Machine learning is a branch of artificial intelligence (AI) that refers to technologies that allow computers to learn and adapt through understanding. It rivals human cognition - i.e. learning based on experience and patterns, rather than by inference (cause and effect). Today, deep learning progressions in machine learning allow machines to teach themselves how to build models for pattern recognition (rather than relying on humans to build them).
The last five years have really seen a rise in AI and ML technologies for enterprises. Most of which can be attributed to advancements in computing power and the evolution of paradigms like distributed computing, big data and cloud computing.
Technology titans like Google (in its search engine), Amazon (with its product recommendations) and Facebook (with its news feed) pioneered early commercial applications of ML. These businesses managed to build a veritable treasure trove of valuable behavioral data from hundreds of millions of users. In order to efficiently collect, cleanse, organize and analyze their consumer data, these companies built scalable big data frameworks and applications then open sourced them to the world. By opening access to these big data frameworks, they better fast, scaled quickly, and allowed businesses to develop more value from their data.
Organizations are already beginning to use AI to bolster cybersecurity and offer more protections against sophisticated hackers. AI helps by automating complex processes for detecting attacks and reacting to breaches. These applications are becoming more and more sophisticated as AI is deployed for security.
Data deception technology products can automatically detect, analyze, and defend against advanced attacks by proactively detecting and tricking attackers. So, when you combine very smart security personnel with adaptive technology that continues to change and become smarter over time, this provides a competitive edge to defenders that have primarily been absent from most cybersecurity technologies to date.
On the other hand, AI can open exposures as well, particularly when it depends on interfaces within and across organizations that inadvertently create opportunities for access by "bad actors" or disreputable agents. Attackers are beginning to deploy AI too, enabling it to have the ability to make decisions that benefit attackers. Meaning they will slowly develop automated hacks that are able to study and learn about the systems they target, and identify vulnerabilities, on the fly.