Data visualization: In this section, you will learn how to create simple plots like scatter plot histogram bar, etc. Data manipulation: You will learn in detail about data manipulation. GUI Programming: This section is a combination of life instructor-led training and self-paced learning. Developing web Maps and representing information using plots: In this section, you will understand how to design Python applications. Computer vision using open CV and visualization using bokeh: You will also learn designing Python application in the section.

As society turns to artificial intelligence to solve problems across ever more domains, we're seeing an arms race to create specialized hardware that can run deep learning models at higher speeds and lower power consumption. Some recent breakthroughs in this race include new chip architectures that perform computations in ways that are fundamentally different from what we've seen before. Looking at their capabilities gives us an idea of the kinds of AI applications we could see emerging over the next couple of years. Neural networks, composed of thousands and millions of small programs that perform simple calculations to perform complicated tasks such as detecting objects in images or converting speech to text are key to deep learning. But traditional computers are not optimized for neural network operations.

NEW DELHI: Google has launched an artificial intelligence (AI) research lab in Bengaluru to "tackle big problems", the technology giant announced on Thursday during its fifth edition of Google for India event. Other key announcements at the flagship event included its partnership with BSNL to bring "fast, reliable and secure public WiFi to villages in Gujarat, Maharashtra and Bihar" and with National Skills Development Corporation (NSDC) for their Skill India programme to make entry-level jobs easily discoverable online. According to Google, the lab will be led by Manish Gupta, a SEM (Society for Experimental Mechanics) fellow. Director of Harvard Centre for Computation & Society, professor Milind Tambe, will serve as director of AI for social good. "Professor Tambe will build a research programme around applying AI to tackle big problems in areas like healthcare, agriculture, or education," the company said.

This piece has been published as part of Slate's partnership with Covering Climate Now, a global collaboration of more than 250 news outlets to strengthen coverage of the climate story. Artificial intelligence is getting smarter, but it isn't getting cleaner. In order to improve at predicting the weather, sorting your social media feeds, and hailing your Uber, it needs to train on massive datasets. A few years ago, an A.I. system might have required millions of words to attempt to learn a language, but today that same system could be processing 40 billion words as it trains, according to Roy Schwartz, who researches deep learning models at the Allen Institute for Artificial Intelligence and in the University of Washington's computer science and engineering department. All that processing takes a lot of energy.

Artificial Intelligence (AI) is no longer a science fiction whimsy, but an everyday reality. AI is now embedded in many aspects of our lives, from supermarket self-checkout cash registers to face-recognition security checks at the airport. Tech giants such as Microsoft and Google are investing millions of dollars in new AI projects. Initiatives such as a Teachable Machine, which trains computer neural network, are making Machine Learning (ML) user-friendly. Technologies such as neural networks and deep learning are being applied in many sectors by companies like Facebook and IBM.

Automation and innovation in the work within business is necessary for the reinvention of the system landscapes. The same is possible with the machine learnings together with the help of the artificial intelligence platform. The industries in the recent time are in the tremendous need of the artificial intelligence platform to increase automation, machine interaction and to save time. Furthermore, problem-solving, social intelligence and general intelligence can also be achieved with the help of the artificial intelligence platform. The artificial intelligence platform market is expected to grow during the forecast period due to growth in adoption of cloud based application and services.

A new law in Illinois will regulate the use of artificial intelligence in job interviews. The Artificial Intelligence Video Interview Act, House Bill 2557, requires companies to notify the applicant when the system is being used, explain how the AI works, get permission from the applicant, limit distribution of the video to people involved with the process and to destroy the video after 30 days. Matthew Jedreski, counsel at Davis Wright Tremaine LLP in Seattle, is a litigator and employment attorney who updates clients on local and state employment laws. Jedreski said AI video interviews apply psychometrics, which is the science of measuring attitude and personality traits. "It's reading data and then analyzing it to determine whether it can draw conclusions about the person being interviewed," Jedreski said.

The Pentagon is figuring ways to harness artificial intelligence (AI) for advantages as far flung as battlespace autonomy, intelligence analysis, record tracking, predictive maintenance and military medicine. AI is a key growth investment area for DoD, with nearly $1 billion allocated in the 2020 budget. The Defense Department's Joint Artificial Intelligence Center (JAIC) will see its budget double to over $208 million, with significant increases likely in 2021 and beyond. JAIC seeks to coordinate all military service and defense agency artificial intelligence activity over a $15 million benchmark. The military is currently seeking to integrate AI into weapon systems development, augment human operators with AI-driven robotic maneuver on the battlefield and enhance the precision of military fires.

Only 20 per cent of the 530 million Indian internet users consume content in English. According to a recent report by research and consulting firm RedSeer, 260 million Indian users are "monetizable". Nearly 210 million of these users, with an annual spending power of $300 billion, prefer digital content in vernacular languages. "India has added Internet users at 8X speed in the last 10 years driven by small towns and villages, not by large cities," the report stated. Most of such people used to go to an agent when they wanted to book a train ticket for their next Vaishno Devi trip with their family, wanted an instance plan and wanted someone to help them with a purchase.

This paper presents an initial design concept and specification of a civilian Unmanned Aerial Vehicle (UAV) management simulation system that focuses on explainability for the human-in-the-loop control of semi-autonomous UAVs. The goal of the system is to facilitate the operator intervention in critical scenarios (e.g. avoid safety issues or financial risks). Explainability is supported via user-friendly abstractions on Belief-Desire-Intention agents. To evaluate the effectiveness of the system, a human-computer interaction study is proposed.