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Creativity & Intelligence


The Fundamental Flaw in Artificial Intelligence & Who Is Leading the AI Race? Artificial Human Intelligence vs. Real Machine Intelligence

#artificialintelligence

Artificial intelligence is impacting every single aspect of our future, but it has a fundamental flaw that needs to be addressed. The fundamental flaw of artificial intelligence is that it requires a skilled workforce. Apple is currently leading the race of artificial intelligence by acquiring 29 AI startups since 2010. Success in creating effective AI, could be the biggest event in the history of our civilization. So we cannot know if we will be infinitely helped by AI, or ignored by it and side-lined, or conceivably destroyed by it.


AI Is No Match for the Quirks of Human Intelligence

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At least since the 1950s, the idea that it would be possible to soon create a machine that was capable of matching the full scope and level of achievement of human intelligence has been greeted with equal amounts of hype and hysteria. We've now succeeded in creating machines that can solve specific fairly narrow problems -- "smart" machines that can diagnose disease, drive cars, understand speech, and beat us at chess -- but general intelligence remains elusive. Let's get this out of the way: Improvements in machine intelligence will not lead to runaway machine-led revolutions. They may change the kind of jobs that people do, but they will not spell the end of human existence. There will be no robo-apocalypse. The emphasis of intelligence testing and computational approaches to intelligence has been on well-structured and formal problems. That is, problems that have a clear goal and a set number of possible solutions. But we humans are creative, irrational, and inconsistent.


AI Is No Match for the Quirks of Human Intelligence

#artificialintelligence

At least since the 1950s, the idea that it would be possible to soon create a machine that was capable of matching the full scope and level of achievement of human intelligence has been greeted with equal amounts of hype and hysteria. We've now succeeded in creating machines that can solve specific fairly narrow problems -- "smart" machines that can diagnose disease, drive cars, understand speech, and beat us at chess -- but general intelligence remains elusive. Let's get this out of the way: Improvements in machine intelligence will not lead to runaway machine-led revolutions. They may change the kind of jobs that people do, but they will not spell the end of human existence. There will be no robo-apocalypse. The emphasis of intelligence testing and computational approaches to intelligence has been on well-structured and formal problems. That is, problems that have a clear goal and a set number of possible solutions. But we humans are creative, irrational, and inconsistent.


Ai-Da has an existential crisis

#artificialintelligence

Named after mathematician and computer pioneer Ada Lovelace, Ai-Da is the world’s first humanoid AI robot artist that can create artistic pieces from sight using her robotic eyes and hands. Ai-Da…


AI might help edit the next generation of blockbusters

#artificialintelligence

The next few Tuesdays, The Verge's flagship podcast The Vergecast is showcasing a miniseries dedicated to the use of artificial intelligence in industries that are often overlooked, hosted by Verge senior reporter Ashley Carman. This week, the series focuses on AI for the video world. More specifically, we're looking at how AI is being used as a tool to help people streamline the process of creating video content. Yes, this might mean software taking on a bigger role in the very human act of creativity, but what if instead of replacing us, machine learning tools could be used to assist our work? That's what Scott Prevost, VP of Adobe Sensei -- Adobe's machine learning platform -- envisions for Adobe's AI products. "Sensei was founded on this firm belief that we have that AI is going to democratize and amplify human creativity, but not replace it," Prevost says.


The challenges of Artificial Intelligence systems in the Nigerian legal system

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We are used to looking only at well-defined and delimited fields, where business thrives and goes on, and where economic resources and technological availability make the road to innovation more straightforward. However, in my opinion, we never stop to analyse what Shakir Mohamed, in his "Decolonial AI", defines as the "peripheries", shifting our "ictu oculi" from the centre towards new paradigms, still unexplored, if not ignored. Therefore, I found this study by Agunbiade Akintunde Ifeanyichukwu, whose name already says it all, since he signs himself Agunbiade A.I., which analyses the relationship between Artificial Intelligence (AI) and the Nigerian legal system, entitled "Artificial Intelligence and Law, a Nigerian Perspective", really interesting. The aim was to explore the ways in which they can influence each other, capturing new and half-known aspects of little-discussed legal systems. This book proposed the development of an indigenous AI system, coupled with ADR mechanisms, that would have the power to reduce the incidence of court congestion, while analysing a comprehensive legal framework of how it would work.


How AI Can Amplify Human Creativity And Drive Great Customer Experience - B&T

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Jeremy Wood is the Head of Product Marketing at Adobe APAC. In today's digital-first economy, there's a perception that artificial intelligence ("AI") and automation can hamper creativity. By introducing automation and software into various processes--whether it's speeding manufacturing or generating effective marketing campaigns--new ideas and innovation can potentially wither. But in reality, nothing could be further from the truth. While we've made great strides in leveraging AI to aid in the creative process, machines ultimately can't think or feel, and need coaching from humans.


Chess AI: Competing Paradigms for Machine Intelligence

arXiv.org Artificial Intelligence

Endgame studies have long served as a tool for testing human creativity and intelligence. We find that they can serve as a tool for testing machine ability as well. Two of the leading chess engines, Stockfish and Leela Chess Zero (LCZero), employ significantly different methods during play. We use Plaskett's Puzzle, a famous endgame study from the late 1970s, to compare the two engines. Our experiments show that Stockfish outperforms LCZero on the puzzle. We examine the algorithmic differences between the engines and use our observations as a basis for carefully interpreting the test results. Drawing inspiration from how humans solve chess problems, we ask whether machines can possess a form of imagination. On the theoretical side, we describe how Bellman's equation may be applied to optimize the probability of winning. To conclude, we discuss the implications of our work on artificial intelligence (AI) and artificial general intelligence (AGI), suggesting possible avenues for future research.


Foundation models : Is it a new paradigm for statistics and machine learning?

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A recent debate on so called Foundation models (CRFM) brings a real question of if we can build very large models on any specified domain, similar to current large language models, and replace our ...


Amazon.com: Thinking in Algorithms: How to Combine Computer Analysis and Human Creativity for Better Problem-Solving and Decision-Making (Strategic Thinking Skills Book 2) eBook : Rutherford, Albert: Kindle Store

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We often have blind spots for the reasons that cause problems in our lives. We try to fix our issues based on assumptions, false analysis, and mistaken deductions. These create misunderstanding, anxiety, and frustration in our personal and work relationships. Resist jumping to conclusions prematurely. Evaluate information correctly and consistently to make better decisions.