- The input to the RNN at every time-step is the current value as well as a state vector which represent what the network has “seen” at time-steps before.
- The weights and biases of the network are declared as TensorFlow variables, which makes them persistent across runs and enables them to be updated incrementally for each batch.
- Now it’s time to build the part of the graph that resembles the actual RNN computation, first we want to split the batch data into adjacent time-steps.
- This is the final part of the graph, a fully connected softmax layer from the state to the output that will make the classes one-hot encoded, and then calculating the loss of the batch.
- It will plot the loss over the time, show training input, training output and the current predictions by the network on different sample series in a training batch.
This is a no-nonsense overview of implementing a recurrent neural network (RNN) in TensorFlow. Both theory and practice are covered concisely, and the end result is running TensorFlow RNN code.
Continue reading “How to Build a Recurrent Neural Network in TensorFlow”
- These are just a few examples of the various Internet of Things (IoT) sensors and other connected devices in Boulder, where electrical, solar and HVAC systems are also tied into IP networks.
- Designing a wireless network to support these applications was a learning process for the city’s IT department, says Benjamin Edelen, a senior system administrator there.
- Aimee Schumm, e-services manager at the Boulder Public Library, notes that staff members made sure to tuck access points in places where they couldn’t be reached easily — such as inside ceiling tiles or on the ceiling itself — so they won’t be tampered with.
- Boulder built out its wireless network with more bandwidth than it needs currently, with the expectation that it will expand its use of IoT sensors and similar technologies in the future.
- Once the IoT sensors were in place, the various city departments generally took ownership of the data, Edelen says.
As the city of Boulder optimized its wireless network to better support IoT sensors, the city’s IT pros found it had a “significant learning curve.”
Continue reading “Designing networks for IoT sensors can be a learning process”
- Well, almost…
“80% Of Marketing Executives Predict Artificial Intelligence Will Revolutionize Marketing by 2020…Yet, Only 10% Are Currently Using It”
Instead of fearing the likelihood that Terminator may happen in the coming years, I’m going to uncover the specific advantages that AI has the potential to bring to your B2B sales team…right now.
- Strong AI, Super Intelligence, Narrow AI, Machine Learning and Deep Learning are terms that often get confused.
- Strong AI is a ‘machine’ that demonstrates behaviour indistinguishable from that of a human being.
- If Strong AI is human-like, Artificial Super Intelligence (ASI) is The Terminator.
- With all variations defined, here are 5 forces of AI to transform your B2B sales methods:
80% Of Marketing Executives Predict Artificial Intelligence Will Revolutionize Marketing by 2020…Yet, Only 10% Are Currently Using It.
Continue reading “The 5 Forces Of Artificial Intelligence In B2B Sales”
- Chen Xiaoping (R), director of a robot research and development team, and Jia Jia, an interactive robot that looks like a real Chinese young woman in traditional outfit, talk through internet with Kevin Kelly on screen, founding executive editor of Wired magazine, in Hefei, capital of east China’s Anhui Province, April 24, 2017.
- Jia Jia was unveiled in 2016 by Chen’s robot research and development team at the University of Science and Technology of China in Hefei.
- “It’s something we could never have imagined,” said Jia Jia’s creator Professor Chen Xiaoping, director of the Robotics Laboratory at the University of Science and Technology of China (USTC) in Hefei, a city in east China’s Anhui Province.
- The first interview conducted by Jia Jia as a special Xinhua reporter on Monday was merely a small step in the era of artificial intelligence (AI), said Chen, who has been long involved in the development of Jia Jia and honored as the “father” of the robot.
- Jia Jia, did a live interview with Kevin Kelly, a U.S. journalist and technology observer, on Monday, which was hailed by scientists as “having symbolic significance” as it was the world’s first interactive conversation between an “AI reporter” and a human being.
Chen Xiaoping (R), director of a robot research and development team, and Jia Jia, an interactive robot that looks like a real Chinese young woman in traditional outfit, talk through internet with Kevin Kelly on screen, founding executive editor of Wired magazine, in Hefei, capital of east China’s Anhui Province, April 24, 2017. Jia Jia was invited as a special reporter of the Xinhua News Agency to conduct the man-machine dialogue with Kelly on Monday. Jia Jia was unveiled in 2016 by Chen’s robot research and development team at the University of Science and Technology of China in Hefei. It took the team three years to research and develop this new-generation interactive robot, which can speak, show micro-expressions, move its lips, and move its body. (Xinhua/Guo Chen)
Continue reading “Feature: This Chinese robot could revolutionize journalism”
- The following are funny pictures related to machine learning or data science I found online.
- I found a lot of the pictures from the following links.
Continue reading “Qingkai’s Blog: Machine learning 10”
- Advancements in AI are creating new opportunities and long with it comes responsibilities.
- How can advancements in Artificial Intelligence benefit society?
- Join Salesforce Chief Scientist, Richard Socher and Nicola Morini Bianzino, Global Lead Artificial Intelligence at Accenture.
Advancements in AI are creating new opportunities and long with it comes responsibilities. How can advancements in Artificial Intelligence benefit society? W…
Continue reading “AI for a Better World”
- Moving beyond a back-end tool for the enterprise, artificial intelligence (AI) is taking on more sophisticated roles within technology interfaces.
- From autonomous driving vehicles that use computer vision, to live translations made possible by machine learning, AI is making every interface both simple and smart–and setting a high bar for how future experiences will work.
- AI is poised to act as the face of a company’s digital brand and a key differentiator – and become a core competency demanding of C-level investment and strategy.
See how Artificial Intelligence plays a wide range of increasingly sophisticated roles in creating better customer interactions at the user interface (UI).
Continue reading “AI as the new UI – Accenture Tech Vision”