Goto

Collaborating Authors

How to Train a Robot-Agent CartPole Using Q-Learning

#artificialintelligence

Q-learning is a model-free reinforcement learning algorithm to learn a policy telling an agent what action to take under what circumstances. It does not require a model of the environment, and it can handle problems with stochastic transitions and rewards, without requiring adaptations. For any finite Markov decision process (FMDP), Q-learning finds an optimal policy in the sense of maximizing the expected value of the total reward over any and all successive steps, starting from the current state. Q-learning can identify an optimal action-selection policy for any given FMDP, given infinite exploration time and a partly-random policy. "Q" names the function that returns the reward used to provide the reinforcement and can be said to stand for the "quality" of an action taken in a given state.


To train better AI, scientists are studying your weird tweets

#artificialintelligence

One of the biggest challenges for language-processing artificial intelligence is figuring out the underlying meaning of slang, colloquialisms, and intentional misspellings. In order to help those hapless machines out, a team of mathematicians from the University of Vermont started to analyze how young people deliberately stretch words when they type. For instance, they've quantified the semantic difference between stretched words like "hahaha" and "haaahaha" in hopes that future AI algorithms can learn to understand us in the informal ways we actually communicate online. In their research, published Wednesday in the journal PLOS One, the team analyzed the so-called "stretchable words" that appeared in 100 billion tweets posted over the past eight years. They then came up with two measurements: balance and stretch.


Survival of the Quickest: How to Hack a Pandemic with Intelligent Automation - Appian Blog

#artificialintelligence

Nobody knows for sure what the post-COVID world will look like. But you can certainly bet it's going to be different. The pandemic has already pummeled the global economy and exposed weaknesses in supply chains and vintage software systems. But it has also accelerated automated delivery of goods and services, autonomous customer interactions and forced companies once skeptical of work-from-home culture to embrace it more than ever before. "And, yet, for many executives," says Muthulakshmi (Lakshmi) N, Global Head, Intelligent Process Automation and AI at Tata Consultancy Services (TCS), "a major roadblock to scaling automation is the misconception that aggressive, holistic automation will produce widespread job loss. But this view fails to imagine the new types of jobs that will be created when automation frees employees from work that can be done faster, better, and less expensively by artificial intelligence (AI)."


Foxconn launches iAI Institute aimed to train people in industrial artificial intelligence

#artificialintelligence

The Foxconn Technology Group is getting in the online education game. On Friday Foxconn launched the iAI Institute "an initiative focused on training the workforce of tomorrow and sharing Industrial AI knowledge across industries." The iAI Institute plans to help train people in industrial artificial intelligence. Individuals can watch online lectures or companies can purchase course packages using "points" although it is unclear as to how someone can collect points. It also allows people to access different data sets for "fault detection" on machines like wind turbines, train bogeys, gearboxes and other data sets.


Elon Musk Reveals How Close Tesla Is to Full Self-Driving Cars At China AI Conference

#artificialintelligence

Elon Musk delivers a remote speech at the World Artificial Intelligence Conference on Thursday. Tesla CEO Elon Musk delivered a brief speech via remote video to the attendants of this year's World Artificial Intelligence Conference (WAIC) in Shanghai, China on Thursday, kicking off the country's most important tech conference. Musk answered questions about Tesla's latest development in artificial intelligence, a central piece of technology behind the company's "Autopilot" semi-autonomous driving system. China is Tesla's biggest market outside the United States. Since introducing the first version of Autopilot in 2014, Tesla has upgraded the system multiple times.


55

#artificialintelligence

Can artificial intelligence be deployed to slow down global warming, or is AI one of the greatest climate sinners ever? That is the interesting debate that finds (not surprisingly) representatives from the AI industry and academia on opposite sides of the issue. While PwC and Microsoft published a report concluding that using AI could reduce world-wide greenhouse gas emissions by 4% in 2030, researchers from the University of Amherst Massachusetts have calculated that training a single AI model can emit more than 626,000 pounds of carbon dioxide equivalent--nearly five times the lifetime emissions of the average American car. The big players have clearly understood that the public sensibility towards climate change offers a wonderful marketing opportunity. IBM has launched its Green Horizons project to analyze environmental data and predict pollution.


Google AutoML Vision for Image Classification

#artificialintelligence

Google's AutoML lets you train custom machine learning models without having to code Training high-performance deep networks is often a big task especially for those who have less experience in deep learning or AI. Also, we might require GPU in addition to RAM and CPU. I experienced a lot of issues while trying to classify with CNN. What if I said Google AutoML Vision will solve our problems? Yes, AutoML Vision enables us to train custom machine learning models to classify our images according to our own defined labels.


AI 50 Founders Predict What Artificial Intelligence Will Look Like After Covid-19

#artificialintelligence

Transportation "can also become truly contactless if needed," says James Peng, who is CEO of ... [ ] self-driving startup Pony.ai. The first few months of 2020 have radically reshaped the way we work and how the world gets things done. While the wide use of robotaxis or self-driving freight trucks isn't yet in place, the Covid-19 pandemic has hurried the introduction of artificial intelligence across all industries. Whether through outbreak tracing or contactless customer pay interactions, the impact has been immediate, but it also provides a window into what's to come. The second annual Forbes' AI 50, which highlights the most promising U.S.-based artificial intelligence companies, features a group of founders who are already pondering what their space will look like in the future, though all agree that Covid-19 has permanently accelerated or altered the spread of AI. "We have seen two years of digital transformation in the course of the last two months," Abnormal Security CEO Evan Reiser told Forbes in May.


Building Knowledge on the Customer Through Machine Learning

#artificialintelligence

Identifying the total value generated by a customer in the entire customer life cycle would help companies in business campaigns and in other activities. So naturally Customer Relationship Management (CRM) becomes a key element of modern marketing strategies. The cost of acquiring new customers is high, so companies are spending more on customer loyalty and retention. Identifying the total value generated by a customer in the entire customer life cycle would help companies in business campaigns and in other activities. So naturally Customer Relationship Management (CRM) becomes a key element of modern marketing strategies.


Why We Need to Be Careful of the Algorithms

#artificialintelligence

Ultimately, the future of AI will be a partnership between humans and machines. As long as humans are the masters, and machines are the ones doing all the heavy lifting, things should be OK. The real problem – and the one that causes tech visionaries like Elon Musk and Bill Gates the greatest anxiety over the future of AI – is that humans might one day decide to hand over some of their management and oversight authority to the machines. They won't do so on purpose, of course. But just like many of us are perfectly OK with Silicon Valley AI algorithms determining what we see, hear and read on social media, many of us might also decide that it's safer, cheaper or more convenient to rely on AI doctors or AI soldiers.