If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
The development of a vaccine to protect against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an urgent biomedical need. Yu et al. designed a series of prototype DNA vaccines against the SARS-CoV-2 spike protein, which is used by the virus to bind and invade human cells. Analysis of the vaccine candidates in rhesus macaques showed that animals developed protective humoral and cellular immune responses when challenged with the virus. Neutralizing antibody titers were also observed at levels similar to those seen in humans who have recovered from SARS-CoV-2 infection. Science , this issue p.  The global coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has made the development of a vaccine a top biomedical priority. In this study, we developed a series of DNA vaccine candidates expressing different forms of the SARS-CoV-2 spike (S) protein and evaluated them in 35 rhesus macaques. Vaccinated animals developed humoral and cellular immune responses, including neutralizing antibody titers at levels comparable to those found in convalescent humans and macaques infected with SARS-CoV-2. After vaccination, all animals were challenged with SARS-CoV-2, and the vaccine encoding the full-length S protein resulted in >3.1 and >3.7 log10 reductions in median viral loads in bronchoalveolar lavage and nasal mucosa, respectively, as compared with viral loads in sham controls. Vaccine-elicited neutralizing antibody titers correlated with protective efficacy, suggesting an immune correlate of protection. These data demonstrate vaccine protection against SARS-CoV-2 in nonhuman primates. : /lookup/doi/10.1126/science.abc6284
It has been theorized that positive intergroup relations can reduce prejudice and facilitate peace. However, supporting empirical evidence is weak, particularly in the context of real-world conflict. Mousa randomized Christian Iraqi refugees to soccer teams that were composed of either all Christian players or a mixture of Christian and Muslim players (see the Perspective by Paluck and Clark). Playing on the same team as Muslims had positive effects on Christian players' attitudes and behaviors toward Muslims within the context of soccer, but these effects did not generalize to non-soccer contexts. These findings have implications for the potential benefits and limits of positive intergroup contact for achieving peace between groups. Science , this issue p. ; see also p.  Can intergroup contact build social cohesion after war? I randomly assigned Iraqi Christians displaced by the Islamic State of Iraq and Syria (ISIS) to an all-Christian soccer team or to a team mixed with Muslims. The intervention improved behaviors toward Muslim peers: Christians with Muslim teammates were more likely to vote for a Muslim (not on their team) to receive a sportsmanship award, register for a mixed team next season, and train with Muslims 6 months after the intervention. The intervention did not substantially affect behaviors in other social contexts, such as patronizing a restaurant in Muslim-dominated Mosul or attending a mixed social event, nor did it yield consistent effects on intergroup attitudes. Although contact can build tolerant behaviors toward peers within an intervention, building broader social cohesion outside of it is more challenging. : /lookup/doi/10.1126/science.abb3153 : /lookup/doi/10.1126/science.abb9990
We usually don't expect the image of a teacup to turn into a cat when we zoom out. But in the world of artificial intelligence research, strange things can happen. Researchers at Germany's Technische Universität Braunschweig have shown that carefully modifying the pixel values of digital photos can turn them into a completely different image when they are downscaled. What's concerning is the implications these modifications can have for AI algorithms. Malicious actors can use this image-scaling technique as a launchpad for adversarial attacks against machine learning models, the artificial intelligence algorithms used in computer vision tasks such as facial recognition and object detection.
Numbers can be multiplied, subtracted and squared in a vacuum, alone in a room. Books, too, on almost any subject, can be processed independently. Emotions, on the other hand, are typically experienced -- and learned -- in context, among people, in a social environment. That's why some California parents are concerned that virtual learning, mandated in areas that have seen a spike in coronavirus cases, might impede their school-age children's social and emotional learning. Experts agree it's not something to take lightly.
TensorFlow Extended (TFX), a TensorFlow based general-purpose machine learning platform provides orchestration of many components--a learner for generating models based on training data, modules for analyzing and validating both data as well as models, and finally infrastructure for serving models in production. The platform is particularly known for training, validation, visualization, and deployment of fresh newly trained models in production continuously relatively quickly. The individual components can share utilities that allow them to communicate and share assets.
The growth of the internet due to social networks such as facebook, twitter, Linkedin, instagram etc. has led to significant users interaction and has empowered users to express their opinions about products, services, events, their preferences among others. It has also provided opportunities to the users to share their wisdom and experiences with each other. The faster development of social networks is causing explosive growth of digital content. It has turned online opinions, blogs, tweets, and posts into a very valuable asset for the corporates to get insights from the data and plan their strategy. Business organizations need to process and study these sentiments to investigate data and to gain business insights(Yadav & Vishwakarma, 2020).
While everyone agrees on the name, there is less consensus on what predictive maintenance really means or how to implement it in industrial operations. But to truly unlock the potential of predictive and industrial maintenance, it needs to be paired with artificial intelligence (AI) and machine learning (ML). Read this whitepaper to get the low down on this approach and its business value.
Developers of artificial intelligence ("AI") continue to push the technology to the next level; not a week goes by without a news story claiming that the next big thing has arrived. One popular recent example is OpenAI's latest machine learning system called GPT-3, which was trained on 45TB of text data and has been pounced upon by fellow developers and commentators alike. Its potential is vast but we are still in the early days of the AI revolution. However, as the AI available to be used grows more powerful, it becomes ever more important to consider the ethical and legal issues involved. In this context, the Information Commissioner's Office ("ICO"), the independent authority in the UK for enforcing data protection laws, has released its "Guidance on AI and Data Protection".
There's no denying the fact that Deep Learning as we know it, how awesome it is when we can see that with minimal or no human-intervention a job can be done. Since, Machine Learning, Deep Learning is dubbed to be one of the sexiest jobs of the 21st century(hyped?) so there has to be some starting point, a sort of a roadmap that you can follow to reach to the other side. Luckily, we can now approach it relatively easier with modern frameworks like Tensorflow, PyTorch which gives you a high-level interface to build awesome stuff! Let's discuss why you should start with PyTorch. That means line-by-line execution of the code and simultaneous building of the computation graphs just like in python.