Latest Big Data Opinions
Artificial intelligence for IT operations (AIOps) has several use cases that IT operations managers can’t deny: reduce alert noise with statistically significant outcomes (up to 80 percent), correlate alerts and events to uncover the critical business issues immediately, analyse data across environments to find root causes, and resolve routine issues (like patching) automatically. Gartner predicts that large enterprise use of AIOps tools to monitor applications and infrastructure will rise from 5 percent in 2018 to 30 percent in 2023.
Concerns about Deepfakes are nothing new, but the technology has advanced far faster than many anticipated and has given rise to a medium that’s terrifying in its potential.
Though watching Jim Carrey’s face on Allison Brie’s body is, admittedly, delightful, the implications for forgery are sobering.
Consider, for instance, the recent Deepfake using Vladimir Putin’s face over MIT Technology Review’s editor-in-chief Gideon Lichfield’s body. Though it’s clear that Putin himself isn’t being interviewed, it isn’t a bad effort. It also doesn’t take a big imaginative leap to envision how the technology can be further enhanced and used with nefarious intent.
In the meantime, here are five useful tips to separate digital sophistry from the real thing:
Therefore, it’s more important than ever to ensure that business owners and managers are doing all they can to understand how their business may recover, and perhaps change, in the future. One of the ways in which this can be achieved is through the use of technology such as artificial intelligence (AI) and business analytics.
When most people think about AI, they tend to think of robots and science labs in which scientists develop AI for large companies. In reality, it’s possible for small and medium-sized businesses to take advantage of AI in order to develop analytics, which results in a better understanding of their market and to model potential future scenarios.
Sport consumption has seen a huge increase in recent years. With record viewing numbers for the likes of Premier League last season, and a novel willingness from consumers to pay for exclusive online content. As a result, sports is a lucrative source of revenue for network and programming brands.
Alongside this increase in popularity, modern television offers fans a more up close and personal experience at a fraction of the cost compared to attending live sporting events. Viewers can watch from the batter’s eyes, and encounter the huge right hand made by MMA fighters. In many ways, the viewing experience has evolved to become what Doug Kramon, ESPN’s senior director of fan support and customer care views as a ‘virtually there’ experience.
As part of a recent entry to Science Robotics, experts argued that “Covid-19 could be a catalyst for developing robotic systems that can be rapidly deployed with remote access […] to front lines”. It is often in times of great strife that innovation truly comes to the fore – the progress made across both public and private sectors in recent weeks is a tribute to just that, encompassing everything from advanced data analytics to the production of ventilators by the likes of McLaren, Mercedes and other F1 teams.
Robotics is no different. Robots are currently handling room service in isolation centres, patrolling the streets to help countries achieve social distancing policies, and helping to entertain the elderly. There are even robots whose purpose aligns perfectly with the specificities of this particular pandemic. UVD Robots, a company founded in 2016 by BlueOcean Robotics, produces a mobile bot with powerful UV lights built into the hardware. The robot can kill 99.99 per cent of all pathogens in the air using those light waves, a feature which will be most welcome in hospitals around the world currently.
Whatever the company, whatever the sector, there’s one phrase at the top of the agenda for every IT director: the ‘skills crisis’.
Undeniably, the crisis is a very real problem for IT, with significant consequences for the competitiveness of UK businesses and the economy at large. Recent Cloud Industry Forum (CIF) research starkly illustrated this problem, revealing that 40 per cent of organisations believe their efforts to implement digital transformation are hampered by a lack of staff and skills.
As the coronavirus emergency develops, these skills challenges are set to aggravate further. Mainframe operations, in particular, may be put under pressure, creating issues for mission critical workloads like on-premise SAP.
Eventually, life and business as we know it will go back to normal – or close to it – and perhaps autonomous databases that fix themselves will become a reality one day, too. However, until that day arrives, this is a wake-up call to get to know and show appreciation for your organisation’s DBAs and the work they do
It’s a turbulent time for many businesses as they face financial disruption and reckon with stay-at-home measures that disrupt business-as-usual. Organisations need a high-performing workforce more than ever, but simultaneously, HR departments are being forced to action redundancies, furloughs and pay cuts to ease the bottom line.
Much attention has been placed on technology and tools that enable remote working, but comparatively less has been placed on a burgeoning subset of analytics that can help HR departments drive employee productivity and wellbeing during this critical period. It’s called Organisational Network Analysis (ONA).
What is the enterprise data mapping problem and why does it need to be solved? Techerati editor James Orme spoke with Jiri Vojtek, COO at data management company CloverDX, to understand the real-world data challenge and how businesses can tackle it.
Despite Cambridge Analytica waking the world up to the manipulative power of AI, algorithmic encroachment on the democratic process shows no signs of abating. Dr. Christian de Vartavan says coding transparency is needed to ensure AI enhances democracy, rather than derails it
There’s no doubt artificial intelligence (AI) has huge potential to transform the modern enterprise. We’re already starting to see its impact – with recent research finding that AI can help organisations grow their annual profits 80 per cent faster and errors being reduced by more than a third (37 per cent). Indeed, AI is dominating many boardroom conversations, and we’re seeing increasing numbers of companies implementing, or considering the use of, the technology in one way or another.
Data created by companies is bigger than ever before, with many seeking to understand how DataOps processes can be used to convert such data into actionable business insights. Gartner defines DataOps as a collaborative data management practice aiming to improve the communication, integration and automation of data flows between data consumers and data managers in a company.
There remains a distance to go until businesses are fully aware of the most effective ways for maintaining good data quality and data management. Major cultural transformation must occur within many companies if DataOps is to be successful. This shift involves accepting that DataOps is a continuous process and serves as an impetus for organisational change by encouraging agility and endorsing change.