In today’s episode we explore the topic of AI-powered human augmentation in the physical world. Our guest is Meghan Kennelly, Head of Global Marketing at German Bionic, a European robotics firm that develops and manufactures wearable robotics that help front-line workers move more efficiently and safely. Meghan discusses German Bionic’s smart exoskeleton product, which uses AI to learn and optimize itself to match the particular body movements of individual workers. We also talk about the industries where their products are getting good results, implications for the future front-line workforce, and some interesting uses for telemetric data collected from these smart devices.

Links:

• https://germanbionic.com/en/
• https://www.linkedin.com/in/meghankennelly/

Today’s conversation with Clint Dunn is a deep dive into arguably the most important business metric out there: customer lifetime value. Clint is the founder of Wilde.ai, an early-stage SaaS startup that delivers customer LTV predictions directly to your data warehouse. In our conversation, Clint explains how having a fine-grained, customer-level understanding of LTV can help businesses make profit maximizing decisions across all major business functions. We also discuss the pros and cons of “warehouse centric” architecture, and how Wilde achieved profitability without building a user interface.

Links:
- https://wilde.ai/

Timestamps:
00:00 Introduction
02:33 Longing to start a company, gained experience.
03:48 Data world challenges, building a repeatable company.
07:36 Integrated data workflow with transparent, adaptable infrastructure.
10:16 Maturity curve, finance team, LTV, profitability, personalization.
16:10 Query on fitting Wyld into marketing and data.
17:58 Phone call discusses human capital limitations in marketing.
20:42 Building content around holistic customer understanding is crucial.
24:00 Managing data inputs for standard retail processes.
29:49 Transparent model with proof of effectiveness.
34:16 Data can be seen as helpful but controlling.
39:23 Data leaders navigating build vs. buy dilemma.
40:23 Unbiased training, DIY versus wild sales, LTV importance.
45:01 Challenges with data modeling and actionability.
47:05 Improving tools, native apps key for growth.

Tune in and gain valuable knowledge about the power of data analytics in shaping the future of businesses. Do not forget to rate or review on your favorite platform!

In today’s episode we explore the current state-of-art in document AI with Andrej Baranovskij, an active open source contributor and founder of Katana ML. Andrej’s work centers using open source AI models to extract structured information from documents, including PDF’s, image files, and more. In our conversation, we discuss how document AI has advanced with the advent of transformer architectures, and increasing use of multi-modal models that combine image recognition capabilities with language understanding. We also talk about Andrej’s vision for Sparrow, his open source project geared toward helping organizations adopt these models more easily.

Links:
- Sparrow: https://github.com/katanaml/sparrow

Timestamps:
00:00 Document AI: evolution, accessibility, and real-world use
05:23 Enterprise expert finds common sense use case.
07:57 Goal: Successful open source product helping companies.
09:47 Advantages of DOM: free, commercial use allowed, key-value data.
15:19 Donut has limitations due to training data.
17:31 Elements automates invoice processing, reduces manual work.
22:20 Paducera groups receipt data exceptionally well with key value pairs.
24:41 Persist data for retrieval and calculate spending patterns.
29:50 Challenging integration with support, but successful.
34:09 AI accessibility for developers, smaller ML models.
35:54 Trend: running ML models locally instead of cloud.
39:08 Adding LLM support with Fast API framework.

Tune in and gain valuable knowledge about the power of data analytics in shaping the future of businesses. Do not forget to rate or review on your favorite platform!