Paxton's Profile

IBM is kind of the old guard in the AI space with the high profile jeopardy application. They haven’t seemed to find much success in broadening the application area for the technology as one might’ve thought. At least in the healthcare space, the Watson-MD Anderson partnership ended in complete disaster. It seems like it is often hard to tell when there is a legitimate usage for these general AI solutions vs when it is just a marketing ploy.

Great topic. John Deere is well known to making efforts in the AI space through its acquisition of Blue River. Agriculture is predicted to be one of the largest sectors of the economy to be disrupted with machine learning and autonomous vehicles in the future. There are a lot of startups in the space and it will be interesting to see how consolidation unfolds.

Helpful information here. Predictive analytics for asset management is a large need and Uptake has certainly become a model effort in the application of ai to a big problem. I wonder what other applications they will expand to as time goes on!

John Deere has been a pioneer in the integration of data sources into its product offering. The Blue River acquisition promises to usher in a new wave of autonomous tractors and agricultural equipment. This seems absolutely necessary if we are going to continue to feed the growing human population. Great work going into the detail of the types of data that farmers can expect to leverage here. It’s a cool story to follow in parallel to the Monsanto blog post!

As controversial as this company is and the products it produces are, it is a very cool application of big data. Personally, increased usage of technology in growing food seems like an unavoidable trajectory if we are going to continue to feed the world’s growing populations. I also like how they integrate so many different types of data into the Monsanto offering.

Helpful summary. We will see whether or not the Brex data driven approach results in lower default rates. As Keagan suggested it may be subject to the usual pitfalls of SV hype. Especially given its primary customer base being startups, it could be very susceptible to a market downturn.

its remarkable how few people in generations above gen-z have heard about the app. It will be interesting to watch how things unfold. Will it grow into another Facebook? Or decline like snapchat!

Seems like an important service they are providing customers in a traditionally very opaque industry. Thank you for providing such a robust analysis.

Love Kaggle and look forward to seeing how the platform evolves. Google doesn’t always do things purely altruistically so I wonder what their plan is for integrating the models that the platform produces in Alphabet offerings.

Important topic and great perspective. I’m shocked at how effective simple cycle planning can be at contraception. Once more shows the power of using ML on the right data. Really cool that it also can be used for improving odds of pregnancy as well. Thanks for sharing!

We’ve seen several car transfer companies like this one the past (Carmax, Shift, etc.) it’ll be fun to watch the market shake out. Seems like this company is growing rapidly but at a decent cost in terms of losses.

Great blog post, thank you for sharing. It will be interesting to see how they expand into other product offerings from the background check space. They will have a ton of interesting data to leverage here!