![]() It was fascinating stuff.īasically, in real life most riders were around 300w. I was following a thread where many road cyclists post their real life watts to hold 25mph (40kph). Zwift humans are the slipperiest humans yet created. I also feel the Zwift rider Cda is far too favorable. Pack dynamics that provide more varied race results. It doesn’t matter how we get to the solution. It must be very challenging to consider so much varied input. In other words, the world is not always as simple as we would like it to be.įorbes Technology Council is an invitation-only community for world-class CIOs, CTOs and technology executives.I’m very happy to see this open discussion. ![]() This is important to stress because there is a risk of oversimplifying a situation that is notably complicated. As an extreme example of this, proponents of the flat Earth hypothesis rely on its apparent simplicity over the (irregularly shaped) ellipsoid that represents our planet’s shape according to science-but the concept of a flat Earth is scientifically absurd and not probable at all. It is crucial to verify if the two or more different scenarios being considered are equally convincing and effective, since opting for a simple explanation still requires it to be entirely probable. ![]() It’s important, however, to not let yourself be mistaken by the simplicity of Occam’s razor’s general statement-you wouldn’t want to inflict damaging cuts to the solution. When people can shape the solution, they feel in control and also make it a much better, streamlined tool that ends up being used and appreciated.Īs an organization, you can save money (by not investing in big projects that might fail due to lack of adoption from the get-go) as well as consistently improve the solution over time, based on user’s feedback, leading to a greater ROI. Introduce AI-powered solutions gradually, make sure to provide necessary training, outlining how people will benefit, and, most importantly, give space to provide feedback. Team members may have a negative sentiment toward modern solutions: They interpret AI as the element that will “come and take their jobs.” They have a genuine fear that they are not skilled enough to understand/make use of the latest developments, plus a belief they might be replaced by younger, digital-native generations.Īpplying Occam’s razor to your AI adoption decisions may solve this challenge as well: Start small, start simple and give people time to get used to the solution. Occam’s razor is not only ignored when it comes to investment, but also when introducing AI systems at organizations and getting non-AI professionals on board with using these tools. Further, considering the law of diminishing returns, it might not be worth the time, effort and budget to go for the most complex solution. But it’s important to remember that there is not a one-to-one correlation between investing in new technology and reaping the biggest returns: It all depends on the specific problem at hand.Įven as state-of-the-art technology floods the market, decades-old technologies can often be easier to understand, much more explainable and cheaper to train, offering a more direct route to a solution in line with Occam’s razor. With all the new options on the market, it’s tempting to think that the newest and most illustrious solution will bring the most value to your organization. Largely because of this, the AI industry generally tends to go against the Occam’s razor, preferring the more complex, modern and/or shiny algorithms over the simple ones. Data science technology and algorithms are changing at a rapid pace.
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