Machine Learning project: Agile or Waterfall approach?

This question is so easy: agile approach. Why? Because it recognizes that the construction of the solution requires different loops. Reason 1: ML models change overtime Machine Learning projects are supported on ML models, and models change overtime. Why do a model change overtime? A model change overtime because the data used to train the … Read more

Deep learning evolution

Evolution happens in different waves of diffusion and deep learning is not an exception. I add this time-line to remind how it evolved, and how the co-evolution of technology has been necessary to enable to end the “neural winter” lived during almost 20 years.

AWS Honeycode

Honeycode is the low-code service in beta version being implemented by Amazon. Things I have noticed: The features are very basic, the templates available basic too. The customers using it are not top tier customers. It’s beta. The number of vacancies opened in amazon.jobs is low and last role available is from April 2022. The … Read more

Print on Demand Services

Since 2015 – 2018 there are different print on demand services available around the world that enable designers to produce and commercialize their products in different geographic areas. The main products sold on this way are shirts, pullover hoddies, zip hoddies and other type of textile products. There are other vendors that offer mugs, caps, … Read more

Making decisions patterns

This is a card for my poor memory about practical ways to make decisions. The Eisenhower Decision Matrix The classic: Making decisions as in Amazon This is not an official way to make decisions in Amazon, but I found it in “Working Backwards” book and I find it useful. Mindset to adopt depending on the … Read more

Amazon, press release process

This is an example of the gameplay press release process, focused on how Amazon does it (basic explanation). During late 2020 we saw in many electronic press that Amazon was launching an online pharmacy and that it has discounts for prime users. For example this one: The reaction? the first reaction has been that companies … Read more

Amazon, sensing engines (ILC: innovation – leverage – commoditize)

This is an example of the gameplay sensing engines, focused on how Amazon does it (basic explanation). ILC comes from “innovation – leverage – commoditize”, Let others to innovate. Use metadata to identify patterns (leverage). Commoditize the “pre-existing act”. This is the map: The summary about the “Amazon, sensing engines” map: Point 1: shaving machine … Read more

Amazon strategy

Background and purpose This post tries to translate some of the elements of Amazon’s strategy into Wardley Map syllabus. The strategy cycle This is the strategy cycle proposed by Simon Wardley, let’s see how Amazon works its own cycles. 1.- Purpose (who we are) Amazon is guided by four principles: Amazon strives to be Earth’s … Read more

how will cars be refueled by 2032?

Background and purpose The raise of electric vehicles (EVs) is something we all have clear, I think that there is not question about that. Cities and roads are full of gas stations, and they are part of the environment (for good and bad reasons). Will they survive to this shift to EVs? How they will … Read more

AWS Sagemaker

These are some notes about the basis of Sagemaker Sagemaker services SageMaker Neo optimizes the trained model and compiles it into an executable. Taking the target hardware where the model will be run as input; the compiler uses a ML model to apply performance optimizations on your model. Ground truth makes easy to label data. … Read more