Some of your most valuable enterprise data might be sitting around in file cabinets, old hard drives, and legacy devices—but only if it can be found in the first place.

Every enterprise worth their salt keeps backups, and they might superficially resemble archives. But the two forms of storage “are definitely not the same and cannot really serve as one another,” Denis Leconte, VP of technology at archival service Iron Mountain, wrote to IT Brew.

Backups are primarily designed to protect against accidental or malicious data deletion and ensuing disruption in the course of everyday business, Leconte wrote, while “archival timescales are much longer—decades, definitely multi-generational, and this is when the usual technologies run out of longevity.” He added they’re also packaged and curated for individuals who may have “no connection with the technical and cultural norms of the time when the archive was created.”

Unfortunately, businesses often aren’t clear on why or how they should properly curate data for long-term preservation, experts told IT Brew.

Spring cleaning

Leconte wrote that while commonplace data storage solutions are “incredibly well-suited” to business time horizons of up to three to five years, data retained longer than that needs special attention as “pretty much all modern information storage technologies, analog or digital, fail eventually.”

Read the rest here.—TM

Got a question about large language models? Three out of four app developers might say: Ask ChatGPT.

An IBM-sponsored survey, released last week, revealed that less than one-quarter of enterprise application developers consider themselves generative AI “experts.”

According to the report, the small pool of confident GenAI pros demonstrates a “skills gap” and “steep learning curve” for IT pros navigating a space with evolving toolkits and frameworks.

“Any simplified AI application that can simplify the workload and enhance productivity? Creating that is actually not simple, and it’s complex and it’s very dynamic in a world that is changing rapidly every day,” Maryam Ashoori, senior director of product management for watsonx models at IBM, told us.

The survey, conducted by Morning Consult, polled more than 1,000 US-based developers, engineers, and data scientists building generative AI applications.

Read more here.—BH

A new year brings with it new challenges for the cybersecurity industry, and experts IT Brew spoke to in December are predicting roles for AI, a change in ransomware, and an increase in security battles on the international stage.

“AI and ML will be used in cyber warfare, with collateral damage outside of conflict zones due to hyper-connectivity,” NCC Group’s Global Head of Digital Forensics and Incident Response Alejandro Rivas-Vásquez told IT Brew.

That usage will have ups and downs, as Pynt CTO Ori Goldberg explained. The more LLMs are deployed both in security and across the industry in general, the more dangers will present for IT teams and other cyber professionals.

“Existing issues like prompt injection and model misuse will evolve into new threats, in tandem with more intelligent models,” Goldberg said. “At the same time, tools powered by LLMs will enhance anomaly detection, automate threat responses, and perform autonomous vulnerability fixes.”

Usage. As with most things AI, it comes down to how effectively the technology can be deployed by both sides. Ismael Valenzuela, VP of threat research and intelligence at BlackBerry, told IT Brew in an interview in December that the capabilities of AI make it dangerous in the wrong hands.

Keep reading here.—EH