A blind woman sits in a chair holding a video camera focused on a scientist sitting in front of her. She has a device in her mouth, touching her tongue, and there are wires running from that device to the video camera. The woman has been blind since birth and doesn't really know what a rubber ball looks like, but the scientist is holding one. And when he suddenly rolls it in her direction, she puts out a hand to stop it. The blind woman saw the ball. Well, not exactly through her tongue, but the device in her mouth sent visual input through her tongue in much the same way that seeing individuals receive visual input through the eyes. In both cases, the initial sensory input mechanism -- the tongue or the eyes -- sends the visual data to the brain, where that data is processed and interpreted to form images.|Video paragraph captioning is the task of automatically generating a coherent paragraph description of the actions in a video. Previous linguistic studies have demonstrated that coherence of a natural language text is reflected by its discourse structure and relations. However, existing video captioning methods evaluate the coherence of generated paragraphs by comparing them merely against human paragraph annotations and fail to reason about the underlying discourse structure. At UCLA, we are currently exploring a novel discourse based framework to evaluate the coherence of video paragraphs. Central to our approach is the discourse representation of videos, which helps in modeling coherence of paragraphs conditioned on coherence of videos. We also introduce DisNet, a novel dataset containing the proposed visual discourse annotations of 3000 videos and their paragraphs. Our experiment results have shown that the proposed framework evaluates coherence of video paragraphs significantly better than all the baseline methods. We believe that many other multi-discipline Artificial Intelligence problems such as Visual Dialog and Visual Storytelling would also greatly benefit from the proposed visual discourse framework and the DisNet dataset. But only a relative few have seen the Cave of Crystals up close. Discovered in 2000 by a couple of miners, Cueva de los Cristales is part of an active mine, and it gets so hot down there that the cave researchers and journalists who have gotten a peek have had to wear full protective gear. Next on the list: miles and miles and miles of caves. Flowstone and stalactites form the Frozen Niagara section of Mammoth Cave. It took 10 million years for Kentucky's Green River to create Mammoth Cave, and it shows: Mammoth Cave lives up to its name. And that's just the part of Mammoth that's has already been explored. It's not just extreme in length, either. Mammoth Cave boasts some interesting life forms, like eyeless fish, shrimp and beetles as well as spiders with no pigmentation. There are tremendous columns, like the 192-foot (59-meter) Mammoth Dome, and rivers running through the lowest levels of the cave.|The morning after receiving de Lucas’ email, I wake up to a long WhatsApp message from Bishop. “I think this has been sent anonymously, for whatever reason, by someone who works in the lab mentioned,” he writes. He points to the CNB heading on the paper, the Spanish words in the letter, and the lack of a postcode on the envelope as evidence that the sender was from Spain. Even if the letter wasn’t genuine, Bishop claims, someone had found his teeth, swabbed them for DNA, and returned them to him from Spain. The notion of an anonymous teeth-returning vigilante is appealing. Who hasn't been dismayed after losing a prized possession while on holiday? If there is a masked DNA-swabbing hero out there reuniting holidaymakers with their lost trinkets, then it means nothing is truly lost. Of course, they’d have to get the DNA in the first place. Retrieving enough DNA to identify someone from 11-year-old lost dentures is theoretically possible but extremely unlikely, says Denise Syndercombe Court, a professor of forensic genetics at King’s College London.
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