Brightwave with Mike Conover| E355

AI enabled research and discovery.

In this episode of Fintech Impact, Jason Pereira interviews Mike Conover, CEO and Co-founder of Brightwave, an AI-driven investment research platform. Mike discusses how Brightwave leverages machine learning and artificial intelligence to provide insightful financial analysis by synthesizing data from multiple sources and uncovering patterns. The episode delves into the challenges of using AI for financial research, the advantages of Brightwave's approach, and the vision for the platform's future in the industry. Jason and Mike also explore the broader implications of generative AI in high-stakes domains like finance.

Episode Highlights:

  • 00:09: Jason Pereira introduces the FinTech Impact podcast with guest Mike Conover, CEO of Brightwave, introducing the AI-driven research platform to the audience.

  • 00:34: Mike expresses his appreciation for being on the show, signalling the start of the conversation about Brightwave.

  • 00:36: Jason asks Mike to describe Brightwave, leading to a concise explanation of the platform's function in investment research.

  • 00:39: Mike explains Brightwave as an AI platform generating valuable financial analysis and insights.

  • 00:51: Jason praises Mike for delivering a concise elevator pitch about Brightwave, setting the tone for the interview.

  • 00:57: Mike humorously acknowledges Jason's appreciation, emphasizing his brief answer .

  • 00:58: Jason transitions to discussing the origin of Brightwave and the problems it aims to solve in the market.

  • 01:06: Mike provides an overview of the purpose of Brightwave, explaining its role in finding under explored market opportunities with AI.

  • 01:41: Jason agrees with Mike, discussing the strengths and limitations of AI in financial research using large language models.

  • 01:45: Mike further elaborates on the advantages of AI in keeping track of numerous details in financial analysis.

  • 02:44: Jason and Mike highlight the importance of augmented humanity and reliability in AI tools for high-stakes fields like finance.

  • 03:26: Mike shares his extensive background in AI and machine learning, outlining his career path leading to founding Brightwave.

  • 04:19: Mike discusses his unique experiences with large-scale data sets from his past roles, emphasizing their impact on his understanding of world systems.

  • 05:14: Mike explains how Brightwave leverages language models to better grasp the complexities of global economic systems.

  • 05:57: Mike describes Brightwave's strategic approach to investment research using advanced AI models, offering a comprehensive view of the markets.

  • 06:19: Jason appreciates the integration of generative AI in Brightwave's functionality, aligning with Mike’s expertise in unraveling intricate world patterns.

  • 06:26: Mike credits his co-founder’s deep financial services experience and their team’s technical expertise in enhancing Brightwave’s performance.

  • 07:28: Jason observes differences in how teams approach AI solutions, pointing out the importance of addressing data reliability and network challenges.

  • 08:30: Mike agrees, suggesting that quality AI solutions require a practical, problem-solving mindset for successful deployment.

  • 09:16: Mike discusses Brightwave's focus on financial services, emphasizing accuracy as a key objective in their AI research platform.

  • 09:42: Jason summarizes how Brightwave offers expansive stock research capabilities, providing users with crucial insights via AI-driven methods.

  • 10:42: Mike talks about the advantages of their system beyond just stock research, including insights on macro themes and unique market patterns.

  • 11:28: Mike details the types of questions Brightwave can address, illustrating the wide-ranging applications of their AI platform in investment research.

  • 12:15: Jason and Mike discuss the behavior of systems trained to find and interpret complex patterns, particularly in financial domains.

  • 12:30: Mike contrasts existing methods with Brightwave, highlighting its ability to process and meaningfully interpret vast amounts of data.

  • 12:52: Jason recounts an anecdote about stock sentiment analysis, emphasizing the limitations of surface-level data interpretation.

  • 13:14: Mike agrees and critiques the usefulness of sentiment analysis in capturing the depth of financial research needed for accurate insights.

  • 14:07: Mike expands on how Brightwave identifies sound investment opportunities by leveraging deeper patterns within large-scale data sources.

  • 15:18: Mike provides examples of Brightwave's capabilities in synthesizing comprehensive insights and supporting investment decision-making.

  • 16:19: Jason acknowledges the enormous potential of Brightwave, which combines extensive data analysis with deep question exploration.

  • 17:53: Mike explains Brightwave's user journey, detailing how it achieves efficiency and enhanced decision-making through data synthesis.

  • 19:16: Mike elaborates on how Brightwave goes beyond typical commoditized AI research features, emphasizing synthesis and idea generation.00:20:14: Mike shares specific use cases illustrating how Brightwave's system enhances user understanding of complex market questions.

  • 22:07: Jason appreciates the depth of exploration facilitated by Brightwave, highlighting its discoveries of unknown connections.

  • 23:15: Mike highlights customer feedback, detailing the positive reception of Brightwave's speed and decision-boost features.

  • 24:57: Mike reveals his wish for a more measured approach to AI technology amidst the current hype, focusing on genuine capabilities.

  • 25:40: Jason reflects on the early excitement about AI, predicting a period of adjustment to realistic use cases and applications.

  • 26:14: Mike mentions the challenge of developing user-friendly, informative interfaces for AI-driven financial analysis systems.

  • 27:49: Jason evaluates the development of tools like perplexity, noting their contributions to clarifying AI-generated information.

  • 28:26: Mike acknowledges the rapid evolution of AI features, particularly emphasizing auditory elements and their potential relevance.

  • 29:46: Mike expresses his enthusiasm for working with a skilled, motivated team, attributing much of Brightwave’s success to their expertise.

  • 30:15: Jason concludes the podcast with a call to action for those interested in Brightwave's innovative research capabilities.

Key Points:

  • Brightwave uses advanced AI to synthesize data, uncovering insightful financial analysis beyond conventional methods.

  • The platform offers rapid data processing, helping asset managers make informed decisions faster with greater confidence.

  • Acknowledging AI's limitations is crucial for ensuring practical applications in high-stakes industries like finance.

  • Despite the AI hype, its value lies in powerful data reasoning, not the creation of an all-knowing entity.

Tweetable Quotes:

  • "Brightwave is an AI platform that unlocks powerful insights beyond conventional financial research methods."- Mike Conover

  • "AI in finance isn't about creating a living god; it's about transforming how we reason over text."- Mike Conover

  • "Synthesis, not just data gathering, is where Brightwave creates true value for financial analysts."- Mike Conover

  • "Our challenge is showcasing AI's thought process, making it legible and valuable for users."- Mike Conover

Resources Mentioned:

Fintech ImpactJason PereiraFintech