Research reveals a curious trend: Large language models (LLMs) are closer to the habits and likes of a specific group of people. We call this group the WEIRD population. WEIRD stands for Western, Educated, Industrialized, Rich, and Democratic.
So, how can we ensure AI serves not just a select few but every individual? The answer lies in Adaptive AI, which transforms AI from a general solution to a special helper. In this article, we will explore how this change is happening and how we might take advantage of it.
Increasing Demand for Personalized AI Solutions
Even though ChatGPT was a big hit at first, its number of users hasn’t grown much in the last year. Instead of using ChatGPT more, users are picking specific alternatives. They use these for creating images, writing, coding, and researching.
Such change shows that people want AI tools made for their preferences, moving beyond large language models (LLMs). Possible reasons for this include:
- Custom experiences boost happiness
- Efficient task completion with tailored tools
- Curiosity-driven engagement
- Personalized learning enhances understanding
Personalized AI solutions lead to improved user experiences and increased product growth. The founder and CEO of Quantcast talks about how personalized AI can change things. Personalized products succeed by adapting to user preferences.
However, users’ preferences vary, and each has unique behavioral patterns and experiences. This is because individuals are becoming more concerned with self-awareness and personal growth. To meet such diverse needs, LLMs alone are not enough, hence we need an AI that can better describe and adapt to diverse users, that is, Adaptive AI.
AI Adaptive Learning from Users
AI has the potential to understand us all more and more, thanks its leveraging of something called a neural network. Much like human brains, AI has neurons-like data formations.
These “neurons” are a series of algorithms that mimic the operations of a human brain to recognize patterns and solve common problems.
- Just like you learn from your experiences, AI learns through a process called “training.” During training, we feed lots of data to the AI. This data could be anything from pictures of cats and dogs to sentences in different languages.
- Over time, as AI gets more data, it starts noticing patterns. For example, if you keep liking pictures of puppies on social media, AI learns that you prefer puppies. So, it starts showing you more puppy pictures.
AI also uses something called a feedback loop. This means it learns from its mistakes. If it shows you something you don’t like, and you ignore it, AI takes that as a hint to change its strategy.
The more data and feedback AI gets, the better it becomes at predicting and understanding your preferences.
The Rise of Personal AI Assistants
The boom in the Personal AI assistant is a testament to the development of AI adaptive learning. They’re not just basic helpers anymore; they can give expert advice in areas like health or travel.
These smart assistants learn from talking to you, getting better at knowing what you like and need. This means they can help you more personally and effectively over time. It’s not like previous assistants that rely on pre-programmed responses.
One notable feature of these personal AI assistants is their ability to anticipate user needs. They can guess what you might need before you even ask. They look at how you do things and suggest proactive help.
Moreover, they offer a personalized experience by creating a unique user profile for each individual. This way, they can change their suggestions based on what you’re into at the moment, making sure the help they offer is always on point.
Plus, they’re great at juggling different tasks or services you use, making everything work together smoothly. This makes life easier and saves you time, something regular AI assistants can’t do.
In short, these advanced AI assistants represent significant advancement. They learn, adapt, and offer help that’s right for you, making them super useful for managing our daily lives.
From AGI Dreams to ADI Realities
As adaptive AI gets smarter, it learns from every move we make and becomes more helpful with each passing day. We are rapidly moving towards a future that resembles a sci-fi movie.
This then raises a big question: are we close to creating artificial general intelligence (AGI)?
People believe that AGI represents the pinnacle of artificial intelligence. That is, machines have the potential to evolve into autonomous species on par with humans. They can learn and apply learned abilities to various tasks as humans, but faster and without getting tired.
The Big Question: What Is General Intelligence?
Talking about AGI opens up the difficult question of general intelligence. Despite all the discussions about AGI, there’s no clear definition of what it is. It’s as if everyone is talking about the same movie but describing different stories.
No matter which perspective you take, the core concept of AGI represents the universal intelligence of mankind. So this brings us back to our original question: how can we assure that AGI helps everyone, not just a chosen few? To address this problem, we need to understand the diversity of intelligence, as well as the generality of intelligence.
From Universal Minds to Personal Geniuses: The Rise of ADI
In the pursuit of diversity, MindOS are building Artificial Diversified Intelligence (ADI). ADI does not try to be a one-size-fits-all kind of intelligence. Instead, it focuses on creating AI that is unique to you.
If a fitness app employs ADI, it would know more than how much you exercise each day, but also when you are too stressed to exercise. And then, it might suggest you try meditating instead. Or better still, it might identify and suggest solutions to fatigue-related issues.
ADI is about embracing the uniqueness of each individual. It’s not trying to create a machine that can win a Nobel Prize (though that would be cool). It’s about making AI that makes your day a little easier, a little brighter, and a lot more personalized.
Resolving Modern User Experience (UX) Challenges
As we begin to focus on diversity, ADI systems can help improve the user experience like never before.
User experience (UX) is the heart of modern services, deciding if digital platforms will succeed or fail. It is more than only how things work but includes the feelings, thoughts, and interactions users have. Great user experience brings satisfaction, efficiency, joy and business growth.
The rise of the internet has reshaped the landscape of online services, making every interaction a little bit less personal. In the past, services were like bespoke tailoring, crafted to fit each individual’s unique preferences and needs. With the digital revolution, these personalized experiences are now handled by software algorithms.
This change has stripped away the human touch. It has also removed the individualized care that characterized traditional service provision. In this bookstore, the owner knows your favorite genres. Now, compare it to a generic online bookstore. This online store recommends books based on algorithms. It misses the personal touch. It also lacks the warmth of human interaction.
Combining AI and UX aims to revive the broken user experiences of the digital age and close the gap between software and human beings. They move from simple interactions to personalized service delivery.
Yet, achieving this transformation is challenging. AI must understand each user’s preferences, behaviors, and interactions. Existing AI such as LLMs cannot do this, necessitating a more novel and personalized solution.
Enhancing UX with ADI and LPM
ADI is changing the game by getting to know what each person likes, making AI more suitable for everyone. MindOS has pioneered the adoption of the Large Personalization Model (LPM) to address this critical aspect.
This AI model learns from your actions and likes, making a unique profile for you. LPM analyzes and learns from real-time feedback to understand what users like. This ensures personalized and engaging experiences for users.
Elevating AI and User Experience with LPM
LPM uses LLMs and LLM-Native’s deep interest network to analyze user interactions on MindOS. This leads to the creation of unique and changing user profiles, which allow for much better recommendations and services.
LPM also uses the latest in AI technology. Some of the latest advances in its arsenal include:
- Real-time model updates
- Parameter-Efficient Fine-Tuning (PEFT)
- Symbolic Distillation.
These technologies refine users’ interest models while keeping responses accurate.
It improves user experiences by meeting their needs, such as making personal email suggestions and info updates
Personalized Recommendations: LPM makes suggestions based on individual preferences captured while using the service.
Dynamic User Profiles: LPM learns and adapts, building profiles that change as users interact more.
Real-Time Analysis: LPM utilizes real-time analysis to provide context-sensitive responses and recommendations.
For instance, if a user often asks an AI for food suggestions, an LPM will consider this and offer tailored recipes based on its analysis.
By integrating LPM into the UX, MindOS ensures a personalized, adaptive, and enriching interaction. This sets a new level in how AI helps with user engagement.
Using ADI and LPM for a Wonderful Vacation
Imagine planning a vacation that feels like it was curated for you, down to every detail. With the integration of ADI and LPM by MindOS, this isn’t a dream. Here’s how ADI and LPM can make your holiday unforgettable:
- Personalized Destination Recommendations: As soon as you think of taking a vacation, ADI analyzes your past travel experiences, preferences. It even analyzes your recent searches to suggest destinations that you’re bound to love.
- Customized Itinerary Planning: Once you’ve picked a destination, ADI crafts an itinerary for you. Whether you love adventure or relaxation, LPM ensures your schedule full of enjoyable experiences.
- Accommodation Selection: ADI helps you find the perfect place to stay. By understanding your preferences for amenities, location, and budget, it offers the best options for you.
- Dining and Food Recommendations: Food is a big part of any vacation. LPM takes note of your dietary preferences to recommend restaurants and specific dishes.
- Real-Time Adjustments: Weather changes or unexpected events? No problem. ADI, with LPM’s real-time analysis, can adjust your plans on the fly, ensuring your vacation remains seamless and enjoyable.
- Personalized Communication: During your vacation, ADI keeps you informed with personalized messages. Never miss out on any important information.
- Post-Trip Learning: After your vacation, LPM learns from your feedback to make your next trip even more personalized and enjoyable.
By leveraging the power of ADI and LPM, your vacation becomes more than a break. From the planning phase to your return, ADI and LPM work together to ensure your holiday is perfect for you. This is the future of travel, where ADI understands you and makes every trip an unforgettable experience.
The Evolution of ADI Enhances Human-AI Collaboration
In the future, ADI will be a big part of our lives, making things faster and more efficient, and giving us experiences that fit right for us. This is due to the advancements in machine learning, natural language processing, and deep learning. These techs enable ADI to operate autonomously, understanding how users act and offering relevant help.
Imagine that a patient goes to their doctor for a regular check-up and the healthcare place uses an ADI system. This system looks at the patient’s medical history, their current symptoms, and their genetic risks. Next, it spots potential health risks as the patient’s needs change, and then suggests treatment options with human doctors.
This blend of doctor know-how and AI insights leads to care that is timely and personalized. The healthcare team, combining human intuition and AI analysis, makes well-informed choices. They find patterns in the patient’s health data and suggest early steps to make their health better.
The evolution of ADI marks a significant change. It focuses on smart, adaptable systems that meet individual needs. This redefines how humans and machines interact, enhancing lives.
Protecting User Privacy in the Era of Adaptive AI
In the realm of Adaptive AI, the use of personal data plays a pivotal role in enhancing user experiences. Two primary categories of data hold significant importance:
- Structured Memories (Databases): Database holds all the basic knowledge that AI systems need. This lets AI systems find and use organized information efficiently.
- Real-time Interaction Data (Preference): These come from talks between users and AI. AI learns what users like from how they talk, how they act, and what they say they like. This fresh flow of information helps AI give answers that fit each user better.
Safeguarding the privacy of personal data is a critical concern in the context of ADI. Real-world examples of data breaches highlight how important it is to have strong privacy measures. We need these measures to reduce risks and keep our information safe.
MindOS, for example, commits to upholding strong privacy protection standards to safeguard user data. Efforts include:
- Data Encryption and Anonymization. MindOS protects user data with advanced encryption and anonymization technologies, ensuring information security.
- Compliance with International Data Protection Regulations. MindOS strictly adhere to international data protection regulations like GDPR. This helps us maintain data privacy standards you can trust.
- Information Encryption Processing. Before the LPM processes any collected information, MindOS encrypts all data.
- Empowering Users with Control. MindOS allows users to define which data is inaccessible to AI, giving them control over their information.
MindOS Leading the Way in Building Adaptive AI
ADI opens a door for everyone and everywhere, creating a world that values our diversity. This advancement sets the stage for a more understanding and inclusive tech environment, making sure no one is left behind. MindOS is working towards a future in which everyone may enjoy personalized support.
Ready to be a part of this revolutionary change? Build your own adaptive AI today with MindOS Mebot and MindOS Studio, equiping it with diverse skills and memories.
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