I took my first attempt trying out the blog editing on both dev.to and on Medium with my thoughts around advocacy, Developer Relations, and being kind!
xConnect Upgrade to 9.2 – Where did the web request handlers go?
Recently, I needed to update my xConnect Tutorial from 9.0 to 9.2 so I could start looking at the new data purge API (more on that another day). I figured it should be an easy enough upgrade, my tutorial wasn’t doing anything complicated. Just some basic Create Contact or Register Interaction stuff.
So, I did the usual:
- Update Target Framework from 4.6.2 to 4.7.2
- Change all the NuGet references to the 9.2 packages
- Recompile
- Squint at all the red compile errors from doing an upgrade…
Continue reading “xConnect Upgrade to 9.2 – Where did the web request handlers go?”
Are you ready for the MongoDB 3.4 EOL?
If you are running Sitecore version 8.2.x, you are running MongoDB 3.4. Unfortunately, that also means you are impacted by the announcement by MongoDB that version 3.4 will reach end-of-life in January 2020.
You have some options on how you want to fix this and it sort of depends on how much tolerance your organization has for running production systems that don’t have commercial support from the vendor.
Over on the Sitecore Technical Marketing blog, I outlined a variety of options and provided a few FAQ answers:
Soul in the Machine – Can we avoid the Google Duplex outrage in Conversational AI development?
This is Part 5 in the Soul in the Machine series.
In the Soul in the Machine series, I will be delving into our collective responsibility to ensure that computing systems are treating users fairly and responsibly. Specifically, I will be raising the ethical questions around current trends such as data privacy regulations and machine learning capabilities.
Right now, in Part 5, we are going to look at some reactions to conversational AI technologies, Responsible AI, and the line between CAN and SHOULD.
Should we build this?
In a previous article, I highlighted the need for teams to stop and ask if they SHOULD be doing something. Let us take an example from Google Duplex.
In this demo from Google, the caller was the AI, but honestly, it could easily have been the restaurant answering with an AI. There is another example of Google Duplex where the assistant books a hairdresser appointment, and others where it can handle interruptions and resume the conversation.
Tiny tips for speakers
With our Sitecore Virtual Developer Day just wrapped, and more speaking events around the corner, I was thinking back to some tips I provided for speakers right before Sitecore Symposium 2018.
Here they are, in one place, for you to find if you ever need them!
Preparing for AI-driven customer experiences
Digital marketers today are caught in the middle of a huge digital transition.
Behind them lie the old, slow, and manual methods of creating content, connecting with customers, tracking engagement, and measuring the results.
Ahead of them is the promise of the brave new intelligence-enabled world, teeming with possibilities—task automation, massive-scale analytics, and real-time, data-driven decision making powered by Artificial Intelligence, Machine Learning, and Deep Learning solutions.
For the most part, these promises have been made in good faith. Connecting clean, structured, and tagged data with powerful machine learning algorithms is an exciting prospect brimming with interesting use cases like:
- Automated content tagging
- Self-assembling web pages
- Dynamic audience discovery
- Predictive scenarios and best next steps
However, for many, this bold new future of seemingly magical efficiencies might be further away than it seems. The industry is currently packed with pundits and vendors getting excited about what might be possible with AI without thinking about the steps needed to get there. While the benefits of becoming an AI-enabled marketer are clear, the journey a marketer and their team needs to take is still hazy.
Soul in the Machine – Combatting Unconscious Bias
This is Part 4 in the Soul in the Machine series.
In the Soul in the Machine series, I will be delving into our collective responsibility to ensure that computing systems are treating users fairly and responsibly. Specifically, I will be raising the ethical questions around current trends such as data privacy regulations and machine learning capabilities.
Right now, in Part 4, we are going to look at building a diverse team capable of implementing ethical AI and ML solutions. How do we ensure that the culture of integrity we are working so hard to support leads to fair results in our machine learning? How can we be conscious about battling unconscious bias in the solutions we develop?
Two heads are better than one
Building up the culture of integrity in an organization allows us to start asking questions about what we’re doing, and how we’re doing it, but a critical step is building a team that is capable of seeing WHEN these questions need to be asked.
Continue reading “Soul in the Machine – Combatting Unconscious Bias”
