What you should know about the future of machines

machine learning, artificial intelligenceBy Mark Wisinger, senior analyst

2017 saw machine learning become the de-facto in-vogue technology, whether the conversation was about data, cybersecurity or even traditional business systems.

In December, Google’s AlphaZero chess engine, utilizing Google’s DeepMind AI, crushed the incumbent chess engine champion, Stockfish. Google’s DeepMind relies heavily on machine learning – the AlphaZero chess engine did not start with any human knowledge, yet was able to learn how to beat Stockfish in 400 hours through machine learning. It’s a clear victory for machine learning – but one that’s easy to simulate. This is a much easier use case than identifying noise from cyber threats or prioritizing and cleaning multiple forms of data.

At immixGroup’s Government IT Sales Summit, we hosted a discussion on artificial intelligence (AI) and machine learning with Ron Gula, president and co-founder of Gula Tech Adventures and former CEO and co-founder of Tenable Networks, Dr. William Vanderlinde, chief scientist at the Intelligence Advanced Research Projects Activity (IARPA) and Rich Friedrich, senior director of cyber security analytics at Micro Focus Government Solutions.

Here are key takeaways to keep in mind when you discuss machine learning and AI with your government customers:

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