of the COVID outbreak. Companies worldwide are currently employing AI in their infrastructure. Technical leads have been inclining to rely on these technologies for better productivity and efficiency of business processes. AI and ML initiatives continue to scale as companies shift their priorities to practical AI rather than experimentation.
However, you can expect a lot of transitions in the field of AI and ML. As different needs emerge, researchers will mold AI to fit the circumstances accordingly. As per Anand Rao, global AI lead at PwC, data privacy and regulations will significantly impact the way we work with AI and ML in the coming years. Similarly, you can expect other areas to receive modified versions of a central intelligent system. The developers aim these at improving business performance.
Over the last year, the world of smart systems has come a long way. Developers and researchers have made numerous improvements and discovered new uses for the technology. Rohan Amin, chief product officer at Chase, said that 86% of companies that employed AI for their customer experience had reported a positive outcome. Moreover, according to Appen’s “The State of AI and Machine Learning” 2021 survey, budget allocation for AI has also increased. 53% of the respondents reported that the budget was in the $500K to $5M range compared to 33% in 2020.
Further, companies are also more aware of the privacy concerns related to intelligent data handling. Almost 9 out of 10 survey respondents reported that their companies were aware of the risks. They also said that the organizations were dealing with these risks professionally. Moreover, companies that employ third-party providers were 1.8 times more likely to state that their privacy policies are excellent. This is primarily because these external providers have strict compliance policies that prevent any data leaks.
Researchers expect the coming years to see an increase in the use of intelligent systems in every aspect of life. They also predict organizations to work for better use of these algorithms in comparison to worrying about the biases associated with them. Muddu Sudhakar, CEO of Aisera, believes that companies will form specific teams to cater to issues and concerns regarding responsible AI. This will not only improve the overall reliability of the systems but also increase reliance on them.
Latest AI and ML Trends
Artificial intelligence is shaping the world we live in. Even if the impact is not huge, it is transforming different areas of our lives every day. What started off as smart assistants have now resulted in smart devices and smart homes. Everything is just a command away. Similarly, the future holds exciting new discoveries and advancements to the field. Researchers expect new domains and innovations to form and increase AI’s collection in a variety of areas.
You should ensure that you are utilizing AI and ML’s capabilities to the fullest. There are several trends you should look out for. The following are four trends that have emerged in 2021:
Automated Machine Learning or AutoML
AutoML is perhaps one of the biggest trends of 2021. It is primarily targeted towards improving the process of labeling data and tuning neural networks. Data labeling is an important aspect of training AI models. This is a tedious task, and companies usually outsource it to people across the globe. Despite manual labor being cheap in several countries, data labeling can lead to several human errors. Hence, impacting the way your algorithm performs. Automated machine learning can be a great, much faster solution that is also more accurate.
Similarly, automating the process of neural network tuning can result in cheaper AI solutions. You can then make these readily available to the public.
In a single model, AI now has the capability to support multiple modalities. These include visual, text, IoT sensors, or speech data. The main aim behind this technology is to find ways to better understand common, everyday tasks. Whether it is understanding a long document or reading patient files, multimodal learning can greatly affect us.
Tiny ML has also been gaining popularity lately. It refers to developing AI and ML models that can run on small, hardware-constrained gadgets and devices, for example, microcontrollers. These devices are used for basic commands. They are capable of performing localized analysis of data to carry out simple tasks. The “OK Google”, “Alexa”, “Hey Siri” wake words are an example of TinyML.
The crossover of quantum computing and intelligent systems can lead to breakthroughs in the future. This advanced technology can have several great benefits for companies. Companies can also use it for solving problems that seem unsolvable today. According to Scott Laliberte of Protiviti, late 2022 and early 2023 are expected to bring huge discoveries. As quantum computers become more powerful and capable, you can expect incredible advancements.
AI and ML have great growth potential. The field of intelligent systems has been in high demand for several years. The future is also expected to follow the same path. Today, AI and ML models are being employed in different areas to improve everyday life. Whether it is turning off a light or driving a car, everything is just a command away. The coming years are expected to bring some exciting new technologies as well!