I am regularly asked to summarize my many posts. I thought it would be a good idea to publish on this blog, every Monday, some of the most relevant articles that I have already shared with you on my social networks. Today I will share some of the most relevant articles about Artificial Intelligence and in what form you can find it in today’s life. I will also comment on the articles.
On timesofindia.com: https://timesofindia.indiatimes.com/blogs/voices/artificial-intelligence-the-future-is-data-capture-not-machine-learning/
Artificial Intelligence: The future is data capture, not machine learning. Adoption of Artificial Intelligence (AI) has accelerated since the pandemic hit as the whole world moved towards digitization. A study by Oxford University and Yale University indicates that AI will outperform humans in many ways and will automate all human jobs in the next 120 years. By 2024, AI will be better than humans at translation, will write bestselling books by 2049, and will perform surgeries by 2053. Machine learning (ML), the proficiency of a machine to mimic human ability to accumulate knowledge and use it to drive insights, is generally considered the basis of AI.
On ZDNet.com: https://www.zdnet.com/article/a-call-to-bring-human-centered-design-to-artificial-intelligence/
A call to bring more human-centered design to artificial intelligence. Artificial intelligence shouldn’t have to be activated through a “big red button” that delivers opaque results that everyone hopes is the final word on a given question. Rather, it should be under some degree of control by humans in the loop who can get a sense of what the results are telling them. That’s the word from Ge Wang, associate professor at Stanford, who urges a human-centered design approach to AI applications and systems. In a recent webcast hosted by Stanford HAI (Human-Centered AI), Wang urges AI developers and designers to step back and consider the important role of humans in the loop. “We’re so far away from answers in AI, we don’t yet know most of the questions,” he points out.
On News.mit.edu: https://news.mit.edu/2022/machine-learning-biased-data-0221
Can machine-learning models overcome biased datasets? A model’s ability to generalize is influenced by both the diversity of the data and the way the model is trained, researchers report. Artificial intelligence systems may be able to complete tasks quickly, but that doesn’t mean they always do so fairly. If the datasets used to train machine-learning models contain biased data, it is likely the system could exhibit that same bias when it makes decisions in practice.
On Wionews.com: https://www.wionews.com/science/breakthrough-in-physics-artificial-intelligence-successfully-controls-plasma-in-nuclear-fusion-experiment-455165
‘Breakthrough in Physics’: Artificial Intelligence successfully controls plasma in nuclear fusion experiment. Scientists were successfully able to control plasma in nuclear fusion experiment by using artificial intelligence. Nuclear fusion comes from the fusing of two atoms at very high temperatures, which then release energy.
On dot.la: https://dot.la/creative-machines-ai-art-2656764050.html
Art Created By Artificial Intelligence Can’t Be Copyrighted, US Agency Rules. Computers can now write poems, paint portraits and produce music better than many humans. But when it comes to the realm of intellectual property law, artwork made by machines can’t receive copyright protection, a federal agency has decided.
On expresscomputer.in: https://www.expresscomputer.in/artificial-intelligence-ai/how-can-artificial-intelligence-help-the-insurance-sector-in-managing-risk/83886/
How can Artificial Intelligence help the insurance sector in managing risk? Insurers are leveraging AI to identify underwriting risks and optimize risk selection. Smart algorithms comb through industry databases to cull pertinent data on customers, efficiently segregating them into pre-decided pricing categories
On Itbrief.co.nz: https://itbrief.co.nz/story/rage-against-the-machine-can-an-ai-programme-be-an-inventor
Rage against the machine: Can an AI programme be an inventor? New Zealand has been caught by a global fight between humans and machines that might define intellectual property rights for the rest of the century. US-based physicist Dr Stephen Thaler is testing patent law around the world to see if his artificial intelligence inventor programme, “Device for the Autonomous Bootstrapping of Unified Sentience” (DABUS), could be considered an inventor. In 2018, Thaler lodged an application for two patents for a food container invented by DABUS with the European Patent Office and later filed an International Patent Application. To date, the only office to grant DABUS a patent was in South Africa. Applications in Europe, the United Kingdom and the United States had all been rejected, with Dr Thaler’s appeals also unsuccessful. It has also been also declined in Australia and New Zealand. The original Australian refusal was overturned by the Federal Court in 2021 which said that the country’s patent act had no specific provision excluding AI systems as inventors, there was no explicit part of patent law that required a human author, and that the term “inventor” must be allowed to evolve over time as technology develops. That decision has now been appealed and the decision is now awaited by local legal experts on both sides of the Tasman, given the similarities in both countries legal frameworks.