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Trump Administration Announces US–UK Artificial Intelligence R&D Agreement

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Today, the Trump Administration announced that the United States and the United Kingdom signed a Declaration on Cooperation in Artificial Intelligence Research and Development. Through this historic R&D cooperation agreement, we will work together to drive technological breakthroughs, promote researcher collaboration, and advance the development of trustworthy AI. Today's announcement is an outcome of the U.S. – UK Special Relationship Economic Working Group, which was established following a meeting between President Donald J. Trump and Prime Minister Boris Johnson last year. "America and our allies must lead the world in shaping the development of cutting edge AI technologies and protecting against authoritarianism and repression. We are proud to join our special partner and ally, the United Kingdom, to advance AI innovation for the well-being of our citizens, in line with shared democratic values," said Michael Kratsios, U.S. Chief Technology Officer.


U.S. Announces AI R&D Agreement with UK - insideHPC

#artificialintelligence

The Trump Administration announced today that the United States and the United Kingdom signed a Declaration on Cooperation in Artificial Intelligence Research and Development intended "to drive technological breakthroughs, promote researcher collaboration and advance the development of trustworthy AI." The announcement is an outcome of the U.S.–UK Special Relationship Economic Working Group, established following a meeting between President Donald J. Trump and Prime Minister Boris Johnson last year. "America and our allies must lead the world in shaping the development of cutting edge AI technologies and protecting against authoritarianism and repression," said Michael Kratsios, U.S. Chief Technology Officer. "We are proud to join our special partner and ally, the United Kingdom, to advance AI innovation for the well-being of our citizens, in line with shared democratic values." The Administration said the agreement will build "upon previous action by the United States to engage with likeminded international partners to accelerate the development of trustworthy AI innovation."


Deep learning helps explore the structural and strategic bases of autism?

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Psychiatrists typically diagnose autism spectrum disorders (ASD) by observing a person's behavior and by leaning on the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), widely considered the'bible' of mental health diagnosis. However, there are substantial differences amongst individuals on the spectrum and a great deal remains unknown by science about the causes of autism, or even what autism is. As a result, an accurate diagnosis of ASD and a prognosis prediction for patients can be extremely difficult. But what if artificial intelligence (AI) could help? Deep learning, a type of AI, deploys artificial neural networks based on the human brain to recognize patterns in a way that is akin to, and in some cases can surpass, human ability.


What We Should Learn from the Tension Between Mind and Machine

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Did medical knowledge engineering/search/expert systems. Every human bliss and kindness, every suspicion, cruelty, and torment ultimately comes from the whirring 3-pound "enchanted loom" that is our brain and its other side, the cloud of knowing that is our mind. It's an odd coincidence that serious study of the mind and the brain bloomed in the late 20th century when we also started to make machines that had some mind-like qualities. Now, with information technology we have applied an untested amplifier to our minds, and cranked it up to eleven, running it around the clock, year after year. Because we have become a culture of crisis, we are good at asking, what has gone wrong? But is the conjunction of natural and artificial mind only ill-favored, or might we not learn from both by comparison?


EntTelligence, Impression-Based Analytics, Launches With Steve Buck as Partner

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EntTelligence announces its launch which will deliver out-of-home (OOH) marketing analytics to the entertainment community. The company will harness data science, machine learning, and a 30,000-person Field Force armed with content listening technology to analyze and interpret OOH initiatives. Additionally, effective October 1st, former MarketCast, and Comscore executive Steve Buck will join as Partner and Chief Strategy Officer to the newly formed entity. EntTelligence CEO Rakesh Nigam says – "We are incredibly thrilled for our launch. As entertainment-based intelligence becomes ever more critical in a post-pandemic climate, our unique approach succinctly and effectively measures potential movie consumers. Moreover, we are equally excited to have Steve Buck, who has brought revolutionary currencies to market, join and lead our strategic initiatives."


Fraud and AML – AI and machine learning done right – Risk.net – IAM Network

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What resources does your financial services organisation need to ensure success when it comes to artificial intelligence (AI) and machine learning? Having an appropriate team in place, including domain experts, analysts and data engineers is a great start – but those teams also need appropriate tools to succeed. Creating interfaces and delivering new models without breaking the system – or the bank – along with access to data, security and continued data behaviour monitoring, are all essential for best practice and allowing accurate real-time decisions. You need to sign in to use this feature. If you don't have a …


Evolution And Artificial Intelligence Face The Same Basic Problem – IAM Network

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In 1966, an unusual symposium was hosted at the Wistar Institute of Anatomy and Biology at the University of Pennsylvania. The topic of the symposium was "Mathematical Challenges to the Neo-Darwinian Theory of Evolution" where mathematicians and engineers presented what they saw as fundamental problems with the theory of evolution. One of the mathematicians, Marcel-Paul Schutzenberger (1920–1996, pictured) worked closely with Noam Chomsky (1928–) on the intersection between linguistics and computer science. Schutzenberger's fundamental objection to many claims about evolution is that DNA, as modified by mutations, produces a very simple kind of language. On the other hand, the organisms and the environment they live within is a very complex domain with very far-ranging interactions.


The Promise of Artificial Intelligence

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As a healthcare leaders scrutinize costs and quality, they're looking to emerging technology to help them optimize processes and improve employee productivity. Artificial intelligence and machine learning are increasingly being used to automate critical business functions and support clinicians making complex clinical decisions. As the pandemic challenges healthcare organizations to think innovatively to improve cost effectiveness, AI is likely to play an even bigger role. Peter Durlach is senior vice president, healthcare strategy & new business development, at Nuance Communications. He holds a pivotal role in advancing the portfolio of healthcare solutions to align with the shifting needs of healthcare clients.


AI can detect how lonely you are by analysing your speech

Daily Mail - Science & tech

Artificial intelligence (AI) can detect loneliness with 94 per cent accuracy from a person's speech, a new scientific paper reports. Researchers in the US used several AI tools, including IBM Watson, to analyse transcripts of older adults interviewed about feelings of loneliness. By analysing words, phrases, and gaps of silence during the interviews, the AI assessed loneliness symptoms nearly as accurately as loneliness questionnaires completed by the participants themselves, which can be biased. It revealed that lonely individuals tend to have longer responses to direct questions about loneliness, and express more sadness in their answers. 'Most studies use either a direct question of "how often do you feel lonely", which can lead to biased responses due to stigma associated with loneliness,' said senior author Ellen Lee at UC San Diego (UCSD) School of Medicine.


Machine learning takes on synthetic biology: algorithms can bioengineer cells for you

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If you've eaten vegan burgers that taste like meat or used synthetic collagen in your beauty routine--both products that are "grown" in the lab--then you've benefited from synthetic biology. It's a field rife with potential, as it allows scientists to design biological systems to specification, such as engineering a microbe to produce a cancer-fighting agent. Yet conventional methods of bioengineering are slow and laborious, with trial and error being the main approach. Now scientists at the Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) have developed a new tool that adapts machine learning algorithms to the needs of synthetic biology to guide development systematically. The innovation means scientists will not have to spend years developing a meticulous understanding of each part of a cell and what it does in order to manipulate it; instead, with a limited set of training data, the algorithms are able to predict how changes in a cell's DNA or biochemistry will affect its behavior, then make recommendations for the next engineering cycle along with probabilistic predictions for attaining the desired goal.