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Andrew Ng has likened artificial intelligence (AI) to electricity in that it will be as transformative for us as electricity was for our ancestors. I can only guess that electricity was mystifying, scary, and even shocking to them — just as AI will be to many of us. Credible scientists and research firms have predicted that the likely automation of service sectors and professional jobs in the United States will be more than 10 times as large as the number of manufacturing jobs automated to date. That possibility is mind-boggling. So, what can we do to prepare for the new world of work? Because AI will be a far more formidable competitor than any human, we will be in a frantic race to stay relevant. That will require us to take our cognitive and emotional skills to a much higher level.
In the AI Age, “Being Smart” Will Mean Something Completely Different
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Despite the recent emergence of browser-based transcription aids, transcription’s an area of drudgery in the modern Western economy where machines can’t quite squeeze human beings out of the equation. That is until last year, when Microsoft built one that could. Automatic speech recognition, or ASR, is an area that has gripped the firm’s chief speech scientist, Xuedong Huang, since he entered a doctoral program at Scotland’s Edinburgh University. “I’d just left China,” he says, remembering the difficulty he had in using his undergraduate knowledge of the American English to parse the Scottish brogue of his lecturers. “I wished every lecturer and every professor, when they talked in the classroom, could have subtitles.”
When Artificial Intelligence Can Transcribe Everything - The Atlantic
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After acquiring a startup called Nervana, Intel is now building a chip specifically for machine learning. IBM is too, creating a hardware architecture that mirrors the design of a neural network. And more recently, Qualcomm has started building chips specifically for executing neural networks, according to LeCun, who is familiar with Qualcomm’s plans because Facebook is helping the chip maker develop technologies related to machine learning.
The Race To Build An AI Chip For Everything Just Got Real | WIRED
More broadly, Apple has built tools for artificial intelligence and augmented reality, and now the company is starting to let outside developers use those tools to enhance their own applications. The thing is, Google already did the same thing, with the Tango mobile augmented reality system and services running in its cloud. To be clear, Amazon, Facebook, Microsoft and Snap have all been busy in both AI and AR. But Google has put AI at the core of its business, with CEO Sundar Pichai going so far as to call it an "AI-first" company.
Apple WWDC: Taking on Google in AI
Bloomberg broke the news a little while ago that Apple (NASDAQ: AAPL) is working on a dedicated processor to handle artificial intelligence, or AI, related tasks internally referred to as the Apple Neural Engine. This chip, Bloomberg reports, would "improve the way the company's devices handle tasks that would otherwise require human intelligence -- such as facial recognition and speech recognition."
Here's When to Expect Apple Inc.'s New AI Chip - Nasdaq.com
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Rohm Semiconductor (Kyoto, Japan) and A*STAR’s Institute of Microelectronics (Singapore) have joined forces to develop an artificial intelligence (AI) chip aimed at boosting efficiency in the predictive maintenance of smart factories. The concept of ‘Predictive Maintenance’ has become widespread in the manufacturing industry as manufacturers begin to digitalize their production lines for increased productivity and competitiveness. By monitoring the function and health of machines based on data received through device logs and sensors, predictive maintenance analytics can forecast machine failures and eventually trigger some alarms so technicians can take counter-measures in time, such as servicing or replacing the affected machine.
AI chip aims at predictive maintenance in smart factories | Smart2.0
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It might not be long before algorithms routinely save lives—as long as doctors are willing to put ever more trust in machines. A team of researchers at Stanford University, led by Andrew Ng, a prominent AI researcher and an adjunct professor there, has shown that a machine-learning model can identify heart arrhythmias from an electrocardiogram (ECG) better than an expert.
The automated approach could prove important to everyday medical treatment by making the diagnosis of potentially deadly heartbeat irregularities more reliable. It could also make quality care more readily available in areas where resources are scarce. The work is also just the latest sign of how machine learning seems likely to revolutionize medicine. In recent years, researchers have shown that machine-learning techniques can be used to spot all sorts of ailments, including, for example, breast cancer, skin cancer, and eye disease from medical images.
The Machines Are Getting Ready to Play Doctor - MIT Technology Review
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The need for accuracy makes for painstaking work, but Forrest, who makes a few centers per picture, enjoys it. “It’s like why some adults color,” she says. “It’s become a relaxing task.” Those millions of annotate photos help an AI identify patterns that help it understand, say, what a human looks like. Eventually the AI grows smart enough to draw boxes around pedestrians. People like Forrest will help double-check the AI's work. Over time, AI will grow smart enough to reliably identify, say, kangaroos. Relying on an army of amateurs might seem odd, but it remains the most efficient way of training AI.
Mighty AI and the Human Army Using Phones to Teach AI to Drive | WIRED
But these AI systems also make decisions for reasons we may never understand. That’s why researchers, consumer rights lawyers, and policy makers have begun to voice concern that unintentional or intentional bias in machine-learning systems could give rise to patterns of algorithmic discrimination with causes that may be difficult to identify. This isn’t theoretical: studies have already found evidence of bias in online advertising, recruiting, and pricing, all driven by presumably neutral algorithms.
Artificial Intolerance - MIT Technology Review
Looking for a new job is getting easier. Google today launched a new jobs search feature right on its search result pages that lets you search for jobs across virtually all of the major online job boards like LinkedIn, Monster, WayUp, DirectEmployers, CareerBuilder and Facebook and others. Google will also include job listings its finds on a company’s homepage. The idea here is to give job seekers an easy way to see which jobs are available without having to go to multiple sites only to find duplicate postings and lots of irrelevant jobs. With this new feature, is now available in English on desktop and mobile, all you have to type in is a query like “jobs near me,” “writing jobs” or something along those lines and the search result page will show you the new job search widget that lets you see a broad range of jobs.
Google launches its AI-powered jobs search engine | TechCrunch
Now, Google has developed an AI that is capable of learning almost as quickly as a human being. Claims of this advancement in speed come from Google’s DeepMind subsidiary in London. They say that not only can their machine assimilate and act on new experiences much more quickly than previous AI models, it will soon reach human-level speeds. Their method mimics the processes of learning that occur in human and animal brains. If you’re unfamiliar with how deep learning works, it uses layers of neural networks to locate trends or patterns in data. If one layer identifies a pattern, that information will be sent to the next layer. This process continues until all the information is collected.
Google Created an AI That Can Learn Almost as Fast as a Human
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Tech companies are keen to bring cool artificial intelligence features to phones and augmented reality goggles—the ability show mechanics how to fix an engine, say, or tell tourists what they are seeing and hearing in their own language. But there's one big challenge: how to manage the vast quantities of data that make such feats possible without making the devices too slow or draining the battery in minutes and wrecking the user experience. Microsoft Corp. says it has the answer with a chip design for its HoloLens goggles—an extra AI processor that analyzes what the user sees and hears right there on the device rather than wasting precious microseconds sending the data back to the cloud. The new processor, a version of the company's existing Holographic Processing Unit, is being unveiled at an event in Honolulu, Hawaii, today.
Quest for AI Leadership Pushes Microsoft Further Into Chip Development - Bloomberg
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Today, Intel subsidiary Movidius is announcing the Movidius Myriad X vision processing unit (VPU), a low-power system-on-chip (SoC) intended for deep learning and AI acceleration in vision-based devices such as drones, smart cameras, and VR/AR headsets. This follows up on last month’s launch of the Myriad 2 powered Movidius Neural Compute Stick. As for the Myriad 2, the Myriad X will coexist alongside its predecessor, which was first announced in 2014. Movidius states that the Myriad X will offer ten times the performance of the Myriad 2 in deep neural network (DNN) inferencing within the same power envelope, while the Myriad 2 will remain a lower performance option.
Intel Announces Movidius Myriad X VPU, Featuring ‘Neural Compute Engine’
Video processor company Movidius, now a subsidiary of Intel, has introduced its third generation of Myriad VPU with an on-chip neural compute engine - a dedicated hardware accelerator for deep neural network inferences. Although Movidius has not said what manufacturing process the Myriad X is implemented in it does claim that it is capable of delivering an aggregate performance of over 4 trillion operations per second (TOPS) and that this makes the chip sufficiently power efficient to perform vision and artificial intelligence applications within drones, smart cameras, smart home, security, VR/AR headsets, and 360 cameras.
Movidius upgrades VPU with on-chip neural compute | eeNews Europe
Unveiled today at IFA 2017, the Kirin 970 chipset goes beyond the initial machine learning implementation of previous designs and is ready to be an AI processing powerhouse. Earlier this year Huawei introduced "the intelligent phone" with its Mate 9(pictured above), but the new hardware could help fix some annoying AI-related drawbacks of the device.
While AI work done in the cloud is one thing, on-device AI computation will continue to grow, with the need for sensors to operate without waiting to send any information back and forth over wireless connections. Native AI processing will enable faster image and voice recognition, as well as "intelligent photography."
Huawei's next mobile chipset is ready for our AI-powered future
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As part of its continued push into the AI sector, Google has just revealed that it has purchased a new deep learning startup. The Indian-based Halli Labs are the latest addition to Google's Next Billion Users team, joining the world-leading tech company less than two months after the startup's first public appearance. The young company has described its mission statement at Google as "to help get more technology and information into more people's hands around the world." Halli announced the news itself in a brief post on Medium, and Caesar Sengupta, a VP at Google, confirmed the purchase shortly afterwards on Twitter.
Google's new AI acquisition aims to fix developing world problems
Google’s Digital News Initiative has committed £622,000 ($805,000) to fund an automated news writing initiative for UK-based news agency, The Press Association. The money will help pay for the creation of Radar (Reporters And Data And Robots), snappily named software designed to generate upwards 30,000 local news stories a month. The Press Association has enlisted UK-based news startup Urbs Media for the task of creating a piece of software that turns news data into palatable content. Once up and running, the team is hoping the software will be able to fill in some of the gaps that are currently being under-serviced as the universal financial strain being experienced by newsrooms around the world deepens. It’s similar to a model The Associated Press has employed for a while now here in the States, mostly tackling financial and niche sports stories. A quick Google News search of the tell taletagline “This story was generated by Automated Insights” reveals hits from news outlets across the U.S.
Google is funding the creation of software that writes local news stories | TechCrunch
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iFlytek’s developer platform, called iFlytek Open Platform, provides voice-based AI technologies to over 400,000 developers in various industries such as smart home and mobile Internet. The company is valued at 80 billion yuan ($12 billion), and has international ambitions, including a subsidiary in the U.S. and an effort to expand into languages other than Chinese. Meanwhile, the company is changing the way many industries such as driving, health care, and education interact with their users in China.
Why 500 Million People in China Are Talking to This AI - MIT Technology Review
For Russia and Vladimir Putin, it is clear that planetary domination and artificial intelligence (AI) are inextricably intertwined. “Artificial intelligence is the future, not only for Russia but for all humankind,” he said via live video feed as schools started this month. “Whoever becomes the leader in this sphere will become the ruler of the world.” Putin isn’t an outlier in his thinking; he is simply vocalizing to match the intensity a race that China, Russia, and the US are already running, to acquire smart military power.
China, Russia, and the US are in an artificial-intelligence arms race - Business Insider
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