When the disruptors become the disrupted, you know the second wave of technology has come – and that’s just what is happening when it comes to augmented intelligence. This second wave of AI, which has been described as “a human-centred partnership model of people and AI working together to enhance cognitive performance”, according to CMS wire, is changing the way organisations interact with AI and is so powerful that Gartner believes it will create as much as $2.9 trillion of business value and 6.2 billion hours of worker productivity globally by 2021.
While it might sound like mere semantics, augmented intelligence is about the seamless blending of human knowledge and skills with artificial intelligence to solve problems. Read More
Daily Archives: September 18, 2019
How Avengers: Endgame’s Visual Effects Were Made | WIRED
The Coming Revolution in Recurrent Neural Nets (RNNs)
Recurrent Neural Nets (RNNs) and their cousins LSTMs are at the very core of the most common applications of AI, natural language processing (NLP). There are far more real world applications of RNN-NLP than any other form of AI, including image recognition and processing with Convolutional Neural Nets (CNNs).
In a sense, the army of data scientists has split off into two groups, each pursuing the separate applications that might be developed from these two techniques. In application there is essentially no overlap since image processing is about processing data that is static (even if only for a second) while RNN-NLP has always interpreted speech and text as time series data.
It turns out though that while RNN/LSTMs remain the go-to technique for most NLP, the more we try to expand time series applications the more trouble we run into. What’s on the horizon may not be so much a modification of RNNs but perhaps a hard fork to several other innovative new AI methods. Read More
Temporal Convolutional Nets (TCNs) Take Over from RNNs for NLP Predictions
It’s only been since 2014 or 2015 when our DNN-powered applications passed the 95% accuracy point on text and speech recognition allowing for whole generations of chatbots, personal assistants, and instant translators.
Convolutional Neural Nets (CNNs) are the acknowledged workhorse of image and video recognition while Recurrent Neural Nets (RNNs) became the same for all things language. …
By mid-2017 Facebook and Google had solved the problem of speed of translation by using CNNs combined with the attention function. Read More
Machine Learning Models Mindmap
7 Must-See TED Talks On AI And Machine Learning
When it comes to educational dialogue, there is nothing more entertaining than a great TED talk. They provide insight into fascinating subjects in an entertaining way often filled with stories, mind-blowing facts and first-hand experiences of those giving the talks. With AI and machine learning at the forefront of so many questions and topics now, what better way to get the scoop on it than by enjoying some great speeches from those on the cutting-edge of innovation. Read More
World Catching Up With China on Surveillance Tech
China leads the world in facial-recognition and other new surveillance technologies, with its own government using the tools at home and Huawei Technologies Co. exporting them globally, according to a new report by the Carnegie Endowment for International Peace.
But other countries are adopting similar technologies, according to the think tank’s report, which is based on research by a former State Department official in the Obama administration. Read More
The Chinese Communist Party Wants It All
In Hong Kong, protesters clash with police, but the real power behind the scenes is the Chinese Communist Party (CCP). The experiences of activists in Hong Kong, Taiwan, and even on the Chinese mainland show that the CCP is a ruthless opponent—but not an unbeatable one. The CCP’s sharp power approach should be considered an extension of its united front method, a vision of the political process as a zero-sum game and a worldview that distinguishes between friends and enemies. Since its founding in 1921, the CCP has invested considerable resources to isolate its perceived enemies and has lobbied waverers to support it.
The resulting party-state’s governing approach is thus a two-pronged process of simultaneous co-optation and coercion, where proverbial carrots and sticks are applied to suppress any political opposition to party-state rule. Read More
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