An internal memo sent to OpenAI staff on Saturday after former CEO Sam Altman's abrupt firing reiterates that "a breakdown in communication" led to the decision, not "malfeasance or anything related to our financial, business, safety, or security/privacy practices," according to Axios and The New York Times. The memo obtained by both publications was sent to employees by OpenAI's Chief Operating Officer Brad Lightcap. Speculation has been nonstop since Altman was ousted unexpectedly as CEO on Friday and dropped from the company's board of directors, with little concrete information from OpenAI itself to go on. In its announcement of the decision, the board said only that he was not "consistently candid in his communications with the board, hindering its ability to exercise its responsibilities." The board named Mira Murati, OpenAI's Chief Technology Officer, as interim CEO. In response, OpenAI's now-former president, Greg Brockman, announced he was stepping down too, tweeting, "Sam and I are shocked and saddened by what the board did today."

"Make everything as simple as possible, but not simpler." This quote often attributed to Albert Einstein surmises a conflict that business leaders are facing with the adoption of artificial intelligence (AI) and machine learning (ML). When it comes to automated forecasting and decision-making, many are now embracing the idea of these advanced predictive solutions--but only until they begin to delve beyond the norms and already-familiar data. In this respect, just like the scientific community, business leaders crave "simplicity." However, they often have different definitions of the word, focusing more on how data can affirm their own gut feelings, rather than how deeper insight and newly proved theories can override that personal experience.

McKinsey has warned the life insurance industry does not realise the full impact artificial intelligence (AI) will have on the sector. Its expert associate partner Nick Milinkovich believes AI will change how businesses are run and serve customers. Milinkovich spoke at the ProtectX4 event organised by Protection Review this morning. He deplored that life insurers have not adopted AI to the same extent as other industries did. He said: "We live fundamentally in a more digital world than we did just 18 months ago. "It means that while we have been able to pivot mostly all of our internal and customer facing processes onto some part of a digital backbone, it provides the foundation on which we can embed artificial intelligence more deeply into how we run our businesses." Milinkovich also found that consumers are now expecting more from life insurance firms. They are also looking to engage differently with the industry. He added that financial services and the retail industry had undergone a "much more fundamental" customer experience transformation. Milinkovich observed that there is a stronger willingness from customers to share more information than before with their insurance carrier. As a result, the amount of data available has increased exponentially. Research by McKinsey found almost every insurance carrier worldwide feel they are not getting the full value of their analytics investments. But most of insurance carriers are looking to invest more next year in analytics. "What we as an industry have yet to figure out is how to scale these investments and see the returns," said Milinkovich. McKinsey considers that there are reasons why there are leaders who have been able to separate themselves from the pack. The first reason is that they focus on a basket of use cases. This means they do not focus on only one part of the enterprise but on its entirety. They also look at a portfolio of AI related investments. Secondly, leaders are deeply embedding AI into the way that they run the business. They also rigorously track impact, so that they can prove value and fund further investments. The third point is that management teams are focusing on business problems and bringing the right set of people together to do that. Milinkovich said that they are fundamentally AI literate. It means they understand the power of AI and know how to use it. He said: "They have brought together the resources in a cross functional way to solve these problems beyond just the traditional silos that we see in most institutions.

Mercer Bell is a customer experience agency. Technically, we were the first in this market as far as being a trademark CX agency. What does that mean nowadays? Nowadays it's a really big complicated broad church of things we do for our clients, including working with aspects of AI. That is everything from deploying it for our clients on an ongoing basis, helping clients message features of artificial intelligence to their clients, and then actually building bespoke things, particularly in the machine learning space for our clients on an ongoing basis.

H2O.ai, the open source leader in AI, today announced the latest additions to the speaker lineup for H2O AI World London, a two-day interactive event featuring deep-dive technical sessions, talks on real-world business use cases and hands-on training. With speakers from PwC, Barclays, NVIDIA, IBM, Citi and more, the conference will bring together data scientists, business analysts and executives across multiple industries to discuss the latest trends in artificial intelligence, machine learning and data science, important use cases and the biggest challenges currently facing the industry. Join H2O.ai in London to connect with the community and learn how to harness the full value of AI, ML, deep learning and data science from industry-recognized speakers and hands-on training sessions. Register here to secure your spot. On day one of the conference, sessions will focus on hands-on technical training for H2O.ai's groundbreaking products, H2O Driverless AI, H2O-3 and Sparkling Water, to empower data scientists and analysts of all levels to work on projects faster and more efficiently through automation and state-of-the-art computing power.

Data is the real capital that's driving the new digital economy. Just consider any successful social media platform or consumer web service: these companies may be short on facilities and capital equipment, but they're rich in intellectual property, thanks to their ability to slice and dice their proprietary reserves of data capital for competitive advantage. Established companies can see similar opportunities, but only if they learn to unlock the full value of their information reserves. Insights into new business opportunities remain hidden because internal data consumers want new combinations of data and analyses not found in standard reports and dashboards. This is the unseen data that's hiding inside every company. How can enterprises bring data capital out of hiding?

The U.S. solar revolution has been a terrific boon to customer choice, the economy and climate policy planning. But solar panels alone can't achieve the full value of solar generation or the aggressive goals of greenhouse gas reductions. Moreover, solar developers face a wave of changes that is challenging their continued growth. Energy markets are shifting, supply chains are becoming more competitive, electric and solar rates are changing and customers' interest in controlling their energy destiny is increasing. As a result, the economics of distributed solar projects are getting skinnier and riskier for the solar developer.

The future of artificial intelligence (AI) in the insurance workplace is not one of efficiency versus jobs. As our Future Workforce Insurance Survey shows, AI will enable collaboration between technology and employees. Insurers will achieve cost savings, but growth will be a much greater benefit--and most executives expect a net gain in employment. Insurance company employees, on the other hand, expect AI to create opportunities for them and to improve their work-life balance. But there's still a disconnect.