Machine Learning is one of the most trending topics for people in the IT industry.
As of late, Machine Learning has found its application in more than the IT industry, such as marketing, healthcare, etc. Statistics reveal that 49% of business owners worldwide plan to employ it. However, Machine Learning trends continue to vary over time. Continue reading to know which of these trends may affect small businesses.
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What does one mean by Machine Learning?
Machine Learning, in simple terms, is a way by which computers learn to make better decisions. They do so using the data provided to them and through some algorithms. A surprising thing about Machine Learning is that it resembles the way humans learn. Also, we do not program the computer to learn; it does it by itself.
Let us consider a game of chess, for example. Suppose you play a match with a computer and win. The computer analyses each move made on the board and it becomes harder for the person to win the next game. That is because of Machine Learning. All we need to do is put the basic moves of chess in the program. Afterward, the computer evolved like humans, learning and bettering itself at the game. Some other examples include chatbots, self-driving cars, etc.
How does Machine Learning help small businesses?
Small businesses can reap countless benefits from Machine Learning. However, owners of these businesses usually neglect those benefits. The most common reason is they think that Machine Learning would cost them more than the benefit it might provide.
Here are some ways in which Machine Learning for small businesses is beneficial:
Machine Learning can help the owners of small businesses with an overview of their enterprises. For example, it can help them trace a pattern in the profits made during a given session. They can also find the time frame in which their profits are maximum. Therefore, Machine Learning helps business owners understand the areas in which they can work to maximize their business prospects.
Every business requires the owners to assess the market status and trends. One way to do it is to analyze the vast amounts of data about the market. However, performing the task on one’s own can be bothersome and may not always yield accurate results. Machine Learning proves a viable solution to the problem, thanks to its innate competence in analyzing and processing data.
Ad Fraud Solution
Each business – whether big or small – requires a good marketing strategy to establish its name in the market. Presently, digital marketing is one of the most accepted and widely implemented marketing strategies. However, digital marketing has a substantial drawback – ad fraud. A report shows that about two-thirds of marketers came across marketing frauds in 2022.
The solution to effective marketing lies in Machine Learning. Studies indicate that Machine Learning might reduce the money spent on combating ad fraud by about $10 billion. Therefore, Machine Learning for small businesses is a sustainable marketing choice.
Businesses often face security issues, such as data theft, costing them significantly. As per a source, about 60% of small businesses close down due to security hacks. Yet another source reveals that small industries are subject to 43% of such cyberattacks. Out of which, only 14% of companies can withstand those attacks. Machine Learning can help such businesses put a firm fight against those attacks.
Round-the-clock customer service
The quality of customer service is in direct proportion to the success of a business. Small business owners may find it hard to provide 24*7 customer support. Machine Learning can help such business owners through its chatbot application. Chatbot features allow customers to chat with the computer and find relevant solutions to their problems. It can also connect the customers to a specific department, should the need arise. It may also help business owners gather statistics on areas where their customers frequently require support and work on it.
Machine learning trends impacting small businesses
The IT industry witnesses innovations every day. Machine learning, being a part of it, also evolves every day. That is why one must know the Machine Learning trends to make the most of it in 2022.
Take a look at the following Machine Learning trends that may prove highly beneficial for small businesses in 2022:
No-code Machine Learning
As the name suggests, no-code Machine Learning means that you do not have to write code to achieve your goals. However, coding does play a vital role in Machine Learning at some level.
Since writing codes is not compulsory for no-code Machine Learning, it saves much time while developing Machine Learning applications. Therefore, the time that businesses might have to invest in developing Machine Learning applications for themselves is available for thinking about strategies to maximize the ROI.
Some examples of no-code Machine Learning are BigML, Google Cloud AutoML, DataRobot, etc.
Tiny ML is a revolutionary piece of technology. It is a part of the much-in-demand IoT, suitable and compatible with hardware, software, and algorithms.
Recent times have found Tiny Machine Learning growing at a remarkable rate. There is a good reason why it has become a Machine Learning trend. When we run a web request, it might take a long time to send the data to a web server. It depends on the size of the data and the latency. The Machine Learning algorithm will process the data on the server and resend it to the former device.
What Tiny ML does is enable on-device operations at much lower power consumption. The power consumption is typically in mW. All IoT devices, such as Alexa, Siri, etc., are examples of Tiny ML.
Auto ML is another Machine Learning trend that helps small businesses save considerable costs on automating their requirements. Machine Learning involves data labeling, that is, labeling raw data and categorizing it based on the data type, for example, image, audio, etc. Doing it helps provide a context for the computer and facilitates accuracy.
Data labeling is a complex process that involves many risks of errors when performed by humans. Auto ML reduces the risk by automating the process. Hence, not only does the chance of miscalculations reduces but, so does the labor cost. That is why about 61% of data analysis firms use auto ML software. Some examples are AutoWEKA, TPOT, etc.
Full-stack Deep Learning
Deep learning is a higher form of Machine Learning. It involves artificial neural networks comprising several processing layers. Deep learning enables users to extract much more sophisticated forms of information than usual Machine Learning.
It has numerous applications across multiple industries. Some examples are virtual assistants, self-driving cars, detection of fraudulent news, etc. That is why an increasing number of business owners are eyeing deep learning. As per a survey, the US market for deep learning software may go up to $80 million. But, even if one has sophisticated deep learning software, it still requires integration with some files that cater to the outside world. Accomplishing it requires full-stack deep learning.
Artificial intelligence has taken the world by storm. It has made many things that were thought impossible a few years back possible today. One crucial component that allows AI to help businesses is Machine Learning.
Machine Learning helps them understand market trends, do things hands-free with a voice command through virtual assistants, and more. Business owners can grow their enterprises by understanding the trends in Machine Learning, as discussed above.