We talked to several well-known software industry figures working within the artificial intelligence (AI) and machine learning (ML) space, and asked what these trends mean for software developers. We also explored how they are building, training, and deploying AI/ML systems in production.
To help you learn more, we’ve compiled a playlist of five essential AI/ML podcasts that will get you up-to-speed in this emerging field. Listen to all five, or enjoy each 30-minute episode individually. Learn from Grady Booch, the co-creator of UML, Emmanuel Ameisen, head of AI for Insight Data Science, and several more experts.
At InfoQ, our goal is to accelerate the software side of human progress, and by sharing valuable knowledge from domain experts we aim to help you unlock your potential, so that you and your team can “stand on the shoulders of giants” and create better software that ultimately delivers even more value to your customers and to the wider community.
The good news is that the systems engineering things that we know and love in building non-AI systems are going to apply for building AI systems as well.
You don’t have to be fancy or use deep learning, but you can take a lean approach to machine learning.
You don’t find yourself writing a lot of for loops, or the order in which things need to happen: you simply describe the world and press go, and the probabilistic programming language figures out the implications of that
What you hear about deep learning is that it learns representations - so instead of you having to come up with a collection of rules to describe a road, it can learn it for you.
One of the words for machine learning is to build discriminators - we are asking the machine to make a decision
Go one level further and get ready to implement some of the key takeaways in your teams and jump in front of your competition:
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