We first created our chatbots for learning more than 2 years ago, to experiment with the pedagogical impact on learning. What we found was astonishing. These ratings would have been extremely commendable for classroom training and with online learning, typical ratings are usually much lower. With our newly created chatbots for learning and Artificial Intelligence (AI), we also won 2 national tech-enabled learning innovation competitions in Singapore at the national level (in 2017 and 2018). The message that we received was the need for users to see eLearning as interaction with human experts rather than with books and chatbots plugged that gap with persona-based chatbots. This conversational approach made learning fun, less formal, more timely and customized.

With the advent of Artificial Intelligence in every imaginable sphere that matters, it is hardly surprising that innovators are now in a rush to build their Intellectual Property portfolio in AI. The popularity of Artificial Intelligence, machine learning, neural networks and all other things related to Intelligent machines has been on the rise for quite some time now. A similarly whopping growth has been observed in the number of machine learning or AI-related patents/applications which have been filed in recent years. A recently published article revealed that patent applications based on machine learning have nearly quadrupled in the last few years, owing to the widespread use of the same in all major technological fields. Since the formal conception of Artificial Intelligence and machine learning, way back in the 50s, more than 300,000 patent applications and over a million scientific journals have been published.

New Delhi: Government is exploring Artificial Intelligence (AI) for tackling the burden of tuberculosis (TB) in India.

The increasing penetration of internet of things (IoT) in the agriculture industry, popularity of cattle facial recognition software, and decreasing price of sensors are instrumental in driving the artificial intelligence (AI) market in agriculture forward. In 2016, the market generated a revenue of $110.3 million and is projected to grow at a CAGR of 23.2% during the forecast period (2017–2023). The substitution of human intelligence and manual efforts by computer-aided technology in gardening and farming applications is referred to as AI in agriculture. The AI market in agriculture is witnessing the trend of robotics in agricultural practices. Farming has become modernized with the growing research and development activities in the field of robotics.

Globally, banks have 10–15% of their staff dedicated to compliance on average. According to a study cited in the Cost of Compliance 2018 Report, on average, regulatory divergence (costs, risks, impacts) costs financial institutions 5–10% of their annual turnover. This consumes senior management's time, as well as capital that could otherwise be focused on identifying emerging risks in the financial system. Ultimately, these costs are a barrier to international growth – the findings conservatively infer more than $780 billion annually in costs to the global economy. These challenges have given rise to a new kind of player – Regulatory Technology (RegTech) startups.

Shanghai is on course to build itself into an artificial intelligence nexus with global influence by fostering research and development platforms, industrial clusters and pilot projects, the city's Party secretary Li Qiang said on Thursday. Speaking at the opening ceremony of the second World Artificial Intelligence Conference in Shanghai, Li stressed the importance of "openness", "innovation" and'inclusiveness" in achieving the long-term AI ambitions of the metropolis. Efforts to catapult Shanghai to the AI front line include establishing cutting-edge innovation platforms that can accommodate various application scenarios, piloting some of the latest AI research in the city and making breakthroughs in AI data sharing, technology promotion and market access, he added. Li said that Shanghai has chosen AI as a strategic priority and has taken frequent measures to accelerate AI's development by forging a benign ecosystem featuring comprehensive production factors, openness and coordination. Earlier achievements in pushing the AI revolution forward include setting up fundamental research platforms in realms like brain science and integrated circuits, expanding industrial clusters that can house a growing number of industry titans and local startups and accelerating construction of a national pilot program, he said.

President Trump's personal assistant, Madeline Westerhout, resigned from the White House amid allegations she shared private information about the president to reporters. President Trump on Friday expressed disappointment over what he described as the "unfortunate" departure this week of his personal assistant Madeleine Westerhout over "hurtful" comments she made to reporters at a recent off-the-record gathering, saying Westerhout explained to him she was "drinking" at the time. "She told me she was very upset," Trump told reporters before boarding Marine One. She said she was drinking." On Thursday, it was reported that Westerhout abruptly left her job after it was determined she shared private information about the president and his family with reporters near Bedminster, N.J., where Trump was on vacation. According to Trump, "She was with reporters and everything she said was off the record." But some of her comments made their way back to the White House. "I think the press was very dishonest," he said. "Because it was supposed to be off the record." The president didn't cite what Westerhout said – but said her comments were a "little bit hurtful." "You don't say things like she said," she said. According to Politico, Westerhout shared intimate details about the president's family – including about daughters Ivanka and Tiffany -- during the dinner with reporters "Tiffany is great," Trump said Friday, in response to those reports. Westerhout served as a gatekeeper to the president, having a desk outside the Oval Office. Trump said: "She's a very good person.

Machine learning is usually applied to man-made targets -- masses of data about the contents of a digital image, or the movement of cars through a city. This week, however, a new study applied the approach to find order in an equally chaotic mass of data: the cell. By using an advanced machine learning approach, a team of researchers from the University of Texas was able to sift through years of experimental data to understand how tadpole cells control their own development, and then used that understanding to take control of the cells themselves. It's a breakthrough they think they can apply directly to developing all new treatments for cancer. When it comes to cancer, cellular control is the whole ball game.

Kathleen Siminyu is a data scientist & machine learning engineer who is Regional Coordinator for the Artificial Intelligence for Development – Africa Network. She is Co-Founder of the Nairobi Women in Machine Learning & Data Science community, and part of the Deep Learning Indaba Steering Committee. Her other interests include natural language processing for African languages and low-cost hardware robotics. We share this story as a demonstration of how AI can indirectly bring people together and empower communities instead of downgrade, divide, or discriminate against them. We believe that community leaders have an important role to play in defining humanity's place in a world of algorithms.