How to overcome the 3 biggest challenges of building a chatbot

Live Webinar | Thursday, October 31 | 10:00am PDT / 1:00pm EDT

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Why do Chatbots fail?

If you have tried your hands on building chatbots to handle customer support, you know that it’s not as easy as it seems. You probably have already spent significant resources on building one or have experienced negative customer feedback.

Why? That’s because of the following 3 challenges:

  1. Time-Consuming – Your organization most likely has a FAQ or simple answers to most questions from customers. Unfortunately, traditional chat solutions require you to think about all the different variations of how your customer could ask the question and map the variations to the answer. If you have 100 answers and each answer requires 10+ variations, you will have to create 1,000 variations! Isn’t that wonderful?! NO!
  2. Technical Resources – Many chatbots still require you to involve expensive technical resources. You will find that even after you built a chatbot that can accommodate 1,000 variations, the accuracy is still subpar, so you need to get that improved or trained. How? It depends on the vendor, but it will involve expensive AI experts.
  3. Impossible to Maintain – Yes, you have accomplished a great feat in the initial 1,000 variations. But as your business evolves, you need to update those questions and variations continuously. Let’s say you need to add ten new questions, which means 100 variations. How much time do you have in your day to do that?

There’s a better way to tackle the above challenges. Join this webinar on Thursday, October 31 to learn how you can utilize artificial intelligence to help you get over these chatbot hurdles.

 

 

 

 

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Bin Zhao Headshot

Dr. Bin Zhao - Vice President of Machine Learning, Petuum

Dr. Bin Zhao is Vice President of Machine Learning, at Petuum, where he leads a team of machine learning engineers and software engineers creating the next-gen RPA+AI solutions, Neurobots. Dr. Zhao has 14 years of R&D experience in machine learning. Zhao’s expertise covers large scale machine learning, computer vision, optimization, statistics, and data mining, with more than 20 publications in top ranked computer science journals and conference proceedings. He has a Ph.D. in machine learning from school of computer science at Carnegie Mellon University, Master of Science from Carnegie Mellon University, Master of Science and Bachelor of Science from Tsinghua University, the top ranked university in China. Zhao has served as Program Committee member and reviewer for top ranked computer science conferences and journals, such as IEEE PAMI, TKDE, DMKD, ICML, NIPS, ICCV, ECCV, CVPR, BMVC, etc.

Victor Thu Headshot

Victor Thu - General Manager of Neurobots, Petuum

Victor Thu is the General Manager of Neurobots at Petuum, partnering closely with Bin Zhao, to build easy-to-use cutting-edge AI/ML solutions that integrate seamlessly into RPA as IPA (intelligent process automation).  Before Petuum, Victor led marketing and product marketing for Digitate, a startup that focuses on solving IT operational challenges using AI and automation. As an industry technologist, Victor held different roles leading go-to-market strategies for innovative technologies, including the converged desktop, mobility, and identity solutions at VMware. Victor was an industry subject matter expert on business and workforce mobility with topics such as BYOD (Bring Your Own Devices). Victor also spent over three years in the Asia Pacific region, leading end-user computing product marketing for VMware and Citrix across the region. Victor has an MBA from Santa Clara University and holds three patents on internet technology.

About Petuum

Petuum is the leading provider of innovative industry solutions using the most advanced artificial intelligence technologies that have been out of reach for most businesses. Petuum’s solutions combine powerful technology, world-class talent and customer domain-specific knowledge to solve complex real-world challenges in a simple, cost-effective manner. These are operationalized on the Petuum Symphony AI platform, which delivers distributed and parallelized data processing as well as machine learning and deep learning workflows, at scale in every environment.