CIO
DECEMBER 7, 2023
In fact, our team has been working with generative and conversational AI in complex professional services applications like insurance, banking, and healthcare for the better part of a decade, and we’ve learned some important lessons along the way. Where will the biggest transformation occur first?
CIO
JANUARY 29, 2024
In lieu of integrating and customizing off-the-shelf enterprise applications such as Salesforce or SAP, Power Home Remodeling has constructed its own proprietary NITRO platform used to run and optimize all aspects of the business and customer experience. Back in the day, IT culture was all about the perks.
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TechCrunch
APRIL 20, 2023
For one, the platform taps AI to recognize “malicious intent,” trained on a data set of millions of real-world ransomware events. Following the Colonial Pipeline incident in 2021, Jon Miller and Ryan Smith wondered why, with the widespread adoption of security tools, ransomware was still growing exponentially.
CIO
JUNE 15, 2023
According to Sim, building an ecommerce offering from scratch meant doing things like capturing imagery and writing product descriptions for every product, choosing a suitable approach to order fulfilment, and training in-store staff to do things they’d never done before. This isn’t to say the execution process was simple, however.
Altexsoft
SEPTEMBER 7, 2021
Insurance companies find it difficult to attract new customers and retain them, especially when almost every insurer offers the same service or product. It’s also challenging since insurance is a low-touch industry, and insurers seldomly interact with their customers. The customer loyalty problem in insurance.
Erik Bernhardsson
APRIL 21, 2015
Yes – we can take historical data and train a binary classifier, but it suffers from a lot of issues (such as observation bias, feedback loops, etc). Focusing on a particular niche makes it easier to build something that works off the shelf. Then there’s a ton of startups: PredictionIO ($2.7M funding), BigML ($1.6M
Erik Bernhardsson
APRIL 21, 2015
Yes – we can take historical data and train a binary classifier, but it suffers from a lot of issues (such as observation bias, feedback loops, etc). Focusing on a particular niche makes it easier to build something that works off the shelf. Then there’s a ton of startups: PredictionIO ($2.7M funding), BigML ($1.6M
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