Published November 16, 2021 by Adam Kempler
The November 2021 GovWebworks AI Lab newsletter covers AI vs ML differences, salary stats for AI-related positions, new language translation APIs, and lessons from Zillow's machine learning forecasting failures.
Welcome to the November AI Newsletter from the GovWebworks AI Lab. The following articles touch on important topics in the industry, including:
We hope you find this information as interesting as we do. If so, feel free to share with your colleagues. Sign up for our newsletters in the box at the bottom of the page. Or email us at ai@govwebworks.com to talk about using AI to optimize your organization’s digital goals.
#1: AI vs ML: What’s the difference?
Key takeaway: A quick and non-technical introduction to the difference between AI and ML (Machine Learning).
Reviewed by Adam Kempler
At this point you’ve probably heard the terms Artificial Intelligence and Machine Learning thrown around quite a bit, but if you aren’t sure what the difference is between the two, then this quick overview (opens in a new tab) can give you a nice introduction to the two terms.
If you want a little more detail, this article provides a bit more background:
AI vs Machine Learning vs Deep Learning Differences (opens in a new tab)
#2: Salary stats for data scientists, machine learning, and other AI-related positions
Key takeaway: An easy-to-skim resource for identifying salary ranges for AI related job positions.
Reviewed by Adam Kempler
As more government organizations look to fill data scientist, machine learning, and other AI positions, this recent salary data sheet (opens in a new tab) can be helpful in understanding what the current salary trends are in those fields.
Learn more about the data sheet here:
Insights: A first update on our salary survey
#3: New language translation APIs can help your organization meet the needs of diverse audiences
Key takeaway: Updated APIs can translate your content on the fly or in batches depending on your needs.
Reviewed by Adam Kempler
Enhanced APIs from Google and AWS can automate the translation of your content into 100+ languages. These services can be integrated with CMS tools for on-the-fly translation of predefined fields and content types, as well as in batches for uploaded documents and migrated content.
These translation services support features like Glossaries (opens in a new tab) that let you define preferred translations for things such as product and department names. Google’s translation service also lets you import previous human-validated translations to improve domain specific automated translations.
Learn about machine translation services from Google and AWS:
Google – New features for translating content globally (opens in a new tab)
AWS – Amazon Translate Features (opens in a new tab)
#4: Difficulties with Machine Learning based forecasting
Key takeaway: Machine Learning models that are driving business models need to be properly vetted.
Reviewed by Adam Kempler
The following article provides an interesting point of view as to what went wrong with Zillow’s Machine Learning based forecasting models that were used to drive their home purchasing business, and ultimately caused them to cut 25% of their staff.
Zillow Just Gave Us A Look At Machine Learning’s Future (opens in a new tab)
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