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Artificial Intelligence Explained in Simple Terms

#artificialintelligence

There are many great articles about Artificial Intelligence (AI) and its benefits for business and society. However, many of these articles are too technical for the average reader. I love reading about AI, but I sometimes think to myself, 'Gee, I wish the author had explained this in simple English.' I will try and explain AI and its related technologies in simple terms, using real-life examples, as though I were talking to someone at a party. Your colleagues or your (close) friends may tolerate your endless and complex ramblings, but I guarantee you that people at parties are far less forgiving.


AI And SAP: Beneficial Combination? - e3zine – E-3 Magazine International

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For the longest time, artificial intelligence (AI) was nothing more than exciting material for science fiction novels and movies. In 1982, Harrison Ford was hunting down replicants in'Blade Runners'; in 2001, Steven Spielberg wove an intricate tale of a relationship between human and machine in'A. Technologies that emulate or surpass human skills and characteristics are fascinating – not only on the big screen. For decades, scientists have dedicated time and money to the topic of artificial intelligence. The workshop'Dartmouth Summer Research Project on Artificial Intelligence', held in 1956 at Dartmouth College in New Hampshire, USA, is seen as the starting point of AI as academic subject.


This AI tool generates your creepy lookalikes to trick facial recognition

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If you're worried about facial recognition firms or stalkers mining your online photos, a new tool called Anonymizer could help you escape their clutches. The app was created by Generated Media, a startup that provides AI-generated pictures to customers ranging from video game developers creating new characters to journalists protecting the identities of sources. The company says it built Anonymizer as "a useful way to showcase the utility of synthetic media." The system was trained on tens of thousands of photos taken in the Generated Media studio. The pictures are fed to generative adversarial networks (GANs), which create new images by pitting two neural networks against each other: a generator that creates new samples and a discriminator that examines whether they look real. The process creates a feedback loop that eventually produces lifelike profile photos.


Making AI Accessible to Any Size Enterprise - insideHPC

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Experience tells us that there is a relationship between organizational size and technology adoption: Larger, more resource-rich, enterprises generally adopt new technologies first, while smaller, more resource constrained organizations follow afterward, (provided that the small organization isn't in the technology business). This pattern has repeated itself for multiple generations across a myriad of technologies. However, once smaller organizations get ahold of a technology, their creativity can drive it in ways that nobody ever imagined. Case in point: The personal computer, which was originally deployed at large companies primarily to do word processing and spreadsheets, but within a decade was being used to compose music, control buildings, front-end complex medical devices, and thousands of other applications. Lenovo, NetApp and NVIDIA have teamed up to help drive Artificial Intelligence (AI) into smaller organizations and hopefully seed that creative garden.


This AI tool generates your creepy lookalikes to trick facial recognition

#artificialintelligence

If you're worried about facial recognition firms or stalkers mining your online photos, a new tool called Anonymizer could help you escape their clutches. The app was created by Generated Media, a startup that provides AI-generated pictures to customers ranging from video game developers creating new characters to journalists protecting the identities of sources. The company says it built Anonymizer as "a useful way to showcase the utility of synthetic media." The system was trained on tens of thousands of photos taken in the Generated Media studio. The pictures are fed to generative adversarial networks (GANs), which create new images by pitting two neural networks against each other: a generator that creates new samples and a discriminator that examines whether they look real. The process creates a feedback loop that eventually produces lifelike profile photos.


The impact of machine learning & AI on advertising in a privacy compliant age

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Sian Williams, Audience Strategy and Planning Director at MediaCom North, explains how AI offers a future of increased automation, faster decision-making and'hyper-personalisation' that will make marketing comms more effective and businesses more efficient. Robots are science fact not fiction, machines may well inherit the earth, and artificial intelligence can actually enhance the way we engage with human intelligence. As more interactions become digitised, the data landscape is only getting bigger and AI, and within it machine learning, will increasingly fuel that growth. The two terms are often used inter-changeably but whilst AI creates the structure of computational human intelligence it is machine learning that, sans specific programming, delivers on how quickly and effectively data will be processed and decisioned against. If AI is the brain itself, full of raw potential, then machine learning is at least one of the'cortexes' able to process information and develop intelligence and skill by using one'experience' to inform another.


Google AI Launches 'Hum to Search': A New Machine Learning System That Helps To Find A Song By Humming

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Google recently launched Hum to Search, a new machine-learned system within Google Search that helps to find a song by humming. This approach produces an embedding of a melody directly from a song's spectrogram without creating an intermediate representation. This allows the model to match a hummed tune to the original polyphonic recordings without a MIDI (Musical Instrument Digital Interface) version of each track or any other complex hand-engineered logic to extract the melody. One of the significant challenges in recognizing a hummed melody is that a hummed tune often contains relatively less information; for instance, this hummed example of Bella Ciao is illustrated. Using the image on the left, the model needs to locate the audio corresponding to the right-hand image.


Role of Artificial Intelligence in Web Development Process - ONPASSIVE

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Companies apply Artificial Intelligence and relevant applications to change their business like never before, completely restarting how organizations execute, contend, and prosper. Implemented responsibly, people use AI to expand away how humans stay and activities. AI is now transitioning to the mainstream. The technology used earlier limited to robots and sci-fi movies will now assist people in improving their bios. Several applications are already created in image recognition, speech recognition, statistical analysis, and far more.


Brutalist AI-generated buildings feature in hypnotic Moullinex music videos

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Lisbon musician Moullinex has shared an exclusive short music video showing an endlessly changing landscape of brutalist buildings drawn up by a generative design algorithm with Dezeen. Moullinex, whose real name is Luís Clara Gomes, created two videos that use artificial intelligence (AI) to imagine a series of brutalist buildings. The first video, which the artist shared on his Facebook page, is based on 200 photographs of modernist, concrete buildings. These images acted as the dataset, which was used to train a generative network via the machine learning tool StyleGAN2, to create a string of entirely non-existent buildings with similar characteristics. "It's akin to showing thousands of pictures of a cat to a child and then asking them to draw a brand new cat based on what they now know are cat-like characteristics," Gomes told Dezeen.


5 Ways to Improve User Experience with Machine Learning - SitePoint

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Hollywood filmmakers love to present artificial intelligence as an intelligent agent who's more capable than humans. Luckily, we haven't reached this state -- yet. We still need engineers to develop innovative algorithms and tools to improve human interactions with software and systems. Don't worry -- we can't solve user experience with machine learning, nor are we close. Machine learning has matured over the years, allowing us to gain more insights from the data we collect.