Old rocket parts and decommissioned satellites are whizzing around in low Earth orbit, where they risk colliding with the ever-growing constellations of modern satellites being launched. A new listing of the 50 most concerning pieces of space debris in low-Earth orbit is dominated by relics more than a quarter-century old, primarily dead rockets left to hurtle through space at the end of their missions. "The things left before 2000 are still the majority of the problem," said Darren McKnight, lead author of a paper presented Friday at the International Astronautical Congress in Sydney. "Seventy-six percent of the objects in the top 50 were deposited last century, and 88 percent of the objects are rocket bodies. That's important to note, especially with some disturbing trends right now."

In Plato's Phaedrus, Socrates tells a story about the Egyptian god Thoth, whose inventions include writing. Socrates relates how Theban king Thamus warned the god that his discovery would "create forgetfulness in the learners' souls". "They will be hearers of many things and will have learned nothing," Socrates recounts, in a translation by Oxford scholar Benjamin Jowett. "They will appear to be omniscient and will generally know nothing; they will be tiresome company, having the show of wisdom without the reality." The passage could be taken as evidence of Phillip Dawson's assertion that "panics" about new technologies and their impacts on learning date back two-and-a-half millennia. Sometimes there is good reason for concern, according to Dawson, associate director of the Centre for Research in Assessment and Digital Learning at Deakin University.

Early intervention is the key to better health outcomes for older adults, but achieving this can be rather elusive in senior care. Care today is reactive and often bogged down in busywork. As it is, many organizations are understaffed, so proactive care in this environment is difficult, if not impossible. Proactive care requires a near-constant stream of data. A certified nursing assistant may be able to provide this kind of care if they were to spend their entire day caring for a single resident, but the reality is that their attention is constantly split between residents, administrative work and everything else that comes their way.

Corporate finance and IT departments along with supply chain managers are the largest benefactors of AI technology, according to an emerging technologies study released this week by Oracle. Separately, Oracle (NYSE: ORCL) new cloud-based database infrastructure along with an expanded interoperability partnership with Microsoft (NASDAQ: MSFT). The AI research released Wednesday (Feb. The survey of 700 finance executives and IT managers concludes that AI-driven technologies such as blockchain and the Internet of Things have "passed the adoption tipping point" and in some cases exceeded corporate expectations. Among the early results are reductions in errors within finance departments and greater use of digital assistants to increase productivity and accelerated financial analysis.

In the webinar, McKnight said the best use for enterprise's data will be training AI algorithms. "AI algorithms are going to be important, and they are obviously trained on great data," he said. "So, a mantra of mine is: 'Let no data escape.' If you've been letting data escape, you are just hamstringing your future AI efforts." In an interview, Forrester analyst Boris Evelson said he agreed with McKnight's view, adding that AI is unquestionably one of the biggest BI and analytics trends in 2019 -- specifically, machine learning.

A would-be data management juggernaut got its first public airing as Cloudera -- a combination of formerly separate Hadoop pioneers Cloudera and Hortonworks -- as the newly stand-alone vendor's leaders publicly mapped the road it intends to take forward. "The combination has made sense for many years," said Tom Reilly, CEO of the combined companies, who held a similar role at the former Cloudera. Others agreed these leaders in open-source-oriented big data tooling -- built along lines drawn by big web companies, such as Google and Yahoo -- are better together than apart and can offer users a unified big data platform. Reilly spoke as part of a prerecorded webcast heralding the new company, which came after confirmation that shareholders of Cloudera and Hortonworks had approved a merger of the firms -- a deal first disclosed last October. Cloudera faces distinct challenges, as it moves data applications to the cloud and tries to convey users to the fast-growing new world of machine learning and AI.

To take advantage of machine learning, you'll need a new set of skills. Here are a few recommendations. My last article on artificial intelligence (AI) and machine learning (ML) concluded that "the split of the necessary AI/ML between the'edge' of corporate users and the software itself is still to be determined." Several readers have reached out to ask about the tools and skills needed to accomplish the edge computing for their companies. For many companies to take advantage of machine learning, they will require new skill sets.

Data management expert William McKnight has long espoused a well-designed information architecture as an effective means of bringing order to a continuous procession of new data technologies. In this Q&A, the second of two parts from an interview with the president of McKnight Consulting Group, he discusses what organizations need to do to adapt as AI and big data streaming rise in importance. McKnight also assesses how the European Union's new General Data Protection Regulation (GDPR) will affect data management processes. Among the areas that now seem to be calling us to revisit essential information architecture principles is big data streaming. What makes that such an active area of interest now?

Find the right focus for artificial intelligence in your enterprise in the coming year. When determining where to apply artificial intelligence in your enterprise, the possibilities are quite broad. In the coming years, almost every new and updated application will depend on some form of AI. Effectively matching AI to the challenges in these business areas requires you to understand what AI does better than a human and better than human-controlled business intelligence. The identification of objects by a well-trained AI-based camera is on par with a human.

To realize the power of artificial intelligence, start with data. Many are talking about artificial intelligence (AI), myself included. AI holds promise for organizations in every industry and every size. Some of the challenge today is how to prepare for AI in the organization and how to plan AI applications when there is a dearth of relevant case studies. The foundation for AI is data.