The evolution of large language models (LLMs) toward artificial superhuman intelligence (ASI) hinges on data reproduction, a cyclical process in which models generate, curate and retrain on novel data to refine capabilities. Current methods, however, risk getting stuck in a data reproduction trap: optimizing outputs within fixed human-generated distributions in a closed loop leads to stagnation, as models merely recombine existing knowledge rather than explore new frontiers. In this paper, we propose language games as a pathway to expanded data reproduction, breaking this cycle through three mechanisms: (1) \textit{role fluidity}, which enhances data diversity and coverage by enabling multi-agent systems to dynamically shift roles across tasks; (2) \textit{reward variety}, embedding multiple feedback criteria that can drive complex intelligent behaviors; and (3) \textit{rule plasticity}, iteratively evolving interaction constraints to foster learnability, thereby injecting continual novelty. By scaling language games into global sociotechnical ecosystems, human-AI co-evolution generates unbounded data streams that drive open-ended exploration. This framework redefines data reproduction not as a closed loop but as an engine for superhuman intelligence.

An open letter published today calls for "all AI labs to immediately pause for at least 6 months the training of AI systems more powerful than GPT-4." This 6-month moratorium would be better than no moratorium. I have respect for everyone who stepped up and signed it. I refrained from signing because I think the letter is understating the seriousness of the situation and asking for too little to solve it. The key issue is not "human-competitive" intelligence (as the open letter puts it); it's what happens after AI gets to smarter-than-human intelligence.

Artificial intelligence was coined in the summer of 1956. Most experts are confident that singularity will happen sooner in the future rather than later. Artificial intelligence (AI) has become a technological reality for businesses and organizations across industries. Even if its benefits may not be always easy to quantify, AI has proven itself capable of improving process efficiency, reducing human errors and labor, and extracting insights from big data. Scientists are still unable to reach technological singularity to surpass human intelligence with a view to outsmart, outperform or outdo it. Reaching singularity could be a defining moment for humanity when machines reach a level of intelligence that exceeds that of humans.

I've heard that in the future computerized AIs will become so much smarter than us that they will take all our jobs and resources, and humans will go extinct. That's the most common question I get whenever I give a talk about AI. The questioners are earnest; their worry stems in part from some experts who are asking themselves the same thing. These folks are some of the smartest people alive today, such as Stephen Hawking, Elon Musk, Max Tegmark, Sam Harris, and Bill Gates, and they believe this scenario very likely could be true. Recently at a conference convened to discuss these AI issues, a panel of nine of the most informed gurus on AI all agreed this superhuman intelligence was inevitable and not far away.

Combining humans with machines to create superhuman intelligence may soon no longer be the plot of science-fiction films, as the US Space Force's chief scientist say it will happen in'the coming decade.' Dr. Joel Mozer, speaking at an event at the Airforce Research Laboratory Wednesday, announced we are entering the age of'human augmentation,' which is crucial to the US's national defense in order to not'fall behind our strategic competitors.' However, his proposal does not turn humans into cyborgs, but employs'AI agents' to assist with strategic military planning. Mozer highlights the abilities seen in developed by a Google subsidiary, AlphaGo Zero, which was able to train itself to play the game of Go at a master level in just a few weeks. Mozer suggests the extortionary capabilities can lead to superhuman capabilities, by means of combining human ingenuity with the power, speed and efficiency of machines.

What kind of projects are you working on in an R&D department in data science or AI field? It is the reality of Superhuman #AI, what guides all my projects, to prove the assumptions which are behind a superhuman intelligence: - AI is already getting smarter than us, at various domains, at an exponential rate. Elon Musk, Stuart Russell, Ray Kurzweil, Demis Hassabis, Sam Harris, Nick Bostrom, David Chalmers, Bart Selman, Jaan Tallinn and Max Tegmark all agreed that superhuman intelligence was inevitable and not far away. I do my best to build a digital superintelligence model as a global AI platform within 10 years showing that the Superhuman AI is a not a myth or religious belief, but a reality, today's reality.

There have been amazing leaps in AI technology within the Fintech sector over the past few decades. Early evidence on this came in 1960's when research was largely focused on Bayesian statistics to predict, audit stock markets, to 1980's-90's when Expert Systems were commercialised. Today, firms are building AI-powered products in order to generate cognitive investment insights, for those who want to participate in the market and take control of their finances, without walking into a branch or contacting an agent. In banking, financial services and insurance (BFSI), an industry overwhelmingly saturated with competition, customer service is one true key differentiator. From voice-based interactions to virtual agents, robo-advisory and intelligent portfolio management for smart decision making are some of the challenges the industry is tackling to not only help customers better manage their money, but also innovate in the process to enable firms for revenue growth and employment.

Artificial intelligence (A.I.) is making the "rise of machines" -- once the stuff of science fiction -- a reality. As 60 Minutes reported on October 9, "It might not be long before machines begin thinking for themselves -- creatively, independently, and sometimes with better judgment than a human." On February 28, 2018, you're invited to "Meet the Future" at DePauw University as the Ubben Lecture Series presents the world's first artificial intelligence-fueled android, Sophia, and her creator, David Hanson. In a 7:30 p.m. program in Kresge Auditorium, Dr. Hanson -- founder, CEO and chief designer of Hong Kong-based Hanson Robotics -- will be joined by his one-of-a-kind robot character. At the free event, which is open to all, the two will deliver a speech, take questions from the audience, and offer insights into the world of tomorrow that we're already entering today.

Siby Abraham is a computer scientist specialising in artificial intelligence. He is an associate professor and head of the department of mathematics and statistics at Guru Nanak Khalsa College, Mumbai. How many years does it take for a child that does not know anything about English to master it at a Shakespearean level? Assume that there is no one to teach the child, and that the child only knows about the fundamentals of English grammar to begin with. Suppose also that there is no book, no help and no support (human or non-human) at all times.

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