People in India can now open an account with a bank that's only accessible via mobile devices. Called Digibank, it's staffed by chatbots intelligent enough to answer thousands of questions submitted via chat. The machine-learning-based technology is a product of Kasisto, a New York startup that spun out of the company that created Apple's Siri assistant. Kasisto trained its KAI artificial-intelligence platform with millions of questions asked by customers during their banking experiences. "A lot of the bots that are out there are what we would consider'dumb bots.' It's very easy to break them, and it's very easy to ask an out-of-context question, and they just don't know how to handle it," says Dror Oren, Kasisto vice president of product.

For all the buzz over conversational bots these days, they're still pretty crude, as some users of Facebook Messenger's new chatbots recently discovered. It's not necessarily that they're dumb, but they do need to be trained to respond intelligently in the specific situations in which they're employed. Today MindMeld Inc., one of the pioneers behind conversational artificial intelligence technology, will roll out a version of its bot platform specifically for retailers and e-commerce companies. MindMeld for Commerce is intended to help customers find products, do messaging-based transactions, check on order status and get support without requiring another human to get involved. Tuttle contends that MindMeld's bots can converse, either in text or by voice, better not only than other bots but also virtual assistants such as Apple's Siri, Amazon's Alexa and Microsoft's Cortana.

Jifiti, the startup attempting to reinvent digital gift-giving, announced this morning that their new chatbot API was approved by Facebook Messenger. It's a big deal for the Columbus, OH startup, who already has relationships with many companies ranging from IKEA to Evite. This new avenue could give Jifiti access to brands lining up to be available in Facebook's ecosystem since chatbot intentions were announced at F8 last month. It's planned to be used for e-commerce, support, personal assistance and other tasks. Jifiti, who we've been covering since their "product teleportation" launch in 2013 (which I always thought was a neat marketing play), through their pivot to white label gift registry in 2014 are now able to integrate their gift-giving process directly with Facebook Messenger chatbots (or any chatbot actually) via this API.

It turns out that the Boltzmann machines of that era did not scale up well, but other architectures designed by Hinton, LeCun, Bengio, Olshausen, Osindero, Sutskever, Courville, Ng, and others did. Was it the one-layer-at-a-time training technique? GPU clusters that allow faster training? I can't say for sure, and I hope that continued analysis will give us a better picture. But I can say that in speech recognition, computer vision object recognition, the game of Go, and other fields, the difference has been dramatic: error rates go down when you use deep learning, and both these fields have undergone a complete transformation in the last few years: essentially all the teams have chosen deep learning, because it just works.

Technology presents huge opportunities and challenges for our health and care system. Shipments of the activity tracking wearable Fitbit are up 25.4% this year, signalling more and more of us want insights into our exercise, eating, weight and sleeping patterns. As we begin to generate our own health data, our relationship with our bodies will change, and the way we understand and seek healthcare will be transformed. "Some of my patients will share outputs from their wearable ... when it comes to their yearly reviews. But this is the exception, rather than the rule at present," says Dr Junaid Bajwa, director of healthcare services, Merck (MSD).

Google is about to hold its biggest show of the year. And we've got a pretty good idea of what's going to happen. The company holds its I/O conference every summer to show off the biggest updates to developers and let them get their hands on its newest products. And this year that's going to be the technology that will power your house, take over your wallet and create the reality that you live in – as well as the now relatively small matter of powering your phone. Google I/O runs from 18 May to 20 May.

Excited to talk about Machine Learning, Data Science, and Artificial Intelligence? Ready to discover the key influencers you need to follow to stay current on all the latest happenings in these fields? We've got the resources you need. You see, at Udacity, we talk a great deal about Machine Learning, Data Science, and Artificial Intelligence. We talk to each other, we talk to our students, and we talk to the world at large.

Welcome to the Silicon Valley Robotics Influencer series, hosted at HAX and curated by Cory Kidd of Catalia Health, Tim Smith of Element Public Relations and Andra Keay of Silicon Valley Robotics.

It's a familiar adage but people still tend to highlight their successes and sweep their failures under the rug, as a professor at Princeton University pointed out last week when he published his "CV of Failures" (pdf), which has since gone viral. Now, in a study published this week in Nature, a team of researchers at Haverford College in Pennsylvania have taken this idea to the next level--by applying it to the scientific community. Even though most experiments fail, it is only the successes that are reported in scientific literature and discussed among experts. The vast majority of the data is discarded, left to collect dust in forgotten laboratory notebooks or never written down at all, making it effectively unavailable for use in further research. "Scientific literature is biased against failure," says experimental chemist Alexander Norquist, one of the study's lead authors.

How to Use Cohort Analysis to Improve Customer Retention; Why Implement Machine Learning Algorithms From Scratch?; 7 Steps to Mastering Machine Learning With Python; R vs Python for Data Science: The Winner is ...