Table of contents
- Top Applications of AI in Food Industry
- Sorting Fresh Produce
- Streamlining the Supply Chain
- Maintaining Food Safety Compliance
- Cleaning Processing Equipment
- Developing New Products
- Consumer’s Choice
- Higher Quality Food
- Virtual Assistants
- Self-Ordering
- Streamlining Business Operations
- The Road Ahead
It is no longer a question of if Artificial Intelligence [AI] will see greater use in the food processing industry. Instead, it is simply a question of how significantly and how swiftly AI and food industry are catching up.
Imagine a world where produce is grown with heightened nutritional and flavor profiles. This produce is sorted with minimal wastage and makes its way to manufacturing plants. Here, it is incorporated into recipes based on consumer preferences amid stringent food safety regulations. With end-to-end visibility and optimized inventory, the product is sold rapidly.
You reserve a table through your phone. Walk into the restaurant and browse the menu at leisure. You order without being conscious of your preferences. Until now you have only interacted with a bot. You are served by a waiter who knows your tastes and makes excellent recommendations. You leave feeling satisfied with the amazing experience and promise to return.
You no longer have to imagine. Artificial Intelligence in food industry is a viable reality.
Artificial Intelligence in food service is not taking over jobs. Instead, it is working with personnel to create a humane and competent source to table ecosystem.
Top Applications of AI in Food Industry
While the food industry has not been the most amenable to technology in the past, AI will be the catalyst for bringing in this revolution.
AI in the food and beverage market was valued at USD 3.07 billion in 2020. This is expected to reach USD 29.94 billion by 2026 at a CAGR of over 45.77%.
Evolving consumer needs for fast, high-quality, affordable, and easily accessible food options have precipitated these changes.
Sorting Fresh Produce
Sorting through produce is one of the most time-consuming processes faced by businesses that receive fresh produce. This is an incredibly time-consuming, labor-intensive job. AI helps in sorting fresh produce based on the end-use and optimizes usage while maximizing resources.
For instance, sorting produce by size. Whether manufacturing french fries, chips, or hash browns, machines are currently programmed to deliver consistent products regardless of the individual characteristics of each potato. Unfortunately, this uniform processing disregards the natural variations in the size and shape of potatoes leading to food waste.
TOMRA, a company founded in Norway, develops sensor-based optical sorting solutions with machine learning capabilities. Potatoes most suitable for the end product [french fries, wedges, or crisps] are identified and separated by deploying various technologies, including cameras and near-infrared sensors. TOMRA claims their sorting and peeling solutions recover 5-10% of production by reducing the amount thrown out.
Similarly, TOMRA also works in sorting through a fresh delivery of tomatoes, and picking out off-color ones decreases the probability of rejection by the retailer or consumer.
Deploying AI in food technology for sorting fresh produce leads to –
- Improved efficiency
- Reduced waste
- Higher yield
- Reduced sorting time
- Enhanced customer satisfaction
Streamlining the Supply Chain
As food safety regulations grow stricter, companies are required to maintain compliance and transparency. Artificial Intelligence in food technology proves to be of immense help in these situations. Being able to evaluate and observe food safety measures throughout the supply chain helps in maintaining accountability.
US food waste is about one-third of everything produced, equaling about 60 tons and $160 billion each year. While some of that waste happens in homes, a large amount is lost in the supply chain.
By 2035, Accenture predicts that AI will boost profitability by an average of 38% in the grocery industry by reducing wastage.
Symphony RetailAI, headquartered in Texas, helps in streamlining the supply chain in food service by deploying AI in food technology. Their technology is capable of providing actionable insights based on real-time data driving improved performance and profit.
Leveraging AI in supply chain management leads to:
- Transparent Pricing
- Maintaining Food Safety
- Simplified Inventory Management
- End-to-End Visibility
- Maintaining Compliance
- Reducing Wastage
With AI tracking market demand, there is end-to-end visibility in the supply chain. This ensures that the available products are optimally assigned and dispatched, avoiding wastage.
Must Read: AI is Boosting Food Innovation
Maintaining Food Safety Compliance
Food safety is non-negotiable. AI and food industry are coming together to maintain good personal hygiene on plant floors or kitchens.
Some of the common pain points in food plants and restaurant kitchens include:
- High consumption of human resources
- Low monitoring capabilities
- Manually checking and reviewing videos
A few years ago, KanKan AI signed a deal to provide an AI-powered solution for improving personal hygiene among food workers in China. As a result, both restaurants and manufacturing facilities can deploy this system.
KanKan works through a combination of technologies, such as
- Cameras to monitor workers
- Deploying facial-recognition software
- Leveraging object-recognition software
Maintainance of standard safety by using appropriate gear can be monitored based on safety laws. Upon detecting any violation, pertinent images from the recording are pulled up for review. The technology deployed by KanKan AI proves to be over 96% accurate.
Deploying AI in kitchens and manufacturing floors helps in:
- Uniform Recognition
- Life Cycle Supervision
- Pre-prevention
- Real-time monitoring
- Checking for sanitized hands
- Recognizing apparel [hats, aprons, hairnets, gloves, masks]
- Behavior Pose Detection
- Intelligent Enforcement
- Trash Bin Detection
- Pest and Rodent Detection
- Disinfection Detection
Cleaning Processing Equipment
Cleaning processing equipment in the food service industry is time-consuming and highly labor-intensive. It requires the following:
- Large amounts of water, consumables, and human resources.
- High amount of energy consumption
- Eating into the productivity of employees
- Excessive use of chemicals
- High cost to manufacturers
- Toxic to environment
To solve this, researchers at the University of Nottingham are developing a system that uses AI to reduce cleaning time and resources by about 20-40%.
The above uses a multi-sensor approach including visual and auditory systems for Self-Optimized Clean-In-Place [SOCIP] monitoring. SOCIP deploys ultraviolet, optical fluorescence imaging, and ultrasonic acoustic sensors to detect and measure food residue and microbial debris within various equipment. This technique subsequently optimizes the cleaning process. Further, this could reduce cleaning times by up to 50 percent, enabling less downtime and more productivity.
The research predicts that the system could save the UK food industry £100 million per year.
Developing New Products
Based on evolving consumer expectations, food manufacturing is changing with respect to ingredients, recipes, and the endless permutations and combinations available.
Gastrograph AI uses ML and predictive algorithms to model consumer flavor preferences. The data generated is analyzed and works toward simulating model consumer flavor preferences and predicting how they will respond to new tastes.
AI in concert with ML helps in categorizing the data generated into multiple demographic groups. These help companies develop new products that are in tune with the preferences of their target audience. For example, deploying AI in the food industry allows manufacturers to predict and anticipate what products will flourish before launch.
Coca-Cola began the installation of self-service soft drink fountains in various locations allowing individuals to customize their drinks. Based on the options available, customers could theoretically create hundreds of different beverages by combining different flavors with their primary beverages.
These drink fountains each dispense hundreds of different drinks a day, simultaneously generating significant data about consumer preferences.
The data demonstrated that consumers created a large number of cherry-flavored Sprite that it would do well as a standalone product. As a result, Cherry Sprite was the first product to be developed based on the insight gained.Developing recommendation engines is a prime application for AI in food technology. These will suggest new products and ingredient combinations that will flourish in the market. These will start with high volume, low-cost foods and work their way towards more complex, layered foods.
Consumer’s Choice
Today the scope of AI has evolved from simply automating. AI and food industry are coming together to understand what flavor combinations different demographics use.
For instance, Kellogg Company launched Bear Naked Custom, allowing people to make their customized granola from over 50 ingredients.
Powered by IBM’s Chef Watson, the system has analyzed thousands of possible ingredient choices. Then, the AI makes suggestions on potential ingredients to add to your granola and offers input on the taste.
However, Chef Watson does not just stop with this. The data generated through this on flavor combinations, preferences, and the number of re-orders for a particular variety creates a feedback loop. Campbell and other companies are deploying Chef Watson through Watson ads in choosing recipes.
Data analysis enables a deeper understanding and refinement of the flavors consumers love. In addition, the data generated provides valuable information on newer products and flavor combinations.TasteMap uses Deep Learning to recommend wines based on experience, environmental facts, and taste. And with Spoonshot, you can make use of the higher-order insights to drive future-forward food innovation decisions.
Higher Quality Food
An estimated 4.1 million data points are predicted to be generated every day at farms by 2050.
While this is a little way from realization, it is not too far off. There is intensive research underway on how AI and ML could help farmers grow better food by creating optimal growing conditions.
The optimal growing conditions are unique to different crops. Food computers equipped with multiple sensors collect data aiding the growth of small amounts of produce in controlled environments. The premise here is that improved flavor profiles and tolerance to external stressors could pave the way towards higher yield, maximal resources, and reduced wastage.
The data collected from these sensors can help determine the best growing conditions for different plants with specific targets using predictable outcomes. For instance, improved flavor profile in basil.
Trace Genomics extracts DNA from the soil, analyzes its microbial community, and provides AI-based recommendations for maximizing soil health and crop yield.
The discovery of unique and critical connections between growing conditions is possible due to AI.
Sentient Technologies, an AI-based company, is working on observing the effects of variables like UV light, salinity, heat, and water stress on basil.
Research from Cornell University demonstrates how a neural network was built and trained to identify brown leaf spot disease on cassava leaves with 98% accuracy. CAMP3 uses and controls wireless sensor networks to gather field images and spot plant diseases and pests early on. Additionally, AI is being deployed in farms to identify plant diseases and pests, enhance soil health, and improve nutritional quality and yield.
Front-End Applications of AI
Gartner predicts that by 2020, a whopping 85% of enterprise-customer relationships will be managed without human interactions.
Virtual Assistants
Another application of AI in food technology is the leveraging of AI-based virtual assistants such as chatbots to resolve queries, and take orders and reservations. Virtual assistants significantly reduce the waiting time, allowing the system to take on basic questions and transfer only serious issues to customer representatives.
There is immense potential for chatbots in restaurants to enhance customer engagement and welcome a hyper-connected demographic. Hotels have begun integrating chatbots in their operational processes. This has led to a remarkable ROI especially by automating their concierge desk.
Self-Ordering
AI-based self-ordering machines lead to an enhanced customer experience by eliminating queues and reducing the waiting time. In addition, these kiosks can take orders and payments directly through integrated card readers, eliminating human interference.
These kiosks leave customers feeling more comfortable as they can peruse the menu at leisure and order without feeling self-conscious about their preferences. Integrating voice ordering with these kiosks is the next big thing to reduce physical touchpoints.
Some restaurants are going a step further by displaying nutritional information. For example, Edamam generates a real-time nutritional analysis of food recipes by extracting food entities from unstructured text using Natural Language Processing.
This reduces the load on employees, allowing them to focus on creating a great customer experience and getting to know each customer individually.
Streamlining Business Operations
AI makes it possible to
- Create and manage employee schedules
- Real-time inventory tracking
- Gain insight on
- Busiest times
- Sales
- Weather and local events
- Discounts
- Pricing
- Competition
- Track social media trends
This optimizes operations and frees up some of your employees’ time so they can focus on mission-critical tasks.
AI works with employees to create a great customer experience by analyzing past data to anticipate future expectations. Then, the staff can use this information in real-time, providing customers what they want even without asking, leading to loyalty and repeat customers.
The Road Ahead
Bringing end-to-end visibility, advanced sensors, and a nuanced understanding of consumer choices, AI in the food industry is here to stay.
AI brings a comprehensive understanding of context and intent that explains customer behavior, needs, expectations, and purchase decisions.
In concert with ML, AI will help drive brand loyalty, better nutrition, and reduced food wastage through data analytics.
Aparna
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FAQs
What are the applications of AI in food industry? ›
AI has been successfully deployed for applications such as sorting fresh produce, managing supply chain, food safety compliance monitoring, effective cleaning in place systems, anticipating consumer preference and new product development with greater efficiency and savings on time and resources.
What will be the benefits of AI in food service industry? ›Better Supply Chain Management
AI in the food industry is also capable of creating accurate forecasts to manage inventory and pricing. This kind of predictive analysis helps keep food businesses one step ahead, enabling them to avoid wastage and unnecessary costs.
AI algorithms can help the food delivery systems to manage the orders accurately. It will reflect the customer's order to two different delivery partners, one who is in the nearby location of the delivery address and the other who is in the nearby location of the restaurant where the customer has ordered the food.
How is AI used in fast food? ›The conversational AI technology can greet customers, take orders, transfer orders to point of sale (POS) systems and do other functions. In a pilot program last year, Checkers & Rally's found that the AI voice assistant had 98% accuracy in taking drive-thru orders and did not need restaurant employees to intervene.
What are the applications of food technology? ›Food technology is the application of food science to the selection, preservation, processing, packaging, distribution, and use of safe food. Related fields include analytical chemistry, biotechnology, engineering, nutrition, quality control, and food safety management.
What are the 10 types of AI? ›- Natural language generation. Machines process and communicate in a different way than the human brain. ...
- Speech recognition. ...
- Virtual agents. ...
- Biometrics. ...
- Machine learning. ...
- Robotic process automation. ...
- Peer-to-peer network. ...
- Deep learning platforms.
- Reactive Machines.
- Limited Memory.
- Theory of Mind.
- Self-Aware.
- Artificial Narrow Intelligence (ANI)
- Artificial General Intelligence.
- Artificial Super Intelligence (ASI)
Manufacturers can also expect to lower productions costs, improve the quality of food, practice better hygiene, improve packaging and do much more by relying on such modern tech. This is precisely why AI in food industry is so popular nowadays and could very well become the norm in the next few years.
How AI is changing the food industry? ›AI in the food industry ensures that the food being processed will reach specific criteria when quality standards are input, creating a far more efficient production process. As a result, less time is spent manually sorting. In addition, there is higher production, better quality, and less waste.
How is AI used in restaurants? ›Voice AI applications have the capacity to process multiple orders at once without being overwhelmed or interrupted with other tasks. With a virtual ordering assistant, workers can focus on preparing orders and serving more guests, helping restaurants double their sales during peak hours.
How is McDonald's using AI? ›
Order Prediction — McDonald's uses machine learning-based decision technology to predict what menu offerings are most likely to drive sales in its drive-thru business.
How is Nestle using AI? ›The company uses AI for providing personalized health and wellness solutions, custom recipes, answer queries, and more. Data analytics and consumer insights enable Nestle to identify different consumer preferences and design products accordingly.
How Mcdonalds is using AI? ›AI and data are helping McDonald's bring together supply and demand. By tying personalized recommendations to its entire supply chain network, the fast-food chain has created a new way of managing its inventory and promoting key products.
Does refrigerator use AI? ›The Intelligent Refrigerator module is designed to convert any existing refrigerator into an intelligent cost effective appliance using ARTIFICIAL INTELLIGENCE. The intelligent refrigerator is capable of sensing and monitoring its contents and counts the age of the contents.
How can we use AI in Zero Hunger? ›AI can provide a significant boost towards combating global hunger. Its presence in improving agriculture, food, storage and distribution processes and the way to intelligently deal with weather can create a crucial advantage, beneficial to all.
Does Starbucks use AI? ›Starbucks has therefore decided to use A.I.: Its algorithms will decide the order in which baristas in stores should brew drinks, based on customers' estimated arrival times and orders.
What are the 10 uses of food? ›- Clean and whiten nails. ...
- Treat flatulence and heartburn. ...
- Impromptu makeup remover. ...
- Relax stiff muscles. ...
- Make a dry shampoo. ...
- Make a shaving cream substitute. ...
- Soothe a burned tongue. ...
- Soothe sore nipples.
- Plastic-free and Smart Packaging. ...
- Drinks That Offer More. ...
- Advanced Computerized Technology. ...
- A Modern Drainage System. ...
- Modernization of Old Processing Techniques. ...
- A Focus on Transparency and Trust. ...
- The Use of Forward Osmosis. ...
- Plant-based, Animal-free Products.
- Food gives you energy to get through the day. ...
- Food helps us to repair muscle and build DNA. ...
- Food can help your body insulate itself and improve your health. ...
- Food can help you feel better, as well as make you appear 'more attractive' ...
- Food helps your brain.
Prominent examples of AI software used in everyday life include voice assistants, image recognition for face unlock in mobile phones, and ML-based financial fraud detection. AI software usually involves just downloading software with AI capabilities from an online store and requires no peripheral devices.
Who is father of AI? ›
Abstract: If John McCarthy, the father of AI, were to coin a new phrase for "artificial intelligence" today, he would probably use "computational intelligence." McCarthy is not just the father of AI, he is also the inventor of the Lisp (list processing) language.
What is the most popular AI? ›- Software #1: Viso Suite Platform.
- Software #2: Content DNA Platform.
- Software #3: Jupyter Notebooks.
- Software #4: Google Cloud AI Platform.
- Software #5: Azure Machine Learning Studio.
- Software #6: Infosys Nia.
- Software #7: Salesforce Einstein.
- Software #8: Chorus.ai.
Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision.
What are different applications on AI in real life? ›Healthcare. Machine learning is currently being used by businesses to produce better and faster predictions than people. Doctors can quickly identify cancer using AI and machine learning before it's too late. AI increases quality and patient safety by increasing predictability, consistency, and dependability.
What are the 5 big ideas of AI? ›In this fun one-hour class, students will learn about the Five Big Ideas in AI (Perception, Representation & Reasoning, Learning, Human-AI Interaction, and Societal Impact) through discussions and games.
What are the 4 levels of AI? ›According to the current system of classification, there are four primary AI types: reactive, limited memory, theory of mind, and self-aware.
How are robots used in the food industry? ›Industrial robots are increasingly being integrated in order to save time and space, as well as improving cleanliness and safety. Food manufacturing robots are commonly used in the dispensing, feed placement, cutting, packaging or casing of food, pick-and-placing products into containers, and sorting.
What are the benefits of using AI in F&B manufacturing? ›- Make smarter business decisions.
- Gain consumer insights for more targeted marketing efforts.
- Improve customer experience.
- Enhance productivity.
- Prevent human errors.
- Increase efficiency.
- Save money.
Improving supply chain
The need to track the data-driven supply chain is critical, and AI can assist by offering new supply chain insights to stay ahead of the game. AI can assist in the tracking of food and beverage across the whole supply chain, from the farm to the manufacturer, distributor, and retailer.
AI algorithms may help better understand and predict the complex and non-linear interactions between nutrition-related data and health outcomes, particularly when large amounts of data need to be structured and integrated, such as in metabolomics.
What is innovation in food industry? ›
Food innovation is the development and commoditization of new food products, processes, and services. Right now, it's happening rapidly. Food and beverage companies are looking for ways to make healthy, nutritious offerings that are not only enticing, accessible, exciting, and unique, but also sustainable.
What are the recent trends in food technologies? ›Robotic chefs and food processing robots further fuel food robotics as a prominent food technology trend. Also, autonomous drones and vehicles are emerging to be efficient substitutes for manual delivery services while saving overall costs.
How is AI used in hospitality industry? ›An Intelligent virtual assistant: Chatbots
An application powered by AI and ML enables the Travel and Hospitality industry to personalize services, analyze user reviews, and offer virtual assistance.
Uber AI's graph neural netowrk based method is used used for improving the quality of dish and restaurant recommendations in Uber Eats. The articledetails the algorithm, the experiments and the pipeline, and also shows examples of how they all work together in production to improve the user experience.
What food companies use robots? ›Miso Robotics
The Pasadena, California-based startup is creating robots that take on repetitive, menial, risky kitchen jobs. White Castle and now Jack in the Box use Flippy and its second-gen version Flippy 2 to whip up burgers and handle french fry duties.
This occupation has been voted '69%' by our users to be fully automated within the next two decades. Our visitors have voted that it's quite likely this occupation will be replaced by robots/AI. This is further validated by the automation risk level we have generated, which suggests a 89% chance of automation.
Will AI replace delivery drivers? ›Delivery drivers, who are often independent contractors barely managing to pay their bills, will not be replaced by machines any time soon.
How does Lemonade use AI? ›Lemonade uses bots, software that automatically performs simple tasks, to deliver insurance through its app and at lemonade.com. By replacing brokers and bureaucracy with bots and machine learning, Lemonade promises zero paperwork, 'instant everything and killer prices'.
Does Coke use AI? ›Coca-Cola uses AI to analyse the social media content of their consumers, generating insights on where, when and how its products are consumed. Based on the consumer behaviour and demographics analysis, Coca-Cola can identify which products are popular in which areas.
How does AI improve customer satisfaction? ›For example, AI makes it easy to analyze browsing history on company websites to determine what customers are looking for and guide them to what they need. It also facilitates proactive support, allowing businesses to quickly identify customer issues before customers even know they have them.
What did Mark Zuckerberg say about AI? ›
"The ability to communicate with anyone in any language is a superpower that was dreamt of forever," he said. Builder Bot was part of Meta's CAIRaoke project to improve AI assistants and allow "AI to see the world from our experience" as people entered virtual reality via headsets or glasses, Mr Zuckerberg said.
How can fast-food chains or restaurants chain use AI? ›With AI, digital customer service assistants can be programmed to hear and understand orders, know every menu item, and even check inventory levels.
Will fast-food jobs be automated? ›Many jobs in the restaurant business are monotonous, becoming easy prey to automation. But for now, it seems as though McDonald's and other restaurants aren't planning to fire the country's nearly 5 million fast-food employees anytime soon.
Does PepsiCo use AI? ›In its quest to create the perfect cheeto, steer sales teams to the most efficient routes, and much more, PepsiCo is finding innovative ways to use AI every day. If you've ever asked Siri or Alexa a question, had a virtual chat with customer service or logged on to social media, you've used artificial intelligence.
› technology › how-mcdonalds-i... ›How McDonald's is using AI to transform into a greasier version of ...
McDonald’s Embraces Artificial Intelligence for Fast Food
Top 5 Uses of AI in McDonald’s
Manufacturers can also expect to lower productions costs, improve the quality of food, practice better hygiene, improve packaging and do much more by relying on such modern tech. This is precisely why AI in food industry is so popular nowadays and could very well become the norm in the next few years.
How AI is changing the food industry? ›AI in the food industry ensures that the food being processed will reach specific criteria when quality standards are input, creating a far more efficient production process. As a result, less time is spent manually sorting. In addition, there is higher production, better quality, and less waste.
What are the major application of AI? ›Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision.
What are the 3 most popular applications of AI in agriculture? ›- Crop and soil monitoring.
- Insect and plant disease detection.
- Livestock health monitoring.
- Intelligent spraying.
- Automatic weeding.
- Aerial survey and imaging.
- Produce grading and sorting.
- The future of AI in Agriculture: Farmers as AI engineers?
Voice AI applications have the capacity to process multiple orders at once without being overwhelmed or interrupted with other tasks. With a virtual ordering assistant, workers can focus on preparing orders and serving more guests, helping restaurants double their sales during peak hours.
How does McDonald's use AI? ›
Order Prediction — McDonald's uses machine learning-based decision technology to predict what menu offerings are most likely to drive sales in its drive-thru business.
Does refrigerator use AI? ›The Intelligent Refrigerator module is designed to convert any existing refrigerator into an intelligent cost effective appliance using ARTIFICIAL INTELLIGENCE. The intelligent refrigerator is capable of sensing and monitoring its contents and counts the age of the contents.
How is Nestle using AI? ›The company uses AI for providing personalized health and wellness solutions, custom recipes, answer queries, and more. Data analytics and consumer insights enable Nestle to identify different consumer preferences and design products accordingly.
What are the benefits of using AI in F&B manufacturing? ›- Make smarter business decisions.
- Gain consumer insights for more targeted marketing efforts.
- Improve customer experience.
- Enhance productivity.
- Prevent human errors.
- Increase efficiency.
- Save money.
Improving supply chain
The need to track the data-driven supply chain is critical, and AI can assist by offering new supply chain insights to stay ahead of the game. AI can assist in the tracking of food and beverage across the whole supply chain, from the farm to the manufacturer, distributor, and retailer.
Prominent examples of AI software used in everyday life include voice assistants, image recognition for face unlock in mobile phones, and ML-based financial fraud detection. AI software usually involves just downloading software with AI capabilities from an online store and requires no peripheral devices.
What is AI applications and examples? ›Face Detection and Recognition
Utilizing face ID for unlocking our phones and using virtual filters on our faces while taking pictures are two uses of AI that are presently essential for our day-by-day lives. Face recognition is used in the former, which means that every human face can be recognized.
AI, like electricity or computers, is a general purpose technology that has a multitude of applications. It has been used in fields of language translation, image recognition, credit scoring, e-commerce and other domains.
What example of AI do we use in daily life? ›Voice assistants, such as Google Assistant, Alexa, and Siri, are the greatest AI examples in real life. hey take your inquiry via voice, process it with your phone's Speech Recognition and Natural Language Processing technologies, and then deliver the results as speech or text.
Which type of AI is the majority of applications in today's world? ›Artificial Narrow Intelligence (ANI)
ANI is the most commonly applied type of AI in the current era. As you go deeper to know what is ANI, we can see that this type of Artificial Intelligence system can perform one or two tasks. It uses the training data and the learning experiences from the previous incidents.