Latest AI Opinions
In March, businesses across the UK were forced to rapidly change ‘Business As Usual’ and adopt a country-wide lockdown. Overnight, teams quickly adopted cloud solutions, from video conferencing to collaboration tools, in an attempt to maintain consistent communication and encourage productivity. While cloud computing saved the day during lockdown, it now has an even bigger part to play as businesses begin to return to the workplace.
Recently, the Committee on Climate Change published its annual Progress Report to Parliament providing new advice to the Government in reducing UK emissions. It assessed the government’s climate change mitigation activity and outlined measures to accelerate the transition to achieving Net Zero by 2050.
There have been ambitious policies introduced in an effort to reach the Net Zero target but have not been as forthcoming as we have hoped. In fact, in 2019 the UK had reduced its emissions by 3-4% but this rate of reduction is simply not high enough to meet our climate goals.
Reopening the economy while avoiding a second wave of Covid-19 is one of the biggest challenges of our time. Maintaining a low rate of transmission while opening up places of work and leisure is a delicate balance to strike, and localised outbreaks must be kept under control before they spread more widely. To do this requires a rapid, joined-up approach between regions, one which technology can enable.
With a raft of issues leading to the recent scrapping of the NHS’s contact tracing app, the pressure is on tech giants Apple and Google to provide a better solution. The apps currently provided are Bluetooth-based.
Throughout the crisis, organisations across the globe have been forced to operate with their hands tied behind their back. Contracts have been significantly scaled back or terminated, supply chains will have been disrupted and workforces have been trimmed. In light of this, having access to accurate data has never been more critical and for many it has acted as the differentiator between success and failure.
As lockdown measures begin to ease and some industries report the first green shoots of recovery, having access to that same accurate data will be equally critical. The public sector is no exception.
The UK social sector is vast. There are around 170,000 charities and nearly 500,000 social enterprises in the UK. These organisations support millions of individuals and countless communities – yet most of them aren’t making use of data science.
They are limited by a lack of resources, the high expected salaries of data experts, and fears about misusing data. However, some brave organisations are leading the way! Below, we highlight projects by organisations at the vanguard of social sector data use.
Imagine this, if you will. You’ve just bought a new car, it’s the latest model with all the frills. All of these extras make parking a doddle, your emissions reduced and your journeys smoother. You use your car nearly every day from that point onwards. You ignore the engine light when it comes on and don’t get that rattling noise checked out.
Now imagine that your organisation has adopted Artificial Intelligence (AI) tools but doesn’t adopt tools and procedures to care for the data. New cars and AI adoption may be miles apart, but for both to function optimally, correct procedures and routine care are essential.
Business intelligence (BI) is the cornerstone of modern business – enabling organisations to analyse information through technology and best practices to help executives, managers and other corporate end users make informed business decisions. But it’s not enough for companies to be data-led – especially in the current pandemic.
Organisations today need to be proactively data-driven and have a comprehensive view of their data – using it to drive change, eliminate inefficiencies, and quickly adapt to market or supply changes.
With 2.5 quintillion bytes of data created each day, a data analytics database is a powerful tool that goes way beyond traditional BI to give businesses greater predictive decision-making power based on real-time insights.
There has been significant coverage on the apparent link between ethnicity and the risk of contracting coronavirus, but what does the data actually reveal?
In 2005, Richard Webber and Trevor Phillips OBE started Webber Phillips, a data analytics business specialising in a software package called “Origins” (developed by OriginsInfo, of which Webber is MD). Origins applies reference tables linking people’s names and cultural backgrounds to the examination of cultural diversity among private and public sector organisations. It wasn’t long into the pandemic before Webber and Phillips realised their software could be applied to Covid-19, amid early indicators that the UK BAME community was disproportionately at-risk.
We spoke to Webber to understand the power of Origins and how the software package might help the UK Government better understand the connection between Covid-19 risk, ethnicity and occupation. In terms of what the data is telling us, Webber warns against oversimplification and says the devil is in the detail.
The pandemic has demonstrated just how much we depend on our online devices. From being able to work in the safety of our homes, to buying groceries online and booking virtual workout classes, it has proved that the move towards a fully digital world is within reach. Our dependence on the internet has also reminded us how much personal information we share – whether on social media, online banking and shopping, or our own professional profiles.
These characteristics that we openly disclose are exactly what fraudsters are looking for to exploit us – from using this information to pull our heartstrings in online dating scams to tricking our banks to gain access to our savings. We often overlook the trail of breadcrumbs of information we are leaving behind us, making it all too easy for a fraudster to take advantage.
Artificial Intelligence (AI) and Machine Learning (ML) aren’t new, in fact mechanical automation has been around for decades – so why is there still an incredibly slow adoption rate across modern-day workforces?
Although it might not have been called AI or ML until recent times, the world has been surrounded by examples of this technology – from having an x-ray to taking out a mortgage. Its primary purpose is to exist to try and make things simpler, quicker and easier for people.
And yet, despite being present for nearly a century, the concerns that machines are ‘going to take over the world’ – or that they’re untrustworthy and will take everyone’s jobs – remains the same today.
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.
ETH Zurich in Switzerland is one of the most highly regarded science and technology universities, one known for its cutting-edge research and innovation.
When it come to data centres, the pinnacle of innovation right now centres on how data analytics, sensors and AI can be used to improve power and performance.
Over the last few years, a group of researchers from both ETH Zurich and the University of Bologna has been at the forefront of advanced data centre monitoring research.