Lifeboat Foundation

Smart cities are supposed to represent the pinnacle of technological and human advancement. They certainly deliver on that promise from a technological standpoint. Smart cities employ connected IoT networks, AI, computer vision, NLP, blockchain and similar other technologies and applications to bolster urban computing, which is utilized to optimize a variety of functions in law enforcement, healthcare, traffic management, supply chain management and countless other areas. As human advancement is more ideological than physical, measuring it comes down to a single metric—the level of equity and inclusivity in smart cities. Essentially, these factors are down to how well smart city administrators can reduce digital exclusivity, eliminate algorithmic discrimination and increase citizen engagement. Addressing the issues related to data integrity and bias in AI can resolve a majority of inclusivity problems and meet the above-mentioned objectives. make smart cities more inclusive for people and communities from all strata of society, issues related to digital exclusion and bias in AI need to be addressed by public agencies in these regions.

Artificial Intelligence is the ability of machines to seemingly think and act as humans do. Humans absorb data through our various senses, process data using our cognitive abilities, and then act. Machines also, in their own narrow way, absorb whatever information is made available to them and take relevant actions when prompted. Those actions may take the form of a conversational bot or a recommender engine. Over time, our decision-making sophistication has increased. We began making decisions relying solely on our judgment. We progressed to summarizing large swaths of data and then applying our judgment to that summary. And at present, we entrust AI with taking decisions across data and recommending actions. In narrow problems, machines have a greater ability than humans to process volumes of data and accurately identify the trends within. Was AI wrong about Nadal? Not really. It said that Nadal had a 4% chance of winning; at that snapshot in time, and based on all past data of similar matches, perhaps that was a fair assessment of his chances against Medvedev. Most humans would also have predicted a Medvedev win even if they hoped for a different outcome. I am sure that as the fifth set played out, the odds of Nadal winning rose steadily in his favor. So, the earlier prediction should not be considered wildly inaccurate just because Nadal ultimately won.

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Can AI measure the heart of a champion?

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The recent advances in machine learning and artificial intelligence, coupled with increases in computational power, have led to a lot of interest and hype in longevity biotechnology 30114–2). Hundreds of data scientists and companies are taking advantage of this hype to propel research and discovery of new technologies in aging research.

One of the major new areas in aging research are biomarkers of aging that give the true biological age of humans that may be different from their chronological age. One of the most advanced biomarkers of aging are deep aging clocks that can help researchers predict biological age as well as mortality of humans. In 2013, Steven Horvath published an article called ‘DNA methylation age of human tissues and cell types,’ in which he outlined the development of a multi-tissue predictor of age that allows for the estimation of the DNA methylation age of most tissues and cell types. He also formed an aging clock that can be used to address questions in developmental biology, cancer, and aging research.

There have been several more studies on such clocks since 2013. For example, I was part of a team in 2016 and we published a study on the first deep aging clock titled ‘Deep biomarkers of human aging: Application of deep neural networks to biomarker development.’ Since our study was published, many other aging clocks that can predict age as well as mortality rapidly entered into many industries. it is clear that there is a boom in the longevity biotechnology industry and huge progress in aging research is expected to be made in the next few years. AI-based aging clocks provide a very good entry point for the insurance companies to get into the field of aging research and actually contribute while protecting their business and innovating in science and technology.

Not science, apparentlyLast month, a Ph.D. student at the Hebrew University of Jerusalem breed a new strain of ‘supercharged’ lettuce that expanded its vitamin C and beta carotene content by 800 percent and 70 percent respectively.

Research Interests.

Genomic/metabolomic/proteomic approaches for identification of novel (regulatory and biosynthetic) aroma genes.

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