Welcome to our exclusive interview with Kisson Lin, COO of Mindverse , a cutting-edge AI company that is transforming industries with AI powered by guided large language models. In this insightful conversation, we’ll delve into the company’s vision for the future of AI, how Mindverse tailors AI to a company’s individual needs, and MindOS’ innovative features that enable rapid AI adoption.
Kisson also raises concerns about applying LLM-based AI in sensitive fields and stresses the importance of ethics in AI development. We explore how feedback from closed beta testing will influence open beta testing and the final release, and discuss the role of MindOS in improving employee satisfaction and productivity. Finally, we’ll touch on the partnership and collaboration opportunities Mindverse envisions across industries, as well as the company’s expectations for adoption of MindOS when it launches later this year.
Join us as we explore the exciting world of artificial intelligence and its potential to revolutionize industries, making our lives more efficient and productive than ever before.
As COO of Mindverse, can you share your vision for the future of artificial intelligence and its potential impact on various industries?
At their core, AIs are just like any technology: they are useful as tools to improve our lives. At Mindverse, we see generative artificial intelligence as a tool to improve team happiness and productivity by freeing people from the mundane and allowing them to focus on the tasks that drive their creativity. AI beings running on controlled large language models have the potential to transform various industries by improving efficiency, accuracy and decision-making while providing users with a personalized experience.
We will see artificial intelligence play as important a role in our daily lives as our smartphones do. We are already seeing exponential progress in generative AI and predict that AI will become a valuable asset to any company’s strategy. Today, almost every industry is talking about how generative AI will shape the future. This will affect industries of all types and sizes, from healthcare to education, from more efficient disease diagnosis to creating personalized learning experiences for students.
How does Mindverse adapt artificial intelligence to the needs of the company?
One of the most interesting features of MindOS is its customizability. MindOS allows users to provide specific information about relevant products or companies through a link to a website, an uploaded document, or by writing directly on the platform. Legacy chatbots were expensive and time-consuming to deploy, and MindOS is a huge step forward in deployment and customization.
Specific information allows for easy business integration and will lead to the creation of customized AI. Additionally, users can provide character bios or life experiences for the AI to use during conversation. The MindOS library also supports more than 30 languages and dozens of product integrations, while offering more than 1,000 pre-developed AIs. MindOS has something for every business!
Can you elaborate on the real-time search and ground-up training features in MindOS and how they help AI adapt quickly?
Real-time search allows artificial intelligence to quickly search large volumes of data and retrieve relevant information in real-time. This can be extremely useful for AI creatures that are still learning and need quick access to information. For example, a chatbot that learns to answer customer queries can use real-time search to quickly find the best answer to a customer’s question.
On the other hand, zero-impact training allows AI beings to learn new tasks and concepts without explicit training. This means that AI can be quickly adapted to new tasks and start working immediately without needing large amounts of training data. For example, an AI that has been trained to respond to customer inquiries in one language can use implicit learning to quickly learn to respond to inquiries in another language without requiring special training in that language.
Together, these features can help accelerate the adoption of AI and reduce the time and resources needed to get it up and running. This can be incredibly valuable for companies looking to implement AI solutions quickly and efficiently. Using the power of real-time search and learning from the ground up, companies can rapidly onboard new AI creatures.
How do you solve LLM-based AI challenges in sensitive fields?
There is a lot of debate about ethics in AI, and I think it’s important that AI developers listen to discussions of algorithmic bias and privacy. Beyond the more general discussions of ethics in AI, I would say that the most common concern with LLM-based AI is information accuracy. We’ve all seen LLM-based AIs “hallucinate” and make things up when the AI doesn’t know the answer to a question. Naturally, this causes companies to worry that a chatbot might give the wrong answer to an important question.
The general purpose GPT tools you see online have a hard time providing correct information because you have no control over what information they learn from. Tools like MindOS are specifically designed to avoid inaccurate results as we allow companies to control the LLM and teach the AI all the facts about the company and its policies. Let’s say an enterprise user imports hundreds of pages of company training documents and product information, and one of those pages is about the refund policy, the AI will always respond with the correct refund policy.
How will closed beta feedback affect the open beta and final release?
At Mindverse, we take feedback very seriously, and the feedback we receive during closed beta will play a significant role in shaping open beta and the final release of our products.
During closed beta testing, we will collect feedback from an invited group of users who are given access to our products. This feedback will be used to identify areas where our products can be improved and what features we can implement to make the tool more useful in certain industries.
Based on this feedback, we will make changes and improve our products before the open beta release.
Can you discuss MindOS’ role in improving employee satisfaction and productivity?
MindOS provides the flexibility to create personalized AI-powered assistants that can be customized, allowing businesses to process customer inquiries or simple transactions in seconds. This allows employees who previously had to spend a lot of time responding to customer inquiries to allocate their efforts to big-picture tasks. This will result in faster workflow and overall better business efficiency, eliminating the need for employees to spend time on mundane, repetitive tasks.
What partnership and collaboration opportunities does Mindverse envision with businesses across industries during and after closed beta testing?
We work in the space of AI as a Service, or as we call it, Mind as a Service. Naturally, this makes it possible to work with distribution partners and white labels who know the mechanics of certain industries. There are also SaaS tools that are vital for certain industries: e-commerce store managers, DIY website builders, event management packages, CRM, marketing tools, task organizers, and process automation.
Most of these tools use third-party partners to provide their chatbot functionality, so we welcome partnerships with SaaS providers who want to add chatbot functionality. There are also opportunities for integration with game studios and those who create virtual worlds, where the painstaking work of creating NPC dialogues or virtual landscapes can be automated.
With MindOS launching later in 2023, what are your expectations for the reception of your technology?
I expect that users will enjoy the ability to customize the appearance and character of the characters. Deploying a chatbot feels very impersonal and distant, more like a spreadsheet than a colleague connection. Creating an embodied AI assistant with a generative AI mind channels some creativity and raises more serious questions about what a brand’s true look, voice, and personality are. For end users, I think they’ll be relieved to finally have a chatbot that actually listens to them and isn’t just the textual equivalent of a maze of phone menus where you can’t really get the answer you want.
Basically, I think reception will be determined by ROI, as the generative cycle of AI hype will eventually come to an end, as all hype cycles do. Unlike some other technology hype cycles, I believe the core value question for LLM-based customizable AI is much more certain: you can immediately deploy it to solve bottlenecks in customer service, product discovery, FAQs, process automation, marketing and sales
Conclusion
In closing, our insightful conversation with Mindverse’s Kisson Lin shed light on the enormous potential of AI and the transformative impact it can have on industries worldwide. It’s clear that Mindverse is at the forefront of AI innovation, from customization and rapid adaptation to solving ethical issues and improving employee satisfaction.
As the company continues to improve its offerings based on valuable feedback from the closed beta, it’s exciting to see the collaboration and partnership opportunities that await Mindverse across industries. With the highly anticipated launch of MindOS later this year, the future of artificial intelligence has never looked more promising.
Follow groundbreaking advances in the world of artificial intelligence as Mindverse continues to shape the future of artificial intelligence and change the way we live, work and interact with technology.
