Luke Kim is the Founder and CEO of Liner, a cutting-edge AI-powered analysis software designed to streamline and improve the analysis course of, serving to customers full their duties 5.5 occasions sooner. As an AI search engine, Liner gives filtered search outcomes for exact info and mechanically generates citations in varied codecs, making it a useful useful resource for researchers, college students, and professionals.
Are you able to inform us about your background and what impressed you to pursue entrepreneurship, particularly within the area of AI and expertise?
My entrepreneurial journey started with a need to handle real-world issues via expertise. As an undergraduate, I used to be struck by how difficult it was to navigate and belief the abundance of data on-line. I used to be motivated to create a software that streamlines the method and helps college students discern between sources. What began as a highlighting software, weeding via accessible info, over time developed into what Liner is at this time: an AI search that gives solely essentially the most dependable outcomes. I used to be drawn to AI for its potential to rework how we course of and work together with knowledge. The chance to create significant options for college students, like my youthful self, continues to encourage me.
How did your expertise with the browser extension you constructed throughout your college days form the imaginative and prescient for Liner?
The Liner highlighter browser extension was my first actual dive into fixing the issue of data overload. It confirmed me how a lot individuals worth instruments that make discovering and organizing key info simpler. I discovered that simplifying even one step of a workflow can have a huge impact, whether or not it’s highlighting vital factors or surfacing related sources. This venture formed Liner’s dedication to making a seamless expertise for customers, and serving to college students and researchers weed via the surplus noise on the web.
What was the unique imaginative and prescient behind Liner, and the way has it developed since its inception?
Liner started as a easy software to assist customers spotlight and save key elements of on-line content material. The purpose was to make it simpler for customers to give attention to essentially the most related info with out being overwhelmed. Over time, we acknowledged that customers wanted greater than a approach to gather and kind info—they wanted higher methods to seek out it and discern its reliability. This realization guided Liner’s transformation into an AI search engine.
What have been the foremost challenges you confronted whereas transitioning Liner from a highlighting software to an AI-driven search engine?
One of the vital challenges was making certain that our AI may persistently ship dependable and correct outcomes. Tutorial analysis requires a excessive diploma of belief, and assembly these expectations was essential. One other problem was integrating years of user-highlighted knowledge into the AI’s coaching course of whereas protecting the platform intuitive. Putting the correct steadiness between technological innovation and a seamless person expertise was important but in addition extremely rewarding.
By constructing Liner’s definition of “agent” from scratch, we have been capable of create a sturdy and steady framework for understanding what an agent actually is. We then applied a search agent that prioritized reliability and credibility. Provided that our audience represents the head of credibility-focused expectations, we would have liked a particular resolution able to addressing essentially the most complicated issues. Our energy lay in leveraging our proprietary datasets, the technical insights gained in the course of the agent definition course of, and our implementation experience. Collectively, these components turned our strongest instruments for achievement.
Are you able to elaborate on how the combination of user-highlighted knowledge enhances the accuracy and reliability of Liner’s AI search outcomes?
Consumer-highlighted knowledge acts as a priceless layer of high quality management, serving to our LLM discern what different customers discover vital and credible. By leveraging this curated knowledge, we’re capable of prioritize related and reliable info in our search outcomes. This method ensures that customers get exact and actionable insights whereas avoiding irrelevant or low-quality content material.
How does Liner differentiate itself from different AI search instruments like ChatGPT or Perplexity?
Liner stands out by prioritizing reliability and transparency. Each search end result features a quotation, and customers can filter out much less dependable sources to make sure accuracy. As an extra measure, college students can pull sources and examine the unique quoted textual content on their display screen. Not like instruments designed for informal queries, Liner is purpose-built for college students, teachers, and researchers, serving to customers give attention to in-depth studying and evaluation as a substitute of verifying details. This dedication to belief and value makes Liner a go-to software for over 10 million customers, together with college students at universities like UC Berkeley, USC, College of Michigan, and Texas A&M. Liner continues to distinguish itself via partnerships, like a latest one with Tako, which integrates data visualization instruments to current complicated knowledge in a extra accessible and interactive format, empowering customers to dive deeper into their analysis.
What measures does Liner take to cut back hallucinations in its AI responses, and the way does this impression person belief?
Decreasing hallucinations requires anchoring AI-generated responses to verifiable sources. Liner achieves this by cross-referencing its outcomes with tutorial papers, authorities databases, and different trusted repositories. Our Supply Filtering System additional permits customers to exclude unreliable content material, offering an added layer of high quality assurance. These steps not solely reduce errors but in addition construct belief with the person.
Liner’s system relies on relevance (the relevance rating between agent-generated claims and reference passages) and factuality (which assesses how properly the agent-generated claims are supported by the reference passages). The extra supportive the passage, the upper the factuality rating.Since our product strongly encourages customers to confirm claims to make sure they’re free from hallucinations, enhancing the factuality of our agent system is essential. In the end, we observe a optimistic correlation between the factuality rating and person retention.
What steps is Liner taking to construct belief amongst customers, particularly these skeptical about counting on AI for essential info?
Constructing belief begins with transparency. Liner gives clear citations for each end result, giving customers the power to confirm the data themselves. Moreover, we rank sources based mostly on reliability and permit customers to have interaction instantly with the unique content material. Steady person training and open communication additionally play a job in demonstrating that AI, when designed responsibly, is usually a reliable ally in training.
What traits do you assume will form the way forward for AI in tutorial analysis {and professional} data retrieval?
AI will change into more and more personalised, adapting to the distinctive wants of every person and offering tailor-made insights. Transparency shall be key, as customers search better readability about how AI processes info and delivers outcomes. Developments may even give attention to addressing info overload and streamlining analysis instruments. By automating repetitive duties like knowledge gathering and synthesis, AI will pace up the early levels of analysis, enabling researchers to focus extra on essential considering, evaluation, and innovation. This steadiness between effectivity and mental engagement will form the way forward for tutorial {and professional} analysis.
Liner just lately efficiently raised a $29 million funding spherical. How will this funding assist Liner develop, and what areas are you specializing in for growth?
This funding permits us to advance our mission of bettering AI in training. We’re rising our world workforce and rolling out new options like Essay Mode, designed to assist college students refine their expertise in writing, structuring, and formatting essays. We’re additionally prioritizing partnerships with universities {and professional} organizations to achieve extra customers and showcase the impression of AI-powered analysis instruments. Current collaborations with firms like ThetaLabs and Tako have expanded our capabilities. This funding highlights the rising want for reliable search options, and we’re keen to construct on this momentum.
Thanks for the good interview, readers who want to be taught extra ought to go to Liner.
