Humans are hard-wired to dream, to create, to innovate. Each of us seeks to do work that gives us purpose -- to write a great novel, to make a discovery, to build strong communities, to care for the sick. The urge to connect to the core of our work lives in all of us. But today, we spend too much time consumed by the drudgery of work on tasks that zap our time, creativity and energy. To reconnect to the soul of our work, we don't just need a better way of doing the same things.

Artificial intelligence is the most powerful technology in generations with the potential to impact U.S. security, welfare and global leadership. U.S. national security agencies must develop and integrate AI-enabled capabilities to compete and defend in the AI era. However, standard methods and AI technologies fall short for the high-consequence and specialized missions of national security. The U.S. Department of Energy's (DOE) National Nuclear Security Administration (NNSA) and National Laboratories are developing the Next-Generation of AI -- innovative methods and technologies designed for national security challenges and operational concepts. National security agencies should leverage NNSA's Next-Generation AI research and development to accelerate AI innovation and enable an AI-ready force.

The star of the show was an experimental model called LaMDA, which Google says could one day supercharge the ability of its conversational AI assistants and allow for more natural conversations. "It's really impressive to see how LaMDA can carry on a conversation about any topic," said Google CEO Sundar Pichai during the presentation. "It's amazing how sensible and interesting the conversation is. But it's still early research, so it doesn't get everything right." To demonstrate LaMDA's abilities, the company showed videos of two short conversations conducted with the model.

The onset of next-generation Artificial Intelligence (AI) applications in Europe presents new regulatory challenges with respect to technologies deemed to present risks to the existing legal framework, rights, and ethics. The scope of potential challenges is broad, with many AI technologies already featuring prominently in our everyday life: algorithms deciding on the fate of our loan applications, recognising faces on public streets, flagging potentially illegal content online, targeting adverts to individual profiles online, estimating the outcome of elections, and even being employed across warzones the world over, as a means to highlight areas of potential hazard and risk. The use of algorithms to supplement human intelligence received a boost at the turn of the Millenium, with the onset of machine learning devices and the realization among technologists that'Big Data' could be taken advantage of in predictive mechanisms, effectively providing machines with the vast intelligence required to conduct complex real-time decisions. In this vein, of vital importance to the operation of AI technologies, is access to and utilisation of data streams. While the EU has strict safeguards on the use of personal data for this cause, as part of its General Data Protection Regulation, it is now seeking to harness the power of industrial data sharing as a means to boost competitiveness with other global players in the field of data-driven innovation.

These kinds of predicaments, which characterize much of what soldiers train to face, are immeasurably improved by emerging applications of AI; artificial intelligence can already gather, fuse, organize and analyze otherwise disparate pools of combat-sensitive data for individual soldiers. Target information from night vision sensors, weapons sights, navigational devices and enemy fire detection systems can increasingly be gathered and organized for individual human soldier decision-makers. However, what comes after this? Where will AI go next in terms of changing modern warfare for Army infantry on the move in war? The Army Research Laboratory is now immersed in a complex new series of research and experimentation initiatives to explore a "next-level" of AI.

As business adoption of artificial intelligence (AI) expands rapidly, so does the vocabulary used to describe the technology and the myriad ways companies are putting it to work. While terms such as algorithm, machine learning and neural networks have become as familiar today as cloud, SaaS and IoT, dozens of new AI terms and trends are already entering the field or rising in importance. Here's a look at some of those--and why you should become familiar with each. A machine-learning training technique in which scientists intentionally expose algorithms to corrupted data to trick them into making faulty predictions or reach incorrect conclusions. The technique allows developers to uncover security vulnerabilities that could be exploited by hackers or to examine the results for hidden bias that could lead to flawed results.

The exponential growth in data has proven to be a gamechanger in marketing, especially with the introduction of cognitive computing and AI. IBM Watson is breaking new ground in this area and speaking more on this is Marta McMichael, global director of performance marketing at IBM Watson IoT. With an extensive background in the high-tech industry, Marta has worked in varied roles, including working as a programmer, a consultant and managing large account sales at IBM. It is here at IBM that she discovered her passion for marketing and transitioned into it. In the interview, Marta shares her big career epiphany that helped her refocus on creating value for her clients.

As business adoption of artificial intelligence (AI) expands rapidly, so does the vocabulary used to describe the technology and the myriad ways companies are putting it to work. While terms such as algorithm, machine learning and neural networks have become as familiar today as cloud, SaaS and IoT, dozens of new AI terms and trends are already entering the field or rising in importance. Here's a look at some of those--and why you should become familiar with each. A machine-learning training technique in which scientists intentionally expose algorithms to corrupted data to trick them into making faulty predictions or reach incorrect conclusions. The technique allows developers to uncover security vulnerabilities that could be exploited by hackers or to examine the results for hidden bias that could lead to flawed results.

The Pentagon on Friday announced it would spend more than $2 billion over the next five years to advance the foundations of artificial intelligence technology. Through the AI Next initiative, the Defense Advanced Research Projects Agency aims to bring about so-called "third wave" AI, tools capable of human-like communication and contextual reasoning that far surpass the abilities of today's most advanced machine-learning and AI technology. The massive investment comes as global powers like China pour significant resources into their own artificial intelligence R&D programs. "I'm proud to tell you DARPA plans to continue and increase its support for AI research, with a significant focus on the technologies that underpin a third wave of AI," said DARPA Director Steven Walker in the announcement at the agency's 60th anniversary conference. "Let's … double down and commit to ensuring our country continues to create technological surprise for many more years and continues to use that surprise for a better and more secure world."

If you paid any attention to Google's big developer conference earlier this year then you'll know artificial intelligence is about to get big - really big. It's already powering most of Google's apps, one way or another, and the other giants in tech are scrambling to keep up. Here we're going to dig deeper into some of the AI announcements Google shared at I/O 2017, and explain how they're going to change the way you interact with your gadgets - from your smartphone to your music speakers. In broad terms artificial intelligence (usually) refers to a piece of software or a machine that simulates smart, human-like intelligence - even if it's just a hollow robot being operated by a person behind a curtain, pretending to respond to your commands, that's still a kind of AI. Within that you've got all kinds of branches, categories and approaches.