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AI in IT tools promises better, faster, stronger ops
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Deep machine learning lets AI think more, respond smarter
Basic machine-learning parameters require a preprogrammed, finite set of rules -- which is useful, but inefficient. With the capacity to learn those rules on its own, AI in IT operations and other fields yields better responses to input, without supervision. Read Now
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How deeply AI learns affects how many resources it needs
Hardware clusters grew frail as data scientists at Google and Facebook piled layer on layer of learning mechanisms into their AI systems. So, how do these industry giants keep their AI -- and their hardware -- kicking? Read Now
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ServiceNow improves product offerings with AI in IT tools
ITSM provider ServiceNow acquired machine-learning firm DxContinuum and strengthened a partnership with IBM to add AI capabilities to its bevy of products. Read Now
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Machine learning improves IT security -- but only with the right data
Feeding large volumes of data to AI-directed security tools is the ideal recipe for improved threat detection -- but only when it's the right datasets. Read Now
Editor's note
Artificial intelligence has spread into business applications and home use tools -- Siri and Alexa can confirm. Within the enterprise, machine learning and AI in IT operations have changed the playing field. Tools such as Hadoop put machine learning into the hands of the average engineer, allowing more organizations to manipulate more data. These tools lead to springboard improvements in processing speed, analytics, insights or security, and the organizations that use these AI-enabled products benefit from increased staff productivity.
Science fiction has prepared the world for autonomous, opinionated robots, but that level of AI is still not even on the horizon. AI in IT operations will cultivate new jobs and give organizations better analytics and smarter security for IT infrastructure and its data -- and probably help run the servers that host the next science fiction movie predicting the downfall of humanity.
1Not every organization can play
AI-powered tools in IT ops can save systems administrators and security specialists from countless hours of rote work. With smart software covering the bases, ops pros can spend their time and energy on the tasks that require nuanced judgment. And because AI tools process volumes of data more efficiently than humans, those ops pros can make better decisions, yielding better results.
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Organizations that look to machine learning need data volume now
Big data seems to surround IT, weaving through every category of products like dog hair in a blanket. Organizations that don't have access to big data now risk finding themselves without enough input for machine learning to process later. Read Now
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The intelligence is artificial -- the productivity improvement is real
AI started out in business apps, but there are clear signs that it will make a splash in IT ops productivity, as evidenced in IPcenter from IPsoft and other tools. Read Now
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Automate IT processes to significantly improve business value
The more of IT operations that pros can automate, the more productive the department gets and the more interesting the job can be. Eliminate the tedious manual processes from day-to-day activity with smart automation tools and find better things to do. Read Now
2Language processing is natural
Data scientists have taught computers how to process natural language to learn what people are saying. If you, a human, need help understanding these smart computers, here is a handy glossary of terms for AI in IT operations.
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Definition
AI (artificial intelligence)
AI (artificial intelligence) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction. Read Now
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Definition
Big data
Big data is a combination of structured, semistructured and unstructured data collected by organizations that can be mined for information and used in machine learning projects, predictive modeling and other advanced analytics applications. Read Now
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Definition
big data analytics
Big data analytics is the often complex process of examining large and varied data sets, or big data, to uncover information -- such as hidden patterns, unknown correlations, market trends and customer preferences -- that can help organizations make informed business decisions. Read Now
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Definition
data analytics (DA)
Data analytics (DA) is the science of examining raw data with the purpose of drawing conclusions about that information. Read Now
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Definition
data science
Data science is the study of where information comes from, what it represents and how it can be turned into a valuable resource in the creation of business and IT strategies. Read Now
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Definition
deep learning
Deep learning is a type of machine learning (ML) and artificial intelligence (AI) that imitates the way humans gain certain types of knowledge. At its simplest, deep learning can be thought of as a way to automate predictive analytics. Read Now
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Definition
IT automation
IT automation is the use of instructions to create a repeated process that replaces an IT professional's manual work in data centers and cloud deployments. Read Now
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Definition
machine learning (ML)
Machine learning (ML) is a category of algorithm that allows software applications to become more accurate in predicting outcomes without being explicitly programmed. Read Now
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Definition
robotic process automation (RPA)
Robotic process automation (RPA) is the use of software with artificial intelligence (AI) and machine learning capabilities to handle high-volume, repeatable tasks that previously required humans to perform. Read Now
3Don't expect any autonomous robo-admins
Sys admins can anticipate seeing AI in IT operations for the foreseeable future. Improved analytics and processing speed necessitate its use -- and bring up new career options.
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AI, big data, machine-learning trends to watch
More organizations are making use of AI and machine learning in a multitude of ways, ranging from security to log management to resource management. But AI in IT has a long road ahead. Read Now
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Redesign IT processes before adding automation, AI
Many traditional IT processes are inefficient and time-consuming. Automating those processes requires a redesign for simplicity and efficiency first. And any IT ops pro working with automation needs a new itinerary. Read Now
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The world needs more data scientists. Interested?
Growing use of AI, machine learning and big data necessitates a swath of data scientists. IT professionals already working with big data -- and enjoying it -- should consider a career change. Read Now
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AI might be for real this time, but so what?
The creation of AI products is beyond the purview of IT ops, but knowing how a tool works will inform how you set up and use it. AI tailored for specific tasks will play an important role in IT operations, but expecting AI to do everything only stultifies ops agendas. Read Now