As hospitals faced the onslaught of scared patients fearing they had Covid-19, some organizations tip-toed into artificial intelligence to help serve as a first line of defense. The impact may send AI into the hospital mainstream.

In the fallout of COVID-19, technology has become the one sector that has uniquely benefited from the isolated workforce and the need for novel medicine. But the reliance on tech, medical technology and biotechnology in this uncertain time has provided opportunities for non-tech firms to unite with tech and medical leaders as well.

The likely approval of the $26 billion merger of T-Mobile US and Sprint Corp. could force the telecom sector into a third stage of acquisitions. This time, mobile purchasing partners could be cable companies, according to CNBC.

Global manufacturing is expected to feel the impact of the spread of the coronavirus — not the least because China is a far larger exporter than it was during the 2003 SARS virus outbreak, according to The Wall Street Journal.

European Union regulators have shown they are serious when it comes to fining global technology companies. They have enacted massive fines against the chipmaker Qualcomm, Google and others in recent years. But is the EU’s reputation of cracking down on tech companies justified?

Companies are increasingly staying private for longer, raising ever larger amounts from private equity and venture capital. SoftBank Technology Corp.’s Vision Fund took the lead in an $8 billion backing of Uber in January 2018, a little more than a year before the company’s IPO, valuing the business at $48 billion.

Despite a government shutdown in early 2019, the IPO market has been fairly strong. Early signs indicate that 2019 could come close to a record last set in 2000, when $97 billion was raised in the dot-com bubble.

Two IPO experts share advice for private equity leaders ahead of going public. They also discuss popular types of IPOs, the trend of direct listings, and why super shares are bad for companies in the long term.

Machine learning has created exciting prospects for industry, science and humanity. It’s also hyped and heavily marketed in misleading ways.