LG Electronics will invest in robots and develop products that combine hardware, contents, and artificial intelligence to work with smart home appliances, a senior executive of the company has said. "We are planning to unveil new robot products by combining [the best] hardware, artificial intelligence, and contents technology that the customer will need," said Jo Seong-jin, LG's home appliance president, in a press conference at the sidelines of the IFA tradeshow in Berlin. "We are also reviewing new businesses that use autonomous driving technology and robot platforms," he said. The firm will utilize the cross-over platform, the Internet of Things, and new robotics technology to evolve the smart home further going forward, the president said. Besides consumer robots, South Korea's second-largest electronics firm already announced it was entering into the enterprise robotics market.

In-demand skills for the IoT include machine learning, data integration, and network connectivity. Placing career bets in IT is something that we do as an ongoing effort. My goal is always to lead, not follow. While I hit some out of the park with that philosophy, there were times when I looked behind me and nobody had followed. Fortunately, I've racked up more wins than losses.

Machine learning has become a core component of companies' analytic initiatives and is no longer the "fine china" only brought out for special occasions, according to a manager with Hewlett-Packard Enterprise, which today announced that its Vertica analytics database now runs popular classes of machine learning algorithms. While previous versions of Vertica could run R algorithms -- as opposed to shipping them off to run on a Hadoop cluster or another adjacent system -- Vertica 8.0 will be the first version of the flagship columnar database that formally supports a broad collection of popular machine learning algorithms, according to Jeff Veis, vice president of marketing for Big Data Platforms at HPE (NYSE: HPE). "It used to be niche, or maybe like fine china for special occasions, to use machine learning, and now it's showing up as a must-have for almost all our customers," Veis tells Datanami. "It's becoming very important to do that form of advanced analytics. We brought that in-database so you can run it across your whole data set."

Work on a new project by Deakin University and Melbourne-based software company Ytek has begun, aimed to develop skills of those training in the emergency response, defence, and aerospace sectors using machine learning algorithms. Dr James Zhang, a researcher from Deakin University's Institute for Intelligent Systems Research and Innovation, is working with Ytek to develop simulation solutions used to train surgeons, emergency workers, soldiers, and pilots. As part of the project, Zhang and Ytek will research how machine learning algorithms can help monitor and evaluate a trainee's conduct in mission-critical simulations by using sensors on training tools, such as manikins, to evaluate how trainers can assess students in practical training. Ytek CEO Richard Yanieri said the desired outcome of the project is to improve the practical training for students. "We've been working with Deakin's School of Medicine to understand their needs so that we can tailor a solution that works for this industry," he said.

It's clear that Messenger is one of the main places where consumers want to communicate and this provides an incredible opportunity to deliver unique experiences to a captive audience and bots are a great way to accomplish this. While it's easy to find great use cases in most verticals, this post will focus on healthcare, specifically medication adherence. Here's a definition of medication adherence: Adherence to, or compliance with, a medication regimen is generally defined as the extent to which a person takes medications as prescribed by their healthcare providers. There's been a big investment in medication adherence and there's good reasons. According to a World Health Organization report (and countless other sources) available in print only "adherence to long-term therapy for chronic illnesses in developed countries averages 50%" and "removing barriers to adherence must become a central component of efforts to improve population health worldwide."

The first intelligent robots that humans interact with on a regular basis will likely be self-driving cars--not a humanoid working in the cubicle next door. Drive.ai, an autonomous vehicle tech startup founded by former graduate students working in Stanford University's Artificial Intelligence Lab, officially came out of stealth mode--a temporary quiet period to avoid alerting competitors--on Tuesday with some details about what it's building and a high-profile addition to its board. Steve Girsky, who sat on the General Motors board for seven years until June, has joined the Drive.ai The Mountain View-based startup, which has raised 12 million from an undisclosed venture capital firm and strategic investors, was forced out of stealth in April when it was awarded a license to test autonomous vehicles in California. But until now, little was known about what Drive.ai was working on. The startup is focused on developing deep learning software--a sophisticated form of artificial intelligence--and applying it to everything the self-driving car does from recognizing objects to making decisions.

Mark Zuckerberg expects artificial intelligence will progress to make computers better than humans at basic sensory perception within the next 10 years, and that Facebook will end up knowing a lot more about you than it does now. The prediction is the latest from a top tech CEO to indicate the fast improvement being made in machine learning systems that just a few years ago would have struggled to recognize a dog from a cat. The Facebook CEO was speaking about core things that humans do, such as seeing, hearing and understanding language and was careful to clarify that computers will still have limited abilities elsewhere. "That doesn't mean that the computers will be thinking or be generally better, but that is useful for a number of things," he told financial analysts on a conference call on Wednesday. In recent months, senior executives at Google have also talked up AI.

What can software designers and ICT specialists learn from maggots? Quite a lot, it would appear. Through understanding how complex learning processes in simple organisms work, EU-funded scientists hope to usher in an era of self-learning robots and predictive computing. Even with limited brain power, an organism can choose the right thing to do in response to external stimuli, which is something that current computational learning theory cannot fully account for. Learning from maggots The EU-funded MINIMAL project, launched in 2014, has focused on the learning processes in a relatively simple animal, the fruit fly larva (maggots).

Zhang Yaqin, president of Baidu Inc, speaks at the global business forum during Baidu Technology Innovation Conference 2016, on Sept 2. [Photo provided to chinadaily.com.cn] Chinese internet giant Baidu Inc seems to be dazzling the world nonstop. Robin Li, its chairman and chief executive, announced "Baidu Brain" on Thursday, the core of the tech company's plans on artificial intelligence, which consists of three parts - artificial intelligence algorithms, computing power and big data. The next day, at the global business forum also during Baidu Technology Innovation Conference 2016, Baidu's President Zhang Yaqin said the company's revenue coming from its global business has more than quintupled by September from a year earlier. Baidu's globalization, along with "Baidu Brain", is the next big vision for the company, said Zhang.

NVIDIA CEO Jen-Hsun Huang made the announcement today during the Baidu World Conference, noting that the companies will unit to merge their individual technical capabilities to crate a new self-driving car architecture from scratch: "end-to-end, top-to-bottom, from the cloud to the car," as Huang explained. Baidu will use the platform created in tandem with NVIDIA to roll out self-driving taxis in China. Though that's the primary purpose for the partnership, the software's applications are numerous, as both Baidu and NVIDIA are working to make it open for other automotive creators to fit with their own plans for self-driving vehicles. NVIDIA already has its own ideas for autonomous cars, with the Drive PX supercomputer for processing data that's inbound from various sensors, a cloud-based 3D map, and an AI operating system. It's called Drive PX 2, and Volvo is already testing it with a set of self-driving vehicles.