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3 roadblocks chatbots face
While we think of them as the latest thing in tech, conversational interfaces have been around for quite some time. From Cleverbot and Smarter Child to labyrinthine phone trees ("say REPRESENTATIVE"), we have been trying for years to build technology that mimics how we interact with humans. Recent advances have positioned these tools for substantial growth and brought them back to the foreground of the conversation on the future of technology. Conversational interfaces for both speech and text have risen to prominence thanks to virtual assistants or "chatbots," such as Apple's Siri and Amazon's Alexa. Also, text-based chatbots, or messaging platforms such as Slack and Facebook Messenger, have seen a huge spike in utilization.
The Robot Revival
Robots have long been a manufacturing mainstay--tasked with doing the heavy lifting on the assembly line or taking over tedious repetitive motions. Up until recently, however, they've been limited to basic activities, typically on the automotive factory floor. But advancements in the form of small, light-weight collaborative robots, cloud analytics and artificial intelligence are ushering in a new era of robot applications and collaboration that will support a wide variety of industries. Industry observers say these new robot systems will transform the way products are made, as well as the way people work. "The next step is changing the way we work globally," said Esben รstergaard, CTO of collaborative robot company Universal Robots during an interview at IMTS 2016.
Gartner Reveals Top 2017 Strategic Technology Trends - Business Intelligence & Advanced Analytics
At the annual Gartner Symposium/ITxpo in Orlando, Florida this week, over 8000 technology leaders gathered to get analyst predictions on where we are heading. Artificial intelligence, machine learning, and smart things were key analytics themes for a savvy digital future. The overall top three themes this year were intelligent, digital, and mesh. For a fantastic free overview, check out the following openly published article, "Gartner's Top 10 Strategic Technology Trends for 2017" and linked resources. Last week I shared an article and webinar regarding the Fourth Industrial Revolution aka Digital Transformation.
Artificial Intelligence is the user interface of data science: Bhaskar Ghosh, Group Chief Executive, Accenture Technology Services
The whole technology landscape is changing and is ushering in new ways to put it to use. The way things have been run in the past 20 years no longer holds water and we need to change to adapt and be relevant. At the Bengaluru ITE.BIZ 2016, Bhaskar Ghosh, Group Chief Executive, Accenture Technology Services, shed light on what the next wave in the IT sector would be. "We went through several waves - IT services, e-commerce, cloud, artificial intelligence (AI) and quantum computing. New tech is maturing faster and the time to learn and execute in the market is short. We need to learn to master the speed. Every business is a software business. Even manufacturing is driven by software," he explained.
AI and Machine Learning, how the trend will continue into 2017
Our 12 days of Christmas predictions has hit lucky seven, and just in time for the 13th of December too! Of course this means 13 shopping days until Christmas Day, but for those who have made their preparations and are not yet tired of Wham and Shakin' Stevens on the airwaves, our countdown continues with a look at one of the key trends of 2016 which is expected to continue into the new year. The concept of machine learning, automation and artificial intelligence (AI) have got a lot of attention over the past couple of years, and it is predicted that this will continue into 2017. Sian John, Chief Strategist of EMEA at Symantec, predicted that AI and machine learning will require sophisticated Big Data capabilities as in 2017, machine learning and AI will only continue to grow. "With this growth comes new, powerful insights for businesses to tap, and an increased collaboration between humans and machines," she said.
The data science ecosystem: R vs Python vs Substitutes
In this post, I show a network analysis of the R and Python ecosystems in terms of their competitors. To identify the typical substitutes/ competitors of a tool, I use the Google search autofill recommendations. Google search prompts identify the most frequently searched terms which occur after a given string and automatically provides a list of suggestions. Thus, this may be treated as a proxy for the common substitutes people search for against a particular tool. In Fig 1 when I start typing "R vs " in the Google Search bar, Google provides a list of suggestions based on their'autocomplete' feature.
Artificial intelligence, machine learning find role in radiology
Artificial intelligence and machine learning capabilities are beginning to make an impact within radiology, as vendors start rolling out initiatives to assist professionals in making diagnoses. The radiology profession is ripe for technology--as radiologists deal with an increasing number of images and bear more responsibility in the clinical process. All Health Data Management content is archived after seven days.
Microsoft dataset to help researchers create AI tools
Microsoft has released a set of 100,000 questions and answers that artificial intelligence (AI) researchers can use to create systems that can read and answer questions as precisely as a human. "The dataset is called MS MARCO, which stands for Microsoft MAchine Reading COmprehension, and can be used to teach artificial intelligence systems to recognize questions and formulate answers and, eventually, to create systems that can come up with their own answers based on unique questions they have not seen before," said Microsoft in a blog post. By providing realistic questions and answers, the researchers said they can train systems to better deal with the nuances and complexities of questions regular people actually ask, including those queries that have no clear answer or multiple possible answers. "Our dataset is designed not only using real-world data but also removing such constraints so that the new-generation deep learning models can understand the data first before they answer questions," added Li Deng, Partner Research Manager of Microsoft's Deep Learning Technology Centre. The MS MARCO dataset is available for free to any researcher who wants to download it and use it for non-commercial applications, Microsoft said.
Artificial intelligence reveals undiscovered bat carriers of Ebola and other filoviruses
IMAGE: This is a map of known and predicted bat hosts of filoviruses, showing hotspots in Southeast Asia. Findings highlight new potential hosts and geographic hotspots worthy of surveillance. So reports a new paper in the journal PLoS Neglected Tropical Diseases. Filoviruses have devastating effects on people and primates, as evidenced by the 2014 Ebola outbreak in West Africa. For nearly 40 years, preventing spillover events has been hampered by an inability to pinpoint which wildlife species harbor and spread the viruses.