Core algorithms might only take up a few times of code and a few minutes to do so. But, the rest of the program may get messy quickly. In this Banana Byte, we tackle the question of when its worth it to invest your time in code and the trade-offs between developing something accurate vs. something quick.
The field of data science is wrought with many unsolved debates. Is data science nothing more than fancy statistics? What performs better: R or Python? Most crucially, do you need to be a great coder to be a great data scientist? In this episode, Chris and Triveni take these burning questions to the debate stage.
Typically when the average person thinks of bots, it rings with a negative connotation. Bots are immediately associated with spam and fake personas. But, is there a positive flip side to this coin? Listen to our 15-minute Banana Byte to find out.
In this episode, Chris and Triveni take a deeper look at CAPTCHA, a completely automated system that has become a nearly inevitable part of a user's online experience. How did complete automation of this system give rise to complications and exclusion of a smaller subset of the online community? How do you distinguish between pure artificial intelligence and artificial intelligence that's being powered by a human? Finally, what ethical concerns should we be taking into consideration?
In this episode, our Banana Data hosts discuss the many implications that can arise from misinterpreted data. What criteria needs to be established for valid conclusions from data and how can we interpret uncertainty?
In this episode, our hosts Chris and Triveni walk us through commonly overlooked implications of what it means to dole out personal data. What are the downstream effects of sharing your data? What are you benefitting and losing from opting out of data collection?
When people generally think of AI they think in futuristic terms defined by movies like The Terminator. However AI, at least at this moment, is nowhere near Skynet, a fictional artificial neural network-based conscious group mind and artificial general superintelligence system that serves as the antagonist of The Terminator franchise. Instead of worrying about Skynet, maybe we should worry about this bear wielding nunchucks, which seems like more of an immediate problem.
We're talking about one of the most frequently asked questions by people looking to jump start their Data Science career: do you need to have every mathematical formula memorized? What are the true prerequisites you need to be prepared in this field? Tune in and we’ll get you up to speed.
This episode, Chris and Triveni take a look at the most common mistakes in AI, and the misconceptions that plague most data scientists as a result. We'll explore how perceptions of data quality, data quantity, and accuracy can impact data science in practice, and what steps you can take to avoid these pitfalls.
For our season 4 kickoff, we’re taking a look at uses of AI that aren’t so black and white. When it comes to deepfakes, filtering, and predictive policing - when do the risks outweigh the benefits? Are these use-cases inherently bad, or is there a way to combat underlying unfairness? We're also welcoming our new host, Christopher Peter Makris to the show in his inaugural episode!