Simplifying and integrating enterprise technology can help companies move faster, respond to disruptions, and build a stronger foundation for AI, says Harish Manohar, SAP IT Director at Jabil. As companies scale, the technology supporting operations can become a liability just as quickly as it becomes an asset. Disconnected systems, site-specific tools, spreadsheets, and manual workarounds can create data silos that make it harder to spot problems early, coordinate responses, and make decisions with confidence. For Jabil, a global manufacturing company with more than 100 sites across more than 30 countries, the answer has been to make integration and simplification a priority. The company adopted a "simplify-first, then-innovate mindset," says Harish Manohar, SAP IT director at Jabil, recognizing that adding new technologies without first reducing complexity risks creating more risk. The goal is to standardize processes, consolidate where possible, and establish a more consistent data backbone across the organization. "Any innovation without simplification is going to add more complexity," Manohar says. That philosophy also changes how Jabil approaches modernization. "Any modernization or transformation should add measurable business value," Manohar says. The company is focused on connecting processes end-to-end across its supply chain and creating a foundation that can scale consistently across regions.

When six-foot-four inch Marty first rolled into Stop & Shop, the robot walked into history. Social robot experts say it is among the first instance of a robot deployed in a customer environment, namely supermarkets in the Northeast. Marty rolls around the store looking for spills with its three cameras. It does take the place of the human worker, called an associate, that did the same thing, but it means the associate can do something else. Doing the walk-around of the store is seen as a mundane task.

AI presents incredible opportunities for organizations to change the way they do business. With 1,000 researchers--including winners of the Turing Award and Fields Medal--in 11 labs, Microsoft has established itself as a leader in AI through its dogged focus on innovation, empowerment, and ethics. Now, the groundbreaking capabilities of AI can move beyond the lab to make a positive impact on every enterprise, every industry. Manufacturers have accrued vast stores of data through digital technologies and IoT--offering new windows into operational efficiency and business performance. Culling that data for actionable insights on predictive maintenance and performance improvements has become increasingly essential for an industry that operates on thin margins.

Manufacturing companies can feel product cycles tightening around them. In our fast-paced world, consumers are tossing out devices with rapid regularity, calling for the newest gadget, the hottest feature, the most instantaneous service. But how will manufacturing companies keep pace with this growing demand while continuing to produce increasingly complex goods? Smart Manufacturing, Industry 4.0, the Digital Enterprise, Factory of the Future or whatever you choose to call it, is revolutionizing the industry as we know it. Unlike the first industrial revolution of steam and iron (remember when hot water was a nifty tool?), this industrial revolution is splicing computing power and machine technologies to fuel a better, more efficient workplace that harnesses the abilities of modern informational, operational and communication technologies.

Microsoft is set to capitalize on its work on integrating field programmable gate arrays (FPGAs) into servers for machine learning workloads, by launching a specialized Azure cloud service. Project Brainwave will be offered in preview, with a limited set of capabilities and allocations, and will only be available in the East US 2 region to begin with. The company also plans to offer Brainwave servers as on-premises edge deployments. "I think this is a first step in making the FPGAs more of a general-purpose platform for customers," Mark Russinovich, chief technical officer for Azure, said at Microsoft Build conference. Brainwave uses Intel's Stratix 10 FPGAs, and builds upon Microsoft's previous work with these chips.

Microsoft has spent the past few years coming up with ways to use artificial intelligence internally. Now it will let customers take advantage of some of these tools while aiming to lure business from Amazon and Google. The company will let customers use a chip system it built to process AI queries cheaper and faster, called Project Brainwave. The first Brainwave service will speed up image recognition so it's almost instantaneous, said Doug Burger, a distinguished engineer in Microsoft Research, who works on the company's chip development strategy for the cloud. Microsoft, starting next year, also will sell an AI-sensor device based on the technology it its motion-controlled Kinect gaming sensor.

At Microsoft's Build Developers Conference, The Company Is Announcing A Preview Of Project Brainwave Integrated With Azure Machine Learning, Which The Company Says Will Make Azure The Most Efficient Cloud Computing Platform For AI Project Brainwave is a hardware architecture designed to accelerate real-time AI calculations. The Project Brainwave architecture is deployed on a type of computer chip from Intel called a field programmable gate array, or FPGA, to make real-time AI calculations at competitive cost and with the industry's lowest latency, or lag time. This is based on internal performance measurements and comparisons to other organization's publicly posted information. At Microsoft's Build developers conference in Seattle this week, the company is announcing a preview of Project Brainwave integrated with Azure Machine Learning, which the company says will make Azure the most efficient cloud computing platform for AI. According to Allison Linn, senior content manager at Microsoft – in her blog – Mark Russinovich, chief technical officer for Microsoft's Azure cloud computing platform, said the preview of Project Brainwave marks the start of Microsoft's efforts to bring the power of FPGAs to customers for a variety of purposes.

When discussions arise around a digital transformation journey, the focus is generally put on the technology. After all, in theory, it is technologies like machine learning, artificial intelligence, automation and additive manufacturing that drive the efficiencies and speed companies long for. But digital transformation is not all about the technology. Digital transformation shifts the mindset of how organizations create value for their end-customers, and none of that would be possible without educated and agile employees. The technology is great, but companies need to ensure they are educating and empowering employees along the way.

There's no question that GoPro is hurting: sales are struggling, its drone plans are dead and it's not clear that the company can survive purely on sales of action cameras like the Hero6. What's it going to do? Offer its technology to other companies, apparently. GoPro has unveiled a licensing deal that lets Jabil use its camera lens and sensor tech for a wide range of products. The two aren't specific about what this will involve, but Jabil sees uses in everything from law enforcement (think body cameras) through to videoconferencing and self-driving cars. Yes, the tech that documents your mountain bike trip could also drive you across town some day.

One June day in Virginia last year, an airplane was grounded by an unlikely adversary: a large swarm of bees. The peculiar story made for great newspaper headlines and serves as a reminder that even with the best technology and planning, some things are truly unexpected. But fortunately, most aircraft delays are caused by far more predictable issues than an unwelcome swarm of bees nesting in a turbine. Airlines, like most asset-intensive businesses, are getting increasingly better at predicting failures and anticipating maintenance problems. Rather than keeping planes grounded for costly and annoying last-minute maintenance -- or, worse, exposing passengers to the risk of flying on a faulty aircraft -- airlines are investing in cutting-edge technology that detects potential problems before they arise.