Sitting in a purpose-built hut in the grounds of the historic Bletchley Park country estate, British officials believed they had pulled off a diplomatic coup. On stage in front of them was the UK's technology secretary, Michelle Donelan, and behind her were high-level representatives from the US and China, together for the first time to discuss the international regulation of artificial intelligence. Even better, both countries were among 28 signatories to the "Bletchley declaration", an agreement to work together on safety standards that may prevent AI systems turning on humanity. Rishi Sunak said on Thursday: "Some said we shouldn't even invite China; others said that we could never get an agreement with them. A serious strategy for AI safety has to begin with engaging all the world's leading AI powers, and all of them have signed the Bletchley Park communique."

The energy requirements of current natural language processing models continue to grow at a rapid, unsustainable pace. Recent works highlighting this problem conclude there is an urgent need for methods that reduce the energy needs of NLP and machine learning more broadly. In this article, we investigate techniques that can be used to reduce the energy consumption of common NLP applications. In particular, we focus on techniques to measure energy usage and different hardware and datacenter-oriented settings that can be tuned to reduce energy consumption for training and inference for language models. We characterize the impact of these settings on metrics such as computational performance and energy consumption through experiments conducted on a high performance computing system as well as popular cloud computing platforms. These techniques can lead to significant reduction in energy consumption when training language models or their use for inference. For example, power-capping, which limits the maximum power a GPU can consume, can enable a 15\% decrease in energy usage with marginal increase in overall computation time when training a transformer-based language model.

Managing Partner and Co-Founder of Scale-Up VC, a Silicon Valley venture capital firm based in Palo Alto, California. Experts have warned against its potential misuse. It's now affecting aspects of our lives that many of us never anticipated: healthcare, education, employment and even national security. What could I be talking about? Artificial intelligence, or the "big AI," as I call it.

Imagine an underwater drone armed with nuclear warheads and capable of operating autonomously. Now imagine that drone has lost its way and wandered into another state's territorial waters. Russia aims to field just such a drone by 2027, CNBC reported last year, citing those familiar with a U.S. intelligence assessment. Known as Poseidon, the drone will be nuclear-armed and nuclear-powered. While the dynamics of artificial intelligence and machine learning, or ML, research remain open and often collaborative, the military potential of AI has intensified competition among great powers.

Artificial intelligence (AI) has been mainly the passion of data science labs and development shops. Lately, however, the implications of its potential impact on business -- in the form of enhanced customer service, expanded intelligent capabilities, and even society at large -- have become clearer. That means the time has come for business leaders to not only understand the implications of AI, but also step up and lead the way. That's because with the great power of AI comes great responsibility. "While AI is quickly becoming a new tool in the CEO tool belt to drive revenues and profitability, it has also become clear that deploying AI requires careful management to prevent unintentional but significant damage, not only to brand reputation but, more important, to workers, individuals, and society as a whole," write Roger Burkhardt, Nicolas Hohn, and Chris Wigley, all with McKinsey.

Are the U.S., China, and Russia recklessly undertaking an "AI arms race"? Clearly, there is military competition among these great powers to advance a range of applications of robotics, artificial intelligence, and autonomous systems. So far, the U.S. has been leading the way. AI and autonomy are crucial to the Pentagon's Third Offset strategy. Its Algorithmic Warfare Cross-Functional Team, Project Maven, has become a "pathfinder" for this endeavor and has started to deploy algorithms in the fight against ISIS.

"Today there are more great powers, so we have a multipolar rather than bipolar competition. The ideological rivalry has shifted from communism against capitalism to a new contest between authoritarian capitalism against liberal democratic capitalism. "There is far more trade between and among the great powers than there was during the Cold War, making all powers more hesitant to risk economically catastrophic conflict. But it also means we are less able to ignore one another or isolate ourselves from one another." The former national security advisor also revealed how the next all out war could escalate – beginning with cyber and anti-satellite tactics by the aggressor nation.

For its proponents, transhumanism – the idea of using technology to redesign humans beyond our biology – is just common sense. Who doesn't want to live a healthier, happier and wealthier life? And wouldn't it be great to live such an "enhanced" life indefinitely? For nearly as long as we have written record, humans have rebelled at the limits of the human condition but, with the development of modern science and technology, we have become increasingly able to overcome what once seemed like absolute limits. Advances in fields such as genetics, synthetic biology, neuropsychology, robotics, artificial intelligence and nanotechnology are putting us on the verge of even more radical breakthroughs, allowing us to imagine that we can ultimately rebuild completely the flawed human product that evolution has bequeathed us.