During the christmas vacation of 2015, I got a motivational boost again and decided try out Kaggle. So I spent quite some time experimenting with various algorithms for their Homesite Quote Conversion, Otto Group Product Classification and Bike Sharing Demand contests. The main takeaway from this was the experience of iteratively improving the results by experimenting with the algorithms and the data. I learned to trust my logic when doing machine learning. If tweaking a parameter or engineering a new feature seems like a good idea logically, it's quite likely that it actually will help.

Content marketing is rapidly evolving. Producing generic content and throwing it out there hoping for a miracle is no longer a marketing strategy for any business that hopes to stay competitive. Spun content on web pages, auto-generated videos, and other poor content marketing strategies will often have a negative impact on your brand, making your business that much less to succeed. TNW Conference is back for its 12th year. Over the past few years, successful brands have been taking advantage of advances in tech to develop successful content marketing strategies.

Bart de Boer of the VUB Artificial Intelligence Laboratory in Belgium then turned the information into a computer model that could predict and simulate a macaque's vocal range based on the physical attributes. Human speech stems from a source sound produced by the larynx that is changed by the positions of the vocal anatomy such as the lips and tongue. They found that a macaque could produce comprehensible vowel sounds -- and even full sentences -- with its vocal tract if it had the neural ability to speak. "This new result tells us that there's still a big mystery concerning where human speech came from," said Laurie Santos, a psychology professor at Yale University. "The paper opens whole new doors for finding the key to the uniqueness of humans' unparalleled language ability. "If a species as old as a macaque has a vocal tract capable of speech, then we really need to find the reason that this didn't translate for later primates into the kind of speech sounds that humans produce.

Eindhoven, Netherlands and Beijing and shenzhen, China and singapore - DECEMBER 27, 2016 - HERE, the Open Location Platform company, NavInfo Co., Ltd ("NavInfo"), a leading provider of digital maps and location services in China, and Tencent Holdings Limited ("Tencent"), a leading provider of Internet value added services in China, today announced their intention to form a strategic partnership to develop and offer best-in-class location services for the Chinese market. Aside from the planned strategic partnership, NavInfo, and Tencent, together with GIC, a leading global investment firm, also intend to jointly acquire a 10% stake in HERE, thereby further broadening the company's shareholder structure. The planned transaction would result in AUDI AG, BMW AG and Daimler AG reducing their indirect shareholding in HERE in equal measure. The transaction is expected to be completed in the first half of 2017, subject to regulatory approvals. The planned formation of a joint venture in China: HERE and NavInfo intend to form a 50/50 joint venture in China enabling location services for Chinese and global customers across a range of industries.

Artificial intelligence (AI) got a lot of press in 2016, not least because of the victory of Google's AI program over Lee Sedol, the world's best Go player. That triumph of machine over human elicited numerous responses, some enthusiastic and some anxious, all sharing the assumption that the goal of artificial intelligence is to achieve "human-level intelligence" or, as some predict, "superintelligence." "I don't care so much whether what we are building is real intelligence," says Peter Norvig, Director of Research at Google. "We know how to build real intelligence--my wife and I did it twice, although she did a lot more of the work. We don't need to duplicate humans. That's why I focus on having tools to help us rather than duplicate what we already know how to do. We want humans and machines to partner and do something that they cannot do on their own."

To companies grappling with complex data projects powered by artificial intelligence, a system that Nvidia calls an "AI supercomputer in a box" is a welcome development. Early customers of Nvidia's DGX-1, which combines machine-learning software with eight of the chip maker's highest-end graphics processing units (GPUs), say the system lets them train their analytical models faster, enables greater experimentation, and could facilitate breakthroughs in science, health care, and financial services. Data scientists have been leveraging GPUs to accelerate deep learning--an AI technique that mimics the way human brains process data--since 2012, but many say that current computing systems limit their work. Faster computers such as the DGX-1 promise to make deep-learning algorithms more powerful and let data scientists run deep-learning models that previously weren't possible. It costs $129,000, more than systems that companies could assemble themselves from individual components.

It's not enough to just collect data -- you have to know how to use it. You should know what to collect, and what to do with that information once you have it in order to improve the bottom line of your business. What is the most creative way you see companies using collected user data? TNW Conference is back for its 12th year. Using collected user data, you can leverage open source machine learning databases to find patterns in human interactions with marketing content.

Key sectors of interest include Internet of Things, FinTech, Future of Work, Logis-cs/Transporta-on, eHealth, Security and others. BootstrapLabs is a Venture Capital firm based in Silicon Valley and focused on Applied Ar:ficial Intelligence About Us 3. Community of Founders, Intrapreneurs, AI/ML Experts, Execu-ves, Professors, Researchers, Investors focused on Innova-on, Technology and Entrepreneurship 30K PEOPLE Our Community 200K FOLLOWERS 1K ATTENDEES Our online community between BootstrapLabs core team and its closer advisors has over 200K followers. We see traffic on our website and deal flow referral coming from over 60 countries BootstrapLabs brought together over 1,000 people during 2016. Our community is a key pillar of our success and we organize many exclusive private and public AI centric events each year 4. Applied AI Digest #1 2016 Google's DeepMind Beats a Top Player at the Game of Go Zucks to create AI-Powered Jarvis JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC IBM Watson Head on the Future of AI Read Full Articles 5. Applied AI Digest #2 Artificial Intelligence Deals on the RiseCould AI Solve the World's Biggest Problems? Harvard is building an AI Engine as fast as the Brain 6. Applied AI Digest #3 Is Big Data Still a Thing?

Self-driving electric cars could make car parks obsolete within the next 10 years and reduce air pollution to almost zero in Scotland's cities, an expert has predicted. The vehicles are likely to be commonplace by 2030, said Simon Tricker, of "smart cities" specialist UrbanTide, which uses technology and data to improve city planning. "Scottish local authorities are already thinking about what city streets will look like in a decade's time - and the answers are pretty astounding," he said. Private companies can't be trusted on driverless cars, minister warns Ford to offer driverless commercial vehicles by 2021 Driverless car safety revolution could stall over moral dilemma Ministers pledge to put UK at heart of driverless car revolution Private companies can't be trusted on driverless cars, minister warns "Self-driving cars won't need parking spaces in cities - they're likely to be rented rather than owned and will just head off and carry out their next journey after dropping passengers off. Many car parking spaces which we now take for granted will simply become obsolete. "The pace at which electric vehicle technology is developing means they're also likely to be electric, so will produce zero emissions as they're driven.

There is a widely reported threat to our economy: robots are going to replace human workers. It is nothing new… In 1930, Keynes, the famous economist introduced the term "technological unemployment"… We are being afflicted with a new disease of which some readers may not yet have heard the name, but of which they will hear a great deal in the years to come--namely, technological unemployment. This means unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour. There is a long Wikipedia article on technological unemployment, where you can learn that people have been concerned about it for centuries… long before we could even imagine robots and computers. It is a recurrent theme of western thought.