At the age of 98, former Secretary of State Henry Kissinger has a whole new area of interest: artificial intelligence. He became intrigued after being persuaded by Eric Schmidt, who was then the executive chairman of Google, to attend a lecture on the topic while at the Bilderberg conference in 2016. The two have teamed up with the dean of the MIT Schwarzman College of Computing, Daniel Huttenlocher, to write a bracing new book, The Age of AI, about the implications of the rapid rise and deployment of artificial intelligence, which they say "augurs a revolution in human affairs." The book argues that artificial intelligence processes have become so powerful, so seamlessly enmeshed in human affairs, and so unpredictable, that without some forethought and management, the kind of "epoch-making transformations" they will deliver may send human history in a dangerous direction. Kissinger and Schmidt sat down with TIME to talk about the future they envision. Kissinger: When I was an undergraduate, I wrote my undergraduate thesis of 300 pages--which was banned after that ever to be permitted--called "The Meaning of History."

The most recent generation of predictive language models also appears to learn something about the underlying meaning of language. These models can not only predict the word that comes next, but also perform tasks that seem to require some degree of genuine understanding, such as question answering, document summarization, and story completion. Such models were designed to optimize performance for the specific function of predicting text, without attempting to mimic anything about how the human brain performs this task or understands language. But a new study from MIT neuroscientists suggests the underlying function of these models resembles the function of language-processing centers in the human brain. Computer models that perform well on other types of language tasks do not show this similarity to the human brain, offering evidence that the human brain may use next-word prediction to drive language processing.

A modified consumer drone was used in an attack on an electrical substation in the US last year, according to a report from the FBI, Department of Homeland Security and National Counterterrorism Center. The report, which is being circulated to law enforcement agencies in the US, highlights the incident at a substation in Pennsylvania last year as the first known use of a drone to target energy infrastructure in the US. The location isn't specifically identified, but the drone crashed without causing damage. The drone was modified with a trailing tether supporting a length of copper wire. If the wire had come into contact with high-voltage equipment it could have caused a short circuit, equipment failures and possibly fires.

Neuroscientists find the internal workings of next-word prediction models resemble those of language-processing centers in the brain. In the past few years, artificial intelligence models of language have become very good at certain tasks. Most notably, they excel at predicting the next word in a string of text; this technology helps search engines and texting apps predict the next word you are going to type. The most recent generation of predictive language models also appears to learn something about the underlying meaning of language. These models can not only predict the word that comes next, but also perform tasks that seem to require some degree of genuine understanding, such as question answering, document summarization, and story completion.

When Amazon introduced its home robot Astro earlier this year, it first showcased the robot following behind a person. It's a simple idea that has captured people's imaginations with depictions in science fiction, like R2-D2 and BB-8 from Star Wars, and in reality, with research projects like DARPA's robotic pack mule. Follower robots have been tapped for senseless pursuits like carrying a single bottle of water, but robots can also carry tools in a warehouse or just-picked fruit from an orchard to a packing station. Artificially intelligent machines trained to follow people or other machines can transform how we think about everyday objects, like carry-on luggage or a set of golf clubs. Now the makers of follower robots want to coordinate movement around the modern workplace.

The past decade has witnessed the unprecedented march of technology and the opportunities, dangers, and disruptions that accompany it. In the last 4-5 years, a synthetic media technology (that uses machine learning techniques and is created by generative adversarial networks – GANs) known as deep fakes, has revolutionised the ways that digital media can be altered. The ability of state and non-state actors to generate, forge, and manipulate media has created clickbait headlines and fake news, 'terrorised women' by substituting faces to create fake porn, and abetted the spread of misinformation and disinformation. An opinion piece in the Washington Post has called this worrying trend of mass-scale manipulation the "democratisation of forgery". In the last 4-5 years, a synthetic media technology known as deep fakes, has revolutionised the ways that digital media can be altered.

One of the signatures of American culture is our respect for the people that fight for our freedom. This has been the case throughout many generations of American history. This is why the statistics on veteran homelessness are rather disturbing. Recent statistics show that veteran homelessness increased by about 4% in 2020, aggravating an already bad situation. The US government and the VA have created very accommodating measures to enable Veterans to become homeowners.

In this special guest feature, Justin Beals, CEO and cofounder of Strike Graph, outlines key considerations when using AI tесhnоlоgіеѕ to іmрrоvе a startup's суbеrѕесurіtу capabilities and manage суbеr rіѕk more efficiently аnd еffесtіvеlу. As a serial entrepreneur with expertise in AI, cybersecurity and governance, he started Strike Graph to eliminate the confusion related to cybersecurity audit and certification processes. He likes making arcane cybersecurity standards plain and simple to achieve. As the CEO, Justin organizes strategic innovations at the crossroads of cybersecurity and compliance and focuses on helping customers get outsized value from Strike Graph. Justin earned a BA in English and Theater from Fort Lewis College.

Shooter video games like Call of Duty are often citied as the motivation for real-life gun crimes. But according to a new scientific study published today, there's no evidence that these games cause violence in the real world. The London-based study author looked at how adolescent boys' violent behaviour is affected by the releases of new violent video games in the US. She concluded that policies intended to place restrictions on video game sales to minors – as attempted by several US states – are unlikely to reduce violence. Real-life displays of violence, such as mass shootings, have famously been blamed on video games by some politicians, rather than lax gun regulation and easy access to firearms.

The legal framework for the development and use of Artificial Intelligence (AI) was launched in Brazil. There was already a lot about regulation in full progress in the European Union and the United States, but here the matter was delayed. The landscape is starting to change. In late September, the Chamber of Deputies approved a bill that establishes the foundations and principles for AI in the country. The framework defines the rules of the game for AI development and outlines how it will be applied to the daily lives of companies and citizens. In line with the General Data Protection Law (LGPD), this regulation serves as a guide for the work of Brazilian companies in the startup and research and development (R&D) sectors in this important area of innovation.