Boston-based Lose It! (incorporated as FitNow Inc.) has released a new beta feature today called Snap It within its weight loss and calorie tracking app. As is easily guessed by the name, Snap It beta lets users take photos of their daily meals and snacks to automatically log them and derive approximate calorie counts. For now, users will be able to open the Lose It! app, pick a meal-type (breakfast, lunch, dinner or snack), take a photo of their food, submit and wait briefly for Snap It to analyze it. Snap It will present users with a few best guesses of what food was portrayed in the submitted pic. Users can then confirm the food seen in the photo, and add more detail.

In this week's post we will have a closer look at a paper dealing with the modeling of style, topic and high-level syntactic structures in language models by introducing global distributed latent representations. In particular, the variational autoencoder seems to be a promising candidate for pushing generative language models forwards and including global features. Recurrent neural network language models are known to be capable of modeling complex distributions over sequences. However, their architecture limits them to modeling local statistics over sequences and therefore global features have to be captured otherwise. Non-generative language models include the standard recurrent neural network language model, which predicts words depending on previous seen words and does not learn a global vector representation of the sequence at any time.

Antivirus software ain't what it used to be. The sneaky, sophisticated security threats your PC faces now have gone far beyond what traditional software can do. The future of protecting your PC will require a multi-pronged approach involving vigilant updates, bug bounties, and artificial intelligence. Like any software, antivirus is susceptible to bugs. Earlier this summer, Google's Project Zero discovered serious flaws in enterprise and consumer products from Symantec that allowed malicious actors to take control of a computer.

In a press call, Partnership On AI members were asked about other larger tech companies that were notably missing from the initiative--mainly Apple. Responding, the group mentioned that Apple had been propositioned to join and in response they were enthusiastic about the effort. However, nothing has been locked in as of yet. In regards to non-American tech companies, a group sorely lacking on the Partnership On AI's initial founders list, the group plans on making announcements in the coming weeks. Along with the previously mentioned tech companies, organizations like the Advancement of Artificial Intelligence (AAAI) and non-profits such as the Allen Institute for Artificial Intelligence (AI2) will also join forces with the Partnership On AI.

There are few highlights for most tech startups as sought after as cracking the international market and for most of these startups none quite as tantalising as breaking into Silicon Valley. The home of some of the world's biggest tech companies including Apple Inc., Facebook and Google, Silicon Valley is the leading hub and startup ecosystem for high-tech innovation and development. According to a January 2016 report from the Martin Prosperity Institute titled Rise of the Global Startup City, the San Francisco Bay Area, which spans Silicon Valley and San Francisco, remains the world's leading centre for venture capital investment attracting nearly 11 billion, more than a quarter of all global venture investment. A growing number of South African startups have also sought to grab a piece of the Silicon Valley slice, however, this does take some work. If you have your sights set on entering the international playing field, the most difficult thing is getting your foot in the door, says Daniel Schwartzkopff, commercial director and co-founder of Cape Town-based startup and machine learning specialists, DataProphet, who also spends part of his time in the US working with DataProphet's Silicon Valley-based clientele.

While its backers believe the rise of AI will allow us to cure disease, end poverty, reduce road accidents and slow climate change, critics say progress is being prioritised with little thought for the implications, and that this could have worrying consequences. The Partnership, which the companies say will be governed by a board featuring an even split of corporate interests and non-corporate ones such as academics and non-profits, will seek to share research and decide on ethical guidelines for the industry. Murray Shanahan, a professor of Cognitive Robotics at Imperial College London, said: "A small number of large corporations are today the powerhouses behind the development of sophisticated artificial intelligence. The inauguration of the Partnership on AI is a very welcome step towards ensuring this technology is used wisely." On Wednesday night, the project unveiled a list of eight rules that it will live by.

Artificial intelligence is increasingly becoming part of everyday life: think Apple's Siri. Major tech firms formed a group to help the public understand AI and develop standards so it isn't misused.

Utter the words and the first thing many people -- if not everyone -- would think of is a "Terminator"-like sci-fi dystopia where sentient machines are hunting humans down. These misgivings about what an AI-dominated world would be like are not alleviated when the likes of Stephen Hawking warn that AI "could spell the end of the human race." Microsoft, Google, IBM, Facebook and Amazon want to change this gloomy perception. The tech giants on Wednesday announced the launch of a new non-profit organization -- the Partnership on Artificial Intelligence to Benefit People and Society, or the Partnership on AI, for short -- to advance the general public's understanding of AI technologies, and debate concerns related to ethics, privacy, and transparency. "Together, the organization's members will conduct research, recommend best practices, and publish research under an open license in areas such as ethics, fairness and inclusivity; transparency, privacy, and interoperability; collaboration between people and AI systems; and the trustworthiness, reliability and robustness of the technology," the companies said in a joint statement.

Last time we investigated the k-nearest-neighbors algorithm and the underlying idea that one can learn a classification rule by copying the known classification of nearby data points. This required that we view our data as sitting inside a metric space; that is, we imposed a kind of geometric structure on our data. One glaring problem is that there may be no reasonable way to do this. While we mentioned scaling issues and provided a number of possible metrics in our primer, a more common problem is that the data simply isn't numeric. For instance, a poll of US citizens might ask the respondent to select which of a number of issues he cares most about. There could be 50 choices, and there is no reasonable way to assign these numerical values so that all are equidistant in the resulting metric space. Another issue is that the quality of the data could be bad. For instance, there may be missing values for some attributes (e.g., a respondent may neglect to answer one or more questions).

In July of 2013 Toby Shapshak, the South African speaker, strategist and editor of Stuff Magazine, did a TED talk called You Don't Need An App For That. Business leaders, innovators and experience designers would soon realize how profound this TED talk was to the rest of the world. Shapshak's astute observations and message to the rest of the world was years ahead of a revolution that Forbes would call "the new way we'll be interacting with computers." Toby's 2013 Ted talk touted that "while the rest of the world is updating statuses and playing games on smartphones, Africa is developing useful SMS-based solutions to everyday needs". Since 2013 his TED talk has been viewed 1,438,046 times as of July 19, 2016. Fast forward a couple of years and we see more apps than anyone knows what to do with, as well as a notable decrease in usage and app-downloads. This has businesses confused and frustrated.