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G7 calls for adoption of international technical standards for AI

TOKYO, May 20 (Reuters) — Leaders of the Group of Seven (G7) nations on Saturday called for the development and adoption of international technical standards for trustworthy artificial intelligence (AI) as lawmakers of the rich countries focus on the new technology.

While the G7 leaders, meeting in Hiroshima, Japan, recognised that the approaches to achieving “the common vision and goal of trustworthy AI may vary”, they said in a statement that “the governance of the digital economy should continue to be updated in line with our shared democratic values”.

The agreement came after European Union, which is represented at the G7, inched closer this month to passing legislation to regulate AI technology, potentially the world’s first comprehensive AI law.

Generative AI Shakes Global Diplomacy At G7 Summit In Japan

Our technological age is witnessing a breakthrough that has existential implications and risks. The innovative behemoth, ChatGPT, created by OpenAI, is ushering us inexorably into an AI economy where machines can spin human-like text, spark deep conversations and unleash unparalleled potential. However, this bold new frontier has its challenges. Security, privacy, data ownership and ethical considerations are complex issues that we must address, as they are no longer just hypothetical but a reality knocking at our door.

The G7, composed of the world’s seven most advanced economies, has recognized the urgency of addressing the impact of AI.


To understand how countries may approach AI, we need to examine a few critical aspects.

Clear regulations and guidelines for generative AI: To ensure the responsible and safe use of generative AI, it’s crucial to have a comprehensive regulatory framework that covers privacy, security and ethics. This framework will provide clear guidance for both developers and users of AI technology.

Public engagement: It’s important to involve different viewpoints in policy discussions about AI, as these decisions affect society as a whole. To achieve this, public consultations or conversations with the general public about generative AI can be helpful.

AI offers leisure, if not happiness

NEW YORK, May 12 (Reuters Breakingviews) — Trying to predict how a nascent and promising technology will affect society is hubris, but history suggests people are going to have some serious leisure time if the development of artificial intelligence continues apace. Whether that makes them happy, and how the spoils will be divided, are harder to predict.

Over the past 50 years, technology has tended to grow faster than the wider economy. From 2006 to 2016, the digital economy grew at an average annual rate of 5.6% according to the U.S. Bureau of Economic Analysis, or almost four times faster than the overall output. That sort of expansion appears to be oddly consistent. Revenue earned by technology companies in Fortune’s list of the 100 biggest U.S. firms has, adjusted for inflation, increased at a similar rate for five decades.

American employee productivity has increased about 2% annually for seven decades. While higher capital intensity and more skilled labor steadily contribute, what varies more is the ability to deploy technology successfully. Sectors able to automate tasks and reduce workers, such as manufacturing, will generally see higher productivity, while others, such as education, may have a harder time. This process also takes time. In 1987, the economist Robert Solow famously said computers were visible everywhere expect in the productivity statistics. A decade later, productivity shot up.

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Integrated solar combined cycle system with steam methane reforming: Thermodynamic analysis

A transition to a carbon-free economy is the reality of the modern energy industry. Reduction in CO2 emission is one of the main challenge in energy engineering in the last decades. Renewable energy sources are playing an important role on the way to a zero-carbon economy [1,2]. Solar energy is one of the main and almost unlimited energy sources in the World. The different technologies of solar energy use have been developed in the last years [[3], [4], [5], [6], [7], [8]]. However, even though the progress in the development of solar energy technologies is notable, there are a lot of challenges for energy science. One of them is the fact that more than 60% of electricity is produced by conventional technologies via hydrocarbon fuel combustion: steam turbines, gas turbines, etc. While the share of electricity produced by using solar energy is no more than a few percent [9].

Among various ways of utilization of solar energy for electricity generation, a combination of solar energy with the traditional steam and gas turbine cycles can be highlighted. The power plants where solar energy is combined with conventional power cycles are named integrated solar combined cycle systems (ISCCS). In these systems, solar energy is used to produce heat and after that heat is used to generate mechanical work or electricity.

Combined cycle power plants (CCPP) show one of the highest energy efficiency among conventional power plants [10]. The modern cycles with high-temperature gas turbines have an efficiency up to 70% and even higher. In such cycles, the high-temperature gas turbines with the turbine inlet temperature (TIT) up to 1,600 °C are applied [11,12]. In the last years, a lot of various integrated solar combined cycle systems (ISCCS) were developed by various scientists and engineers. The main way to use solar energy in such cycles is a steam generation in CCPP [[13], [14], [15], [16]]. In other words, solar energy in such ISCCS is utilized as an energy source in a steam turbine cycle.

In three years, this Israeli startup could offer lunar flying services to drop payloads on the Moon

As per the company, traditional rovers may not be able to traverse everywhere and perform tasks like their drone-like hopper.

For decades, Earth’s natural satellite has been one of the most popular destinations for space exploration. The upcoming Artemis missions, along with the excitement on establishing a human settlement on the Moon, have collectively boosted the lunar economy market substantially in recent years.

Several startups have been preparing to offer their technological solutions to gain a better understanding of the valuable resources available and provide services to future astronauts.

Could AI Reduce How Much We Trust Other People?

The researchers suggest that a pervasive design perspective is driving the development of AI with increasingly human-like features. While this may be appealing in some contexts, it can also be problematic, particularly when it is unclear who you are communicating with. Ivarsson questions whether AI should have such human-like voices, as they create a sense of intimacy and lead people to form impressions based on the voice alone.

In the case of the would-be fraudster calling the “older man,” the scam is only exposed after a long time, which Lindwall and Ivarsson attribute to the believability of the human voice and the assumption that the confused behavior is due to age. Once an AI has a voice, we infer attributes such as gender, age, and socio-economic background, making it harder to identify that we are interacting with a computer.

The researchers propose creating AI with well-functioning and eloquent voices that are still clearly synthetic, increasing transparency.

Interdependent superconducting networks

In 2010 Prof. Shlomo Havlin and collaborators published an article in the journal Nature proposing that the abrupt electricity failure causing the famous 2003 Italy blackout was a consequence of the inter-dependency of two networks. According to Havlin’s theory the dependency between the power network and its communication system led to cascading failures and abrupt collapse. Havlin’s seminal work ignited a new field in statistical physics known as “network of networks” or “interdependent networks” and paved the way for understanding and predicting the effects of the interaction between networks.

The main novelty of Havlin’s model is the existence of two types of links that represent two qualitatively different kinds of interactions. Within networks, links between nodes describe connectivity such as or communication connections. Between networks, on the other hand, links describe dependency relationships in which the functionality of a node in one network depends on the functionality of a node in the other. The communication hubs need electricity and the electric power stations depend on communication control. This dependency leads to a cascading effect in which failure of a single node in one of the networks could lead to an abrupt breakdown of both networks.

Over the past decade or so since, Havlin, from the Department of Physics at Bar-Ilan University in Israel, and others have applied this concept to a variety of abstract systems, such as the internet, road traffic, the economy, infrastructure, and more. But being a theorist, Havlin was unable to manifest the hypothesis on real experimental physical systems and thus the theory couldn’t be confirmed in controlled experiments, nor could it be implemented for device-type applications.

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