“Whoever wins the personal agent, that’s [going to be] the big thing. Because you will never go to a search site again, you’ll never go to Amazon again” - Bill Gates
By dr. Paul Jurcys
In the very near future, each of us will our personal AI assistants for every aspect of our lives. Each of us will have our personal AI doctor, personal AI coach, personal AI nutritionist, or digital assistant that will help us organize our calendars, schedule events, and purchase items on our behalf.
Such AI-powered assistants will augment our abilities and help get rid of time-consuming tasks, and focus on things that matter most.
Buzz In the Market
In the past few months, there has been quite a bit of excitement about the possibility of building truly personal AI:
A massive investment in InflectionAI could be seen as an attempt to stave off any potential competition and secure dominance in this rapidly emerging domain.
Shortage of Experts
Today, we are unfortunately facing a remarkable shortage of experts. With over 8 billion people on Earth, there are a mere 10 million doctors. Teachers struggle to spend enough time on direct interactions with every student in the class.
On a personal level, we often lack someone equally knowledgeable or passionate about our favorite topics. In times of grief, suffering, and emotional pain, the desire for a close companion to provide advice and understanding becomes ever more acute.
This is where the transformative power of AI comes in. In the near future, countless individuals, potentially everyone, will be able to augment their personal capabilities with our own personal AI assistants.
The trajectory toward universal access to intelligence is clearly mapped out: we can expect that any person with access to the internet and a hand-held device will have access to the same expert advice from a doctor, an educator, or any other specialist, all through their personal AI.
2 Ways to Build Personal AI
As technology continues to leap forward at ever-increasing speed, personal AI assistants are evolving to become more sophisticated and versatile.
There are two paths of bringing AI superpowers to humans:
A top-down approach: after the release of ChatGPT and other generative AI tools, we are witnessing an influx of various personal AI assistants that are supposed to hello us find information, summarize text, or generate images.
The top-down approach is rooted in creating software applications - personal AI assistants - that are marketed as tools to help us solve various daily tasks and assignments or offer us a companion, a buddy that is available 24/7. Think of InflectionAI’s Pi, Midjourney, Dalle, and countless others.
However, most of our essential tasks are rooted in the physical world: we need to eat, sleep, and and go to the bathroom. As cheap sensors are being integrated in our wearable devices and environments around us, individuals have tools and ability to track personal biological clock - we start living quantified lives. If you are a runner, you probably have a fitness tracker to measure your running distance and heart rate, as well as recovery rate. Also, our cars track hundreds of data points (e.g., acceleration, braking, engine performance, and outside factors).
Scientists around the world are building assistive robots to help us to recover from injuries or learn important skills.
These sensor-derived data sets also lead to the development of AI-powered applications that help optimize different aspects of our lives. This sensor-data-AI path resembles a bottom-up approach to building personal AI.
Data Eats the World, But How to Access Data?
AI assistants such as ChatGPT, or PI, are amazing in answering our general questions and performing general tasks. However, if you ask anything personal, something related to yourself, they stumble. Let’s see what responses we get to the question “How did I sleep last night?”:
How come!? Isn’t it odd that if you wear Apple watches that track our activity, sleep and process various biometric data, Siri - an AI assistant built by Apple for Apple’s products - is not able to answer such a simple question?!
Eventually, every company building personal AI will face the challenge of connecting the personal AI to the user’s own data.
To build a truly personal AI, we need not only general knowledge from publicly available sources and research repositories, we also need to bring this general, publicly available knowledge and correlate it with the specific data of each individual. In other words, to build a truly personal AI, Ai assistant must be able to access to the user’s personal data. Otherwise, the AI assistant will be a generalist, not a personal:
This is where Prifina’s human-centric approach to data comes into play: with Prifina’s user-held data model, it is possible to bring those personal AI assistants to each individual and run those personal AI assistants “on top of” each user’s own data, privately.
In Prifina’s personal data ecosystem, each individual user connects their data from personal data sources to their own data “vault”, where data is collected and unified. AI-powered apps and assistants run in each individual users’ data environment. Each individual user’s data is private by default.
A human-centric approach to data opens vast opportunities for the use of personal data: not only personal AI assistants can answer the question about last night’s sleep, but ML and LLMs can offer new possibilities for personalization and automation of tasks and generate new value for individuals.
So how many personal AI assistants can there be? And how many AI assistants can one person handle?
As humans, we have limited time and a limited attention span. Our guess is that each of us will be really interacting with 5, 7 or 10 digital agents (similar to a manager at a corporation who has 7-10 directly responding employees).
The image below illustrates the universe of digital assistants in the human-centric environment:
These digital agents will also vary in their expertise, capabilities, and proximity to the individual human being. It is likely, that people will have their own AI doctors, AI coaches, and AI-powered shopping assistants who will help to achieve specialized tasks.
Some of them will operate in the “inner orbit” - on top of the user’s own data, privately, while other AI assistants will be generalists, and will not have access to user’s own data.
In this multi-agent environment, one possible scenario is that each individual will have one primary and preferred assistant - we can call it “my personal AI.” But how will those digital agents and assistants interact with one another? What technological infrastructure is needed to make them talk to one another?
Assume you feel unwell and suffer from an upset stomach, which personal AI assistant do you go first? You might go to your “own private AI” and ask “Why do I feel pain in my stomach”? Your own personal AI may refer you to your personal AI doctor.
In this kind of scenario, it will be important to make sure that the initial inquiry made by you to your own personal AI is automatically transmitted to other agents. This will ensure that your AI doctor will already know your concern and will be able to continue the conversation.
Such communication between AI-powered agents can only be possible in the human-centric data environment, where all the AI experts run on the user’s side. Sharing sensitive data outside of the user’s own personal data environment is not optimal. In fact, such communication between agents would be impossible in the old, enterprise-centric data ecosystem where data is locked in separate silos.
As we stand on the entrance gates to the age of AI, the future seems quite exciting: how will our lives change when each of us will be able to tap into the potential of our Personal AI? The integration of Personal AI agents into our daily lives is not a question of if, but when and how.
To bring this vision into reality, a shift in thinking is required. We need to embrace a human-centric data paradigm where our Private AI is operating on our side, on our own data, privately.
At Prifina we are building an infrastructure to empower each individual with such “steamengines of the mind”; we want to empower developers to build Personal AI applications for people to augment each individual’s creative potential. Join us!
Unlocking the Lifelong Value of Data: Personalization of Consumer Experiences in the Insurance Market
Prifina’s CEO Markus Lampinen spoke to Alex Bond on the podcast about the current trends with personal data and how individualized data-driven innovation could be introduced to the insurance services market.
Markus: My name is Markus Lampinen, I'm based in San Francisco where I run a company Prifina. We help make products smart. We do this by embedding sensors into different types of physical products. For example, I'm wearing - not that you can see it on the podcast - a really nice kimono-based silk jacket produced by a Tokyo-based company Ichijiku. This jacket has an embedded sensor that can measure a number of different things around, e.g., how the jacket is doing, surrounding data like humidity, etc. Our role at Prifina is to overlay different types of datasets like the sensor data and correlating them with other types of data, e.g., your heart rate when you wear the jacket.
Prifina allows companies to build different types of applications that enable them reimagine the end-user experience for how we interact with not only physical products but data. Our vision is that in the future, have more data than ever - how can we use it to create new experiences? Something that's different from what we've had?
Alex: That's great. I think that when people hear about sensor-driven technology in clothing, they think about performance, sportswear. But it's much more than that, isn't it?
Markus: That's right. We work with pro athletes that want to improve their performance, e.g., top basketball clubs. For them, it's about understanding performance, recovery, sleep, stress, hormonal activities, and so on. From a player’s point of view, how can players themselves understand what's going on with their body and their environment to essentially get better? But it's not just about performance sports, it's also about stress - how do you manage stress?
There is a lot of data that we already have, e.g., our sleep data.
We can go all the way to, for example, luxury fashion and thinking about how does the clothing that you wear impact your your mood or happiness? As for all this data, we're kind of sitting on this goldmine: we, individuals, have so much data but we're just not using it. It's a huge opportunity.
With user-generated data, it is possible to build new types of experiences.
Alex: We're now talking at the MENA Insurance Summit. How does this relate to, for example, insurers?
Markus: We work with a lot of insurance companies around the world are looking look at preventative health, mental health and wellness. If you can make your policyholders healthier and happier, then they're going to be better customers for the insurance company, because they have very similar incentives as the insurance company does.
Alex: Okay, applications are really wide for the insurance industry. … Markus, you explained that it's not just about kind of tracking the data, but it is about the lifetime value of a product that is enhanced by your own data.
Markus Lampinen: Indeed, the lifetime value is one important aspect of a product. How are you maintaining your car? Are you driving it too fast, and so on and so forth.
But then, we get into this very delicate balance as well: the data should benefit you as an individual, not the insurance company alone. At the end of the day, for example, when it comes to different types of collectibles, tracing the entire value chain (where everything came from, who actually owns it, etc.) becomes important, especially for maintaining the value and also secondary transactions.
This fits into a broader conversation about what is authentic, especially in the digital environments powered by applied AI and deep fakes. We have Barack Obama thats now trying to sell you some skin care product. How do you know that something is authentic?
But our focus is very much on reimagining the whole of the consumer experience using data. There are incredible applications as we move forward. For example, cars generate a lot of data. So do you as an individual. What if you could just enter into the car which already knows that, am I a five star driver today? Or that I am only a three star driver today? If you slept really poorly of if you had a little bit more than one drink…? We're not talking about sharing it anywhere, but using your own data for your own benefit.
That’s where there's this interplay between all the data that we have and all the things around us. How can we tie them into a unique importable experience going forward? It's a very, very big theme, of course, but that's kind of something that we look at as an inevitable trend.
Alex Bond: I think people are just starting to wake up to be protective of that. I’d like to finish with one more question: what does it mean for insurance? I'm an insurance guy. What about applications for the insurance sector?
Markus Lampinen: Sure. Insurance emerged as a very clear secondary market for personal data use-cases. Let's take an example. After today’s summit here in Doha, I'm traveling to Switzerland where we're working with our partner that has a sensor embedded into both the left and the right ski boot as well as the helmet.
So you can actually get your triangulate the skier and their position to maybe help them improve. Now, performance athletes may care about the angle of tilt on their 760 turn on the mountain. But most skiers don't.
But if you start essentially hitting this type of data on skiers, could you create individualized insurance per skier per day in dynamic conditions? Could you give them incentives to ski safer based on those? These are some things that are currently really hard to price dynamically. But if you started having this type of data, could he actually create almost like reverse marketplaces for these types of products? Could you do this on, let's say, a resort by resort basis? You can also use it as, let's say recommendations for routes on different types of ski resorts. You can also use it for insurance products as well.
So that's been very much our foray into thinking about starting off in a very, very clear value prop for the individual, but then realizing that there's this entire ecosystem.
Alex Bond: Markus, you've been very generous with your time. Thanks for being a guest.
You find the entire conversation on , here it is.
In the heart of Bern, Switzerland, an innovation and future conference - The 2291 Festival - recently provided a platform for Prifina to showcase its remarkable progress in collaboration with its Swiss partner companies. This event brought together visionaries, industry leaders, and venture capital firms, highlighting the transformative potential in the areas of sensors, personal data and AI.
Prifina, along with Heierling, known for their high-end ski boots and equipment, took center stage at the event. We unveiled next-generation of ski boots and helmets that collect skiing data and seamlessly integrate it into their personal data cloud provided by Prifina. Users can then access applications that leverage this data, such as an AI ski coach, providing personalized insights and recommendations.
Markus Lampinen and Jouko Ahvenainen took the stage to deliver thought-provoking talks during the event. Their focus centered on the fundamental question of personal data ownership and control, emphasizing that it is not only about owning the data but also enabling ordinary individuals to access applications built on their personal data.
“Empowerment with personal data is crucial for individuals to lead healthier and more fulfilling lives.” - Jouko Ahvenainen
Prifina's current primary focus revolves around leveraging data and applications to enhance people's well-being based on health and wearable data. By harnessing the power of personal data, Prifina aims to provide individuals with the tools they need to lead healthier lifestyles and make informed decisions about their well-being.
Throughout the event, there were compelling discussions on the role of innovation in improving the lives of people. It was acknowledged that while technological advancements have the potential to revolutionize various aspects of our lives, there are also concerns about how companies and governments may misuse personal data for control. In this context, the consensus was that giving individuals better control over their personal data can empower them to lead better, healthier lives.
Switzerland, known for its commitment to individual freedom and empowerment, has always held personal data control in high regard. The Swiss people recognize the importance of safeguarding personal data and ensuring that individuals retain the rights to make decisions regarding their own information. It is this shared belief that has facilitated a fruitful collaboration between Prifina, Heierling and Code Fabric, as they work together to redefine personal data ownership and control.
Prifina’s collaborations with Swiss companies shows the immense potential with user-generated personal data. By combining our expertise in technology, skiing equipment, and personal data management, we are pushing the boundaries of what is possible. This represents a unique opportunity for other consumer brands seeking innovative approaches to their product offering that have a positive impact on people's lives.
Our general takeaway is that the future with user-generated personal data looks promising. Our vision of empowering individuals through personal data control resonates strongly with the Swiss people and the global community at large.
Stay tuned for more updates as Prifina strives to revolutionize the way we experience sports and personal data, ultimately enhancing our lives in ways we never thought possible.
On May 3rd, 2023, the Prifina team with its co-organizers at New York Life, hosted a panel on how AI-driven innovation and advances will impact consumer experiences. The event was sold out and we thank all attendees who braved the spontaneous rain in San Francisco to join in person.
We’re grateful for such lively audience participation and brilliant questions for our panel, which included Mickey McManus, BCG, Malavica Sridhar, Founder, Northstarre, Markus Lampinen, Co-Founder and CEO, Prifina and moderator Amber Wang, Women in AI / Cerebral Valley.
The panelists together raised various observations and addressed the trends in the current market:
With such a boom in generative AI, personal data and private use of personal data become fundamentally important. Not only because of privacy concerns but also because of representation; if apps and services are built utilizing individual models that represent the users, we can truly deliver private AI that helps us achieve what we want in life. Like an audience member asked: which human activities should we trust to AI and which should we want to perform ourselves?
Questions like these are at the very heart of the debate, but should it not be our choice as individuals based on our preferences? After all, studies show that outsourcing tasks and chores you do not wish to do increases your overall satisfaction in your life.
Thank you all for the wonderful debate and we cannot wait to see you soon to showcase more of what Personal AI can deliver, privately, to each of us.