Hustlers are cashing in on China's OpenClaw AI craze The AI tool has become the country's latest tech obsession. Feng Qingyang had always hoped to launch his own company, but he never thought this would be how--or that the day would come this fast. Feng, a 27-year-old software engineer based in Beijing, started tinkering with OpenClaw, a popular new open-source AI tool that can take over a device and autonomously complete tasks for a user, in January. He was immediately hooked, and before long he was helping other curious tech workers with less technical proficiency install the AI agent. Feng soon realized this could be a lucrative opportunity. By the end of January, he had set up a page on Xianyu, a secondhand shopping site, advertising "OpenClaw installation support."

With advanced AI/ML, there has been growing research on explainable AI (XAI) and studies on how humans interact with AI and XAI for effective human-AI collaborative decision-making. However, we still have a lack of understanding of how AI systems and XAI should be first presented to users without technical backgrounds. In this paper, we present the findings of semi-structured interviews with health professionals (n=12) and students (n=4) majoring in medicine and health to study how to improve onboarding with AI and XAI. For the interviews, we built upon human-AI interaction guidelines to create onboarding materials of an AI system for stroke rehabilitation assessment and AI explanations and introduce them to the participants. Our findings reveal that beyond presenting traditional performance metrics on AI, participants desired benchmark information, the practical benefits of AI, and interaction trials to better contextualize AI performance, and refine the objectives and performance of AI. Based on these findings, we highlight directions for improving onboarding with AI and XAI and human-AI collaborative decision-making.

"At every major inflection point, there has to be an evolution," says Humera Shahid, chief diversity, equity, and inclusion officer and head of talent development at Intuit. "That means the way that we're organized is different, [and] the skill sets that we need are rapidly changing, especially in technology," Shahid says. Intuit has undergone many iterations since its inception in 1983 as a digital checkbook to help people pay bills, later known as Quicken. Over the past four decades, the $13 billion software firm has repeatedly reinvented itself, notably selling Quicken in 2016, then pivoting from operating solely as a tax and accounting platform to a more holistic financial platform for individuals and small businesses. It recently made two big acquisitions in Credit Karma ($8.1 billion) and MailChimp ($12 billion) as part of its data play.

Hyperautomation improves productivity, reduces expenses and generates operational efficiency to help organizations achieve excellence. Hyperautomation means utilizing automated technology to streamline and smoothen every possible process in a company. It allows for repetitive tasks to run without any human guidance or intervention. Hyperautomation is a combination of robotic process automation (RPA), artificial intelligence (AI), and machine learning (ML). Companies tend to get frustrated due to wavering automation processes implemented in their operation.

This course is all about A/B testing. A/B testing is used everywhere. A/B testing is all about comparing things. If you're a data scientist, and you want to tell the rest of the company, "logo A is better than logo B", well you can't just say that without proving it using numbers and statistics. Traditional A/B testing has been around for a long time, and it's full of approximations and confusing definitions.

Speaking to established patent attorney Nick Transier, we explore why there has been a boom in AI and the special considerations behind AI patents.

The ground breaking advancements in Artificial Intelligence (AI) is creating tremendous opportunities for transforming industries and virtually every aspect of our existence. The demand for people well versed with AI skill-set is exploding and it is expected to generate over 50 million new jobs in the coming years. There are thousands of educational materials out there for learning Artificial Intelligence (AI). However, much of AI Tutorials and Courses are without Graded Assignments or Peer Feedback and have a poor quality. So, I decided to inspire your AI journey by compiling the best courses from the world-class educators, so that you can learn to create AI powered applications that can give you an edge in becoming a skilled AI -- Engineer/ Scientist/ Researcher/ Practitioner.

Melissa Mulholland was 16 weeks pregnant with her second child when her doctor noticed something unusual in an ultrasound scan. It was a rare fetal condition called posterior urethral valves, PUV, and it meant her son wouldn't survive the womb without medical intervention. She was fortunate to have a doctor skilled in detecting the condition and intervening to address it, and the good news is that her son, Conor, is now 5 years old. But the experience left Mulholland thinking about the families who aren't so lucky to have such expert health care. She wondered if technology could be a solution. She's not an engineer, and doesn't have a technical background, but she works at Microsoft, so she's familiar with the latest technologies in her role working with the company's cloud customers and partners. She asked a question that not a lot of people would ask: could artificial intelligence help?

Research has found that one of the main hindrances of effective AI deployment within industry, is the inability to demonstrate clear, effective data-strategies with specific results in mind. This course will allow you the unique opportunity to apply effective design thinking methodologies to applied AI and machine learning across a range of industries, to affect positive change within your organization and re-think the way data is being used. This highly interactive and hands-on workshop offers a deep dive into AI, machine learning, and other emerging technologies targeted at leaders responsible for creating disruptive new digital products & services. The program is intended for those with or without a strong background in machine learning, AI, and related technologies - no technical expertise is assumed. Participants can expect to walk away with a comprehensive understanding of how AI and machine learning work as core technologies and a wide range of applications, including; recommendation engines, personalization, predictive analytics, conversational/voice interfaces, and process automation.

Evelyn Berezin, who has died aged 93, invented the Data Secretary, the first electronic word processor for secretarial use, and in 1969 founded a company in Hauppauge, Long Island, to manufacture and sell it. She had bumped into the glass ceiling and it was the only way she could get a senior position running a company. The choice of product was tactical. As one of the few women developing computer hardware at the time, she was a two-finger typist and said she had to stay as far away as possible from looking like a secretary. However, she needed something that a small team could create at a price low enough to sell. In the 1960s, most computers were so expensive that companies rented them.