Instead of entering a hotel search and receiving a page with hundreds of options, new data-driven travel agents—using humans, AI or both—are tailoring options based on a traveler’s personal preferences. These new agents use chatbots or messaging to communicate with travel bookers. Elaine Glusac, writing at The New York Times, offers these examples of data-driven travel planners.
Pana caters to frequent travelers. For a monthly fee, Pana is available 24 hours. It uses member profiles and past trips to funnel travel requests to human agents.
Mezi uses chatbots to handle travel booking. If a complicated issue arises then humans get involved; afterward they train the bots to handle it in the future. The more you book with Mezi, the more it learns about your preferences.
Savanti Travel helps frequent travelers cut costs while gaining status with travel companies. It doesn’t operate on commission to avoid the urge to find more expensive bookings.
Hello Hipmunk is a travel-planning messaging system. It runs through Facebook Messenger, Skype or Slack, and lets you topic hop as if you were talking to a human. It can offer tips such as on the cheapest times to travel.
Flightfox specializes in complicated itineraries. The service books flights only; for a fee, agents find the best prices and send you links so you can do the booking yourself. It also uses points systems to find the best deals.
Mattel scrapped a “smart home” device designed with kids in mind after awful reviews and privacy concerns.
“Aristotle” was first shown off at CES earlier this year. The red-and-white device is meant to be kept in a child’s room where its WiFi-enabled camera acts primarily as a voice-controlled baby monitor. It can adjust lighting levels, noting when babies wake up and then playing a lullaby or turning on a nightlight.
The device also claimed to be able to extensively interact with a young child. It can recognize and answer questions, play games, do singalongs, and teach the ABCs. Aristotle’s voice-interaction capabilities are intended to be like a kid-centric version of Amazon’s Alexa.
Last week, two members of Congress sent a letter (PDF) to Mattel about the device.
Rep. Joe Barton (R-Tex.) and Sen. Ed Markey (D-Mass wrote “Never before has a device had the capability to so intimately look into the life of a child,” consumers should know how this product will work and what measures Mattel will take to protect families’ privacy and secure their data.” Instead of answering those questions, Mattel has withdrawn the product.
The newest developments show that using sodium, zinc, and aluminum constructed batteries make the mini-grid a solid possibility for providing 24-7, reliable and clean energy to entire small rural towns.
New materials such as Graphene are emerging and are going to change the world forever. Think about the Bronze Age…the Iron Age—these newest materials each contain a single layer of atoms and are two-dimensional. The potential positive impacts of evolving materials are limitless and bound only to the reach of scientists and how far they choose to push.
Self-driving cars are already in the here-and-now, but just how soon will be helping to improve the lives of handicapped and elderly will change the quality of life for millions.
From your own personal robot assistant that can anticipate your every need and perform tasks at your whim, to entire AI environments—this could be affordable to everyone with the emerging availability of Open AI ecosystems.
1000 Black techies, thought leaders, and entrepreneurs in 1 room for 2 days on the water in San Francisco? AfroTech, the largest black tech conference in Silicon Valley!
With two full days of the latest technologies and hottest startups, you will have a chance to learn from some of the best, and connect with fellow innovators.
The Standford Study suggests that computers have a better ‘gaydar’ than humans brings up all sorts of questions about the morality of such technology and the potential consequences of it falling into the wrong hands.
An algorithm associated with the software correctly identified gay men 81% of the time, while it was accurate for 74% of the women it tested.
Research of more than 35,000 faces – taken from a dating website – was published in the Journal of Personality and Social Psychology and first reported in the Economist, and claimed that gay men and women had ‘gender-atypical’ features, expressions and grooming styles.
Data also claimed to show that gay men had narrower jaws, longer noses and larger foreheads than straight men.
The paper claims to show for once and for all that exposure to certain hormones before birth determines sexual orientation; that being gay is not a choice, in other words.
However, those critical of the research claim that the technology could easily fall into the wrong hands.
The fear is that spouses could use it to identify a ‘closeted’ husband or wife, or that teenagers could deploy it as a means of outing their peers. Worse again, that anti-gay governments – such as Russia – could use it to target members of a country’s population.
Critics suggest that profiling people based on their appearance, then identifying them is wrong.
Microsoft Research is developing technology which may end up in the next version Microsoft’s classroom software. In a recent publication, Microsoft Research describes an AI-driven system which could help teachers automatically assess reading performance for students, saving them time and allowing more individual attention to students who need it the most. Their research paper, “Automatic Evaluation of Children Reading Aloud on Sentences and Pseudo words,” automatically predicts the overall reading aloud ability of primary school children (6-10 years old), based on the reading of sentences and pseudo words.
A silicon wafer designed to sort particles found in bodily fluids for the purpose of early disease detection.
IBM’s research labs are already working on a chip that can diagnose a potentially fatal condition faster than the best lab in the country, a camera that can see so deeply into a pill it can tell if its molecular structure has more in common with a real or counterfeit tablet, and a system that can help identify if a patient has a mental illness just from the words they use.
More work have to be done before the systems are ready for rolling out commercially. The next few years could also see IBM using artificial intelligence and new analytical techniques to produce a ‘lab on a chip’ — a pocket-sized device that would be able to analyse a single drop of blood or other bodily fluid to find evidence of bacteria, viruses, or elements like proteins that could be indicative of an illness.
Perhaps its greatest use, however, could be allowing people to know about health conditions before any symptoms begin to show.
While analyzing the contents of a drop of blood at a nanoscale level will need huge AI processing power, the real challenge for IBM in bringing labs on a chip to market is in the silicon. Mental health, however, is one area where artificial intelligence will chew up vast quantities of data and turn it into useful information for clinicians. Over the next two years, IBM will be creating a prototype of a machine learning system that can help mental health professionals diagnose patients just from the content of their speech.
Speech is already one of the key components that doctors and psychiatrists will use to detect the onset of mental illness, checking for signs including the rate, volume, and choice of words. Now, IBM is hoping that artificial intelligence can do the same, by analyzing what a patient says or writes — from their consultations with a doctor or the content of their Twitter feeds.
IBM already has form with such tools: one of the first commercial uses of Watson, Big Blue’s cognitive computing system, was as a doctor’s assistant for cancer care. Now the company is working with hospitals and other partners to build prototypes for other cognitive tools in healthcare. IBM hopes using machine learning will make the process faster and give an additional layer of insight.