Nowhere is the advance of technology more evident than in the rise of robots and artificial intelligence. From smart devices to self-checkout lanes to Netflix recommendations, robots (the hardware) and AI (the software) are everywhere inside the technology of modern society. They're increasingly common in ads, too: During the 2019 Super Bowl alone, seven ads aired featuring either robots or AI. Since I began studying human-robot interactions almost a decade ago, I've observed that in most ads, robots typically fall into one of three general categories: scary, sad or stupid. All three perpetuate common misconceptions about technologies that are already beginning to play a pivotal role in people's lives.

We are said to be standing on the brink of a fourth industrial revolution – one that will see new forms of artificial intelligence (AI) underpinning almost every aspect of our lives. The new technologies will help us to tackle some of the greatest challenges that face our world. In fact AI is already very much part of our daily lives, says Dr Mateja Jamnik, one of the experts who appear in the film. "Clever algorithms are being executed in clever ways all around us... and we are only a decade away from a future where we are able to converse across multiple languages, where doctors will be able to diagnose better, where drivers will be able to drive more safely." Ideas around AI "are being dreamt up by thousands of people all over the world – imaginative young people who see a problem and think about how they can solve it using AI… whether it's recommending a song you'll like or curing us of cancer," says Professor Stephen Cave.

OpenAI, the non-profit organization that researches artificial intelligence, co-founded by Elon Musk in 2016, has been making big advancements -- even after Musk parted ways amid disagreements about its direction. Researchers have developed systems that can play games, write news articles, and move physical objects with groundbreaking levels of dexterity. OpenAI has caused controversy with its research. Last week, it announced the development of a language model, GTP2, that can generate texts with limited prompts. Given the human-written prompt "Miley Cyrus was caught shoplifting from Abercrombie and Fitch on Hollywood Boulevard today," the system produced a believable complete story that continued with "the 19-year-old singer was caught on camera being escorted out of the store by security guards."

After taking healthcare, education, and telecommunication sectors by storm, artificial intelligence (AI) is all decked up to revolutionize the consumer electronics industry within the next five years. As per IBEF'S industry analysis report, Indian consumer electronics market is expected to grow at 41 percent CAGR during 2017-20 to reach $ 400 billion. Evidently, the combination of AI and IoT into the market products is further going to fuel the exponential growth. Though some of the product segments, including smartphones, alarm clocks, watches, etc, have evolved into smart ones, many are going through a rapid AI transformation phase. The application of AI into the industry of consumer electronics opens up many growth avenues and opportunities.

AI - 'artificial intelligence' - promises to bring revolution to many parts of our lives: Smart assistants, fully robotic workplaces, driverless cars, "fake news" propaganda. As the digital world around us becomes smarter, what are the implications socially & economically? And what does the future really hold for us in a world of AI? This interesting and informative talk is delivered by Sven Latham from Noggin. Sven is a self-confessed data and computer geek, using big data & AI to analyse town centres.

Say the phrase "big data," and people tend to picture the TV show Black Mirror. They imagine a creepy dystopian future in which robot overlords control everything. But those fears are overblown. What people should think of when they think of big data is Netflix or Amazon: personalized recommendations and a customized experience that make it easier and faster for the consumer to find what they're looking for. In fact, you could say that, when it comes to big data, consumers worry about Black Mirror but hope for more Netflix.

Our model, called GPT-2 (a successor to GPT), was trained simply to predict the next word in 40GB of Internet text. Due to our concerns about malicious applications of the technology, we are not releasing the trained model. As an experiment in responsible disclosure, we are instead releasing a much smaller model for researchers to experiment with, as well as a technical paper. GPT-2 is a large transformer-based language model with 1.5 billion parameters, trained on a dataset[1] of 8 million web pages. GPT-2 is trained with a simple objective: predict the next word, given all of the previous words within some text. The diversity of the dataset causes this simple goal to contain naturally occurring demonstrations of many tasks across diverse domains. GPT-2 is a direct scale-up of GPT, with more than 10X the parameters and trained on more than 10X the amount of data. GPT-2 displays a broad set of capabilities, including the ability to generate conditional synthetic text samples of unprecedented quality, where we prime the model with an input and have it generate a lengthy continuation. In addition, GPT-2 outperforms other language models trained on specific domains (like Wikipedia, news, or books) without needing to use these domain-specific training datasets. On language tasks like question answering, reading comprehension, summarization, and translation, GPT-2 begins to learn these tasks from the raw text, using no task-specific training data.

What should companies know about AI and the future of work, and what risks can harm the advantages of artificial intelligence?

We already had a robot that could make fast food burgers. And now we have an artificial intelligence that can take your order for one.

Minimax, as the name suggest, is a method in decision theory for minimizing the maximum loss.