Archive 06.01.2025

ChatGPT Can Approximate — But Not Completely Mimic — Your Writing Style

Here’s the truth: While ChatGPT can mimic your writing style to some extent, the AI is not yet able to offer you an exact, 100% match of the way you choose your words — at least for now.

That said, unless you’re a professional writer — or someone who simply loves words with abandon — you may be perfectly satisfied with a quick, down-and-dirty prompt that mimics the broad strokes of your writing style in a ‘good enough’ way.

For example, if you’re not overly picky, you can use a down-and-dirty, write-like-me prompt using these words: “You are a world-class writer — with an irreverent sense of humor — known for clear, concise, colorful prose. Please rewrite the text following the colon using no less than 300 words and no more than 315 words:”

Such a prompt should be more than adequate for you –unless you’ve found yourself unable to sleep some nights because you’re tortured by a phrase you know should have been written just a bit differently.

Essentially: If you are among the easy-going-ilk, you can use the above prompt — or something similarly brief that better reflects your writing style– skip the rest of this post and saunter happily away, snickering at the rest of us.

However, if you’re like me and you often derive a deep, dark, twisted — and some might say concerningly disturbed — pleasure in agonizing over the wording, feel, cadence or some other highly esoteric feature associated with a single sentence, a single phrase — or even a single word — I’m afraid a down-and-dirty prompt won’t work for you.

Put another way: If you’ve suffered the fate of being a ‘born writer’ or a ‘born word-lover,’ you’ll need a much more sophisticated prompt to get you within shouting distance of what you consider to be your highly personal writing style.

For the record, the reason why ChatGPT is not yet able to offer you an exact, 100% match of your writing style is rooted in the method the AI uses to learn your writing style.

Specifically: ChatGPT learns to mimic your writing style by:

*Analyzing one or more samples of your writing

*Assembling of a list of generalized descriptors that it believes characterizes your work

*Referring to that list of generalized descriptors when you ask it to auto-write an email — or other text — in your writing style

The problem with ChatGPT’s approach: While resorting to assembling a list of general descriptors to characterize your writing style takes a decent stab at defining a highly personal writing style, its methodology unfortunately falls short — by its inherent design — of being able to fully mimic a highly personal writing style.

For example, ChatGPT may analyze a number of examples of your writing and conclude that one of its key features is that it’s ‘witty.’

But the problem with that descriptor is that witty is a generic term that applies to any number of variations of wit.

Robin Williams is witty.

But so is Mae West, George Carlin, Maria Bamford, Dave Chapelle, Ali Wong, Ricky Gervais, Amy Schumer and Eddie Izzard.

But as we all know, no one would ever mistake the wit of Robin Williams for the wit of Maria Bamford, confuse Dave Chappelle with Ali Wong, or listen to Amy Schumer and think, “Hmm, she sounds just like Eddie Izzard.”

Each of these world-famous comedians have etched their unique, comic perspectives on the world.

And that is the reason, in great part, why these masters of wit are so famous: They are witty like no one else on earth.

Unfortunately, this problem of using the generalized descriptor of ‘witty’ is compounded exponentially by the fact that ChatGPT also uses other, equally general and equally generic descriptors of your writing after reading a few samples of what you consider to be your best stuff.

For example: After analyzing your writing, ChatGPT may also conclude that your highly personal writing style is gripping, evocative, persuasive, authoritative — as well as any number of other adjectives that can be used to characterize what you’ve written.

And again, those descriptors do get ChatGPT closer to describing your singular, highly personal writing style.

But in the real world, as we know — and as we’ve seen with the characterization of ‘witty’ — there are countless shades of meaning that these descriptors are attempting to capture.

That said, with the right prompt that you personally fabricate, ChatGPT can still offer you a decent approximation of your writing style — which you can use as a strong draft of text that you subsequently polish.

Plus, given that ChatGPT has become increasingly more powerful and more refined with each new revision, there’s a chance that someday, ChatGPT may become so powerful and so perceptive, it may in fact be able to analyze your writing style with an unmatched, piercing, nano-focused insight — and then mimic your highly personalized writing style with breathtaking precision.

In the meantime, the good news is that getting ChatGPT to auto-write in a style that is a reasonable approximation of your writing style is fairly straightforward.

Here’s a quick summary of the steps:

Step One: Ask ChatGPT to analyze one or more samples of your writing style and generate a prompt to be used to mimic your writing style (which you’ll refine further).

Step Two: Take note of the descriptors ChatGPT uses in its report to you that serve as the basis of the prompt it created.

Step Three: Ask ChatGPT to run a second analysis of the descriptor categories it missed that you’d like included in its characterization of your writing style.

Step Four: Edit ChatGPT’s prompt to your liking.

Step Five: Test the prompt.

Step Six: Revise the prompt as needed.

Give it a shot — and then when ChatGPT comes out with its promised upgrade early this year, give it another shot.

You may get much better results the second time around.

Share a Link:  Please consider sharing a link to https://RobotWritersAI.com from your blog, social media post, publication or emails. More links leading to RobotWritersAI.com helps everyone interested in AI-generated writing.

–Joe Dysart is editor of RobotWritersAI.com and a tech journalist with 20+ years experience. His work has appeared in 150+ publications, including The New York Times and the Financial Times of London.

The post Close, But No Cigar appeared first on Robot Writers AI.

A research team from Seoul National University has proposed a gripper capable of moving multiple objects together to enhance the efficiency of pick-and-place processes, inspired by humans' multi-object grasping strategy. The gripper not only transfers multiple objects at once but also places individual objects at desired locations. The study, which analyzed human motion principles and successfully applied them to a robotic gripper, is published in the journal Science Robotics.

Roboticists at the Tallinn University of Technology (TalTech) have developed a new class of bio-inspired feet that significantly enhance robot mobility on challenging terrains like mud and wet snow. The findings, published in Bioinspiration & Biomimetics, could expand the capabilities of robots, allowing them to navigate in complex natural terrains to conduct sensitive environmental monitoring, aid in agriculture and participate in disaster response.

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Artificial intelligence has the potential to improve the analysis of medical image data. For example, algorithms based on deep learning can determine the location and size of tumors. This is the result of AutoPET, an international competition in medical image analysis. The seven best autoPET teams report on how algorithms can detect tumor lesions in positron emission tomography (PET) and computed tomography (CT).

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The post iPhone SE 4: A Bold Leap or a Confusing Rebrand? appeared first on 1redDrop.

By combining Samsung Electronics’ AI and software technology with Rainbow Robotics’ robotics technology, the collaboration plans to accelerate the development of intelligent advanced humanoids.

Robot systems explore unfamiliar terrain, buildings or danger zones with cameras. In the 3D-InAus project, researchers from the Fraunhofer Institute for Communication, Information Processing and Ergonomics FKIE are using a LiDAR laser on a mobile robot, emitting laser pulses to measure distances. The results are used to produce geometrically accurate 3D environments.

How AI is Revolutionizing the Food Industry with Automation?

The food business is renowned for its rich history, but because of its continuous challenges, such as labor shortages, supply chain disruptions, and food waste, this industry has shifted its focus to technology to simplify its business and enhance customer experience.

Artificial Intelligence (AI) is severely transforming this sector by embracing automatons. AI application development in the food business is a global trend now. From smart kitchens to optimizing food delivery, predictive analytics, and improvements of customer services, AI is increasingly being integrated into the way food businesses operate. This article guides on how automation is transforming the food industry through AI.

AI and Its Impact on the Food Industry

From speech and image recognition to making data-driven decisions, AI performs tasks that people consider unique to human intelligence. In the food industry, AI is no longer a concept but a tool that accelerates automation across the supply chain, production (cooking), and customer-facing services delivery. AI app development remains at the forefront of these processes in the future ahead and saves a lot for companies.

Let’s examine how AI app development is improving all facets of the food industry and automating processes.

1. Smart Kitchens and Food Preparation

In a modern kitchen, efficiency and consistency play a huge role. AI-based robotic chefs and automation tools have transcended human capabilities for unprecedented accuracy in cooking. They can chop, stir, grill, or even plate a dish. They depend on AI algorithms which allow them to replicate human culinary action.

Besides that, AI improves the overall workflow of a kitchen. Apps integrated with AI can predict inventory levels of ingredients and suggest new recipes based on stock available. Even smart cooking systems that work through AI can adjust to conditions such as temperature changes or spoiled ingredients, so dishes are always at the best they can be.

AI-based systems can also find inefficiencies in kitchen practices based on past cooking sessions data. Such systems make recommendations to improve operations and reduce wastage and staff utilization. Such automation does not only enhance efficiency but also efficiency and quality, both important aspects in sustaining the satisfaction of customers.

2. Food Delivery and Logistics Optimization 

Perhaps the most impactful change AI is making in the food sector is related to delivery and logistics. As more consumers begin to place orders online, this necessitates greater food business efficiency in their delivery operations. AI development of food apps plays a critical role in streamlining it.

With its power to know real-time traffic, weather conditions, and historical delivery performance, AI-powered apps can accurately predict delivery times. AI algorithms also determine the most efficient routes for delivery drivers to ensure that food arrives at its destination hot and on time. AI systems can also predict the demand for deliveries in specific areas so that food businesses can better allocate their resources (delivery drivers, for example).

Additionally, AI-powered smart logistics platforms assist restaurants and food companies to manage their supply chains in more efficient ways. By analyzing past data or based on forecast demand, AI applications help businesses maintain proper stock levels. This reduces waste and makes sure a business does not overstock or run out of popular ingredients.

3. Customer Service Automation

In the food industry, good customer service is key to business success. AI-powered chatbots and virtual assistants help businesses automate customer interactions that result in faster response times and more personalized experiences.

These chatbots powered by AI can take orders, answer frequently asked questions, or suggest menu items based on previous customer behavior and preferences. The use of machine learning algorithms has made AI chatbots more efficient at analyzing the user’s queries and providing quick response.

Furthermore, AI applications can gather data on customers and evaluate the same for a customized experience. For example, with AI, the order history of a customer can be traced, and it can provide a list of similar products or even offer discounts on items that have been most purchased. It helps in building loyalty among customers and also enhances their overall experience.

AI also changes the in-restaurant experience. Many fast-food chains as well as restaurants make use of in-kiosk ordering through AI systems that gather a customer’s order. Such kiosks can recognize customer’s preferences, propose combinations of food and even deal with payments that reduce waiting time and free time for wait staff to perform something else.

4. Inventory Management and Waste Reduction

There is always the challenge of either overstocking or understocking food businesses. Overstocking resulted in food spoilage and waste, while understocking led to missed sales and customer dissatisfaction. Fortunately, AI-powered inventory management systems are being used by food businesses to optimize stock levels, minimize waste, and increase profits.

Using factors include seasonality, weather, local events, and historical data, predictive analytics apps can forecast the demand for various food items. This helps businesses predict their needs for proper inventory at the right time without overordering at any given moment. AI tracks expiry dates; it will make automatic suggestions to reorder items close to going bad, thus minimizing waste and ensuring the kitchen is fully stocked with fresh ingredients.

Restaurants can also make use of AI to understand the preferences of customers and sales records. It informs and lets restaurants know exactly how much of each ingredient is required for any given dish, hence waste is minimized. For example, when a restaurant consumes fewer amounts of a particular dish, the AI system decreases the stock of that particular dish automatically, hence reducing food waste.

5. Personalized Recommendations and Menu Optimization

AI-powered recommendation engines transform the way food businesses approach menu design as well as interacting with their customers. AI apps are capable of gauging customer preferences and purchasing behavior and even sentiment from social media or online reviews to help businesses tailor their menus according to customers’ needs.

For example, AI applications create new menu items based on the preferences of the customers, trends, and even nutritional requirements. This enables restaurants and food companies to provide different types of dishes and bring in more customers.

Apart from optimizing the menu, AI can make recommendations to the customer. Customers using AI-powered food ordering apps will gain added personalization-based suggestions based on their past order history and dietary preferences. These personalized experiences create a far more engaging customer journey, resulting in higher satisfaction, and thereby more business.

6. Predictive Analytics for Demand Forecasting

Using historical data, customer behavior, and market dynamics, AI food apps can predict the demand of a particular dish or an ingredient at a certain time. For example, using AI applications, the pizza restaurant can predict demand on Friday evenings or during peak days. A business will ensure they have in stock all the ingredients to cater to their customers without overstocking, which not only improves a business’s operational efficiency but also ensures that food wastage and the inconvenience of a customer are reduced.

AI is also unavoidable when it comes to the seasonal fluctuations of demand in food businesses. Like, for instance, restaurants might have a huge peak during holidays like Thanksgiving or summer. Through AI-based apps, businesses can track such shifts and adjust their production schedules, as well as the number of employees, simultaneously aligning their inventory levels.

7. Enhancing Food Safety and Quality Control

Artificial Intelligence applications also track food preparation processes from raw material preparation up to packaging to determine potential faults that might influence quality or safety. It can be in the form of contamination or spoilage in food through the examination of visual and sensor data, which gives advance warnings against dangerous food products’ circulation, reducing the instance of food poisonings and maintaining good hygiene and safety standards in commerce.

Additionally, AI can help ensure that food products meet regulatory requirements. Apps driven by AI can monitor compliance with food safety standards, track the certification process, and produce reports so food businesses are on top of regulations.

Conclusion

Applications of Artificial Intelligence also monitor the preparation processes of foods from the preparatory stages of raw materials to the packaging. This helps identify the potential faults that may affect quality or safety. It may include contamination and food spoilage, which is through analyzing visual and sensor data, providing advance warnings on hazardous food products circulation; thereby lowering instances of food poisoning and upholding high standards of hygiene and safety in commerce.

Apart from controlling food safety, AI is also there to ensure that products offered pass the regulatory requirements. AI-driven apps monitor compliance with food safety standards, track the certification process, and produce reports so food businesses are on top of regulations.

 

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How AI is Revolutionizing the Food Industry with Automation?

The food business is renowned for its rich history, but because of its continuous challenges, such as labor shortages, supply chain disruptions, and food waste, this industry has shifted its focus to technology to simplify its business and enhance customer experience.

Artificial Intelligence (AI) is severely transforming this sector by embracing automatons. AI application development in the food business is a global trend now. From smart kitchens to optimizing food delivery, predictive analytics, and improvements of customer services, AI is increasingly being integrated into the way food businesses operate. This article guides on how automation is transforming the food industry through AI.

AI and Its Impact on the Food Industry

From speech and image recognition to making data-driven decisions, AI performs tasks that people consider unique to human intelligence. In the food industry, AI is no longer a concept but a tool that accelerates automation across the supply chain, production (cooking), and customer-facing services delivery. AI app development remains at the forefront of these processes in the future ahead and saves a lot for companies.

Let’s examine how AI app development is improving all facets of the food industry and automating processes.

1. Smart Kitchens and Food Preparation

In a modern kitchen, efficiency and consistency play a huge role. AI-based robotic chefs and automation tools have transcended human capabilities for unprecedented accuracy in cooking. They can chop, stir, grill, or even plate a dish. They depend on AI algorithms which allow them to replicate human culinary action.

Besides that, AI improves the overall workflow of a kitchen. Apps integrated with AI can predict inventory levels of ingredients and suggest new recipes based on stock available. Even smart cooking systems that work through AI can adjust to conditions such as temperature changes or spoiled ingredients, so dishes are always at the best they can be.

AI-based systems can also find inefficiencies in kitchen practices based on past cooking sessions data. Such systems make recommendations to improve operations and reduce wastage and staff utilization. Such automation does not only enhance efficiency but also efficiency and quality, both important aspects in sustaining the satisfaction of customers.

2. Food Delivery and Logistics Optimization 

Perhaps the most impactful change AI is making in the food sector is related to delivery and logistics. As more consumers begin to place orders online, this necessitates greater food business efficiency in their delivery operations. AI development of food apps plays a critical role in streamlining it.

With its power to know real-time traffic, weather conditions, and historical delivery performance, AI-powered apps can accurately predict delivery times. AI algorithms also determine the most efficient routes for delivery drivers to ensure that food arrives at its destination hot and on time. AI systems can also predict the demand for deliveries in specific areas so that food businesses can better allocate their resources (delivery drivers, for example).

Additionally, AI-powered smart logistics platforms assist restaurants and food companies to manage their supply chains in more efficient ways. By analyzing past data or based on forecast demand, AI applications help businesses maintain proper stock levels. This reduces waste and makes sure a business does not overstock or run out of popular ingredients.

3. Customer Service Automation

In the food industry, good customer service is key to business success. AI-powered chatbots and virtual assistants help businesses automate customer interactions that result in faster response times and more personalized experiences.

These chatbots powered by AI can take orders, answer frequently asked questions, or suggest menu items based on previous customer behavior and preferences. The use of machine learning algorithms has made AI chatbots more efficient at analyzing the user’s queries and providing quick response.

Furthermore, AI applications can gather data on customers and evaluate the same for a customized experience. For example, with AI, the order history of a customer can be traced, and it can provide a list of similar products or even offer discounts on items that have been most purchased. It helps in building loyalty among customers and also enhances their overall experience.

AI also changes the in-restaurant experience. Many fast-food chains as well as restaurants make use of in-kiosk ordering through AI systems that gather a customer’s order. Such kiosks can recognize customer’s preferences, propose combinations of food and even deal with payments that reduce waiting time and free time for wait staff to perform something else.

4. Inventory Management and Waste Reduction

There is always the challenge of either overstocking or understocking food businesses. Overstocking resulted in food spoilage and waste, while understocking led to missed sales and customer dissatisfaction. Fortunately, AI-powered inventory management systems are being used by food businesses to optimize stock levels, minimize waste, and increase profits.

Using factors include seasonality, weather, local events, and historical data, predictive analytics apps can forecast the demand for various food items. This helps businesses predict their needs for proper inventory at the right time without overordering at any given moment. AI tracks expiry dates; it will make automatic suggestions to reorder items close to going bad, thus minimizing waste and ensuring the kitchen is fully stocked with fresh ingredients.

Restaurants can also make use of AI to understand the preferences of customers and sales records. It informs and lets restaurants know exactly how much of each ingredient is required for any given dish, hence waste is minimized. For example, when a restaurant consumes fewer amounts of a particular dish, the AI system decreases the stock of that particular dish automatically, hence reducing food waste.

5. Personalized Recommendations and Menu Optimization

AI-powered recommendation engines transform the way food businesses approach menu design as well as interacting with their customers. AI apps are capable of gauging customer preferences and purchasing behavior and even sentiment from social media or online reviews to help businesses tailor their menus according to customers’ needs.

For example, AI applications create new menu items based on the preferences of the customers, trends, and even nutritional requirements. This enables restaurants and food companies to provide different types of dishes and bring in more customers.

Apart from optimizing the menu, AI can make recommendations to the customer. Customers using AI-powered food ordering apps will gain added personalization-based suggestions based on their past order history and dietary preferences. These personalized experiences create a far more engaging customer journey, resulting in higher satisfaction, and thereby more business.

6. Predictive Analytics for Demand Forecasting

Using historical data, customer behavior, and market dynamics, AI food apps can predict the demand of a particular dish or an ingredient at a certain time. For example, using AI applications, the pizza restaurant can predict demand on Friday evenings or during peak days. A business will ensure they have in stock all the ingredients to cater to their customers without overstocking, which not only improves a business’s operational efficiency but also ensures that food wastage and the inconvenience of a customer are reduced.

AI is also unavoidable when it comes to the seasonal fluctuations of demand in food businesses. Like, for instance, restaurants might have a huge peak during holidays like Thanksgiving or summer. Through AI-based apps, businesses can track such shifts and adjust their production schedules, as well as the number of employees, simultaneously aligning their inventory levels.

7. Enhancing Food Safety and Quality Control

Artificial Intelligence applications also track food preparation processes from raw material preparation up to packaging to determine potential faults that might influence quality or safety. It can be in the form of contamination or spoilage in food through the examination of visual and sensor data, which gives advance warnings against dangerous food products’ circulation, reducing the instance of food poisonings and maintaining good hygiene and safety standards in commerce.

Additionally, AI can help ensure that food products meet regulatory requirements. Apps driven by AI can monitor compliance with food safety standards, track the certification process, and produce reports so food businesses are on top of regulations.

Conclusion

Applications of Artificial Intelligence also monitor the preparation processes of foods from the preparatory stages of raw materials to the packaging. This helps identify the potential faults that may affect quality or safety. It may include contamination and food spoilage, which is through analyzing visual and sensor data, providing advance warnings on hazardous food products circulation; thereby lowering instances of food poisoning and upholding high standards of hygiene and safety in commerce.

Apart from controlling food safety, AI is also there to ensure that products offered pass the regulatory requirements. AI-driven apps monitor compliance with food safety standards, track the certification process, and produce reports so food businesses are on top of regulations.

 

[contact-form-7]

The bustling streets of New Orleans, renowned for their vibrant celebrations and cultural richness, witnessed an unthinkable tragedy on January 1, 2025. A devastating act of violence unfolded on Bourbon Street, leaving 10 dead and 35 injured. This act, labeled as a terrorist attack by local authorities, has not only shaken the city but also...

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