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    Technology

    AI Loves Data Podcast

    The official podcast of Data Science Salon which is now AI Loves Data. We interview top and rising luminaries in data science, machine learning, and AI on the trends and business use cases that are propelling the field forward. The AI Loves Data series is a unique vertical focused conference which brings together specialists face-to-face to educate each other, illuminate best practices, and innovate new solutions in a casual atmosphere with food, great coffee, and entertainment.

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    Copyright: © 2019 Formulatedby

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    Latest Episodes:
    AI in Action: From Machine Learning Interpretability to Cybersecurity with Serg Masís and Nirmal Budhathoki Aug 06, 2024
    Show notes

    In this DSS Podcast, Anna Anisin welcomes Serg Masís, Climate and Agronomic Data Scientist at Syngenta. Serg, an expert in machine learning interpretability and responsible AI, shares his diverse background and journey into data science. He discusses the challenges of building fair and reliable ML models, emphasizing the importance of interpretability and trust in AI. Serg also talks into his latest book, "Interpretable Machine Learning with Python," and provides valuable insights for data scientists striving to create more transparent and effective AI solutions. In another compelling episode, Anna sits down with Nirmal Budhathoki, Senior Data Scientist at Microsoft. Nirmal, who has extensive experience at VMware Carbon Black and Wells Fargo, focuses on the intersection of AI and cybersecurity. He shares his journey into security data science, discussing the unique challenges and critical importance of applying AI to enhance cybersecurity measures. Nirmal highlights the pressing need for AI in this field, practical use cases, and the complexities involved in integrating AI with security practices, offering a valuable perspective for professionals navigating this dynamic landscape. Writer and Host: Anna Anisin Produced, edited, and mixed by the Formulatedby Team


    AI at the Crossroads: Bias, Diversity, and Scalability with Boshika Tara and Dr. June Andrews Jul 23, 2024
    Show notes

    In this week's DSSPodcast, Anna had a conversation with Boshika Tara, Technical Machine Learning Product Manager at H&M Group. Boshika brings over 7 years of experience in technical product development, engineering, and building large-scale ML systems in NLP and Computer Vision. In this episode, she dives into the critical issue of bias in AI, discussing various types of biases in machine learning, how to detect them, and the importance of creating more equitable teams with diverse representation to mitigate these biases. Additionally, Anna had the pleasure of hosting Dr. June Andrews, the Founder of Lat Long Labs. Dr. Andrews shares her incredible journey from leading the Style Discovery team at Stitch Fix to her role as a Tech Lead at LinkedIn. She discusses the complexities of scaling and transforming AI projects, particularly in predicting consumer preferences and enhancing product discovery. Writer and Host: Anna Anisin Produced, edited, and mixed by the Formulatedby Team


    Elevating Computer Vision and Female Voices with Alex Levinson and Sheila Beladinejad Jul 09, 2024
    Show notes

    In this episode of the DSS Podcast, Anna Anisin introduces two powerhouse guests in the realms of AI and robotics. First, Anna welcomes Alex, Principal Algorithms/AI Engineer at Elbit Systems of America, based in Miami. Alex shares her journey into the field of AI, particularly computer vision, and discusses common use cases, pitfalls, and success stories in sourcing and improving data for computer vision models. She also offers valuable recommendations for data scientists starting out in the field and highlights an exciting trend in AI that she's currently following. Next, Anna introduces Sheila Beladinejad, President of Women in AI & Robotics. Sheila talks about the network she built in Germany, dedicated to fostering gender-inclusive, ethical, and responsible AI and robotics solutions. She highlights the importance of creating such a network and the positive impact it has had on the AI and robotics community. Writer and Host: Anna Anisin Produced, edited, and mixed by the Formulatedby Team


    Using AI & Machine Learning to Develop Better Healthcare Experiences with Sumayah Rahman and Vaibhav Verdhan Jun 24, 2024
    Show notes

    In this episode of the Data Science Salon Podcast, host Anna Anisin sits down with two leading experts in the ML/AI healthcare industry. First, Sumayah Rahman, Director of Data Science - Machine Learning and Infrastructure at Cedar, discusses optimizing the patient experience to make healthcare more affordable and accessible. She explains how ML-powered discounts can benefit both patients and providers, sharing practical examples of using data to enhance patient experiences and highlighting the transformative impact of AI/ML in healthcare. Next, Vaibhav Verdhan, Analytics Leader at AstraZeneca, dives into the role of computer vision in healthcare and his favorite technologies in the healthcare analytics space. He discusses how advanced analytics are driving innovation at AstraZeneca by developing, deploying, and maintaining decision support capabilities. Both guests provide valuable insights into how AI and ML are revolutionizing healthcare, offering listeners practical knowledge and inspiration. Writer and Host: Anna Anisin Produced, edited, and mixed by the Formulatedby Team


    Lessons Learned from Applying Data Science in Finance and a Deep Dive into Drift with Mabu Manaileng and Adam Lieberman Jun 17, 2024
    Show notes

    In this episode, Anna sits down with two leaders in the finance industry, exploring the forefront of AI and ML innovations. First, we have Mabu Manaileng, Lead Data Scientist at Standard Bank Group. Mabu shares his journey and current role, highlights the challenges of applied data science in the financial sector, and discusses the transformative impact of AI on banking in the coming years. Next, we welcome Adam Lieberman, Head of AI and ML at Finastra. Adam defines the concept of drift, discusses statistical measures to quantify it, and provides strategies for maintaining model health, ensuring that models continue to serve users' needs effectively. Writer and Host: Anna Anisin Produced, edited, and mixed by the Formulatedby Team


    Leveraging Statistical Models and ESG to Grow Your Business with Laura Gabrysiak and Rochelle March Jun 10, 2024
    Show notes

    In this episode, Anna sits down with two leaders in the finance industry, exploring the forefront of AI, ML, and ESG innovations. First, let's welcome Laura Gabrysiak, Data Science Leader at Visa. Laura develops statistical models and decision analytics tools that enable Visa clients to transform massive amounts of data into actionable ML models and AI implementations. She's also passionate about fostering the local data science community in Miami as the Founder of R-Ladies Miami. In this conversation, they dive into the future of ML/AI in financial services and the impactful work being done with Code Art to promote diversity in tech. Next, we have Rochelle March, former Head of ESG Product at Dun & Bradstreet. Rochelle specializes in impact analysis related to carbon, water, and the Sustainable Development Goals, and applies machine learning to ESG products. She also teaches data and analytics at Bard College’s MBA program, sits on the advisory board for USL Technology, Inc., and mentors fellows in the Environmental Defense Fund’s Climate Corps program. Since recording this episode, Rochelle has started her own company, People Places Words Actions. In our discussion, we explore her journey in ESG innovation and analytics, why ESG data is crucial for responsible investment decisions, and how it drives sustainable business practices. Tune in to learn from these industry thought leaders and gain insights into the cutting-edge applications of AI and ESG data in the finance sector. Writer and Host: Anna Anisin Produced, edited, and mixed by the Formulatedby Team


    FinTech Insights: AI Innovations, Privacy Strategies, and Synthetic Data with Harry Mendell & Supreet Kaur Jun 03, 2024
    Show notes

    In this episode, Anna sits down with two distinguished leaders in the ML/AI finance industry. First, we have Harry Mendell, Technology Group Data Architect at the Federal Reserve Bank of New York, who brings over 30 years of expertise in FinTech. Harry shares compelling stories and discusses emerging trends in the finance sector. Following Harry, Supreet Kaur, AVP at Morgan Stanley and product owner for various AI products, joins the conversation. Supreet provides insights into the use of synthetic data to protect customer privacy in FinTech, ensuring informed decision-making. This deep dive into synthetic data highlights its growing importance in the industry. Writer and Host: Anna Anisin Produced, edited, and mixed by the Formulatedby Team


    Context Matters: Generative AI, the spectrum of worldviews, and understanding propaganda's appeal Oct 24, 2023
    Show notes

    Ben Dubow studied the Middle East during his undergrad and took a job tracking terrorist groups. After a brief stint at a large tech company, he launched Omelas, a company that combines AI and subject matter expertise to deliver intelligence to national security professionals.In today's episode, our Senior Content Advisor Q McCallum caught up with Ben to learn more about what Omelas is up to and how the company applies AI and data analysis to its mission.Along the way they explore the value of data in context; why it's important to ask the right questions of the right data, and not just the whole pool; the power of involving humans in the data pipeline; and what it takes to do NLP and NER at scale. The two also talk about the impact of generative AI on democracy and authoritarianism. A topic which, interestingly enough, holds lessons for corporations that plan to release AI chatbots.Links mentioned in this episode:

    • Ben's LinkedIn profile
    • Omelas website
    • Ben's writing on the Center for European Policy Analysis (CEPA) website
    • Article in Les Echos describing the project "Le Monde in English": "« Le Monde » parie sur l'étranger pour stimuler sa croissance"
    • Q's write-up on "Risk Management for Generative AI Bots" is available on both his O'Reilly Radar page and his blog.

    Writer and Host: Anna Anisin

    Produced, edited, and mixed by the Formulatedby Team


    When companies try to "sprinkle some AI" on a product May 17, 2023
    Show notes

    If you've been in the data game long enough, you've probably seen this before: a stakeholder or product owner approaches you with a project that's 95% done, and they'd like you to … "sprinkle some AI on it." They've heard that this "AI" thing can be useful so they want some of it in their latest effort.Data scientist-turned-product person Noelle Saldana has experienced the "sprinkle some AI on it" request more times than she'd care to remember. Our Senior Content Advisor Q McCallum met up with Noelle to explore this phenomenon. How does this happen? (Hint: "corporate FOMO.") What should you do when stakeholders insist on implementing AI that isn't actually going to help? What about when your data scientist peers seem like they're doing this for the sake of "résumé-driven development?"Ultimately, the pair work through the bigger issue: how do you make peace with companies throwing money at AI like this? And how can these companies use this approach to their advantage?As a bonus, Noelle shares how she made the move from a data scientist role into product management. If this path sounds interesting to you, take a listen.

    • Noelle's Data Council talk, "Hot Takes and Tragic Mistakes: How (not) to Integrate Data People in Your App Dev Team Workflows"
    • Find Noelle on LinkedIn: https://www.linkedin.com/in/noellesio/
    • Q's blog post (which came out much better thanks to Noelle's help): "AI isn't something you just add to a company"

    Writer and Host: Anna Anisin

    Produced, edited, and mixed by the Formulatedby Team


    Building data products with Solomon Kahn Mar 07, 2023
    Show notes

    Sometimes the most valuable data IN your company ... is the data LEAVING your company.That's Solomon Kahn's view on data products, as well as the premise behind his latest venture: Delivery Layer.For this episode, our Senior Content Advisor Q McCallum reached out to Solomon to check in on the new startup, and to tap his expertise in the world of data products.Solomon's been at this a while. He's run high-revenue data products in some notable places, including Nielsen. Over the years he's learned a lot and we're excited for him to share some of that hard-earned knowledge here on the show.In this extended conversation, the two explore: the reasons why building a data product is different (and, in many ways, more difficult) than building traditional software products; how the people involved can impact the outcome; why a good sense of risk management can make all the difference; and what purple cars have to do with all of this. (No, seriously. Purple cars.)Along the way, the pair talk about the early days of the data field, and how much it has changed.

    • Solomon is active on LinkedIn. You can follow him for his daily updates at https://www.linkedin.com/in/solomonkahn
    • Delivery Layer: https://www.deliverylayer.com/

    Writer and Host: Anna Anisin

    Produced, edited, and mixed by the Formulatedby Team


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