If you regularly work with open-source code or produce software for a large organization, you are already familiar with many of the challenges posed by collaborative programming at scale. Some of the most vexing of these tend to surface as a consequence of the many independent alterations inevitably made to code, which, unsurprisingly, can lead to updates that do not synchronize. Difficult merges are nothing new, of course, but the scale of the problem has gotten much worse. This is what led a group of researchers at Microsoft Research (MSR) to take on the task of complicated merges as a grand program-repair challenge--one they believed might be addressed at least in part by machine learning (ML). To understand the thinking that led to this effort and then follow where that led, ACM Queue asked Erik Meijer and Terry Coatta to speak with three of the leading figures in the MSR research effort, called DeepMerge.a Meijer was long a member of MSR, but at the time of this discussion was director of engineering at Meta. Coatta is the chief technology officer of Marine Learning Systems. Shuvendu Lahiri and Christian Bird, two of the researchers who helped drive this effort, represent MSR, as does Alexey Svyatkovskiy, who was with Microsoft DevDiv (Development Division) at the time. Terry Coatta: What inspired you to focus on merge conflicts in the first place? And what made you think you'd be able to gain some advantage by applying AI techniques? Christian Bird: Back in the winter of 2020, some of us started talking about ways in which we might be able to use machine learning to improve the state of software engineering.

Mindtree co-founder and former CEO of Birlasoft and Sasken, Anjan Lahiri says his latest venture Navikenz is focused on helping enterprises discover and implement Artificial Intelligence (AI) enabled solutions to improve business processes. The technology industry veteran said that while Navikenz which was launched during the onset of the first Covid wave and thus flew under the radar for some time, has now been able to scale by engaging with Fortune 500 customers to determine what Artificial Intelligence can do for them, utilizing its Business Process Consulting, Enterprise Architecture, Cloud and Data Science capabilities. The company says both in life sciences and discrete manufacturing sectors it has bagged several large clients. "Navikenz has pioneered a differentiated approach to AI-solutioning. By taking learnings from Kaizen and TQM frameworks, we have formulated a proprietary framework. Services within the framework are designed to speed up organizational capabilities in AI-service generation and fulfilment, creating a pipeline of business generated use-case within a matter of weeks. Big and small enterprises need to leverage AI for enhancing better efficiencies in their process and we enable that to happen," Lahiri said.

The Pentagon didn't mince words in March when introducing the Joint Enterprise Defense Initiative, or JEDI Cloud program: "This program is truly about increasing the lethality of our department and providing the best resources to our men and women in uniform," the Defense Department's chief management officer, John H. Gibson II, told industry leaders and academics at a public event. JEDI aims to bring DOD's computing systems into the 21st century by moving them into the cloud. The Pentagon says that will help it inject artificial intelligence into its data analysis and equip soldiers with real-time data during missions, among other benefits. For the winning bidder, the contract will be lucrative: Bloomberg Government estimates it will be worth $10 billion over the next decade. Or at least that's how it should have worked.