Ask a random person for an example of an AI system and chances are he or she will name self-driving vehicles. In this episode of the O'Reilly Data Show, I sat down with Shaoshan Liu, co-founder of PerceptIn and previously the senior architect (autonomous driving) at Baidu USA. We talked about the technology behind self-driving vehicles, their reliance on rule-based decision engines, and deploying large-scale deep learning systems.

An Uber self-driving Ford Fusion sits at a traffic light on Beechwood Boulevard and waits to turn onto Fifth Avenue in Pittsburgh. Among the tenuous notions that have sprouted amid the fervor for autonomous vehicles is that Detroit and Silicon Valley are entwined in a titanic battle for supremacy. What is occurring is a very positive cross-pollination between two hubs of innovation. It is not a zero-sum game in which one industry will win and the other lose. There will be winners -- and occasionally losers -- all over the map.

San Francisco (AFP) - Major technology firms are racing to infuse smartphones and other internet-linked devices with software smarts that help them think like people. The effort is seen as an evolution in computing that allows users to interact with machines in natural conversation style, telling devices to tend to tasks such as ordering goods, checking traffic, making restaurant reservations or searching for information. The artificial intelligence (AI) component in these programs aims to make create a world in which everyone can have a virtual aide that gets to know them better with each interaction. Google is making a high-profile push into AI, with the internet titan's chief referring to it as a force for change as powerful as powerful as smartphones. Google Assistant software is being built into new Pixel handsets -- aiming to outdo Apple's Siri -- enabling users to organize and use information on the devices and in the cloud -- to check emails, stay up to date on calendar appointments, news or ask for traffic and weather data.

I run a small web archive for about twenty thousand people. Being invited to speak at the Library of Congress is like being a kid who glues paper fins to a cardboard tube and then gets asked to talk to NASA about rocket propulsion. As every speaker has correctly said, it is a signal honor to be here. It also feels strange to be speaking in D.C., at the seat of government. In most of the talks I give, the U.S. government is an adversary. But today I am at a government institution that champions not just freedom, but the fundamental right to privacy, and the dignity that that entails. During the panic that followed September 11, Carla Hayden, then head of the American Library Association, took a principled stand against provisions in the Patriot Act that required librarians to reveal what their patrons were reading. She did it in the face of ridicule from Attorney General Ashcroft and the administration. And of course just a few days ago, she became our new Librarian of Congress. It saddens me that those provisions in the Patriot Act, which seemed so threatening and un-American at the time, look almost quaint today. And this time it's not the government, but the commercial Internet that has worked so hard to dismantle privacy.

In computer science, a logistic model tree (LMT) is a classification model with an associated supervised training algorithm that combines logistic regression (LR) and decision tree learning.[1][2] Logistic model trees are based on the earlier idea of a model tree: a decision tree that has linear regression models at its leaves to provide a piecewise linear regression model (where ordinary decision trees with constants at their leaves would produce a piecewise constant model).[1] In the logistic variant, the LogitBoost algorithm is used to produce an LR model at every node in the tree; the node is then split using the C4.5 criterion. Each LogitBoost invocation is warm-started[vague] from its results in the parent node. Finally, the tree is pruned.[3]

Talking to a smartphone as if it were a person may seem strange at first, but chances are you will be getting the weather report, ordering a new laptop or requesting a day off with a chat bot pretty soon… if you aren't doing so already. And this is just the beginning. Using natural language – whether via voice or text – is so powerful because it is so human. People want to talk like humans, not in a limited set of staccato commands that are easy for machines to understand but require us to learn and just plain feel ridiculous. Although the richness of human speech, with its jargons, dialects, and turns of phrase, has taken computer engineers time to master, the technology has evolved rapidly.

Launched by digital health and weight-loss platform Lose It!, the new feature of an already existing app proposes a simple solution to those who struggle to keep track of their caloric intake: Take a photo of your food, and Snap It will immediately display its calorie count Showing people the caloric value of their foods before they eat them can help modify their eating habits. Some studies have shown that keeping a food journal helps people stick to their diet. And in an effort to fight rising obesity rates, the FDA announced in 2014 that chain restaurants throughout the U.S. will have to post calorie information in their menus (the rule is set to go into effect sometime next year). But the FDA rules won't apply to all restaurants. And food diets are cumbersome, tending to go the way of new year's resolutions.

Forget what you've heard: The broad generalization that artificial intelligence systems will steal jobs isn't true. In fact, while AI will replace certain roles, others will sprout and smart machines will make many jobs easier by providing quick access to information. Beyond the job market fears, many technology providers overhype what AI can do or misuse the term to cash in on the trend. Don't allow their artificial statements and false beliefs impede your intelligence on this emerging technology market. A request by the White House for information about the future of artificial intelligence shows a divide between those who embrace intelligent machines and those who worry about a future in which robots run the world.

"Hindi ke liye 1 dabayein, for English press 2…" Is how we are greeted most of the time when we dial any company. From being the first line of defense protecting our borders to becoming the first line of interaction at most places – a feat that is only possible due to rapid advancement Technology that robots are everywhere . Humans have been successful in creating machines to perform routine tasks so that we can spend time on more productive issues. And one such productive issue that we definitely spent our time on is putting brains in those machines – Machine Intelligence or Machine Learning – as it is popularly known as is a field of Computer Science and a brother of Artificial Intelligence is what we are going to talk today, from BIT to BOT – a giant technological leap for mankind! Due to technology we seldom spend time socializing with our friends as we are busy with our virtual lives.

New drugs typically take 12-14 years to make it to market, with a 2014 report finding that the average cost of getting a new drug to market had ballooned to a whopping 2.6 billion. It's a topic I've covered before, with a study published earlier this year highlighting how automation could be used to reduce the cost of drug discovery by approximately 70%. It's an approach that a number of companies are taking to market. For instance, London based start-up Benevolent.AI utilizes complex AI to look for patterns in the scientific literature. They have already managed to identify two potential drug targets for Alzheimer's that has already attracted the attention of pharmaceutical companies.