Beijing – Browsing the internet as a young policeman in China, Ma Baoli recalls the sheer volume of web pages telling him he was a pervert, diseased and in need of treatment -- simply because he is gay. "I felt extremely lonely after I became aware of my sexual orientation," says Ma, at the time a newly minted officer in a small coastal city. Two decades later, the softly spoken 43-year-old now helms Blued, one of the world's largest dating platforms for gay men. The app went public last July with an $85 million debut on Nasdaq, a remarkable tech success story from a country that classified homosexuality as a mental illness as recently as 2001. Parent company BlueCity's sunlit Beijing campus teems with young and casually dressed programmers who hold meetings in rooms named after Oscar Wilde and other prominent LGBTQ figures from around the world.
Background: Misinformation spread through social media is a growing problem, and the emergence of COVID-19 has caused an explosion in new activity and renewed focus on the resulting threat to public health. Given this increased visibility, in-depth analysis of COVID-19 misinformation spread is critical to understanding the evolution of ideas with potential negative public health impact. Methods: Using a curated data set of COVID-19 tweets (N ~120 million tweets) spanning late January to early May 2020, we applied methods including regular expression filtering, supervised machine learning, sentiment analysis, geospatial analysis, and dynamic topic modeling to trace the spread of misinformation and to characterize novel features of COVID-19 conspiracy theories. Results: Random forest models for four major misinformation topics provided mixed results, with narrowly-defined conspiracy theories achieving F1 scores of 0.804 and 0.857, while more broad theories performed measurably worse, with scores of 0.654 and 0.347. Despite this, analysis using model-labeled data was beneficial for increasing the proportion of data matching misinformation indicators. We were able to identify distinct increases in negative sentiment, theory-specific trends in geospatial spread, and the evolution of conspiracy theory topics and subtopics over time. Conclusions: COVID-19 related conspiracy theories show that history frequently repeats itself, with the same conspiracy theories being recycled for new situations. We use a combination of supervised learning, unsupervised learning, and natural language processing techniques to look at the evolution of theories over the first four months of the COVID-19 outbreak, how these theories intertwine, and to hypothesize on more effective public health messaging to combat misinformation in online spaces.
As the recent rise in Covid-19 threatens once again to shutter advertising agencies, film studios, and similar media "factories" globally, a quiet, desperate shift is taking place in the creation of new media, brought about by increasingly sophisticated AI capabilities. A new spate of actors and models are making their way to people's screens, such as pink-haired Imma, right, who has developed an extensive following in Japan on Instagram and TikTok, and is appearing increasingly on the covers of Japanese magazines. Imma joins a growing host of digital avatars who are replacing human actors, models, and photographers with computer-generated equivalents. Cloud-based GPUs and sophisticated game and modeling software have increasingly attracted the attention of a new generation of artist/programmers who are taking advantage of this to generate images, video, and audio that are becoming increasingly indistinguishable from reality, especially when that reality is otherwise captured via jump cuts, and matte overlays that have made tools such as TikTok and Reels the primary tools for video production for the typical Instagram celebrity. The business potential for such virtual models and spokespeople is huge, according to a recent piece by Bloomberg on digital avatars. Such avatars have obvious benefits over their flesh and blood counterparts.
Amid the COVID-19 pandemic, adoption of AI is on the upward trend. Especially, the #education field has transformed itself from the physical environment to the digital one. Technavio's "Artificial Intelligence Market in the US Education Sector 2018-2022" report predicts a nearly 48? Moreover, #educationalAI offers the potential for schools to deliver personalized learning strategies and offers analytics-based performance insight. The next step is to leverage AI tools into your system.
This is an article by Gabriel Leung, Dean of Medicine at Hong Kong University Medical Center and Malik Peiris Professor at the University Hong Kong 1) COVID vaccines are needed, even if they have minimal impact on transmission 2) COVID vaccines may not help us achieve herd immunity 3) COVID vaccine trials primarily assess prevention of virologically confirmed disease - not infection or transmission 4) an "effective" vaccine confers protection from disease but might not reduce spread 5) if COVID vaccines are effective in reducing morbidity & mortality in high-risk groups, they would have an important role, irrespective of impact on transmission and population immunity 6) if high-risk populations can be shielded by vaccination, COVID control measures could be recalibrated 7) the idea that COVID vaccine-induced population immunity will allow a return to normalcy may be based on false assumptions 8) no country will be truly safe until the entire world is vaccinated. This new study from Akiko Iwasaki, PhD and colleagues at Yale University offers the first clear evidence that COVID can invade brain cells 1) 40-60% of hospitalized COVID patients experience neurological complications including nerve damage and stroke 2) this study suggests that COVID in the brain may be more lethal than the respiratory infection caused by COVID 3) COVID hijacks brain cells to make copies of itself then exploits the brain cells' machinery to multiply 4) then COVID chokes off oxygen to adjacent brain cells causing them to die 5) a few days into the infection there is a dramatic decrease the number of synapses (the connections between neurons in the brain) 6) the researchers didn't find any evidence of an immune response to remedy this problem. It's a silent infection with evasion mechanisms 7) some people may be susceptible because of their genetic background or high viral load. Researchers used Summit Supercomputer to analyze 2.5 billion genetic combinations from COVID; then they made the Bradykinin Hypothesis 1) it took Summit 1 week to run the numbers. These high-powered microscopic images show very high viral loads of SARS-CoV-2 on human respiratory surfaces ready to spread the virus 1) Camille Ehre PhD and colleagues at UNC Chapel Hill School of Medicine generated these microscopic images showing very high viral loads of SARS-CoV-2.
The economic recession that follows as a consequence of the Covid-19 crisis and in particular the demise of certain sectors of the economy (physical retail, hospitality sector, etc) means that there will be greater pressure on politicians around the world to consider how to stimulate GPD growth in the post-pandemic world. However, there are also increasing pressures on politicians to combat the threat posed by Climate Change. Are the desired objectives of GDP and employment growth as well as reducing pollution at odds with each other? What if there is a pathway to GDP growth with the creation of new jobs and yet at the same time we are able to reduce emissions of Green House Gasses (GHGs)? A report entitled "How AI can enable a sustainable future" by PWC and commissioned by Microsoft (lead authors Celine Herweijer of PWC and Lucas Joppa of Microsoft) estimates that using AI for environmental applications across four sectors – agriculture, water, energy and transport. The report estimated that such applications could contribute up to $5.2 trillion USD to the global economy in 2030, a 4.4% increase relative to business as usual.
COVID-19, the disease caused by the SARS-CoV-2 virus, has been declared a pandemic by the World Health Organization, which has reported over 18 million confirmed cases as of August 5, 2020. In this review, we present an overview of recent studies using Machine Learning and, more broadly, Artificial Intelligence, to tackle many aspects of the COVID-19 crisis. We have identified applications that address challenges posed by COVID-19 at different scales, including: molecular, by identifying new or existing drugs for treatment; clinical, by supporting diagnosis and evaluating prognosis based on medical imaging and noninvasive measures; and societal, by tracking both the epidemic and the accompanying infodemic using multiple data sources. We also review datasets, tools, and resources needed to facilitate Artificial Intelligence research, and discuss strategic considerations related to the operational implementation of multidisciplinary partnerships and open science. We highlight the need for international cooperation to maximize the potential of AI in this and future pandemics.
During the last COVID-19 process, it has been seen that artificial intelligence can provide advance information about upcoming epidemics that have not yet been seen worldwide. To this end, the BlueDot company warned, using artificial intelligence algorithms, to abstain about the Chinese city of Wuhan in December 2019. However, the World Health Organization was able to make a similar warning only in January 2020. "BlueDot's outbreak risk software safeguards lives by mitigating exposure to infectious diseases that threaten human health, security, and prosperity" https://bluedot.global/ Thanks to the exploratory analysis and the rapid processing of up-to-date data, companies like BlueDot continue to predict where other Asian city outbreaks may occur by analyzing travel routes and flight paths.
Based out of Singapore, Gero develops new drugs for ageing and other complicated disorders using its proprietary developed artificial intelligence (AI) platform. Recently, the company has secured $2.2 million (€1.9 million) in Series A funding, bringing the total capital raised since Gero's founding to over $7.5 million (€6.4 million). Gero's founder Peter Fedichev, said, "We are happy with the recognition and support from these strategic investors who themselves are acknowledged leaders in the fields of AI and biotechnology. This will help us attain the necessary knowledge at the junction of biological sciences and AI/ML technologies that is necessary for the radical acceleration of drug discovery battling the toughest medical challenges of the 21st century. We hope that the technology will soon lead to a meaningful healthspan extension and quality of life improvements " The round was led by Bulba Ventures with participation from previous investors and serial entrepreneurs in the fields of pharmaceuticals, IT, and AI.
The first question many people ask about artificial intelligence (AI) is, "Will it be good or bad?" The answer is … yes. Canadian company BlueDot used AI technology to detect the novel coronavirus outbreak in Wuhan, China, just hours after the first cases were diagnosed. Compiling data from local news reports, social media accounts and government documents, the infectious disease data analytics firm warned of the emerging crisis a week before the World Health Organization made any official announcement. While predictive algorithms could help us stave off pandemics or other global threats as well as manage many of our day-to-day challenges, AI's ultimate impact is impossible to predict.