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Thoughts on AI, content, product, and whatever I'm learning.
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5 Productivity Tools I Absolutely Love in 2024
Five favorite productivity tools for 2024, from the Groove coworking community to ChatGPT, Claude, digital planners, Google Calendar, and Finch.
21 Jul 2024
A Simplified Guide to AI Governance in Africa
An accessible overview of how African countries govern AI through policies and regulations, with key players, core issues, and a Rwanda case study.
21 Jul 2024
Building a Simple Web Server in Go
A beginner-friendly Go tutorial that builds a small web server handling HTTP requests and returning JSON, with greet and penguin endpoints.
1 Jul 2024
Responsible AI Practices for Product Managers
As AI has become an integral part of our lives, shaping almost everything from our online experiences, critical decision-making processes and handling day-to-day interactions.As product managers, it is our responsibility to ensure that the AI systems we develop adhere to ethical guidelines and promote responsible practices.By implementing these principles, we can create products that utilize AI to have a positive impact on users and society at large.In this article, we will explore some essentia
20 Jul 2023
Inclusivity, Values to Shape Future Scenarios When AI Outwits Humans
Only if humanity can devise AI systems that are inclusive and align with its shared values may it avert the AI apocalypse.
27 Jun 2023
Sourcing Data for AI Model Building: Exploring Methods and Considerations
In the field of AI product management, the availability and quality of data play a crucial role in building successful models.The process of sourcing data involves considering various factors such as open and closed sources, outsourcing data collection and annotation, in-house efforts, and alternative methods.In this article, we will explore these different approaches, their pros and cons, and determine which methods work best based on specific situations. Let’s begin:1. Open SourcesOpen sources
19 Jun 2023
Challenges and Considerations for AI Product Managers
With great power comes great responsibility. As product managers embark on the journey of implementing machine learning systems, they must navigate various ethical and privacy concerns, ensure data quality and mitigate bias, integrate with existing systems, and prioritize continuous learning and improvement. Furthermore, effective collaboration with the data and machine learning team is crucial for success.In this article, we will delve into these key considerations and explore how product manag
8 Jun 2023
Key Steps in Implementing Machine Learning Projects
Successful implementation of machine learning projects requires careful planning and execution.This article will outline the key steps in implementing machine learning projects and provide questions to help product managers navigate the processes effectively.Problem Definition and Goal SettingThe first step in implementing a machine learning project is to clearly define the business problem that needs to be addressed and establish specific goals for the ML project.Product managers must have a de
7 Jun 2023
The Basics of Machine Learning for Product Managers
Inthis article, we will delve into the fundamental concepts of artificial intelligence, machine learning and explore their significance for product managers.Let’s begin.What is Artificial Intelligence (AI)?Artificial Intelligence (AI) refers to developing computer systems that can perform tasks that typically require human intelligence.It encompasses a wide range of technologies, algorithms, and approaches to enable machines to mimic cognitive functions like learning, problem-solving, perception
7 Jun 2023
Exploring Prototyping Methods for AI Products: From Wireframes to Functional Models
Prototyping is crucial in developing AI products, allowing for iterative testing, refining, and gathering user feedback.When it comes to AI, prototyping involves not only the user interface but also the underlying intelligence.In this article, we will delve into various prototyping methods specifically tailored for AI products. From low-fidelity wireframes to functional models, these techniques enable rapid experimentation, validation, and refinement of AI-driven ideas.Let’s take a look:Wirefram
5 Jun 2023