Conversational Archives - Artificial Intelligence

FROM E-COMMERCE TO EDUCATION: CONVERSATIONAL AI IS ONE SIZE FITS ALL

aiuniverse — Mon, 14 Jun 2021 05:14:37 +0000

Source – https://www.analyticsinsight.net/

Conversational AI is Advancing towards the Sector of Education

May be ‘Talking tom’ was just not a toy but also an epitome of Conversational AI that is reigning the present and will continue to do so in future as well. Besides, the pandemic happens to be a significant inducer of artificial intelligence to such an extent that AI is now a habit and a lifestyle. In the current era of technological modernization, enterprises are augmented with digital transformation. This stands true especially for Fortune 500 companies that are leveraging AI to best of their advantages to enhance and refurbish their business dimensions.

Conversational AI is one of the most advanced forms of AI bots that are heavily employed by e-commerce platforms. While Conversational AI has occupied a significant space in the e-commerce industry, it is also transforming the education sector as well.

The Socio-economic Status of Education Sector during Covid-19

With social distance as the norm, education and pedagogy have become mobile, in its entirety. Education institutions are seeking novel methods to disseminate extensive teaching methods without any loop holes. AI has been a significant and constant filler of gaps that often arise in research and education, thereby, delivering personalized and impeccable standards of education.

According to reports by World Economic Forum, the global education technology investment had touched a high growth of US$18.66 billion. The education sector is thriving by adoption of high-end technologies, eliminating all the possible drawbacks entailed by online education. Hence, it can be confidently asserted that the socio-economic status of education amidst the pandemic has remained unhindered.

Incorporation of Conversational AI in Education

Conversational AI has emerged to be an inseparable limb of modern day teaching and learning methods. This innovative AI tool stimulates smooth communication between users and computers by enabling natural dialogue. Natural dialogue is one of the cardinal requisite in virtual education. With the support of natural language processing (NLP), Conversational AI aims to attend and clarify queries from students and deliver human-like responses in short periods of time.

While conversing with AI chatbots can seem intimidating at first, Conversational AI performs like humans to meet the needs of students. Here is a list of multiple benefits generated by Conversational AI:

1. Personalized Learning Experience: The demands and requirements of teaching and learning keeps varying. Conversational AI is capable of providing customized and personalized learning that suits an individual the best.

2. Automated Administrative Works: Administrative works are crucial parts of the education sector. While handling administrative tasks can be overwhelming at times, the onus can be put on Conversational AI that automates all the administrative works.

3. Authentic Delivery of Feedbacks: Feedback is imperative for both faculties and students. Conversational AI organizes the right feedback for students and teachers. Feedback paves ways for opportunities to fill up the gaps in the process of teaching and learning.

Conversational AI is the New Pygmalion of the Education Sector

Integration of conversational AI in the education has demonstrated results that have helped to transform the face of education sector, making virtual education a part of the new normal.

The post FROM E-COMMERCE TO EDUCATION: CONVERSATIONAL AI IS ONE SIZE FITS ALL appeared first on Artificial Intelligence.

Uber unveils a conversational AI platform called Plato

aiuniverse — Thu, 18 Jul 2019 12:14:41 +0000

Source: siliconangle.com

Uber Technology Inc. has open-sourced a conversational artificial intelligence engine called the Plato Research Dialog System that’s set to compete with similar offerings such as Google LLC’s Dialogflow, Microsoft Corp.’s Bot Framework, and Amazon.com Inc.’s Lex.

In a blog post today, Uber’s AI research team explained that Plato is designed for building, training and deploying prototype and demonstration systems. It can also facilitate conversational data collection.

Plato comes with a “clean and understandable” design that makes it ideal for users with a limited background in conversational AI, the company said. And it can integrate with existing deep learning models, thereby reducing the need to write any code.

Plato version 0.1 can support interactions with humans, data and other conversational AI agents through speech, text and “structured information,” Uber said. It also supports multiple agents and can incorporate pre-trained AI models for each component of those agents. Those models can be trained using either datasets or via interactions, using popular open-source machine learning frameworks such as Google’s TensorFlow, Facebook Inc.’s PyTorch and Uber’s very own Ludwig.

Another aspect of Plato is its “modular design,” which breaks up data processing into seven parts. Those include speech recognition, language understanding, state tracking, API calls, dialogue policies, language generation and speech synthesis.

Plato also handles data logging by keeping track of events with its Dialogue Episode Recorder. The recorder saves information about previous dialogue states, what actions were taken and also current dialogue states.

“We believe that Plato has the capability to more seamlessly train conversational agents across deep learning frameworks, from Ludwig and TensorFlow to PyTorch, Keras and other open-source projects, leading to improved conversational AI technologies across academic and industry applications,” Uber’s AI researchers wrote in a blog post. “[We’ve] leveraged Plato to easily train a conversational agent how to ask for restaurant information and another agent how to provide such information; over time, their conversations become more and more natural.”

Analyst Holger Mueller of Constellation Research Inc. said one of the most interesting aspects of the Plato system was its ability to support multiple agents, which is necessary for Uber as it needs to facilitate multi-party chat between its customers, drivers and its own support and customer service agents.

“This means there need to be intelligent conversation sharing, and so it makes sense for Uber to throw its hat in the ring with Plato, despite the already crowded nature of the chatbot framework space,” Mueller said. “As with all new open-source projects we need to check on adoption in a few quarters, as the act of open-sourcing code assets does not guarantee developer or enterprise adoption.”

The release of Plato follows the debut of the aforementioned Ludwig, which is a set of open-source tools built on top of Google’s TensorFlow framework that allows users to train and test AI models without having to write code.

The post Uber unveils a conversational AI platform called Plato appeared first on Artificial Intelligence.

AWS Brings Conversational AI to Alexa

aiuniverse — Tue, 11 Jun 2019 10:45:11 +0000

Source:- nojitter.com

If ever there was a song that described the state of voice assistants today, it’s Elvis Presley’s “A Little Less Conversation.” Queue up the record:

A little less conversation, a little more action, please

All this aggravation ain’t satisfactioning me

The song came to mind last week while attending the Amazon Web Services (AWS) re: MARS event for machine learning, automation, robotics, and space and hearing about Alexa Conversations, an update to the company’s voice agent aimed at making a conversation more interactive rather than being a series of discrete statements.

Within the context of digital assistants, Elvis’ words mean that sometimes when it comes to conversations, less is more. At the event, Eric Posen, principal product manager from Atom Tickets supported this statement by discussing the process of using Alexa to purchase movie tickets through Atom.

The interactions would go something like this:

Movie-goer: Alexa, launch Atom App.
Alexa: What do you want to do?
Movie-goer: Alexa, buy tickets.
Alexa: For which day?
Movie-goer: Alex, today.
Alexa: For what movie?
Movie-goer: Spiderman – Far From Home.
Alexa: What ZIP code are you in?

And the conversation goes on and on. The full flow can be seen in the below image. You can see the tie to what Elvis meant when singing about wanting less conversations and more action to reach a desired level of “satisfactioning.” Faster, more direct interactions are obviously better. Prior to this update, the process could make using Alexa burdensome and tiring and more difficult than using an app, Posen admitted. Most users typically choose the path of least resistance, so if the app is easier to use than Alexa, guess what? Bye-bye Alexa, at least for this kind of use case.

The goal behind Alexa Conversations is to remove many of these steps by making discussions with the voice agent more natural. This is done by taking advantage of things Alexa knows and predicting what the user will want instead ahead of the request. Based on past history, Alexa should be able to guess where a user wants to see a movie, at what time, and how many tickets to buy. This can significantly cut the flow down and turn a long conversation into a very short one, which is likely faster than using the app.

Posen showed the “after” slide as he walked through the interaction using contextual AI. Once asked, Alexa responds with:

Alexa: Spiderman – Far From Home is playing at Arclight Hollywood in premium or standard format. Which format would you like?
Movie-goer: Standard
Alexa: There is a 9:30 p.m. showing, is that what you want?
Movie-goer: Yes
Alexa: Your total is $20, should I book it?
Movie-goer: Yes

Three words. That’s all it took to book tickets. This should meet the criteria of a little less conversation, a little more action… and raise a customer’s satisfactioning level.

In addition to providing a better customer experience, the dialog is much simpler to program. AWS has done much of the heavy-lifting in the area of AI training so programmers have less work to do. For Atom Tickets, the conversational AI took about one-third less code than previous Alexa programs, Posen estimated.

OpenTable and Uber presenters, also in this session, reiterated the challenge of using Alexa for simple conversations. Any time an interaction requires multiple steps, there’s a heavy burden of having to have the speaker say “Alexa” to initiate the interactions and have the voice assistant perform tasks. In the case of OpenTable, the phone is still its biggest competitor as people tend to call when requests aren’t straightforward. The conversational agent is better able to handle these requests as it’s using all of its inherent knowledge.

During the session, AWS highlighted an initiative called “Night Out” where all three of these services come together to create a complete evening. The user merely tells Alexa that he or she wants to book a night out for two and Alexa comes up with a recommended combination of movie and dinner and can even prearrange an Uber to take them. The user just needs to wait for the recommendations and say yes or no to them or perhaps even just a single yes to a series of proposed events.

I do believe we are at an inflection point for the voice interface to become real. Alexa, as well as its peers Apple Siri, Microsoft Cortana, and others, have made it much easier to speak a command to complete simple tasks. Now that people have grown accustomed to this, it’s time for the voice assistants to start tackling bigger problems. Alexa Conversations enables larger problems to be solved, with less effort and less programming. Seems like a win for all parties involved. Maybe next year, I’ll be able to ask Alexa to write this post for me!

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