Good code has both substance and style. It provides all necessary information, without extraneous details. It is accurate, succinct and eloquent enough to be read and understood by humans. But by the late 1960s, advances in computing power had outpaced the abilities of programmers. Many computer scientists created programs without thought for design.

Upon meeting for the first time at a dinner at Stanford earlier this year, Fei-Fei Li and Jennifer Doudna couldn't help but note the remarkable parallels in their experiences as scientists. Stanford's Fei-Fei Li and Jennifer Doudna of UC Berkeley will discuss the ethics of artificial intelligence and CRISPR technology. Both women helped kickstart twin revolutions that are profoundly reshaping society in the 21st century – Li in the field of artificial intelligence (AI) and Doudna in the life sciences. Both revolutions can be traced back to 2012, the year that computer scientists collectively recognized the power of Li's approach to training computer vision algorithms and that Doudna drew attention to a new gene-editing tool known as CRISPR-Cas9 ("CRISPR" for short). Both pioneering scientists are also driven by a growing urgency to raise awareness about the ethical dangers of the technologies they helped create.

The 3rd Annual Internet of Manufacturing South is a very important conference for the construction and support of the industrial ecosystem. It's a great pleasure to come and compare new ideas. In the build up to Internet of Manufacturing South 2019 we caught up with Arnie Kravitz the CTO of Advanced Robotics for Manufacturing (ARM) to discuss Digital Twin Technologies, AI, & Automation and its benefit for manufacturers. What are your views on Digital Twin technologies? How do you think they will affect manufacturers' operations in the future?

Jerry has extensive experience in machine learning, storage systems, online service, distributed systems, virtualization, and OS kernel. He has worked on high performance and large-scale systems at companies such as: Lyft, Box, Twitter, Zynga, and Microsoft. He has also authored the open-source project Lib Crunch and is a three-time Microsoft Gold Star Award winner. Jerry completed his master's degree in computer science at Shanghai University. His most recent startup is Datatron.

Everything you need to know about Duchess of Sussex Meghan Markle and her new life as part of the British royal family. There's something about that "Markle sparkle" that has the world transfixed, seeing as Meghan Markle has now been named the world's "most powerful dresser" in a 2019 report from Lyst, a fashion search engine. It was a big year for the Duchess of Sussex, who stylishly seized the spotlight at dozens of public appearances and royal tours, and even when introducing the world to baby Archie -- and according to Lyst, shoppers took notice. There's something about that "Markle sparkle" that has the world transfixed, as Meghan Markle has been named the world's most powerful dresser of 2019. According to Lyst's annual Year in Fashion roundup, each of the Duchess' numerous fashion statements sparked a 216-percent average increase in search for similar items.

It can be a bit difficult to wrap your brain around what exactly neural interface startup Ctrl-labs is doing with technology. That's ironic, given that Ctrl-labs wants to let your brain directly use technology by translating mental intent into action. We caught up with Ctrl-labs CEO Thomas Reardon at Web Summit 2019 earlier this month to understand exactly how the brain-machine interface works. Founded in 2015, Ctrl-labs is a New York-based startup developing a wristband that translates musculoneural signals into machine-interpretable commands. But not for long -- Facebook acquired Ctrl-labs in September 2019. The acquisition hasn't closed yet, so Reardon has not spoken to anyone at the social media giant since signing the agreement. He was, however, eager to tell us more about the neural interface technology so we could glean why Facebook (and the tech industry at large) is interested. In short, Ctrl-labs wants us to interact with technology not via a mouse, a keyboard, a touchscreen, our voice, or any other input we've adopted. Reardon and his team expect that in a few years we will be able to use individual neurons -- not thoughts -- to directly control technology. Reardon has said many times that his company is tackling the "mother of all machine learning problems."

Beyond cortical and limbic systems, the company Neuralink could add a third layer of digital superintelligence to humans and avoid artificial intelligence enslavement, its founder Elon Musk claimed Tuesday. The brain-computer linkup firm is working to treat medical conditions using its implanted chip as early as next year, but during a podcast appearance, Musk reiterated his belief that the technology could avoid some of the worst consequences of advanced machines. "It's important that Neuralink solves this problem sooner rather than later, because the point at which we have digital superintelligence, that's when we pass the singularity and things become just very uncertain," Musk said during an interview with MIT professor Lex Fridman. Musk was keen to note that the singularity, a hypothesized point where machines grow so advanced that humanity slips into an irreversible change, may not necessarily be good or bad. He did state, however, that "things become extremely unstable" after that point, which means Neuralink would need to achieve its human-brain linkup either before or not long after "to minimize the existential risk for humanity and consciousness as we know it."

Jack, it'll take an hour of your time and it can save your life.

Due to the increasing involvement of state players in automation warfare, when AI-driven automation is on its way to becoming a war weapon, what will it mean for an enterprise to stay competitive for survival? Artificial intelligence is redefining the very meaning of being an enterprise. The rapidly advancing artificial intelligence (AI) capability is on its way to revolutionizing every aspect of an enterprise. The ability to access data has leveled the playing field and brought every enterprise a unique possibility of progress. What needs to be seen is in this level playing field, which enterprises will be able to compete and lay a new foundation for fundamental transformation and which ones will decline.

Tom Davenport has literally written the book on analytics. Actually, several of them, to be precise. Over the course of his career, Tom has established himself as the authority on analytics and how their role in the modern organization has evolved in recent years. Tom is a distinguished professor at Babson College, a research fellow at the MIT Initiative on the Digital Economy, and a senior advisor at Deloitte Analytics. The discussion was timely as Tom had just written an article about a financial services company that had trained its employees on human-centered design so that they could ensure any use of AI would be customer-driven and valuable. "If you survey organizations and ask them, 'Does your company have a data-driven culture?' they almost always say no. Surveys even show a kind of negative movement over recent years in that regard. And it's because nobody really addresses that issue. They only address the technology side." Eventually, I think some fraction of [AI and analytics solutions] get used and are moderately effective, but there is not nearly enough focus on this. A lot of analytics people think their job is to create models, and whether anybody uses it or not is not their responsibility…We don't have enough people who make it their jobs to do that sort of thing. I think we need this new specialist, like a data ethnographer, who could sort of understand much more how people interact with data and applications, and how many ways they get screwed up.--Tom I don't know how you inculcate it or teach it in schools, but I think we all need curiosity about how technology can make us work more effectively. It clearly takes some investment, and time, and effort to do it.-- TD Wealth's goal was to get [its employees] to experientially understand what data, analytics, technology, and AI are all about, and then to think a lot about how it related to their customers.