Tag: machinelearning

Lessons from two weeks with a CGM

I received a CGM (Continuous Glucose Monitor) about two weeks ago via the Levels start-up. The package arrived a few days after ordering, and the initial setup was relatively easy and painless. I was able to easily export the data from the Levels website.

So how do the results look? The easiest way I can think of to show you the results are using Python (pandas, matplotlib, seaborn libraries) so here we go: (I’m skipping some data wrangling bits here..)

Glucose level distribution as a histogram

Glucose Level Time Series with rolling statistics

Honestly this data has me a bit worried because generally doctors, Peter Attia MD and the Levels program all suggest that fasting glucose should be less than 100/mg/dl…

Also, I wanted to correlate the glucose readings with the time of day, so we can do that eg with a heatmap:

Glucose Levels by Day, Hour in a Heatmap

This chart is really interesting to me because here a number of things stand out to me:

  • I was in Austin from April 26th to April 28th for a conference, and those days I did a light workout in the morning, and had a light lunch. So clearly a lighter lunch, moving around in the afternoon leads to lower fasting glucose.
  • I slept really badly Fri-28th-Sat 29th due to a late flight, and clearly a bad night sleep results in a bad fasting glucose.
  • I generally workout in the afternoon – between 4PM and 6PM, and so higher readings there are not alarming to me. 
  • What strikes me as odd is the differences in the morning fasting glucose -say 5AM to 10AM – varies between 66 mg/dl to 120 mg/dl…The mean is still around 100 mg/dl (which is not great), but I’m surprised about the high variability.
  • Since I do intermittent fasting (lunch is my first meal) I had generally thought that my morning glucose would be lower. 
  • There is a missing block on May 2nd as I switched the old sensor to the new one – as you have to do that every 10 days. The most painful thing was tearing the Levels patch off my hairy arms 🙂

All in all I’m very happy to have all this data from the CGM/Levels to explore, giving a lot of actionable intelligence – so I will try some life-style, diet modifications soon.

Generative Agents: Five Bold Examples of AI Revolutionizing Product Development

Image created with Canva, no generative agent used here :-)
Image created with Canva, no generative agent used here 🙂

(first published on Linkedin)

As we are seeing ChatGPT become more widely used, companies of all sizes must ask themselves how do they adapt their products and their competitive strategies in this new world? 

To recap – ChatGPT by OpenAI is a generative agent that is designed specifically for generating text by predicting what comes next in a given sequence. As a generative agent, ChatGPT can create new content, write code, carry out conversations, and even provide assistance in various tasks, depending on the context and the data it has been trained on.

Generative agents are poised to redefine product development, offering unmatched creativity, efficiency, and innovation. Here are five compelling examples of how these AI-powered systems are transforming the way we create and consume products:

Personalized Products: AI-Driven Sneaker Revolution

1.Generative agents will enable brands like Nike or Adidas to analyze user preferences and create customized sneaker designs tailored to individual tastes. These one-of-a-kind shoes will foster deep connections between consumers and brands.

Rapid Prototyping: Hyper-Iterative Rocket Design

2. Companies like SpaceX can leverage generative agents to rapidly generate multiple rocket designs, streamlining the prototyping process, and pulling our sci-fi dreams closer to the present.

Sustainable Design: Eco-Friendly Furniture Evolution

3. Generative agents can help IKEA analyze material data and environmental impact, creating innovative designs that minimize waste and promote sustainability. These eco-friendly products will resonate with environmentally conscious consumers, bolstering IKEA’s brand reputation.

Democratization of Design: Small Business AI Explosion

4. As AI systems become more accessible, Etsy’s small business owners will harness the power of generative agents to create professional, high-quality products. This democratization will unleash a wave of innovation and competition, transforming the online marketplace.

Metaverse Product Sales: The Ultimate Autonomous Agent Experience

5. Generative agents will bring the metaverse to life, creating autonomous agents that interact believably with users for product sales. Imagine the next generation of virtual real estate, where AI-driven real estate agents engage with potential buyers, personalizing the experience and providing valuable feedback to sellers.

Generative agents are set to transform the product development landscape with their AI-powered capabilities. Do you agree, disagree? Pls let me know in the comments.