When ChatGPT was announced a few months ago, it blew the doors off a business community who hadn’t been keeping up with the progress of complex AI models. Artificial intelligence (AI) is no longer a futuristic concept reserved for science fiction movies. It’s here, and it’s changing the way we do business. As AI technology continues to evolve, it is becoming increasingly accessible and more prevalent in various industries. Companies that want to remain relevant and be successful in today’s market will have to augment their processes and technology with AI to keep up with the competition.
Types of AI used by Businesses
There are several types of AI that businesses can leverage to improve their operations and customer experience. The most common terms you’ll hear related to AI used by businesses are machine learning, natural language processing (NLP), computer vision, robotics, and predictive analytics.
-
Machine learning is a type of AI that allows computers to learn from data, without being explicitly programmed. This type of AI is used in a wide range of applications, such as image and speech recognition, natural language processing, and predictive analytics.
-
NLP is a branch of AI that deals with the interaction between computers and human language. It is used in applications such as sentiment analysis, text generation, and language translation.
-
Computer vision is a branch of AI that deals with the ability of computers to interpret and understand visual information from the world, such as images and videos.
-
Robotics is a branch of AI that deals with the design, construction, and operation of robots.
-
Predictive analytics is a branch of AI that uses statistical techniques, machine learning and data mining to analyze current and historical data to make predictions about future events.
It’s worth noting that while most popular types of AI require some level of machine learning, it’s not a requirement for all types of AI. Some AI systems can still function by using predefined rules and decision logic, but the majority of AI systems use machine learning to improve their performance and adapt to new situations.
AI in Plain Sight
Whether it’s recognized or not, AI has already permeated most aspects of the technology you use on a day to day basis:
-
Spam Filters: Most email services use AI to filter out spam messages. This is done by training a machine learning model to recognize patterns and features in emails that are likely to be spam.
-
Digital Assistants: Virtual assistants like Amazon’s Alexa, Google Assistant, and Apple’s Siri use AI to process natural language and respond to user queries.
-
Social Media Feeds: Social media platforms use AI to personalize the content shown to users on their feeds. This is done by analyzing the user’s behavior, preferences and interactions to show them the content they are most likely to engage with.
-
Recommendation Systems: Many online platforms use AI-powered recommendation systems to suggest products, videos, music, and other content to users based on their previous interactions and preferences.
-
Image Recognition: Many mobile apps use AI-powered image recognition to identify objects in images and offer additional information or actions. Examples include scanning barcodes, QR codes, or identifying plants and animals.
-
Fraud Detection: Many financial institutions and online retailers use AI-powered fraud detection systems to detect and prevent fraudulent transactions by analyzing patterns and anomalies in user behavior.
-
Speech Recognition: AI-powered speech recognition technology is used in applications such as voice-controlled devices, dictation software, and accessibility features for people with disabilities.
-
Autonomous vehicles: Self-driving cars use AI in various ways to make decisions, such as planning routes, detecting obstacles, and recognizing traffic signals
Off-the-Shelf Services for AI
You don’t have to have in-house experts in AI to start leveraging the endless opportunity offered by its use. Companies can leverage pre-built ML models, libraries and tools to develop custom ML solutions for various business use cases without having to have subject matter expertise in ML.
-
Amazon Web Services (AWS) offers a variety of ML services such as Amazon SageMaker, which allows developers to build, train, and deploy ML models. You can also use several pre-built NLP services, such as Amazon Comprehend.
-
Google Cloud Platform (GCP) offers services like Cloud AutoML, which allows developers to train custom ML models using a user-friendly interface. TensorFlow is another popular tool that allows developers to develop and deploy their own ML models quickly and easily.
-
Microsoft Azure offers services such as Azure Machine Learning Studio, which allows developers to build, deploy and manage ML models.
-
IBM Cloud offers services such as IBM Watson Studio, which allows developers to develop, train and deploy ML models.
-
Algorithmia, an independent platform, provides a marketplace of pre-built ML models and libraries that can be used to develop custom solutions.
-
OpenAI, the company that has brought us ChatGPT, offers dozens of pre-built APIs that allow access to their NLP models for various use-cases. They recently lowered their prices, making extremely powerful models available at a very low cost.
These services offer a wide range of tools and capabilities to help companies develop their own usage of ML, including pre-built models, libraries, and tools for data preparation, model training, and deployment. Additionally, some of these services also offer the ability to manage and monitor the performance of deployed models, and provide visualization and analytics capabilities.
Examples of Companies Using AI
Amazon is a pioneer in the use of AI. They have used AI to improve their logistics and supply chain, resulting in faster delivery times and more accurate predictions of customer demand. This has not only made their position as a market leader stronger, but also revolutionized the entire e-commerce industry. Another example is Netflix, which uses AI to recommend content to its users based on their viewing history. This not only improves the customer experience but also allows Netflix to stay ahead of the competition by constantly providing its users with new and relevant content. It’s not just classification and suggestion that Netflix has used AI in the pursuit of – they also used AI to shrink the required bandwidth needed to stream their movies by a significant margin. These are just a couple of examples, but there are many other companies that have leveraged new advances in AI in unique ways to become market leaders or to strengthen their position as one.
Conclusion
It’s clear that AI will become a standard part of all companies’ strategies in the near future. If you’re not already using AI, you’re already behind. Start exploring ways to incorporate AI into your processes and technology and use them to question business processes that may be outdated. Remember, the future belongs to those who embrace change and innovate. From healthcare to finance, retail to transportation, AI is being used to improve efficiency, reduce costs, and improve the overall quality of products and services. The key takeaway is that AI is not just for big companies, it’s also accessible to smaller and lesser-known companies and startups, and can help them gain a competitive edge in their respective industries. With the right approach, AI can be a powerful tool that can help companies stay ahead of the game and achieve long-term success.
