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Why business chatbots must understand customer intent
Not all bots are created equal. To find one that can help you meet business goals, you're going to need one that can do much more than obey a few simple commands or respond humorously to questions. If your criteria for success goes beyond entertainment and engagement, and you're looking to achieve tangible business benefits -- such as reducing call volumes to the contact center or offsetting online shopping cart abandonment over the holiday season -- then understanding the difference between chatbots is critical. If you've ever engaged a virtual assistant like Alexa (or Google Assistant, Siri, or Cortana), then you probably don't have a lot of confidence in their ability to help improve your business in a serious way. And you're correct to be skeptical.
Microsoft Takes Another Crack at Health Care, This Time With Cloud, AI and Chatbots
Microsoft Corp. is trying again in health care, betting its prowess in cloud services and artificial-intelligence can help it expand in a market that's been notoriously hard for technology companies. A new initiative called Healthcare NExT will combine work from existing industry players and Microsoft's Research and AI units to help doctors reduce data entry tasks, triage sick patients more efficiently and ease outpatient care. "I want to bring our research capabilities and our hyper-scale cloud to bear so our partners can have huge success in the health-care world," said Peter Lee, a Microsoft Research vice president who heads Healthcare NExT. Microsoft has tried to expand in health care before, with mixed results. It had a Health Solutions Group for many years, but combined that into a joint venture with General Electric Co.
Marketers, Keep Your Eyes Wide Open on A.I. and Chatbots
In Investment Management, we are just getting a grasp on this social media thing, marketing automation, and trying to simplify to an investor what Alts are –and I want you to concern yourself with something out, on the horizon? We are typically late to the party with bleeding edge marketing capabilities –a blessing and a curse. We let other industries test and learn while warming Compliance up to fancy newish "toys." We are pardoned time of these means to engage with investors and/or Financial Advisors but when leadership or sales partners get hip to these channels, we play catch-up with aggressive deadlines. Not to mention the impact to our brand with not having parity with our friends in other categories.
AI Scientists Gather to Plot Doomsday Scenarios (and Solutions)
Artificial intelligence boosters predict a brave new world of flying cars and cancer cures. Detractors worry about a future where humans are enslaved to an evil race of robot overlords. Veteran AI scientist Eric Horvitz and Doomsday Clock guru Lawrence Krauss, seeking a middle ground, gathered a group of experts in the Arizona desert to discuss the worst that could possibly happen -- and how to stop it. Their workshop took place last weekend at Arizona State University with funding from Tesla Inc. co-founder Elon Musk and Skype co-founder Jaan Tallinn. Officially dubbed "Envisioning and Addressing Adverse AI Outcomes," it was a kind of AI doomsday games that organized some 40 scientists, cyber-security experts and policy wonks into groups of attackers -- the red team -- and defenders -- blue team -- playing out AI-gone-very-wrong scenarios, ranging from stock-market manipulation to global warfare.
Beware the unfettered machine
Niederhoffer will be sitting on the panel Artificial Intelligence – should we unplug man from the machine? In his view, whilst it is clear that in some domains machine learning and artificial intelligence is starting to make a big difference, the key is understanding which domains are appropriate and which domains are potentially problematic. Some domains, like object and speech recognition, linguistic analysis, and credit analysis are perfect for machine learning and particularly, deep learning algorithms. But in Niederhoffer's experience, making short term market predictions using machine learning is perilous, though possible.
Why the Benefits of Artificial Intelligence Outweigh the Risks
The following was published on CMSWire.com on Feb. 22, 2017. The argument against artificial intelligence (AI) is driven by fear. According to Stephen Hawkings we do have reason to beware of the consequences of the advancement of artificial intelligence, including the possibility of the end of the human race. The rise of the machines won't be happening imminently, after all AI is still at its primitive stage. The most realistic fear that has been discussed recently is that AI will take people's jobs.
Meet The 5 Startups That Are Part Of GSF Accelerator's Fifth Batch - Inc42 Media
Founded in 2012 by Rajesh Sawhney, GSF Accelerator has announced the list of startups graduating from its fifth batch. The graduating five startups have also received $65K to $100K as Seed funding, the startups are currently working out of Gurugram and are being mentored. The startups will travel to San Francisco and Tokyo next month with an aim to explore tech ecosystems outside of India. The accelerator provides promising startups with unparalleled access to venture and business networks, intensive mentoring, and initial capital. It is a multi-city programme and extends beyond India, with partners in London, Silicon Valley, and Singapore. Commenting on the development, Rajesh Sawhney, founder, GSF Accelerator said, "This is our fifth iteration and we have chosen 5 startups.
ICYMI: Ford's Autolivery is the future of delivery
Today on In Case You Missed It: Ford used virtual reality to demo its "Autolivery" concept service at Mobile World Congress. The package delivery system of the future would consist of a self-driving van and a drone working together to deliver parcels and orders right to your door -- even if your door is on the 30th floor. While it's unlikely that anyone will see this system in action for several years -- the company anticipates the fleet won't be ready until at least 2021 -- it would go a long way to reducing urban gridlock and pollution. Meanwhile, Facebook is testing out an AI feature that uses pattern recognition to detect posts from users who may be in distress or suicidal. While users already have the ability to report a friend's status if they believe they're in trouble, the AI will flag status' for review by the Community Operations team. Additionally, there are new Messenger tools that help users connect to suicide prevention organizations in chat, and a report feature for potentially concerning livestreams.
Yves Behar designs a security robot for Cobalt Robotics
Cobalt Robotics has launched their stylish security robot. The robot was designed by Yves Behar and as a fabric covered robot, it's putting a new spin on soft robotics! Behar's goal was to create a robot that didn't conform to Hollywood stereotypes but instead as an augmentation of human ability and an enhancement to the human environment. "Creating the right form for Cobalt is crucial to its success. As a service for security and concierge, it becomes part of an office culture. This balance between approachability and discretion became a thematic challenge throughout the design process. We decided that the robot should not adopt a humanoid personality. Instead, it should aesthetically align with the furniture and décor of the office environment. The Cobalt robot's semi-cylindrical self-driving mechanism, sensors and cameras are covered by a tensile fabric skirt. This helps maximize the access and usability of the internal technologies, creates airflow to prevent overheating, and conveys a soft and friendly persona." said Behar.
Machine Learning in Finance with Classification approach - Online Technical Discussion Groups--Wolfram Community
We discuss classification as the data-mining technique in patterns recognition and supervised machine-learning. Comparison of classification to other data exploration methods is presented and the importance of this approach is further discussed. We demonstrate the machine-learning method in finance and show how credit risk categorisation can be easily achieved with classification technique. Searching for patterns in economic and financial data has a long history. One of the oldest approached explored by econometricians was the data arrangement into groups based on their similarities and differences. As computer resources improved there was a growth in the scope and availability of new computational methods.