Sam Altman is the cofounder of AI research lab OpenAI, which developed the software that took on the humans at Dota 2 . Machines have scored another victory over humans in the ongoing man vs machine saga after a team of AIs working together successfully beat five semi-professional humans at the multiplayer online battle arena (MOBA) video game of Dota 2. 'Silicon beat meat' (as one spectator put it) 2-1. The team of AIs are known as OpenAI Five and they were developed by OpenAI, an artificial intelligence research lab founded by Elon Musk and Y Combinator president Sam Altman. OpenAI's agents previously beat some of the top human players in 1v1 matches but this is the first time a group of agents have come together to beat a team of humans in the top 99.95 percentile at Dota 2. The team modes are harder as they require more coordination and long-term planning. Greg Brockman, OpenAI cofounder and CTO, described the day of play as an "emotional ride" on Twitter.

Intolerance, crusades, national differences, terrorism and interpersonal disagreements – all those to some extent resulted from conflicting religious views.

According to marketing guru, Seth Godin, "Artificial intelligence does a job we weren't necessarily crazy about doing anyway, it does it quietly, and well, and then we take it for granted." Today, we see AI walking boldly across the corridors of any company, any industry, and any business-type. And although artificial, the technology has added a personal touch to the way we shop and trade. AI in e-commerce is enhancing the entire buy-sell experience for both buyers and sellers. AI in e-commerce cannot be discussed without referring to chatbots.

The Japan House in Los Angeles has commissioned a series of art installations solely focused on artificial intelligence, robotics, and 3D printing for August 2018. The exhibits feature clocks with arms that hug you when you walk by, robots with fully formed spin-like vertebrae seamlessly crawling towards the future and wooden archer dolls, engineered to pluck arrows out of a quiver and shoot which was crafted by a ninth-generation Japanese master craftsman. From Aug. 17 to October 10, 2018 design engineer and professor at the University of Tokyo, Dr. Shunji Yamanaka will give a demonstration of Halluc, a robotic vehicle with eight wheels and legs designed to drive or walk over a wide range of obstacles as part of the exhibit Prototyping In Tokyo: A Visual Story of Design-Led Innovation. This is the first time his work has been on exhibit in the US. Yamanaka has designed industrial products ranging from wristwatches for Issey Miyake, to railway cars for the East Japan Railway.

How do you describe a business? There's an interesting little secret that people in IT likely know, but that doesn't always get to the C-Suite. Programming, at its core, is all about creating models. Sometimes those models are of classes of things, sometimes they better describe processes, but it is rare for a piece of software in your organization to not have some relevance to perhaps a few dozen critical types of things. In large enterprises, it's not at all uncommon for that organization to go through a form of fire drill known as "creating the enterprise data model" (in TLA-speak, "EDM").

A decade ago, a group of Internet companies, civil society organizations, academics, and investors launched the Global Network Initiative (GNI), a collaborative effort to promote free expression and protect user privacy on the Internet. Google helped lead this effort and a parallel project devoted to developing a human rights framework for the Internet. In 2010, Google further demonstrated its leadership by making a principled decision to withdraw its search-engine services from China. In a very public way, the company acknowledged the inherent contradiction between Chinese Internet censorship and Google's commitments to its users and the GNI to promote free expression. It was thus disturbing to read recent reports suggesting that Google now is seriously considering re-entering the Chinese market and succumbing to Chinese censorship in exchange for commercial opportunity.

Tesla's second-quarter earnings call included a discussion of the computational hardware system that Tesla uses for its Autopilot driver assistance functionality. Tesla CEO Elon Musk revealed that Tesla is building its own computational hardware, as opposed to the traditional automotive approach of sourcing computational units from semiconductor suppliers. Furthermore, Musk revealed that Tesla's computer is, "an order of magnitude improvement in the frames per second." Musk included the top three leaders of Autopilot on the call: Stuart Bowers (VP of Engineering), Peter Bannon (Director of Silicon Engineering), and Andrej Karpathy (Director of AI). But it's an incredible job by Pete and his team to create this, the world's most advanced computer designed specifically for autonomous operation.

The Apollo 3.0 Launch Event in Mountain View last night highlighted the strides made by the open-source self-driving car project backed by Chinese Internet giant Baidu. The project's leaders announced a new collection of low-speed driving capabilities, such as delivery vehicle driving and self-parking, alongside a wide array of sensors that independent groups can now connect with Apollo software. Apollo is becoming increasingly prominent as a foundation for automotive and technology companies that want to develop autonomous vehicles, but do not want to develop the entire software stack themselves. Two other companies, NVIDIA and Tier IV, also support software stacks that third-parties can use to develop self-driving cars. NVIDIA's DRIVE software platform is tightly coupled to their DRIVE line of computational units.

President Xi Jinping's "Made in China 2025" strategy, unveiled in 2015 and now thrust back into the limelight by President Trump's bellicose stance on trade, holds three important lesson for global industry. This should be a non-controversial statement, but it is not. Economists often mock "the manufacturing fetish" and argue there is no reason to consider manufacturing a better driver of economic growth than any other sector. As economies get richer, they tend to shift from agriculture to industry, and then to services. Manufacturing accounted for nearly 30% of the U.S. economy in the 1950s; it was still 20% in the 1980s; today it accounts for just 11%.

It drains your productivity, builds frustration, and ultimately makes the broader computing experience one big mess. You can dramatically improve your PC's performance with these tools. But there's also little you can do to stop the slow descent into obsolescence. The technology world is changing at a rapid rate and as technology improves and new computers, apps, and services launch, older machines become old and less relevant. Still, there are ways to extend the longevity of your machine.