Welcome to our exclusive interview with Kisson Lin the COO of Mindverse, a cutting-edge AI development company that’s transforming industries with AI beings powered by controllable large language models. In this enlightening conversation, we delve into the company’s vision for the future of AI beings, how Mindverse tailors AI beings to individual company needs, and the innovative features of MindOS that enable rapid onboarding of AI beings.
Kisson also addresses concerns regarding the application of LLM-based AI in sensitive fields and emphasizes the importance of ethics in AI development. We explore how feedback from the Closed Beta will shape the Open Beta and the final release, and discuss the role of MindOS in enhancing employee satisfaction and productivity. Finally, we touch upon partnership opportunities and collaborations Mindverse envisions across various industries and the company’s expectations for the reception of MindOS when it launches later this year.
Join us as we uncover the fascinating world of AI beings and their potential to revolutionize industries, making our lives more efficient and productive than ever before.
As the COO of Mindverse, can you share your vision for the future of AI beings and their potential impact on various industries?
Fundamentally, AI beings are just like any technology: they’re useful as tools to make our lives better. At Mindverse, we see generative AI as a tool to increase the happiness and productivity of teams by liberating people from the mundane and letting them focus on tasks that channel their creativity. AI beings powered by controllable large language models have the potential to transform various industries by improving efficiency, accuracy, and decision-making, while simultaneously providing personalized experiences to users.
We’ll see as time goes on that AI beings will play as vital of a role in our day-to-day lives as our smartphones. We’re already seeing exponential advancements in generative AI and predict that artificial intelligence will become a valuable asset to any company’s strategy. Today, there are conversations in almost every industry about how generative AI will shape the future. Industries of all types and sizes will be affected from healthcare to education, from diagnosing illnesses more effectively to creating personalized learning experiences for students.
How does Mindverse tailor AI beings to a company’s needs?
One of the most exciting features of MindOS is its customization abilities. MindOS allows users to provide custom information about relevant products or companies via a website link, uploaded document, or by being written directly on the platform. Legacy chatbots were expensive and time-consuming to deploy, and MindOS represents a huge step forward in deployability and customization.
Custom information allows for easy business integration and will result in the creation of a tailored AI. Additionally, users can provide a character biography or life experiences for AI’s to utilize when in conversation. The MindOS library also supports over 30 languages and dozens of product integrations, while offering over 1,000 predesigned AI beings. There’s something in MindOS for every business!
Can you elaborate on the real-time searching and zero-shot training features of MindOS, and how they contribute to the rapid onboarding of AI beings?
Real-time searching allows AI beings to quickly search through large amounts of data and retrieve relevant information in real time. This can be incredibly useful for AI beings that are still in the process of learning and need to access information quickly. For example, a chatbot that is being trained to answer customer inquiries can use real-time searching to quickly find the best response to a customer’s question.
Zero-shot training, on the other hand, allows AI beings to learn new tasks and concepts without explicit training. This means that AI beings can be quickly onboarded to new tasks and start working immediately, without the need for extensive training data. For example, an AI being that has been trained to answer customer inquiries in one language can use zero-shot training to quickly learn how to respond to inquiries in another language, without needing to be explicitly trained in that language.
Together, these features can help to accelerate the onboarding of AI beings and reduce the time and resources needed to get them up to speed. This can be incredibly valuable for businesses that are looking to implement AI solutions quickly and efficiently. By leveraging the power of real-time searching and zero-shot training, businesses can rapidly onboard new AI beings.
How do you address concerns with LLM-based AI in sensitive fields?
There’s plenty of discussion about ethics in AI, and I think that it’s essential that AI developers listen when it comes to discussions of algorithmic bias and privacy. Beyond the more general discussions of ethics in AI, I’d say that the most common concern about LLM-based AI is the accuracy of information. 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 concern in companies that a chatbot might give the wrong answer to an important question.
The general purpose GPT tools you see online struggle with giving the right information because you can’t control what information it’s been trained on. Tools like MindOS are tailor-made to avoid inaccurate outputs because we allow companies to control the LLM and train the AI on all of the facts about a company and its policies. Say an enterprise user imports hundreds of pages of company training documents and product information, and one of those pages happens to be about a refund policy, the AI will always respond with the correct refund policy.
How will Closed Beta feedback shape Open Beta and the final release?
At Mindverse, we take feedback very seriously, and the feedback we receive during the Closed Beta will play a significant role in shaping the Open Beta and the final release of our products.
During the Closed Beta, we will be collecting feedback from our invited group of users who have been given access to our products. This feedback will be used to identify areas where our products can be improved and what features we can introduce to make the tool more useful in certain industries.
Based on this feedback, we will make changes and improvements to our products before the Open Beta is released.
Can you discuss the role of MindOS in improving employee satisfaction and productivity?
MindOS provides the flexibility to create personalized AI-powered assistants that are highly customizable, enabling businesses to handle customer inquiries or simple transactions in seconds.This allows for employees that previously needed to spend copious amounts of time responding to customer inquiries to allocate their efforts on big picture tasks. This will lead to expedited workflow and overall better business performance, eliminating the need for employees to spend time on mundane, repetitive tasks.
What kind of partnership opportunities and collaborations does Mindverse envision with businesses across different industries during the Closed Beta and beyond?
We operate in the AI as a Service space, or as we call it, Mind as a Service. Naturally, this lends itself to collaboration with distribution and white-label partners who know the mechanics of particular industries. There are also SaaS tools that are vital to certain industries: e-commerce store managers, DIY website builders, event management suites, CRMs, marketing tools, task organizers, and process automation.
Most of those tools use third-party partners to power their chatbot functionalities, so we welcome partnerships with SaaS providers looking to add chatbot functionalities. There are also possibilities for integration with game studios and those who build virtual worlds, where the painstaking work of generating NPC dialogue or virtual landscapes can be automated.
With the launch of MindOS later in 2023, what are your expectations for the reception of your technology?
I expect that users will enjoy the ability to tailor character appearances and personalities. Chatbot deployment feels very impersonal and distant, more akin to a spreadsheet than onboarding a colleague. Creating an embodied AI assistant with a generative AI mind channels a bit of creativity and begs larger questions about what is the real appearance, voice, and personality of a brand. For end users, I think they’ll be relieved to finally have a chatbot that actually listens to them, rather than just being the text equivalent of a phone menu maze where you can’t actually get the answer you need.
Fundamentally, I think that the reception will be determined by ROI, because the generative AI hype cycle will end eventually, like all hype cycles. Unlike some other tech hype cycles, I think the core question of value is much more certain for a customizable LLM-based AI: you can immediately deploy it to solve bottlenecks in customer service, product discovery, FAQ answers, process automation, marketing, and sales
In conclusion, our insightful conversation with Mindverse’s Kisson Lin has shed light on the immense potential of AI beings and the transformative impact they can have on industries worldwide. From customization and rapid onboarding features to addressing ethical concerns and enhancing employee satisfaction, it’s clear that Mindverse is at the forefront of AI innovation.
As the company continues to refine its offerings based on valuable feedback from the Closed Beta, it’s exciting to see the collaborative opportunities and partnerships that lie ahead for Mindverse across various industries. With the highly anticipated launch of MindOS later this year, the future of AI beings has never looked more promising.
Stay tuned for more groundbreaking advancements in the world of AI beings, as Mindverse continues to shape the future of artificial intelligence and redefine the way we live, work, and interact with technology.