Match Group, the largest dating app conglomerate in the US, doesn't perform background checks on any of its apps' free users. A ProPublica report today highlights a few incidents in which registered sex offenders went on dates with women who had no idea they were talking to a convicted criminal. These men then raped the women on their dates, leaving the women to report them to the police and to the apps' moderators. These women expected their dating apps to protect them, or at least vet users, only to discover that Match has little to no insight on who's using their apps. The piece walks through individual attacks and argues that the apps have no real case for not vetting their users.

Disclaimer: There are statements about potential uses of AI within this post that some people may find disturbing. When the formal study of AI was conceived back in the post-WW2 era it's potential was heralded as a boon for mankind and viewed in a almost exclusively positive light. What could be bad about that? Well, beyond science fiction's killer robots and ghosts in the machine stories, AI still has much of that positivity surrounding it as we enter into the era of autonomous vehicles, functional digital assistants, and recommendation engines that actually make good recommendations. But is the rise of functional AI actually hiding another more sinister development, one which has the potential to do serious harm to those who are on the wrong side of the algorithm?

When Google introduced the Home Mini two years ago, it was playing catch-up to Amazon's Echo lineup. The Echo Dot, a tiny and affordable version of the larger Echo smart speaker, had been on sale for more than a year and a half, and Google was clearly responding to the Dot's popularity. The Home Mini bested the Dot in several ways, though, including a better speaker and more attractive design. Naturally, Amazon responded a year later with the third-generation Dot. It ditched the glossy black plastic and took inspiration from the Home Mini's fabric-covered exterior.

Fusion Informatics builds a team of eCommerce virtual assistants to our clients that are exclusive to their company. We also hired and trained 1 x customer support representatives to help answer hundreds of emails that our clients receive per day in his ecommerce business. We provided with all support and training documents for their company, we then trained their staff members and within a few weeks, the staff had answered the message without the support of the client or Fusion Informatics. Finally, we successfully plant a Virtual Assistant and provided solutions for our customers who benefit from an increase in sales of 30% in the first month itself.

Tensor Recovery from Noisy and Multi-Level Quantized Measurements Ren Wang, Meng Wang, Jinjun Xiong Abstract --Higher-order tensors can represent scores in a rating system, frames in a video, and images of the same subject. In practice, the measurements are often highly quantized due to the sampling strategies or the quality of devices. Existing works on tensor recovery have focused on data losses and random noises. Only a few works consider tensor recovery from quantized measurements but are restricted to binary measurements. This paper, for the first time, addresses the problem of tensor recovery from multilevel quantized measurements. Leveraging the low-rank property of the tensor, this paper proposes a nonconvex optimization problem for tensor recovery. We provide a theoretical upper bound of the recovery error, which diminishes to zero when the sizes of dimensions increase to infinity. Our error bound significantly improves over the existing results in one-bit tensor recovery and quantized matrix recovery. A tensor-based alternating proximal gradient descent algorithm with a convergence guarantee is proposed to solve the nonconvex problem. Our recovery method can handle data losses and do not need the information of the quantization rule. The method is validated on synthetic data, image datasets, and music recommender datasets. I NTRODUCTION Many practical datasets are highly noisy and quantized, and recovering the actual values from quantized measurements finds applications in different domains.

The holidays are here, and if you haven't already started decorating, it's time to get going on creating an awesome display. Is the thought already stressing you out? You can simplify managing your amazing holiday light show by using smart plugs and other products that can be controlled remotely. Here are the five smart products you need to create an awesome holiday display. Control your holiday lights (or other festive decorations that plug into an outlet) from anywhere when you use an outdoor smart plug.

At a time when we seem to be busier than ever, productivity is the magic word. We're constantly trying to reach the holy productivity grail. Automated voice assistant technology can take us one step closer to offloading or effectively completing the'little' tasks, allowing us to refocus our efforts on the more creative, imaginative, explorative parts of life. There is clearly an appetite for the likes of Siri, Alexa, and Google Assistant but, equally, where there is demand there is often contempt.

Artificial intelligence will reach human levels by around 2029. Follow that out further to, say, 2045, we will have multiplied the intelligence, the human biological machine intelligence of our civilization a billion-fold.

Here's an interesting stat from the Pew Research Center: more than half of smart speaker owners in the US (54 percent) report saying "please" at least occasionally to their AI assistants, with one-in-five (19 percent) saying please frequently. Curiously, the question of AI politeness also breaks down along gender lines, with 62 percent of women reporting that they say "please" at least sometimes, versus 45 percent for men. One possible answer is that men are generally ruder to women, and this latter category now includes AI assistants coded as female. Experts have long noted that the design choices for AI bots could have misogynist effects by reinforcing gender stereotypes. "Because the speech of most voice assistants is female, it sends a signal that women are ... docile and eager-to-please helper," a report from the UN noted earlier this year.