More and more agencies and brands are relying on machine learning these days to analyze mountains of data and provide insights they can use to better inform advertising campaigns. Using ML, artificial intelligence tools can recognize patterns in data gleaned from existing campaigns to see how ads are impacting customer engagement, purchase intent and conversion rates.
In case you missed it, insurtech — technology developed to improve and transform the insurance industry — is having a bit of a moment. Forrester recently reported record-breaking funding for insurtechs, closing Q3 at $15 billion – more funding than in 2019 and 2020 combined – with more deals anticipated by the end-of-year.
The ‘Internet of Things’ was first coined to help people understand the concept of digital appliances that could communicate with an app or central hub. If you’ve been to CES at any point in the last decade, you could see many examples on the show floor, such as connected weight scales or a connected fridge. But these early examples of ‘connected’ tech felt more gimmicky than useful, and were largely contained to the consumer electronics industry.
Researchers discovered that diagnostic artificial intelligence models used to detect cancer were fooled by cyberattacks that falsify medical images. Diagnostic artificial intelligence (AI) models hold promise in clinical research, but a new study conducted by University of Pittsburgh researchers and published in Nature Communications found that cyberattacks using falsified medical images could fool AI models.
It’s true that AI and machine learning have already provided us with some opportunities to transform entrenched methods of recording and monitoring communications in regulated industries. However, to date, most companies’ injection of AI has been limited and solutions have been piecemeal. But that’s all about to change as the rapid expansion in the applications of AI in compliance is just around the corner.
Recent news about Log4j has enterprises and vendors scrambling for information and answers, including customers of messaging middleware and Integration Infrastructure Management (i2M) products. Nastel Technologies customers will not be exposed to any risks from this vulnerability, but enterprises are encouraged to check with their Cloud and other solution vendors to protect themselves and their data.
Our technology-empowered world continues to evolve at rapid pace, and so do the expectations of customers. The brands that will succeed tomorrow and in the future will be those that keep up with that change. While the vast majority of companies have transformation initiatives, in my digital transformation consulting work, I have noticed four common misconceptions about digital transformation that have the potential to derail even the most well funded efforts.
It seems that every few weeks, we are alerted to a new significant security issue within one of the plethoras of code elements that are widely used. The same pundits discuss the same range of concerns with open-sourced code each time. The list of “usual suspects” is long, and I know I could add at least 20 additional “reasons” to this list without thinking about it too hard. I’m not sure that open-sourced code is riskier than proprietary developed code. There I said it.
The Internet of Things (IoT) is a term that describes the increasingly sophisticated ecosystems of online, connected devices we share our world with. The slightly odd name refers to the fact that the first iteration of the internet was simply a network of connected computers. As the internet grew, phones, office equipment like printers and scanners, and industrial machinery were added to the internet.
There’s little doubt that cloud computing is now the absolutely dominant force across enterprise computing. Most companies have switched from buying their own hardware and software to renting both from vendors who host their services in vast anonymous data centers around the globe.
