Goto

Collaborating Authors

* to NOW


Deep Reinforcement Learning Hands-On: Apply modern RL methods to practical problems of chatbots, robotics, discrete optimization, web automation, and more, 2nd Edition 2, Lapan, Maxim, eBook - Amazon.com

#artificialintelligence

RL development is being driven by several companies and research groups, including Google, Microsoft, and Facebook. It requires lots of investment in research, as there are not that many directions that are developed enough to be able to just take their methods and apply them to a problem. This is similar to how natural language processing and computer vision were several years ago. Having said that, the field of RL is attracting lots of attention, both from researchers and practitioners. This book helps readers to understand RL methods using real-life problems, and make the exciting RL domain accessible to a much wider audience than just research groups or large AI companies.


Horse rides astronaut

#artificialintelligence

"In the past few years, our tolerance of sloppy thinking has led us to repeat many mistakes over and over. If we are to retain any credibility, this should stop. It is hard to say where [we] have gone wronger, in underestimating language or overestimating computer programs." In April, Open AI released a neural network model called DALL-E 2 that blew people's minds; last week a new model came out from Google Brain called Imagen, and it was even better. Both turn sentences into art, and even a hardened skeptic like myself can't help but be amazed.


Pinaki Laskar on LinkedIn: #Autonomousvehicles #sustainability #electricvehicles

#artificialintelligence

AI Researcher, Cognitive Technologist Inventor - AI Thinking, Think Chain Innovator - AIOT, XAI, Autonomous Cars, IIOT Founder Fisheyebox Spatial Computing Savant, Transformative Leader, Industry X.0 Practitioner Reimagining transportation is of critical importance in the race against the climate and equity crises -- making sure people can get where they need to go in a sustainable manner. Self-driving cars could represent a solution to the global transition to carbon neutrality. Despite many advantages, there are societal and environmental implications that cannot be ignored. The biggest environmental issue related to gas engine cars has to do with the emissions they generate. How much AVs actually pollute depend on where they get their electricity from.


Driverless cars make people nervous, but they're already safer than human drivers

#artificialintelligence

People are scared of not being in control. That's partly why so many of us are more scared of flying than of driving: we're not the one flying the plane. Even though the drive to the airport is actually more dangerous than the flight, it feels safer, because we're in control. So it's probably not surprising that, as i reported this week, the public is wary about autonomous vehicles (AVs), also known as self-driving cars. A study by British researchers found that more than half of people were uncomfortable with either using them or sharing a road with them.


This Driverless Semi-Truck Parks Itself If Systems Fail

#artificialintelligence

In the video above, one of Kodiak's trucks can be seen traveling down the highway at 65 miles per hour in the right-most lane. An occupant inside the truck (but not at the wheel) cuts a cable to simulate a sudden loss of communication between the truck and its main computer. That's when Kodiak's Actuation Control Engine kicks in. ACE is Kodiak's fallback system which enables the truck to safely pull over to the side of the road when it notices a crucial system failure. In this circumstance, ACE recognizes the interruption from the cut cable and plots a lane path ahead of the truck to move onto the shoulder and begins to brake.


These 3 technologies could make self-driving cars safer

#artificialintelligence

Fully autonomous vehicles are already operating on city streets, but a study published last year in AI and Ethics reported that 74% of survey respondents said they do not trust AVs nor believe AVs can perform better than a normal driver. However, a number of companies are developing technologies to enhance safety for and around autonomous vehicles in urban areas. According to Statista, 58 million autonomous vehicles are projected to be sold globally in 2030. Cities need to be ready for them. "The nation's city leaders see that AV technology is here so it cannot be ignored or left in a regulatory limbo while it operates on our streets," said Houston city council member and Vice Mayor Pro Tem Martha Castex-Tatum in testimony to the U.S. House of Representatives Committee on Transportation and Infrastructure earlier this year.


The Future Of AI: Careers In Machine Learning - AI Summary

#artificialintelligence

Machine learning is a branch of data science which involves using "data science programs that can adapt based on experience," said Ben Tasker, technical program facilitator of data science and data analytics at Southern New Hampshire University. As the fields of science and engineering continue to advance, artificial intelligence is becoming "a lot less artificial and a lot more intelligent," Tasker said. Because so much about the field of data science in general and AI in particular is new, there are many opportunities to "make your own niche, especially now that many companies have started to invest in the idea of artificial intelligence," Tasker said. AI Engineer: In this role, one may be involved in the different facets of designing, developing and building artificial intelligence models using machine learning algorithms. Big Data Engineer: Overlapping with the role of a data scientist, the person in this role analyzes a company's volume of data known as "big data," and then uses the analyses to mine useful information in support of the company and its business model.


Results of Deep Funding -- Round 1

#artificialintelligence

This marks a new phase in the SingularityNET ecosystem, where we will foster the growth of the platform by supporting projects with AGIX tokens, knowledge and experience. We are very happy to present the projects that have been selected by our engaged community to be awarded with their requested amounts. While the portal was open, a total of 47 proposals were submitted for the $1million worth of AGIX token treasury funds, which made this round a fair success! After reviewing the proposals on their formal compliance to the Deep Funding rules, only 28 made it to the voting round. All of these 28 had more than the required 1% of cast votes, but only a minority of 12 proposals received an average grade of 6,5 or higher.


Parallel computing in Python using Dask

#artificialintelligence

Parallel computing is an architecture in which several processors execute or process an application or computation simultaneously. Parallel computing helps in performing extensive calculations by dividing the workload between more than one processor, all of which work through the calculation at the same time. The primary goal of parallel computing is to increase available computation power for faster application processing and problem solving. In sequential computing, all the instructions run one after another without overlapping, whereas in parallel computing instructions run in parallel to complete the given task faster. Dask is a free and open-source library used to achieve parallel computing in Python. It works well with all the popular Python libraries like Pandas, Numpy, scikit-learns, etc.


Artificial Intelligence Here's How Your Business Can Be Prepare

#artificialintelligence

Artificial Intelligence is poised to have a massive impact on how people and businesses operate. It will transform industries from healthcare to transportation and retail. But it won't just affect things from your favorite apps to your day-to-day life. It's going to have a major impact on your company too. Think about the ways AI could help your company.