))
Predictive Analytics and AI with Pawel Zimoch of Featrix.AI
Manage episode 450197323 series 2903792
Rob May & HalfCourt Ventures, Rob May, and HalfCourt Ventures에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Rob May & HalfCourt Ventures, Rob May, and HalfCourt Ventures 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
Welcome back to another episode of AI Innovators with Rob May, the podcast that deep dives into how AI is reshaping industries and the groundbreaking minds behind it.
In today's episode, we're joined by Pawel Zimoch, co-founder of Featrix AI, a company known for pioneering vectorization solutions for the enterprise.
As we explore the world of vectors and embeddings, Pawel unpacks the significance of data predictability and why some data sets work better with AI than others.
We'll also delve into the evolution of Featrix, from its founding story to its innovative strides in custom embeddings and multi-modal data analysis.
Whether you're an entrepreneur, a data scientist, or simply curious about the future of AI, this episode is packed with insights you won't want to miss. Tune in for a fascinating conversation on the complexities, challenges, and exciting advancements in the realm of AI.
Pawel Zimoch's Links
( Featrix.ai )
(Linkedin)
( Featrix)
Rob's Links
00:00 - Embeddings use cosine similarity for comparative analysis.
04:57 - Predictive data value varies; feature engineering necessary.
06:28 - Efficient AI system predicts project viability quickly.
12:04 - Human judgment and problem-solving skills prevail.
13:59 - Learning computer science is essential for understanding AI.
16:26 - Managing models requires significant context from data scientists.
22:28 - Connect with others for broader learning perspectives.
23:28 - Success in entrepreneurship relies on understanding people.
52 에피소드
공유
