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  • Episode 46: Empowering Democracy with LLMs

    Episode 46: Empowering Democracy with LLMs
    2024/09/25
    Genevieve Hayes Consulting Episode 46: Empowering Democracy with LLMs With all the reports about the spread of misinformation and disinformation on social media, sometimes it feels like one of the biggest threats to democracy is technology. But no technology is inherently good or bad. It’s how you use it that matters. And just as technology has the potential to harm democracy, it also has the potential to enhance it.In this episode, Vikram Oberoi joins Dr Genevieve Hayes to discuss how he has been using generative AI and large language models (LLMs) to enhance people’s access to NYC council meetings through his work on citymeetings.nyc. Guest Bio Vikram Oberoi is a software engineer, fractional CTO and co-owner of Baxter HQ, a boutique early-stage tech product development firm. He also built and operates cityme
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    48 分
  • Episode 45: AI-Powered Investment Insights

    Episode 45: AI-Powered Investment Insights
    2024/09/11
    Genevieve Hayes Consulting Episode 45: AI-Powered Investment Insights Succeeding in stock market investing is all about timing – buying low, selling high and being able to read the signs to determine when things are going to change. But as anyone who’s ever tried to get rich through stock trading can tell you, this is easier said than done.Given the massive amounts of financial data published each day, for people who aren’t experts in the field, it can be too hard to spot the patterns and keep up with the constant change. As a result, many people are either investing in markets based on guesswork or not investing at all.This is where AI can help, because there’s nothing that AI does better than finding patterns in large volumes of data. AI has the potential to democratize access to investment insights.In this episode, Andrew Einhorn joins Dr Genevieve Hayes to discuss how AI can help ordinary investors find better investment opportunities
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    45 分
  • Episode 44: Designing Data Products People Actually Want to Use

    Episode 44: Designing Data Products People Actually Want to Use
    2024/08/28
    Genevieve Hayes Consulting Episode 44: Designing Data Products People Actually Want to Use As a data scientist, there’s nothing worse than devoting months of your time to building a data product that appears to meet your stakeholders’ every need, only to find it never gets used. It’s depressing, demotivating and can be devastating for your career.But as the old saying goes, “You can lead a horse to water, but you can’t make it drink”. Or can you?In this episode, Brian T O’Neill joins Dr Genevieve Hayes to discuss how you can apply the best techniques from software product management and UI/UX design to create ML and AI products your stakeholders will love. Guest Bio Brian T O’Neill is the Founder and Principal of Designing for Analytics, an independent data product UI/UX design consultancy that helps data leaders turn ML & a
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    50 分
  • Episode 43: Shaping the Future of AI

    Episode 43: Shaping the Future of AI
    2024/08/14
    Genevieve Hayes Consulting Episode 43: Shaping the Future of AI Two years ago, no one could imagine the impact generative AI would have on our world, and most of us can’t even begin to imagine the impact the next generation of AI will have on our world two years from now. The only thing that is certain is uncertainty.But that uncertainty brings with it great opportunities and choices. We can choose to sit back and let the future of AI play out in front of us or engage with this new technology and shape the future of AI and the world as we know it.In this episode, Dr Eric Daimler joins Dr Genevieve Hayes to discuss his extraordinary work in shaping the future of AI and what that future might look like. Guest Bio Dr. Eric Daimler is the Chair, CEO and Co-Founder of Conexus AI and has previously co-founded five other companies in the technology space. He
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    50 分
  • Episode 42: Should You Outsource Your Data Team?

    Episode 42: Should You Outsource Your Data Team?
    2024/07/31
    Genevieve Hayes Consulting Episode 42: Should You Outsource Your Data Team? Chances are, you’re reading this summary on a device you didn’t build yourself. Why would you? Tech companies can build you a far better device for a much lower cost than you could ever manage alone. As with many other cases in life, this is an example of where it is better to buy than to build.Yet, in building a data team, many organisations assume the only solution is to build from within. And although this may be the right solution for some organisations, building a solution isn’t right for all.In this episode, Collin Graves joins Dr Genevieve Hayes to discuss what a bought solution might look like in the data science space, and whether it is right for you. Guest Bio Collin Graves is the CEO of North Labs, a leading fractional cloud data analytics firm that helps growi
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    49 分
  • Episode 41: Building Better AI Apps with Knowledge Graphs and RAG

    Episode 41: Building Better AI Apps with Knowledge Graphs and RAG
    2024/07/17
    Genevieve Hayes Consulting Episode 41: Building Better AI Apps with Knowledge Graphs and RAG When ChatGPT was first released, there was talk it would lead to traditional search engines, like Google, soon becoming obsolete. That was until users discovered generative AI’s one major drawback – it makes stuff up.Because of the stochastic nature of ChatGPT, it is never going to be possible to completely eliminate hallucinations. However, there are ways to work around this issue. One such way is through leveraging knowledge graphs and retrieval augmented generation (or RAG).In this episode, Kirk Marple joins Dr Genevieve Hayes to discuss how knowledge graphs and RAG can be leveraged to improve the quality of generative AI. Guest Bio Kirk Marple is the CEO and Technical Founder of Graphlit, serverless, cloud-native platform that streamlines the development of
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    46 分
  • Episode 40: Making Data Science Teams Profitable

    Episode 40: Making Data Science Teams Profitable
    2024/07/03
    Genevieve Hayes Consulting Episode 40: Making Data Science Teams Profitable For many people, data science is synonymous with machine learning and many data science courses are little more than overviews of the most used machine learning algorithms and techniques.Where the majority of data science courses fall short is they neglect to bridge the gap between data science theory and business reality, resulting in many data scientists who are technically strong but unable to create value from their work. However, this doesn’t necessarily have to be the case.In this episode, Douglas Squirrel joins Dr Genevieve Hayes to discuss systems and techniques data scientists and their managers can use to make data science teams profitable. Guest Bio Douglas Squirrel has been coding for forty-five years and has led software te
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    1 時間 3 分
  • Episode 39: The Impact of Data Science on Data Orchestration

    Episode 39: The Impact of Data Science on Data Orchestration
    2024/06/19
    Genevieve Hayes Consulting Episode 39: The Impact of Data Science on Data Orchestration One of the big promises of data science is its ability to combine multiple disparate datasets to produce value-creating insights. But this is only possible if you can get all those disparate datasets together, in the one location, to begin with. The has led to the rise of the data engineer and the data orchestration platform.In this episode, Sandy Ryza joins Dr Genevieve Hayes to discuss the impact of the data scientist on the creation of the next generation of data orchestration tools. Guest Bio Sandy Ryza is a data scientist turned data engineer who is currently the lead engineer on the Dagster project, an open-source data orchestration platform used in MLOps, data science, IOT and analytics. He is also the co-author of Advanced Analytics with Spark.
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    39 分