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According to Ashwini Bhide, managing director, MMRC, all TBMs will reemerge by the end of 2019.The TBM weighs around glove machine Manufacturers tonnes with a diameter of 6.4 metres, the 100-metre-long machine will help in building a tunnel of finish size of 5.8 metre. The 33.5-km-long underground corridor will be made operational by December 2021.Mumbai: The Mumbai crime branch has busted a gang of thieves for targeting several gullible people by fraudulently withdrawing money from their accounts, using ATM machines. The two members of the gang arrested by the police are brothers. The officials said that the arrested accused would divert the attention of the person, right after they punched in the password by telling them that the ATM machine was not working.The duo has been identified as Satendra Mishra (32) and his brother, Bhupendra (35), both residents of Amethi in Uttar Pradesh.

It’s unlikely that anyone but the most extreme wine connoisseur will need to track wine-preserving argon gas levels in a half-finished bottle of pinot noir. But a maker of bottle-opening gadgetry, Coravin, lets you do just that. The device needles wine out of a bottle without pulling the cork. What’s new is connectivity and an app, so you’re alerted when the gadget needs cleaning or a new battery. All this reflects a cottage industry striving to imbue every last household appliance or wearable item with connectivityWhat one person considers a silly idea is another person’s breakthrough, and many innovations displayed at CES could find long-term commercial success among niche audiences even if they aren’t widely adopted, said technology analyst Tom Coughlin, president of Coughlin Associates. "Some stuff is before it’s time.

Some stuff is partially thought through," Coughlin said. But you never know, he said, because "sometimes people don’t know what they need until they see it." At CES, Coughlin said, "you see the hopes and dreams, the fantasies, both mad and sublime and clever things that people can think of doing."In the Netherlands, start-up entrepreneurs often look mockingly back to a late-1990s video that asked random people in Amsterdam if they ever wanted a mobile phone, said Stefan Witkamp, co-founder of smart home startup Athom B.V."Now it’s unthinkable not to have your smartphone," said Witkamp, whose company’s Homey product links various connected devices to a single system. Similar scepticism now affects smart devices, he said.The reality is that it’s a lot easier to connect an appliance to the inteet than it is to build "Rosie," the robotic maid that TV cartoon show "The Jetsons" launched into the world’s imagination a half-century ago.

Samsung is one of the world's leading manufacturers of home appliances, smartphones and other tech products, including batteries and memory chips.In the current recall, the company is offering consumers a choice between a free repair and a rebate toward the purchase of a new washing machine. Consumers who purchased an affected model in the last 30 days are being offered a full refund.The recall affects 34 models of top-loading washing machines manufactured between 2011 and this year. They were sold at Best Buy, The Home Depot, Lowes, Sears and other stores for prices between $450 and $1,500.When Twitter reported glove machine for sale its firs quarter eaings last year, it came way under expectations. The company’s 2016 eaings — $595 million was way less compared to what the analysts expected. According to a report published by The Verge, Twitter’s stock fell more than 12 per cent at that time.

It’s not a secret anymore: Twitter is facing problems. The social media giant has struggled to maintain a positive outlook ever since and things have become even more complicated especially given how well apps like Instagram and Snapchat have been doing.However, Twitter CEO Jack Dorsey is pretty positive about bringing about a change. Speaking to investors at the Goldman Sachs Technology and Inteet conference in San Francisco, he says that the company is gradually shifting its focus to AI and machine leaing techniques to cater to its user’s interests. As reported by Mashable, Dorsey said a new emphasis on machine leaing and AI ineally has helped make the service easier to understand and more relevant to its users.

"Twitter is still the best place to get a sense of what’s going on in the world but as we get better and better at applying machine leaing and AI to our system, which we really haven’t done in the past — it’s been very mechanical — it gets easier and easier, and we believe that topics and interests are a big part of that future to make it easier," Dorsey said.At the conference, he further went on talk about the platform’s recently-added "explore" tab which delivers a more personalised experience to its users. "As you exhaust your timeline you can go to explore and you can actually see topics. And the goal is eventually to become a lot more topic-based and interest forward," he added."I think for the majority of our life weve been fairly mechanical and that manifests in making people do the work and now we have a much stronger machine leaing artificial intelligence discipline within the company where we can do things for people.

 The same way cars have to go through crash tests to ensure safety, this method offers a pre-emptive test to catch errors in autonomous systems," he explained.Findings of the study were discussed in China flat knitting machine Suppliers Design, Automation and Test meeting.Typically autonomous vehicles "lea" about the world via machine leaing systems, which are fed huge datasets of road images before they can identify objects on their own.But the system can go wrong. In the case of a fatal accident between a self-driving car and a pedestrian in Arizona last March, the software classified the pedestrian as a "false positive" and decided it didnt need to stop."We thought, clearly there is some issue with the way this perception algorithm has been trained. When a human being perceives a video, there are certain assumptions about persistence that we implicitly use: if we see a car within a video frame, we expect to see a car at a nearby location in the next video frame. This is one of several sanity conditions that we want the perception algorithm to satisfy before deployment," explained Jyo Deshmukh, co-author of the study.

For example, an object cannot appear and disappear from one frame to the next. If it does, it violates a "sanity condition," or basic law of physics, which suggests there is a bug in the perception system.The team of researchers formulated a new mathematical logic, called Timed Quality Temporal Logic, and used it to test two popular machine-leaing tools--Squeeze Det and YOLO--using raw video datasets of driving scenes.The logic successfully honed in on instances of the machine leaing tools violating "sanity conditions" across multiple frames in the video. Most commonly, the machine leaing systems failed to detect an object or misclassified an object.For instance, in one example, the system failed to recognize a cyclist from the back, when the bikes tire looked like a thin vertical line.

 Instead, it misclassified the cyclist as a pedestrian. In this case, the system might fail to correctly anticipate the cyclists next move, which could lead to an accident.Phantom objects--where the system perceives an object when there is none--were also common. This could cause the car to mistakenly slam on the breaks--another potentially dangerous move.The teams method could be used to identify anomalies or bugs in the perception algorithm before deployment on the road and allows the developer to pinpoint specific problems.The idea is to catch issues with perception algorithm in virtual testing, making the algorithms safer and more reliable. Crucially, because the method relies on a library of "sanity conditions," there is no need for humans to label objects in the test dataset--a time-consuming and often-flawed process.