Transforming learning with AI tutors - Gustav Grimberg (Ezri)
How will AI tutors become learning companions? We explore the potential and implications of this AI-powered education in K-12 with the fresh startup Ezri based out of France.
The Guest
AI tutors will play a very important role in the future of education. What exactly they will look like and how they will work and how they will fit into the learning process are still questions that need to be addressed fully. But, at Ezri, we believe and we work towards a future where AI tutors will be a learning companion that all students will have.
Gustav Grimberg is the co-founder of Ezri, a company dedicated to developing AI tutors that transform online learning. With a background in human-computer interaction, Gustav has long been passionate about creating technologies that are natural and intuitive for human beings to interact with, especially in education. In October 2023, he co-founded Ezri to bring this vision of affordable, personalized education to life.
Recently, Ezri launched its first AI tutors in Germany through a white-label model in collaboration with the K-12 publishers Cornelsen and Duden Learnattack. Their machine learning systems converted tens of thousands of videos, exercises, and articles into interactive AI tutors, offering personalized student support tailored to the content.
The company is now focused on releasing its next generation of AI tutors, which work in multiple modalities to deliver even more effective personal tutoring.
Company profile
Segment: K-12 (to start with)
Business model: B2B
Geo: Global
Year started: 2023
Funding: Bootstrapped
Location: Paris, France
The view of the Garage
With rapid advancements in artificial intelligence and machine learning, the potential for AI tutors to become integral to the learning process is immense. Will AI tutors become indispensable learning companions for all students? We are still in the stone age of AI development, so what we see now will be very different from what we have in just a couple of years. For now, there are a few challenges left to tackle (outside of obvious the Large Language Models issues with hallucination and bias):
1. Accessibility: AI tutors have the potential to bridge the gap when there is no teacher or tutor available to support students. However, the current interface and user experience set a huge barrier to general accessibility and usage (as discussed in the episode with Nick from 360Learning). The arrival of multimodality and particularly the ability to dialogue through natural voice, will open up the market as long as quality and relevance is high.
2. Personalized learning: One of the greatest strengths of AI tutors is their ability to offer personalized learning experiences. These tutors can adapt to individual student needs, learning speeds, and styles, thereby making education more effective and engaging. The current integrations of AI tutors depend on having the context, history and overall understanding of the user for personalization which depends on getting as much relevant user data as possible. For publishers, schools and education they might want to share only limited amount of user data with external providers for both competition reasons and for…
3. Data privacy and security: Robust data privacy and security measures must be in place to protect student information and build trust. Especially in K-12 this data is sensitive and any breach will have serious consequences both for learners, schools and external providers. How can startups provide such guarantees and build trust to ultimately provide better personalization?
Do you have other views? Don’t hesitate to throw in a comment on what you think is the way ahead for AI tutors.
Listen to the story
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Extracts
Human tutors vs AI tutors
So how do you compare an AI tutor to a human tutor? There are similarities and there are differences, of course. And I think that going forward there will be ways that these two modes of learning will complement each other.
So in similarities between AI tutors and human tutors, there's the active learning part, there's understanding the gaps in knowledge, there's promoting critical thinking, promoting thinking about your thought processes. Human tutors are human and there's definitely something to explore about how exactly and if it can be replicated in AI tutors.
On the other hand, AI tutors, they are very scalable. They are very affordable. They can be made available at a fraction of the price of a human tutor and they're available 24/7.
So no matter how you prefer to learn, no matter how long time it takes, you don't have to worry about a human sitting there being impatient. You don't have to worry about saying something stupid because they won't judge you, the agents.
Developing personal relationships
An important feature of human tutoring is a mutual understanding and feeling some kind of harmony or some kind of connection with the tutor. And this is something that is also important to explore in AI tutoring systems. If you should make this or try to develop this interpersonal connection with the tutee, with the student.
From what we see, it is definitely a path to go down to try and develop these more close relationships where the tutor has a better understanding of the student, has an ability to not just tutor, but also, go off topic sometimes to develop a more close connection to the student because that in the end can foster and promote better learning.
The interface and user experience
Anything that keeps you up at night? It is thinking about the interface, how learners going forward should interact with AI systems and language models. So what happens from the user either uploads their homework or ask the first question to they at some point end up at having understood the content that they didn't understand before. How to deliver the content or how to deliver the messages, voice, real time, asynchronous. How long the interaction should be, how to plan a good tutoring session automatically is something that keeps me up at night.
And something that I've spent a lot of time thinking about is how to make good dialogue management systems for tutoring, which is very much where we see that large language models right now they lack some quality. They're good at delivering text, but they're not so good at developing, delivering tutoring sessions and bridging this gap to make large language models good at tutoring is a technical challenge, for sure, that we spend a lot of time thinking about right now.
Dynamic vs static tutors
I guess it was interesting to discuss and think about what an AI tutor is exactly. So whether an AI tutor, is only this kind of tutor that we're developing at Ezri, where it's like completely dynamic and interactive or whether it can also be a bit more static, you know, adapting your learning experience, suggesting content, even suggesting questions that can have predefined answers and so on.
If we also allow that category as a tutor, there's a lot of work being done. Both in Europe and in America. For the kind of smaller subset of AI tutors that we are working on that are these very dynamic and personalized tutoring interactions, there haven't been that many AI tutors released now that are used on a big scale in Europe.
And we are seeing interest in this. We're seeing that there are established players that are interested in going into this, both publishers, schools and private tutoring companies. And we definitely expect that this will be the path forward at Ezri.
Voice system and dialogue management
I would love to have a really good voice system that works very well, especially with K-12 students. That delivers a very human like voice interaction. And then just find this dialogue manager that can really just steer the interaction as the best tutor in the whole world. So if I could order one thing and plug into our tutors, it would definitely be the best tutor dialogue management system, which we are working towards at Ezri.
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Frank Albert & the EdTech Garage crew