Cyber criminals are constantly seeking new ways to perpetrate a breach but thanks to artificial intelligence (AI) and its subset machine learning, it's becoming possible to fight off these attacks automatically. The secret is in machine learning's ability to monitor network traffic and learn what's normal within a system, using this information to flag up any suspicious activity. As the technology's name suggests, it's able to use the vast amounts of security data collected by businesses every day to become more effective over time. At the moment, when the machine spots an anomaly, it sends an alert to a human – usually a security analyst – to decide if an action needs to be taken. But some machine learning systems are already able to respond themselves, by restricting access for certain users, for example.

Cyber criminals are constantly seeking new ways to perpetrate a breach but thanks to artificial intelligence (AI) and its subset machine learning, it's becoming possible to fight off these attacks automatically. The secret is in machine learning's ability to monitor network traffic and learn what's normal within a system, using this information to flag up any suspicious activity. As the technology's name suggests, it's able to use the vast amounts of security data collected by businesses every day to become more effective over time. At the moment, when the machine spots an anomaly, it sends an alert to a human – usually a security analyst – to decide if an action needs to be taken. But some machine learning systems are already able to respond themselves, by restricting access for certain users, for example.

Cyber criminals are constantly seeking new ways to perpetrate a breach but thanks to artificial intelligence (AI) and its subset machine learning, it's becoming possible to fight off these attacks automatically. The secret is in machine learning's ability to monitor network traffic and learn what's normal within a system, using this information to flag up any suspicious activity. As the technology's name suggests, it's able to use the vast amounts of security data collected by businesses every day to become more effective over time. At the moment, when the machine spots an anomaly, it sends an alert to a human – usually a security analyst – to decide if an action needs to be taken. But some machine learning systems are already able to respond themselves, by restricting access for certain users, for example.

Well, Half-Life 3 is finally here. Or is it Half-Life 2: Episode 3? Hard to say, but in any case, it arrived exactly as expected: A whispered surprise, traveling in the wee hours of the night by word of mouth alone. Instead, longtime Valve writer Marc Laidlaw (ex-Valve writer as of last year) seems to have posted the hypothetical plot to a never-going-to-be-made Episode 3 on his blog. It's thinly disguised as "Epistle 3," and the character names and genders have been tweaked too. This forms the basis of Laidlaw's current deflection, which is that it's "a genderswapped snapshot of a dream I had many years ago." He also refers to it as "fanfic."

Marc Laidlaw's departure from Valve last year was a shock. The author was responsible for single-handedly writing both Half-Life and Half-Life 2, and worked as the story lead on the latter's two episodic sequels. Chet Faliszek and Erik Wolpaw, co-writers on Half-Life 2: Episode One and Episode Two, stuck around however, meaning some of the series' writing talent still remained at Valve. In February of this year, Wolpaw departed Valve to work on Psychonauts 2, and today GamesIndustry.biz reports that Faliszek has also left the company. The pair have a long history together: they ran the highly influential gaming site Old Man Murray through the late '90s and early '00s, before both joining Valve.