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Informationweek
IT Automation: Still Room for Improvement in Some Spots
We ve come a long way with autonomous computing. Here s a look at what s working in production, and areas that are still considered a work in progress.
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IT operations was an early focus area for autonomous computing, artificial intelligence, and automation. Now that we have some history, which automation and AI techniques are working in IT, and which have yet to make an impact?
Here are four areas of automation that work well in production now:
1. Network automation. Automation tools have enabled IT to automate network provisioning along with network health monitoring for performance, maintenance, and diagnostics.
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Informationweek
What s New in IT Security?
With new security threats continuously emerging, what can organizations do to harden their security and to better protect themselves from network intrusions and avoid damage?
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This past December, news broke about a highly sophisticated cyberattack, allegedly perpetrated by Russian hacker group APT29. The attack targeted the federal departments of State, Defense, Homeland Security and Commerce. The attack apparently penetrated agency networks through malware that was embedded in a software release from SolarWinds, which provides network management solutions.
But that’s not all.
Last month, security firm Malwarebytes reported that it had been targeted by the same attacker that compromised SolarWind’s software, only this time the attack was attempted when the attacker gained access to company emails that exploited flaws in Microsoft cloud services.
Informationweek
How to Explain AI, ML, and NLP to Business Leaders in Plain Language
Your ability to explain artificial intelligence and its components to business leaders could mean the difference between acceptance and resistance. Here s how to do it.
When I visit with non-IT corporate executives and ask them about artificial intelligence (AI), machine learning (ML) and natural language processing (NLP), they tell me that they have initiatives underway. But they don t exactly know what AI, ML, and NLP are.
Trying to explain what AI, ML, and NLP are, how they work, and how they deliver results for the business isn t easy. Yet, all of these technologies have prominent roles in analytics as IT deploys them. It s incumbent upon CIOs and IT leaders to find ways to break down these technologies and their business deliverables in plain language for non-technical stakeholders.