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In this episode,Sasha Bartashnik shares her insights on howlarge language models (LLMs) are transforming the development ofdata products, making advanced AI-driven solutions moreaccessible and scalable. We dive into thechallenges of traditional data tools, theadvantages and risks of LLM integration, and how businesses shouldadapt to the changing landscape of AI-driven decision-making.
Key Takeaways
πΉWhat Are Data Products? β Any software that processes or surfaces data to users, including dashboards and AI-powered insights.
πΉChallenges in Building Data Products β Team complexity, data quality, and model training require specialized knowledge and resources.
πΉHow LLMs Help β They speed up development, make AI-driven insights more accessible, and improve data cleaning and structuring.
πΉRisks and Limitations β Accuracy concerns, hallucinations, and over-reliance on AI-generated outputs require human oversight.
πΉChanging Stakeholder Expectations β Faster and more scalable data solutions raise business expectations for AI-driven insights.
πΉWhere to Start with LLMs? β Safer applications likeinternal chatbots before tackling complex structured data analysis.
Timestamped Highlights
π[00:00] β Introduction to Sasha Bartashnik & Vendeluxβs role in event intelligence
π[01:25] β Defining what a "data product" really means in the AI-driven era
π[03:00] β Key challenges in building scalable data products
π[06:45] β The impact of traditional data tools and their limitations
π[07:54] β How LLMs accelerate development and improve AI-driven insights
π[10:00] β Risks of LLMs: Accuracy concerns, hallucinations, and human oversight
π[14:18] β The evolving role of data engineering teams with LLMs
π[17:31] β Where should businesses start when implementing LLMs?
π[22:00] β The responsibility of AI builders in ensuring data accuracy and transparency
π[23:43] β How to connect with Sasha for more insights
Quote of the Episode
"LLMs are not a silver bullet. They donβt replace humans; they just shift where expertise is needed." βSasha Bartashnik
Connect with Sasha
π LinkedIn: Sasha Bartashnik
π§Enjoyed this episode?
Subscribe, leave a review, and share it with someone exploring LLMs in data products! π
5
5252 ratings
In this episode,Sasha Bartashnik shares her insights on howlarge language models (LLMs) are transforming the development ofdata products, making advanced AI-driven solutions moreaccessible and scalable. We dive into thechallenges of traditional data tools, theadvantages and risks of LLM integration, and how businesses shouldadapt to the changing landscape of AI-driven decision-making.
Key Takeaways
πΉWhat Are Data Products? β Any software that processes or surfaces data to users, including dashboards and AI-powered insights.
πΉChallenges in Building Data Products β Team complexity, data quality, and model training require specialized knowledge and resources.
πΉHow LLMs Help β They speed up development, make AI-driven insights more accessible, and improve data cleaning and structuring.
πΉRisks and Limitations β Accuracy concerns, hallucinations, and over-reliance on AI-generated outputs require human oversight.
πΉChanging Stakeholder Expectations β Faster and more scalable data solutions raise business expectations for AI-driven insights.
πΉWhere to Start with LLMs? β Safer applications likeinternal chatbots before tackling complex structured data analysis.
Timestamped Highlights
π[00:00] β Introduction to Sasha Bartashnik & Vendeluxβs role in event intelligence
π[01:25] β Defining what a "data product" really means in the AI-driven era
π[03:00] β Key challenges in building scalable data products
π[06:45] β The impact of traditional data tools and their limitations
π[07:54] β How LLMs accelerate development and improve AI-driven insights
π[10:00] β Risks of LLMs: Accuracy concerns, hallucinations, and human oversight
π[14:18] β The evolving role of data engineering teams with LLMs
π[17:31] β Where should businesses start when implementing LLMs?
π[22:00] β The responsibility of AI builders in ensuring data accuracy and transparency
π[23:43] β How to connect with Sasha for more insights
Quote of the Episode
"LLMs are not a silver bullet. They donβt replace humans; they just shift where expertise is needed." βSasha Bartashnik
Connect with Sasha
π LinkedIn: Sasha Bartashnik
π§Enjoyed this episode?
Subscribe, leave a review, and share it with someone exploring LLMs in data products! π
30,051 Listeners