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So far, 2023 has been all about new technology changing the way we live and interact. If predictions around the powers of artificial intelligence (AI) are correct, new technologies are all set to create a disruptive change in every domain, from healthcare to banking to aeronautics. Bots, chatbots, robots, and AI are the trendy lexicons which have gripped the tech space right now, however different they may sound; they sometimes even leave the industry insiders perplexed. Here are the key differentiators between the technologies behind the buzzwords and how can you leverage your business by their implementation.
The Automated Task PlannerThe term, bot is not interchangeable with chatbot as popular conventions go. Instead, bots are automated programs that crawl the internet pages in the search of specific information. In simple words, bots are programs that process information with or without humans noticing. The bot technology is behind when the phone recognizes a date in the text messages and suggests the user to add it to his/her Google calendar suggesting an important event, or a meeting. When you are ordering food just by texting a number and having it delivered without talking to a real human, bots is the technology behind it. Put in simple words, a bot is an application performing an automated task, like setting an alarm, informing about the weather, shopping for clothes, saving money and finding restaurants.
Conversing with TechnologyChatbots are simply programs designed to interact with humans through an automated conversation. While bots perform automated tasks without human interaction, a chatbot on the other hand, must chat and exchange information with the humans such as checking flight times or confirming travel dated before listing trains for reservations.
Tasks Performed by MachinesA
Myths Behind Chatbots and RoboticsMyth#1: AI Powers All Chatbots While chatbots are very good at answering pre-programmed questions, they go off script when they are asked complex questions like refinancing student loans, or booking single hotel rooms with additional bedding for a parent and child. For now, through chatbots, we do have very good machine learning algorithms but are far away from programs that can learn for themselves. There are flow-oriented chatbots minus the machine learning technology that work with buttons and display predefined answers when a corresponding button is pressed. Even the creators of IBM Watson supercomputer, don’t use the term Artificial Intelligence but refers the technology to be augmented intelligence that redefines the partnership between humans and machines. Myth#2: Chatbots and Robotics will Snatch Human Jobs A PwC report claims that robots and AI will take away 38% of all U.S. jobs in the next 20 years. However that may be a myth, Chatbots do reduce workload from human employees and leave them free for critical decision making jobs. Chatbots are good at repeated, routine job profiles like an assembly line, answering FAQ, receiving requests, lead generation etc. This will make way for a newer form of job profiles to emerge that require more of human critical thinking like customer relationship management, or employment is the creative and artistic fields. Myth#3: Customers Hate Human Interactions Going by Gartner reports, by 2023 85% of a customer’s relationship with a brand will be through technology like chatbots, giving fuel to predictions that about 80% of companies will be using chatbots by 2023. Chatbots can handle simple queries in shopping or healthcare, but when it comes to talking about preferences and empathy, a human assistant is what is often needed. A consumer study by PwC last March found that 8 in 10 U.S. consumers would still want to talk to a human, even if they have technology powered chatbots around them.
So far, 2023 has been all about new technology changing the way we live and interact. If predictions around the powers of artificial intelligence (AI) are correct, new technologies are all set to create a disruptive change in every domain, from healthcare to banking to aeronautics. Bots, chatbots, robots, and AI are the trendy lexicons which have gripped the tech space right now, however different they may sound; they sometimes even leave the industry insiders perplexed. Here are the key differentiators between the technologies behind the buzzwords and how can you leverage your business by their chúng tôi term, bot is not interchangeable with chatbot as popular conventions go. Instead, bots are automated programs that crawl the internet pages in the search of specific information. In simple words, bots are programs that process information with or without humans noticing. The bot technology is behind when the phone recognizes a date in the text messages and suggests the user to add it to his/her Google calendar suggesting an important event, or a meeting. When you are ordering food just by texting a number and having it delivered without talking to a real human, bots is the technology behind it. Put in simple words, a bot is an application performing an automated task, like setting an alarm, informing about the weather, shopping for clothes, saving money and finding restaurants.Chatbots are simply programs designed to interact with humans through an automated conversation. While bots perform automated tasks without human interaction, a chatbot on the other hand, must chat and exchange information with the humans such as checking flight times or confirming travel dated before listing trains for reservations. Chatbots allow users to interact via graphical interfaces or graphical widgets, including WeChat, Facebook Messenger and Whatsapp. These platforms allow web views on which developers create completely customized graphical interfaces. Put in simple words, a chatbot is another way where humans interact with technology and software. robot is designed by machines to execute programmed tasks automatically with speed and precision. The term Robot which first appeared in a 1920 play by Czech writer Karel Capek, R.U.R.: Rossum’s Universal Robots comes from the Czech word, Robota, which means “forced labor.” Today, Robots dominate the world in industries and in resembling humans. Robots are increasingly being deployed as industrial robots to perform repetitive tasks in the logistics and the assembly line. The latest development in the robotics industry is the humanoid like Sophia, Junko Chihira Erica and Geminoid DK which resemble humans and are programmed to mimic human attics, thinking and emotions.While chatbots are very good at answering pre-programmed questions, they go off script when they are asked complex questions like refinancing student loans, or booking single hotel rooms with additional bedding for a parent and child. For now, through chatbots, we do have very good machine learning algorithms but are far away from programs that can learn for themselves. There are flow-oriented chatbots minus the machine learning technology that work with buttons and display predefined answers when a corresponding button is pressed. Even the creators of IBM Watson supercomputer, don’t use the term Artificial Intelligence but refers the technology to be augmented intelligence that redefines the partnership between humans and machines.A PwC report claims that robots and AI will take away 38% of all U.S. jobs in the next 20 years. However that may be a myth, Chatbots do reduce workload from human employees and leave them free for critical decision making jobs. Chatbots are good at repeated, routine job profiles like an assembly line, answering FAQ, receiving requests, lead generation etc. This will make way for a newer form of job profiles to emerge that require more of human critical thinking like customer relationship management, or employment is the creative and artistic fields.Going by Gartner reports, by 2023 85% of a customer’s relationship with a brand will be through technology like chatbots, giving fuel to predictions that about 80% of companies will be using chatbots by 2023. Chatbots can handle simple queries in shopping or healthcare, but when it comes to talking about preferences and empathy, a human assistant is what is often needed. A consumer study by PwC last March found that 8 in 10 U.S. consumers would still want to talk to a human, even if they have technology powered chatbots around them. Bots, Chatbots, and AI are changing the ways we interact today. Data generated by our phones, web page visits or check-ins generate valuable inputs for technology to assist us through bots, chatbots and robots in customer service, healthcare banking and other industry offerings. The future is bright for these technologies to redefine interaction and business enterprises are taking their best efforts forward to deliver technology that was never the way before.
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You know that little voice in your head, the one that says,”Maybe jumping off this cliff isn’t a good idea,” or, “You can’t drink a whole gallon of milk?”
That murmur is self-doubt, and its presence helps keep us alive. But robots don’t have this instinct—just look at the DARPA Robotics Challenge. But for robots and drones to exist in the real world, they need to realize their limits. We can’t have a robot flailing around in the darkness, or trying to bust through walls. In a new paper, researchers at Carnegie Mellon are working on giving robots introspection, or a sense of self-doubt. By predicting the likelihood of their own failure through artificial intelligence, robots could become a lot more thoughtful, and safer as well.
To gauge whether an action will fail or not, the key is prediction. As humans, we predict outcomes naturally, by imagining everything that could go wrong after making a decision. In the case of deciding a drone’s flight path, an algorithm would have to look at the video coming from the drone’s camera, and predict based on the objects in the picture if its next action will cause a crash. The drone would have to imagine the future.
This idea goes beyond object detection, a feature found in some drones now. That detection is simple: if there’s something in the way, don’t go there. But this framework would allow the A.I. to actually determine if the scenario could be detrimental to its primary mission. That includes weather conditions that block the drone’s sensors, or a lack of light needed for a its cameras. It’s understanding a potential threat, rather than reacting to it.
In Carnegie Mellon’s tests, researchers set a modified drone to fly autonomously through trees in a park. By predicting the drone’s trajectory and the likelihood of it crashing if it took that course, it flew more than twice as long as attempts without introspection—more than 1000 meters weaving through obstacles.
But still, this work is preliminary, and not alone. Microsoft Research’s Eric Horvitz has been working on this idea for years, focusing on making many decision-making algorithms work together.
“We’re developing active systems that reflect about many many things at once that can think together and coordinate elegantly many competencies and functions, so that they operate more or less like a well-practiced symphony,” Horvitz said.
One of these scenarios reenacted a game show, but with an A.I. host and two human competitors. The A.I. would pose questions, and the humans would answer. But to maintain a proper conversation—like asking if the contestant needed more time—the A.I. would calculate to see how long it would take to compute a response, and check that against how long before a human would probably speak. If it would take too long, the robot would stay silent.
“Adding that layer was beautiful, it made the system much more elegant,” Horvitz said.
If there’s a path to self-awareness in robots, it’s through teaching introspection. It’s instilling a crude imperative to survive, a thought that might make some futurists shudder. But at least for now, these robots can barely dodge trees—so humans will be safe for another few years at least.
AI chatbots have rapidly gained popularity in recent years, and their ability to generate text is one of their most important features, providing numerous benefits for businesses and individuals alike.
Artificial intelligence (AI) chatbots have the potential to change the way content is created. Text generation allows chatbots to have more natural and engaging conversations with users, and it can also be used to create a variety of other content, such as articles, blog posts, and even creative writing.
In this article, we will explore everything you need to know about AI chatbots and their text generation capabilities.
What is an AI chatbot?An AI chatbot is a computer program that uses artificial intelligence (AI) to simulate conversations with human users. AI chatbots are often used in customer service applications, where they can answer questions, provide support, and resolve issues. They can also be used for marketing and sales, education, and entertainment.
AI chatbots are trained on large datasets of text and code, which allows them to learn how to understand and respond to human language. They use natural language processing (NLP) to understand the meaning of human language, and machine learning to generate responses that are relevant and helpful.
AI chatbots are still under development, but they have the potential to revolutionize the way we interact with computers. They can provide a more personalized and engaging experience for users, and they can help businesses to improve efficiency and customer satisfaction.
Here are some of the benefits of using AI chatbots:
Improved customer service: AI chatbots can provide 24/7 customer service, which can help businesses to improve customer satisfaction.
Reduced costs: AI chatbots can help businesses to reduce costs by automating tasks that would otherwise be done by human employees.
Increased productivity: AI chatbots can help businesses to increase productivity by freeing up human employees to focus on more complex tasks.
Improved data collection: AI chatbots can collect data about customer interactions, which can be used to improve products and services.
How do AI chatbots generate text?There are a few different ways that AI chatbots can generate text. One common approach is to use natural language processing (NLP). NLP is a field of artificial intelligence that deals with the interaction between computers and human (natural) languages. NLP techniques can be used to understand the meaning of human language, and to generate text that is both grammatically correct and relevant to the context.
Another common approach is to use machine learning (ML). Machine learning is a field of artificial intelligence that deals with the development of algorithms that can learn from data. Machine learning techniques can be used to train AI chatbots to generate text that is similar to the text that they have been trained on.
Finally, AI chatbots can also be used to generate creative text. This can be done by using techniques such as natural language generation (NLG) and deep learning. NLG is a field of artificial intelligence that deals with the generation of natural language text. Deep learning is a type of machine learning that uses artificial neural networks to learn from data.
AI chatbots that are able to generate creative text can be used for a variety of purposes, such as writing stories, poems, and scripts. They can also be used to generate text that is tailored to a specific audience, such as marketing copy or customer service responses.
As AI technology continues to develop, AI chatbots will become even more sophisticated and capable. They will be able to generate text that is more natural, more creative, and more relevant to the context. This will make them even more useful for a variety of applications.
What are the different types of AI chatbots?There are many different types of AI chatbots, but they can generally be divided into two categories: rule-based chatbots and machine learning chatbots.
Rule-based chatbots are the simplest type of AI chatbot. They are programmed with a set of rules that define how they should respond to certain prompts or questions. For example, a rule-based chatbot might be programmed to answer questions about the weather, provide customer service information, or make appointments.
Machine learning chatbots are more sophisticated than rule-based chatbots. They are trained on large datasets of text and code, which allows them to learn how to understand and respond to human language in a more natural way. Machine learning chatbots can be used for a variety of tasks, such as customer service, sales, and marketing.
Here are the pros and cons of the two main types of AI chatbots:
Simple to develop and maintain
Can be used for a variety of tasks
Can be limited in their ability to understand and respond to complex questions
May not be able to learn and adapt over time
Machine learning chatbots
Can understand and respond to complex questions
Can learn and adapt over time
Can be used for a variety of tasks
More complex to develop and maintain
Can be more expensive
May not be able to handle all types of requests
Ultimately, the best type of AI chatbot for a particular application will depend on the specific needs of the user.
Here are some other types of AI chatbots:
Hybrid chatbots combine the features of rule-based and machine learning chatbots. They are programmed with a set of rules, but they can also learn and adapt over time.
Virtual assistants are AI chatbots that are designed to provide assistance to users. They can be used to answer questions, make appointments, and perform other tasks.
Chatbots for education are used to provide instruction and support to students. They can also be used to assess student learning and provide feedback.
Chatbots for entertainment are used to provide games, quizzes, and other forms of entertainment. They can also be used to connect users with each other.
Comparison of Accuracy, Fluency, Creativity, Relevance, and PlagiarismAI chatbots are becoming increasingly sophisticated, and their ability to generate text is becoming more impressive. However, there are still some key differences between the text generated by AI chatbots and the text generated by humans.
here is a comparison of text generated by AI chatbots:
Accuracy: One of the biggest differences is accuracy. AI chatbots can be very accurate, but they can also make mistakes. It is important to evaluate the accuracy of an AI chatbot before using it for important tasks.
Fluency: Another difference is fluency. AI chatbots should be able to generate text that is fluent and easy to read. If the text is choppy or difficult to understand, it may be a sign that the AI chatbot is not very good. It is important to choose a chatbot that can generate text that is fluent and easy to read.
Creativity: The creativity of text generated by AI chatbots can also vary. Some chatbots are able to generate text that is original and thought-provoking, This can be a great asset for businesses that want to create engaging content for their customers, while others produce text that is repetitive or unoriginal. The creativity of the text will depend on the chatbot’s training data and the complexity of the text.
Relevance: The relevance of text generated by AI chatbots also varies. AI chatbots should be able to generate text that is relevant to the topic at hand. If the text is off-topic or irrelevant, it may be a sign that the AI chatbot is not very good.
Plagiarism: Plagiarism is a concern with AI chatbots. They can sometimes plagiarize text from other sources. This is a problem because it can lead to legal problems for businesses that use AI chatbots. It is important to use an AI chatbot that has a good plagiarism detection system.
Ultimately, the best AI chatbot for a particular application will depend on the specific needs of the user. If you are looking for an AI chatbot that is accurate, fluent, creative, relevant, and free of plagiarism, then you will need to do some research to find the right one.
Factors to consider when choosing an AI chatbotThere are many factors to consider when choosing an AI chatbot. Some of the most important factors include:
Purpose of the chatbot: What do you want the chatbot to do? Do you want it to answer questions, provide customer service, or something else?
Target audience: Who will be using the chatbot? What are their needs and expectations?
Features: What features are important to you? Do you need the chatbot to be able to answer questions, generate text, or translate languages?
Budget: How much are you willing to spend on a chatbot? AI chatbots can range in price from free to thousands of dollars per month.
Level of customization: Do you want a chatbot that is customized to your specific needs?
Ease of use: How easy is it to use the chatbot? Can users easily find the information they need?
Security features: Does the chatbot have security features in place to protect user data?
Support: Does the chatbot provider offer support? If so, what kind of support is available?
Once you have considered these factors, you can start to narrow down your choices and choose the best AI chatbot for your needs.
Here are some additional tips for choosing an AI chatbot:
Talk to a provider: If you have any questions, don’t hesitate to talk to a chatbot provider. They can help you choose the right chatbot for your needs.
Which AI chatbot is the best?There is no one “best” AI chatbot, as the best chatbot for you will depend on your specific needs and requirements. However, some of the most popular and well-regarded AI chatbots include:
ChatGPT: ChatGPT is a chatbot developed by OpenAI that is known for its accuracy and fluency. It can generate text that is factually accurate and consistent with the information that it has been trained on.
Bard: Bard is a chatbot developed by Google AI that is known for its creativity and relevance. It can generate text that is original and thought-provoking, and it can also generate text that is relevant to the topic at hand.
Xiaoice: Xiaoice is a chatbot developed by Microsoft that is known for its popularity in China. It has been used by over 600 million people, and it has been praised for its ability to provide companionship and support.
YouChat: YouChat is an artificial intelligence-powered search assistant developed by chúng tôi It is designed to improve web searching using a chat-based interface that allows users to ask questions and receive relevant responses in a conversational manner. YouChat is based on large language models and machine learning algorithms that allow it to understand and interpret natural language queries and generate accurate and informative responses. It can answer general questions, explain concepts, suggest ideas, translate, summarize text, compose emails, and even write code snippets. YouChat is constantly learning and improving based on user feedback, and aims to provide a more efficient and interactive way of searching and accessing information on the internet.
The best way to choose an AI chatbot is to try out a few different ones and see which one works best for y
It is important to note that AI chatbots are still under development, and they are not perfect. They can sometimes make mistakes, and they may not always be able to understand your requests. It is important to be patient with AI chatbots, and to provide them with feedback so that they can learn and improve.
Comparison of Text Generated by ChatGPT and Bard AIFeatureChatGPTBardAccuracyChatGPT is generally accurate, but it can sometimes make mistakes. For example, it may misspell words or make grammatical chúng tôi is very accurate, and it rarely makes mistakes.FluencyChatGPT’s text is generally fluent and easy to read. However, it can sometimes be choppy or difficult to understand.Bard’s text is very fluent and easy to read. It is always clear and concise.CreativityChatGPT can be creative, but it is not as creative as Bard. Bard is able to generate text that is original and chúng tôi is very creative, and it is able to generate text that is original and thought-provoking.RelevanceChatGPT’s text is generally relevant to the topic at hand. However, it can sometimes go off on tangents or introduce irrelevant information.Bard’s text is always relevant to the topic at hand. It is never off-topic or irrelevant.PlagiarismChatGPT can sometimes plagiarize text from other sources. This is a problem because it can lead to legal problems for businesses that use chúng tôi has a good plagiarism detection system, and it never plagiarizes text from other sources.
Overall, Bard is a more accurate, fluent, creative, relevant, and plagiarism-free chatbot than ChatGPT. If you are looking for a chatbot that can generate high-quality text, Bard is the best option.
Future of AI chatbotsThe future of AI chatbots looks very promising. Chatbots have already become a popular way to automate customer service and provide quick and efficient responses to common questions.
As AI chatbots continue to improve, they may also become better at understanding human emotions and providing more personalized interactions. However, developing ethical and responsible AI solutions will continue to be an important consideration in the development and implementation of AI chatbots.
Over 70% of chatbot conversations are expected to be with retail conversational AI systems in 2023. Additionally, in a survey, ±40% of U.S. consumers stated that they have used chatbots to engage with the retail industry. And as of 2023, ±54% of consumers had daily AI-enabled interactions with retail organizations.
Chatbots provide 24/7 support, answer FAQs, and can offer promotions to customers based on their intent, making them a great candidate for retailers to improve customer satisfaction and brand loyalty.
Top 12 chatbot use cases in retail
According to the National Retail Federation, 54% of shoppers go online to purchase something specific, and what makes them choose a specific brand to shop is:
The ability to find what they want quickly and easily (58%).
Quality customer service (44%).
Speedy and simple checkouts (42%).
These features can all be embedded into the chatbots, making them excellent integrations with retail websites and communication platforms.
Salesforce is the CRM market leader and Salesforce Contact Genie enables multi-channel live chat supported by AI-driven assistants. Salesforce Contact Center enables workflow automation for many branches of the CRM and especially for the customer service operations by leveraging chatbot and conversational AI technologies for a personalized customer experience.
Chatbot use cases in retail include:
1. Search for products 2. RecommendationsRecommendation engines integrated to chatbots can help retailers increase revenue and help users discover products that fit well with their tastes. Such adaptation of chatbots especially on messaging apps like WhatsApp is also called conversational commerce and enhanced customer satisfaction due to recommendations cause customers to spend more.
3. Locate nearby storesA customer may want to see or try on a product that they found while browsing the website, in person. Via the chatbot, the customer can locate nearby stores, enquire about the product’s availability, and find out about opening hours.
4. Place orders and pre-ordersCustomers can choose the product they want to purchase, set up their address and contact information, and place their order via the chatbot.
Additionally, the chatbot can provide information about upcoming products that are relevant to the customer’s preferences , and allow them to pre-order new products before they start shipping.
For example, an office supplies retail company, Staples, integrated IBM Watson’s chatbot to their Facebook messenger, Slack, and texting services. The chatbot allows customers to place orders for current and up-coming products from the Staples stores.
5. Track packagesOnce the order is placed via the chatbot, the customer can ask about the whereabouts of the package, date and time of delivery, and information about the post service, such as their local branch’s contact information.
6. Customer education / FAQInstead of speaking to a live agent, the customer can get information from a chatbot about the product, such as the return policy of products, promotional campaigns, discounts coupons, and FAQs.
7. Support live agentsChatbots are linked to the company’s database where all information about products, services, features, and locations exist. If customers prefer speaking to live agents, the agent can rely on the chatbot to quickly look up answers and prevent wrong information being communicated to customers.
Haptik builds sales chatbots and intelligent virtual assistants (IVA) for many firms from a variety of industries to improve their processes, sales and customer satisfaction.
Haptik’s chatbots have answered over 4bn customer queries as of today, and thus making them suitable to be leveraged in the retail sector.
8. Send personalized notificationsChatbots typically ask users for their contact info during the conversation. This provides an opportunity for retailers to use the customers’ info to send users updates and notifications about new products, annual or seasonal sales, as well as branch openings and events.
These messages and notifications are based on a customer’s information, demographics, preferences, searches, and previous orders.
To find case studies regarding personalized notifications you can read our Top 5 Conversational Commerce Examples & Success Stories article.
9. Manage loyalty pointsFor retailers that provide customers with loyalty points, chatbots can ping the users and tell them about currently available points in their credit, and direct them to purchasing links or promotions where they can spend these points.
Source: Miracle Software Systems
10. Manage complaintsThe chatbot can register online complaints by asking about the incident details. The data and insights gathered through the chatbot for oversight and policy development purposes.
11. Collect customer feedbackInstead of reaching out to the customer to fill a satisfaction survey after a purchase, a chatbot can directly ask the customer questions, such as, ranking the product, the mail service, packaging, etc. in order to analyze consumer behavioral patterns and enhance the shopping experience.
12. Monitor use sentimentNLP and affective AI technologies can analyze all customer conversations to infer their levels of satisfaction without asking them to fill surveys.
Integrating such technologies to chatbots enable a better customer experience. For example, they can help predict customers’ emotions. Some example use cases include:
Enhance the customer’s experience or provide warnings when the user is in distress.
Identify which recommendations derive delightful experiences for customers and try to replicate those experiences.
Other technologies for retailChatbots are one of many technologies which the retail industry can benefit from. Other eCommerce technologies include AI, RPA, intelligent automation, web crawling, and analytics which we’ve wrote in detail about. Combining these technologies will enable:
Brand endorsement by customizing shopping experiences.
Data and prediction-driven merchandize and promotions.
Managing a higher volume of orders at the same time.
Reduction of cost-to-serve:
Chatbots can serve as helpers in self-service cashier stands.
Analytics can offer predictions about customer service workload.
Analytics can also offer estimations about in-store replenishment workload, such as shelving.
However, to reap the benefits of AI technologies, especially chatbots, a high level of training and testing is required to recognize the user’s intent and provide them with proper responses. Otherwise, chatbots may say unacceptable things, or simply not take no for an answer which could drive customers away from the brand. Feel free to read our articles about chatbot failures and A/B testing to avoid them.
For more on chatbotsFor more applications of chatbots in different industries, feel free to read our articles:
To learn more how AI is helping businesses today, feel free to read our article 100+ AI Use Cases & Applications: In-Depth Guide
If you have any more questions about conversational AI, download our comprehensive whitepaper on the topic:
You can also download our voice bot whitepaper:
And if you are ready to invest in an off-the-shelf conversational AI product, we can help:
This article was drafted by former AIMultiple industry analyst Alamira Jouman Hajjar.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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Robots made out of flexible materials have huge potential, and in recent years they’ve been the subject of a lot of research and development. But the field still has far to go, and one hurdle is the fact that robots are usually controlled using computers—which tend to be hard and inflexible. Now, a team of researchers from Harvard University has come up with a soft replacement for those hard electronic components, in the form of a rubber computer that runs on “digital logic.” Robots that have this computer as part of their design will be completely made of soft parts.
Soft robotics has “really come a long way over the past decade,” says study first author Daniel Preston. “What’s really been missing is the ability to control things with a completely soft computation,” he says. Autonomous soft robots would be able to take some of the benefits of squishy mechanoids—being relatively simple, durable, and long-lasting, as well as interacting safely with humans due to their soft touch—much farther.
Completely soft robots do already exist, and their movement is powered by pressurized liquid moving through tiny channels, in a process called microfluidics. But those devices are generally small, says Preston, and not able to provide the levels of airflow most robots need to move around and grip things. Low levels of airflow also make computations slower. “We designed our devices at a little bit larger scale,” he says. Higher airflow rates using their technique allow the soft robot to make computations in about a second, using pressurized air flowing through channels that are about one millimeter (0.03 inches) in diameter.
The computer works on the same principles as any other: a series of gates that open and close, transferring information down pathways. In this case, the soft computer is made out of silicon tubing and pressurized air. The air moving through “gates” in the rubber acts in the same way as electricity does moving through the computer chips in your laptop or smartphone: it triggers inputs and outcomes at each stage in the rubber, thereby dictating the bot’s movements.
“It allows devices that are completely soft to be able to interact with their environment, and with human users through things like completely soft sensors and also things like completely soft buttons,” Preston says.
Currently, the team’s robots have 10-20 logic gates, and in future research, they hope to design robots with up to 100 or even 1000, he says. Each of those extra moves would make the mechanoid more sophisticated. Each gate transmits a message, in the form of air, to the next, telling it what to do. The more complicated the network of gates, the more actions the robot can take.
An all-soft robot can interact with humans more effectively, which is what Preston is most excited about. After all, we’re pretty soft, and hard metal or plastic robots need to be carefully calibrated in order not to hurt us. Soft robots simply can’t exert enough force to cause harm by accident, which makes them ideal for performing surgical procedures.
Right now, “the field of soft robotics is attempting to augment or find new abilities,” says Robert Shepherd, a Cornell University soft roboticist who was not involved in the current study. Mimicking something we know a lot about—digital logic, the sort underpinning smartphones and computers—is a logical way to move forward with making soft robots that think for themselves, he says.
If it works out in the field, Shepherd says, the Harvard researchers’ innovation could have “great applications.” Soft robots are generally cheaper to make, safer to work with, and need to do fewer computations to work than their hard-shelled counterparts, which means they could be easier to manufacture, work alongside, and use. If they can think for themselves, too, they might come in handy for things like search and rescue, picking up and sorting animals like mice in a laboratory environment, and even working in a manufacturing setting, where their soft bodies make them better coworkers for fragile humans.
The Indonesian Navy’s Kapitan Pattimura-class corvette, KRI Sultan Thaha Syaifuddin, tested a 7 barrel Type 730 CIWS last year. The Indonesians liked it enough to purchase two for modernizing their fast attack boats, more order may soon follow. defense.pk
The High Speed Intercept Boat is a very fast (80 knots!) USV still being tested by the PLAN, and already offered for export. Currently capable of being armed with machine guns, its arsenal will likely expand once it enters service.
Chinese Third Offset
This concept from September 2024 shows a network of Chinese fast USVs undertaking various tasks, including escort, interdiction of civilian freighters, patrolling offshore assets and working in a system of systems with other unmanned systems, including drones and submersibles.
The CH-901, a micro-UAV, is already in service with the PLA. While a useful recon tool, it can kamikaze into enemy forces and detonate its warhead for some quick carnage.
The Switchblade is a similar micro UAV to the CH-901, with both reconnaissance and a suicide attack capability. The US Army and Marine Corps have been deployed with 4,000 Switchblades in Afghani operations.
The CH-901 would serve a wide range of uses for both the PLA and foreign customers in Southeast Asia and elsewhere. Instead of having to rely on air support or artillery fire that may be unavailable for whatever reason, small infantry units can mount sneak attacks on vital enemy infrastructure. Also, the CH-901 would be a powerful force multiplier for the average solider in urban combat, and a cheap weapon in counterinsurgency fights.
More Guns for the Garuda
The Indonesian Navy’s Kapitan Pattimura-class corvette, KRI Sultan Thaha Syaifuddin, tested a 7 barrel Type 730 CIWS last year. The Indonesians liked it enough to purchase two for modernizing their fast attack boats, more order may soon follow.
Moving to a more conventional weapons category, Indonesia has agreed to purchase two Type 730 Close In Weapons System to arm its KCR-60M missile boats. The PLAN already uses the Type 730, a seven barrel 30mm Gatling cannon, for close area defense of warships like the Type 052D destroyer, against enemy missiles and small boats. The Indonesia Navy has already been testing the Type 730 CIWS onboard one of its missile boats since last year. Given the need for an effective CIWS to have top notch radars and cameras to target missiles in just a couple seconds, Indonesia must have judged it to be competitive with Western systems that Indonesia already has. Taken in conjunction with previous Indonesian purchases of C-701 antiship missiles, Indonesia looks set to be a repeat customer for Chinese weapons, in spite of occasional maritime disputes.
Special Forces ZH-05
This ZH-05 is a Chinese smart grenade/rifle, with a 20mm grenade launcher that can fired munitions programmed for individual engagements. China’s development and field of smart rifles and micro attack drones are the first wave in Chinese innovations for infantry weapon technology, coming soon to the 21st century battlefield.
China’s willingness to offer weapons already used by or even still in testing with its military is looking a look like a pivot by China to go beyond economic trade and aid when winning friends aboard. And in addition to the high profile categories like long range missiles and submarines, China also has the killer apps for the average grunt on the ground. If western nations like the U.S. won’t export personal infantry digital equipment and robots, China seems well positioned to fill that supply gap.
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