Mensing.AI


Learnings & Musings on AI, ML, Data Science & Python

AI Could Create A Defense Dark Horse 🐎

A lot of focus is placed on the US-China AI space race (guilty), but the nature of AI could make for a surprise victor. Or at least a leveling of the playing field. 🚜 There is a risk that the United States, like many leading powers in the past, could take an excessively cautious approach to the adoption of AI … Read More


When People Do Bad Things With Algorithms 😈

There is a lot of concern surrounding decisions made by algorithms and bias baked into said systems, but that is far from the only concern. These podcast episodes do a tremendous job illustrating what happens when people use neutral data for the wrong things. When the reason for the data becomes perverted. At the end of the day AI systems … Read More


The Economist Opens Their Data πŸ‘

The Economist has announced they will be open sourcing their data, starting with the Big Mac Index. πŸ” It also sounds like they’ll be providing a glimpse into their process via Jupyter notebooks, which is really cool. πŸ““ Src: The Economist


Will Robots Understand Value? πŸ’Ή

A while back I wrote about how I didn’t think robots would become the new consumers in capitalism. Turns out I’m not the only one.Β πŸ‘¬ This piece scratches my economics itch in a lot of ways, but I think the heart of it is the fact that we typically believe the economy/market/capitalism operates like a rational machine and not an … Read More


China vs. the US: Round ? πŸ€·β€β™€οΈ

In the continuing narrative that is the space race between the US and China in the realm of AI, we get an entry on what the US can learn from Chine. πŸ‡ΊπŸ‡ΈπŸ‡¨πŸ‡³ It boils down to the two countries excelling at the usual, the US creates visionary ideas and China puts them into production. China has a massive treasure trove … Read More


China’s Social Submission, er…Scoring System

There is a lot of focus on the China vs. USA space race happening in AI right now (at least in my world there is, I’m very interested in the topic). Most of it revolves around spending, governmental support, talent, etc. But maybe the most important aspect is what the implications of either country winning would be, if there truly … Read More


When Unbiased Machines Meet Biased Humans πŸ₯Š

I’m worried about the implications of transferring our biases to machines and then turning up the speed dial to 11. But I hadn’t thought about how we biased mortals might react to truly unbiased decision making. 🀯 So while creating unbiased systems is important, it doesn’t guarantee success in the messy real world once decisions are made. Ultimately debiasing systems … Read More


A Brief History of AI: A Timeline πŸ—“

1943: groundwork for artificial neural networks laid in a paper by Warren Sturgis McCulloch and Walter Pitts, “A Logical Calculus of the Ideas Immanent in Nervous Activity“. πŸ“ƒ [1] 1950: Alan Turing publishes the Computing Machinery and Intelligent paper which, amongst other things, establishes the Turing Test πŸ“ [6] 1951: Marvin Minsky and Dean Edmonds design the first neural net … Read More


Lazy Faire πŸ‡ΊπŸ‡ΈπŸ‡¨πŸ‡³

At the US government’s current rate of uninvolvement in the AI sector, China will overtake it in its quest for AI overlord status by the end of the year. At least when it comes to spending, the rest might not be far behind though. πŸ’° One of the recommendations from a subcommittee is to expedite the approval of the OPEN … Read More


That’s Instructor AI, Cadet

The Air Force is embracing AI to mix up their training process, and could be inventing the future of all education while they’re at it. πŸŽ“ The overall objective is to move away from an β€œindustrial age” training model with pre-set timetables and instruction plans to one that adapts to each airman’s learning pace. Hmmmmm….what else follows an industrial model? … Read More