Articles about Artificial Intelligence

Today, 80 percent of digital marketers feel growing pressure to meet customer acquisition and revenue goals, saying they feel like they are "running on a never-ending hamster wheel."

And that’s true: You may be overstretching your marketing muscle to get your customers to find you through organic search -- but it’s something you have little control over and is reactive. Traditional advertising media is becoming more obsolete, but the problem is that many businesses still don’t realize how technology can reverse that. Take the example of the automotive industry, where customer acquisition is still very reactive. The majority of customers still find the auto dealer and brand, and not the other way round. A recent study found that car dealers' first point of contact with more than half of their buyers is when they physically walk into the dealership, essentially leaving it to chance that their dealership or brand gets picked for a walk-in. There’s no doubt that companies across the board are rapidly experimenting with adopting artificial intelligence (AI) in various departments, including business performance and automating the human tasks, the low-hanging fruits. But it’s time you thought about bringing it in to enhance your customer acquisition strategy.

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AI and automation were becoming standard business practices long before the pandemic. As coronavirus shutdowns send shockwaves throughout the economy, though, companies turn to these solutions faster than ever before. Organizations around the world are investing in automated systems to maintain efficiency through the outbreak.

Companies are having to deal with a myriad of complications as a result of the ongoing COVID-19 pandemic. Many have had to scale back and let staff go, and some are facing new and unexpected demands. Tools like AI have become vital to sustainment amid the growing recession.

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Normally at this time of year IBM's annual Think conference would be getting underway. This year's event is, of course, being held digitally and has kicked off with some new announcements.

The first is the unveiling of IBM Watson AIOps, a new offering that uses AI to automate how enterprises self-detect, diagnose and respond to IT anomalies in real time.

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There are privacy concerns following the revelation that confidential data from UK coronavirus patients is being used by technology firms and government to build predictive computer models to help fight the pandemic.

US big data firm Palantir and UK AI startup Faculty are working together to put together what has been described as a "COVID-19 datastore". Pulling together information from government databases as well as information from health services, the project also makes use of highly personal data relating to individual patients according to documents seen by the Guardian.

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The rapid evolution of cybersecurity remained a major issue for small businesses in 2019, being named the top concern for all businesses, regardless of their size. Along with an increase in the number of cybercrimes, the cost of recovering from an attack means keeping ahead of the curve is vital for SMBs going forward.

This is challenging enough for businesses operating on a small budget, but fast-paced changes in technology mean that security resources are increasingly being stretched in a number of directions. Rather than protecting a single, traditional office, security must now cover a whole range of devices used for IoT and mobile working. Proactivity is now essential to an effective security strategy. By looking ahead to the trends of the next 12 months, SMBs can begin to identify the new challenges around cybersecurity that they will need to prepare for.

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Nothing in our lifetimes has prepared us for what's happening in our world today. We've certainly had our share of major catastrophes in the past 100 years -- both natural and man made -- but nothing matches the impact of the COVID-19 pandemic. We are living in a time when fundamental assumptions about how our societies function are being thrown out and re-written with blinding speed.

The degree of global disruption is unprecedented in scope and scale, and we're still in the early phases. Given the confluence of medical, social, political, and economic factors, we have not yet reached the peak of the impact, and the world we'll inherit as the storm tide recedes will be significantly changed, and changeable. This is not to suggest that "the end is nigh" or that all changes wrought by the pandemic will be bad. But the undeniable truth is that we are experiencing an unexpected and extreme test of our AI technologies and their ability to automate and improve our ability to make good decisions quickly in increasingly complex situations. With respect to AI, we are entering an especially critical phase.

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When it comes to making quick, real-time business decisions, Artificial Intelligence (AI) has proven to be a vital component of any effective business strategy. This is reflected in statistics showing how AI implementation jumped from 48 percent in 2018 to 72 percent in 2019. As technology continues to improve, no doubt this number will continue to increase with AI becoming an even larger asset to improve your operational capacity.

If utilized correctly, real-time AI has the ability to vastly improve real-time decisions for companies throughout the customer journey – from acquisition through to customer service and customer retention.

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The cloud has revolutionized making it easy to build, launch, and scale a service. That's driven a wave of spending on the major cloud providers, as made evident by the latest earnings reports from Microsoft (Azure), Amazon (AWS), and Google (Google Cloud). Microsoft just reported 62 percent QoQ growth for Azure, AWS brought in nearly $10 billion for Amazon in Q4 2019, and Google reported cloud earnings for the first time in January.

Companies of all sizes are clearly investing billions on the cloud and there doesn't seem to be a ceiling. Gartner predicts that by 2022 overall cloud spend will reach more than $330 billion, and that number grows every year. But at the same time, current estimates reveal that billions of this spend is the result of needless and wasted outlay. A recent survey of companies that spend at least $5 million on the cloud annually found that a vast majority (69 percent) regularly overspend on their cloud budget by 25 percent or more.

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The UK government has announced plans to spend £1.2 billion ($1.6 billion) on what it describes as "the world's most powerful weather and climate supercomputer".

The investment will make weather forecasts faster and more accurate, and the computer will make it easier to predict the impact of climate change. It will be managed by the Met Office, and will be used to help communities and government agencies better prepare for severe weather.

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More than a third of AI and analytics projects in the cloud are failing due to poor quality data according to a new survey.

The study from data specialist Trifacta surveyed 646 data professionals across different industries and titles to examine how organizations are handling the accelerating transition of data to the cloud, the obstacles of data cleaning for analytics and the time constraints they face when preparing data.

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Artificial intelligence is making its way into more and more areas of our lives. But how much of this is hype and how much is genuine innovation? And can improved AI learning models deliver better commercial solutions?

We spoke to Ben Lamm, CEO of Hypergiant Industries, a company at the cutting edge of solving problems with AI, to find out.

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Over the last decade we've seen significant advances in AI and machine learning. But there's more on its way, with ML set disrupt almost every industry sector in the decade to come.

We spoke to Eric Loftsgaarden, VP of Data Science and co-founder of consulting services company Atrium to find out how ML can be used to set businesses apart from their competitors and give start ups an edge in traditional industries.

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We’ve all heard the scare stories -- it’s only a matter of time before artificial intelligence will destroy millions of professionals’ livelihoods. Given the media frenzy accompanying the rapid advancements of artificial intelligence (AI), it’s not surprising that many people hold such a view. And while there is some truth to these dystopian predictions, they’re not as apocalyptic as they’re often made out to be.

Let’s start with some concrete research to shed a light on what professionals can expect in the coming months and years. In 2018, the World Economic Forum released a report suggesting that 75 million jobs may be displaced globally by a shift in the division of labor between humans and machines in the next five years. It goes on to say that, at the same time, 133 million new roles may emerge that are more adapted to this division. This insinuates that we could see the creation of 58 million new jobs in just half a decade. What it also suggests is that, perhaps we’re asking the wrong questions. Instead of worrying about robots taking over our jobs, we should instead be considering how AI might reshape the workforce -- and how we can adapt. 

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Visions of the future have long featured robots and cyborgs. We've seen robots, and even rudimentary human augmentation already, but now scientists have created the world's first living robots.

American researchers used cells from African clawed frogs to build biological machines from the ground up. Built from different biological tissues, scientists have brought into being "living, programmable organisms" and potentially opened up an ethical can of worms.

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Many predictions that we saw around artificial intelligence (AI) for 2019 leaned towards one extreme or the other -- ranging from the notion that AI will no longer be a thing to the idea that it’ll realize its full potential and completely change how industries work at a fundamental level. Advancing AI is going to be an incremental process and it’s unrealistic to think that the world will suddenly abandon it completely or exponentially accelerate its development in that area.

But in the security industry, we have still seen progress surrounding AI, as we’ve gotten better at using machine learning technology to identify and recognize behaviors to identify security anomalies. In most cases, security technology can now correlate the anomalous behavior with threat intelligence and contextual data from other systems. It can also leverage automated investigative actions to provide an analyst with a strong picture of something being bad or not with minimal human intervention.

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