The Frontier of AI Consciousness As we reflect on the past twelve months, we can’t help but be captivated by the potential of AI. But as we consider what LLMs can do, we should also be mindful of their limitations. We’re still at the start of this new era, where […]
Everyone is talking about Generative AI (Gen AI) and the hype is deafening. Almost every media outlet, technology company and influencer is trying to stake a claim in this burgeoning market. So, in an effort to cut through the noise and provide some clear, straightforward advice, here is a cheat […]
The Power of AI in Personalizing Financial Education The financial services industry is evolving rapidly, with AI taking center stage in facilitating customer-centric digital transformations. A key application of AI in this space is the personalization of financial wellness content, which aims to increase accessibility and relevance to customers with […]
Intro Efficient portfolio allocation is a fundamental aspect of investment management, as it is vital to diversify assets to maximize risk-adjusted returns. Financial institutions encounter numerous challenges in portfolio management, including market volatility, economic uncertainty, and the need for rapid adaptation to shifting market conditions. One solution to these challenges […]
It’s Not What A Book Says, It’s How It Makes You Feel “Boring, but a real problem to solve” Article after winning FutureBook BookTech Company of the year (thanks for the backhanded comment!) If you buy a TV, you’re interested in the viewing experience, the depth of color, the fluidity […]
Keywords / Deconstructing Amazon Search / Through The Dark Web After indulging in an attempt to find the holy grail of publishing, I pivoted to applying data science to solving a less lofty, but real need in publishing: keywords. The simple pitch was: There was a clear industry need to […]
The Holy Grail Of Publishing: Bestseller Prediction After validating that I could successfully classify novels into industry standard book categories (BISAC), I turned my focus back to the prize of predicting the next bestseller. I tackled this problem along two lines: Slush Filter In publishing, the flood of unsolicited manuscripts […]
I initially founded Kadaxis as a vehicle to experiment and validate hypotheses I had on applying machine learning models to book data. The goal was to see what models worked, then to wrap as a product and bring it to market (a little in reverse but I was intentional about […]
This post originally appeared on the Kadaxis blog. So you’ve found the perfect keywords for a book, how do you know if they’re effective? Off-page keywords aren’t visible to potential customers, so assessing whether they’ll work or not takes a completely different approach to assessing visible metadata (title, description, etc.) about a […]
There’s been much recent conjecture on whether book sales can be predicted by text analysis alone. My company, Kadaxis, has dedicated the past few years to machine learning research and product development for the publishing industry. In our early days, we set out to build an algorithm to predict bestsellers, […]
