'There are a lot of people that are scared to even talk about what's going on because it is their livelihood,' says Jim Delmage who runs the blog and YouTube channel Sip and Feast with his wife, Tara. 'There are a lot of people that are scared to even talk about what's going on because it is their livelihood,' says Jim Delmage who runs the blog and YouTube channel Sip and Feast with his wife, Tara. Google AI summaries are ruining the livelihoods of recipe writers: 'It's an extinction event' T his past March, when Google began rolling out its AI Mode search capability, it began offering AI-generated recipes. The recipes were not all that intelligent. The AI had taken elements of similar recipes from multiple creators and Frankensteined them into something barely recognizable.

For all the chaos going on down here on Earth, it's easy to forget that we live in a volatile galaxy full of formidable dangers. From space rocks flying at thousands of miles per hour, to black holes that could rip our planet apart, sometimes it's best not to think about them. But what would actually happen to the human body if we perished at the hands of these wild astronomical phenomena? MailOnline spoke to experts to find out – and to see if there's any chance of them actually occurring while humanity still exists. Before any of them happen, Homo sapiens could be responsible for their own demise – likely by creating dangerous AI or the emission of greenhouse gases.

From Armageddon to the Day After Tomorrow, there have been plenty of Hollywood movies about how our world might end. But if there is to be a global apocalypse, what might be to blame for wiping out all life on Earth? A wandering black hole, giant asteroid impact and nuclear war could all trigger such disaster, as could the rise of killer robots or the reversal of our planet's magnetic field. Many of these might seem far-fetched but with the Doomsday Clock being placed at a record 90 seconds to midnight this year – and scientists warning that humanity's continued existence is at greater risk than ever before – the threat is now all to real. So how exactly would these devastating possibilities come about? End of days: Ff there is to be a global apocalypse, what might be to blame for wiping out all life on Earth?

Evidence from past extinctions cannot be used as a definitive way of predicting future biodiversity loss, scientists have found by using AI. A team of researchers including Dr. James Witts of the University of Bristol's School of Earth Sciences and led by Dr. William Foster from Hamburg University used fossils from previous mass extinctions to see if AI-generated models can accurately predict extinction vulnerability. Despite expectations, this research found that mass extinctions could not be used to generate predictive models for other biodiversity crises, with no common cause flagged. This is because marine communities are constantly evolving and no two mass extinctions are impacting the same marine ecosystem. Co-author Dr. Witts explained, "In a time of increasing extinction risk, knowing whether we can make predictions about the vulnerabilities of different organisms to extinction is essential."

A new study applies machine learning to the fossil record to visualize life's history, showing the impacts of major evolutionary events. This shows the long-term evolutionary and ecological impacts of major events of extinction and speciation. Colors represent the geological periods from the Tonian, starting 1 billion years ago, in yellow, to the current Quaternary Period, shown in green. The red to blue color transition marks the end-Permian mass extinction, one of the most disruptive events in the fossil record. The idea that mass extinctions allow many new types of species to evolve is a central concept in evolution, but a new study using artificial intelligence to examine the fossil record finds this is rarely true, and there must be another explanation.

Scientists have long believed that mass extinctions create productive periods of species evolution, or ''radiations,'' a model called ''creative destruction.'' However, new analysis provide evidence for different outcome. A new study led by scientists affiliated with the Earth-Life Science Institute (ELSI) at Tokyo Institute of Technology used machine learning to examine the co-occurrence of fossil species and found that radiations and extinctions are rarely connected, and thus mass extinctions generally don't cause mass radiations.

Neuroevolution commonly uses speciation strategies to better explore the search space of neural network architectures. One such speciation strategy is through the use of islands, which are also popular in improving performance and convergence of distributed evolutionary algorithms. However, in this approach some islands can become stagnant and not find new best solutions. In this paper, we propose utilizing extinction events and island repopulation to avoid premature convergence. We explore this with the Evolutionary eXploration of Augmenting Memory Models (EXAMM) neuro-evolution algorithm. In this strategy, all members of the worst performing island are killed of periodically and repopulated with mutated versions of the global best genome. This island based strategy is additionally compared to NEAT's (NeuroEvolution of Augmenting Topologies) speciation strategy. Experiments were performed using two different real world time series datasets (coal-fired power plant and aviation flight data). The results show that with statistical significance, this island extinction and repopulation strategy evolves better global best genomes than both EXAMM's original island based strategy and NEAT's speciation strategy.

Back in 1973, Daniel Bell published a pioneering book, called The Coming of Post-Industrial Society. He described how society was undergoing relentless change, driven by rapid advances in technology. Services would become more important than goods. There would also be the emergence of a "knowledge class" and gender roles would evolve. According to Bell: "The concept of the post-industrial society deals primarily with changes in the social structure, the way in which the economy is being transformed and the occupational system reworked, and with the new relations between theory and empiricism, particularly science and technology." Among the many readers of the book was a young Tom Siebel.

While the AI hype cycle is in full cyclone mode at this point, the truth of the matter is that some of it is completely justified. There has been extraordinary growth in field – evidenced in the number of papers, the startups working on key problems and the breakthroughs. Even in the face of an "AI winter" there is enough going on in the field, enough avenues of pursuit, enough low hanging fruit to revolutionize entire industries – even if new and better techniques were not developed. AI technology has effectively outpaced the talent inside most organizations. They can't consume what already exists – which means that the opportunity is as much in making it easier to consume than it is to develop new approaches.

In this work, we describe a self-replication-based mechanism for designing agents of increasing complexity. We demonstrate the validity of this approach by solving simple, standard evolutionary computation problems in simulation. In the context of these simulation results, we describe the fundamental differences of this approach when compared to traditional approaches. Further, we highlight the possible advantages of applying this approach to the problem of designing complex artificial agents, along with the potential drawbacks and issues to be addressed in the future.