A few stories have emerged lately about how companies are having difficulty hiring enough people to fill key positions. These articles allege that automated talent acquisition (TA) or Applicant Tracking Systems (ATS) reject millions of candidates solely due to minor flaws in their applications such as gaps in their work histories, failing to meet a long list of exacting job requirements, or failing to use the language of the job description on their resume.

Machine learning and artificial intelligence (AI) systems have long been touted as the future of medicine. A patient can walk into a doctors office, and after a quick scan discover their risk for a variety of diseases, and be given information on how to prevent them from occurring. Patients suffering from diseases like cancer can have treatment decisions made by an AI that can optimize care and maximize likelihood of survival.

For the last two years, it’s an understatement to say we’ve witnessed big shifts in the relationship between most employees and their work environment. Many of us saw our work experience transform seemingly overnight into predominately a digital one as working from home became the ‘new normal.’

For decades, scientists and tech visionaries have envisioned a day when computers become so powerful that they become smarter than the human race. There is no shortage of science fiction stories and movies about robot uprisings. We are very far from that scary scenario, but at the same time artificial intelligence (AI) is no longer sci-fi. Many applications of AI abound today in business, and it is even being used in creative professions.

On your journey from reactive to proactive IT operations, you may be unsure where to start. If your organization is lacking visibility into your operations, that’s the best place to begin. Automation and artificial intelligence (AI) can help you gain that needed visibility. AIOps and visibility Artificial intelligence for IT operations (AIOps) offers numerous benefits, including faster response time, improved IT health, and simpler IT management.

Social media conglomerate Meta is the latest tech company to build an “AI supercomputer” — a high-speed computer designed specifically to train machine learning systems. The company says its new AI Research SuperCluster, or RSC, is already among the fastest machines of its type and, when complete in mid-2022, will be the world’s fastest. “Meta has developed what we believe is the world’s fastest AI supercomputer,” said Meta CEO Mark Zuckerberg in a statement.

The term “Industry 4.0” originated from a committee of German technocrats who wanted to make predictions about where technology was headed next. And certainly, it fits nicely in the storyline of the initial Industrial revolution with the rise of machines powered by steam and water, the second revolution sparked by the use of electricity, and the third revolution of automated production with robots.

Observability has gained a lot of momentum in the past year, be it full stack observability or data observability. Modern complex IT systems using clouds, microservices and serverless are easy to develop and deploy but extremely difficult to observe. These systems generate tremendous amounts of data and need an automated way of handling the volume. The next era of delivering customer experience is underpinned by the full stack observability capability.

The topic of artificial intelligence (AI) is wide-ranging and extensive, providing what seems like limitless possibilities for the world of work. As such, it’s easy for leaders to get lost in the excitement of implementing an AI model for their enterprise.