Tag: Business For Sale

Here’s why your laptop keyboard stinks

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About six years ago, some engineers at Razer got the idea to put a mechanical keyboard into a laptop. The goal was to bring the satisfying clickiness of classic desktop keyboards–and Razer’s gaming keyboards in particular–to the company’s sleek gaming notebooks. After years of working through a wide range of engineering challenges, the Razer Blade Pro launched in 2016, debuting what Razer called the “World’s First Ultra-Low-Profile Mechanical Keyboard” in a laptop. It should have been a triumph, both for PC gamers and for serious typists. Instead, it was a bust. A new version of the Blade Pro, which Razer announced last month, will abandon mechanical keys for a more traditional laptop keyboard. “Razer has received positive sentiment from consumers regarding the tactile feedback of the Razer Blade 15 keyboard,” the company said in a statement, “so we decided to deploy that technology in the Razer Blade Pro.” The sad demise of the Blade Pro’s mechanical keyboard is a prime example of why today’s laptop keyboards are, for the most part, not so great. The race to make laptops slimmer and smaller has put the squeeze on even the most well-established keyboard designs, let alone ambitious new ones like Razer’s mechanical keys. The most fertile ground now for laptop keyboard innovation is in making them even thinner without rendering them intolerable, rather than truly excellent. And as Apple has experienced with its Macbooks’ failure-prone “butterfly” keyboard mechanisms , those efforts can backfire. In other words, as laptops follow phones and tablets into the realm of ultrathin designs with edge-to-edge screens, they’re ruining one of the defining features that would lead you to use a laptop in the first place. Read More …

“Machine teaching” is a thing, and Microsoft wants to own it

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Microsoft is rallying behind a new buzzword as it tries to sell businesses on artificial intelligence. It’s called “machine teaching,” and it’s loosely defined by Microsoft as a set of tools that human experts in any field can use to train AI on their own. After steadily developing and acquiring some of these tools, Microsoft is hoping to popularize the concept of machine teaching with a big public push . The hope is that more companies will build their own AI software—running on Microsoft’s cloud computing platform, of course—even if they haven’t hired their own AI experts. “We believe that this is going to be one of the big transformative forces of how AI can be applied to a lot more scenarios and be available to a lot more people in the world,” says Gurdeep Pall, Microsoft’s corporate vice president of business AI. Closing the chasm Microsoft pitches machine teaching as a complement to machine learning, which refers to the way that AI systems analyze data and learn to predict things, like whether a photo contains a human face. With machine teaching, humans guide the system along by breaking a task into individual lessons, akin to how someone learning to play baseball might get coached on tee-ball before graduating to underhand pitches and full-blown fastballs. “Machine learning is all about algorithmically finding patterns in data,” Pall says. “Machine teaching is about the transfer of knowledge from the human expert to the machine learning system.” Microsoft can’t claim sole ownership of the term. Xiaojin (Jerry) Zhu , a professor at University of Wisconsin-Madison, has used “machine teaching” to describe a set of approaches to training machine learning algorithms since 2013, though he and Microsoft both agree there’s some overlap in their definitions. While Microsoft says machine teaching is most conducive to fields like autonomous systems, where the AI has to decide between lots of potential real-world actions, it’s also just a way to make AI more accessible. With the right tools, a subject matter expert should be able to train an AI system without having to understand machine learning, in the same way that a baseball coach doesn’t have to learn brain chemistry. “[Subject matter experts] can basically start using AI largely without understanding a lot about how machine learning itself is working,” Pall says. “And they’re able to basically transfer the knowledge that they have as human experts in a particular area to the AI that needs to run it.” Last year, Microsoft acquired a startup called Bonsai to help abstract away the complexities of AI development. Similar to how Visual Basic is a simpler programming language than C, Bonsai has its own language, called Inkling, which is supposed to be simpler than than low-level AI development. Pall says that with these kinds of tools, industries such as energy, finance, and healthcare can build AI applications without having to hire their own AI experts, who are in high demand and short supply. Mark Hammond , Microsoft general manager for Business AI and former Bonsai CEO, developed a platform that uses machine teaching to help deep reinforcement learning algorithms tackle real-world problems. Read More …