In this week’s episode we focus on AI application in the customer service business function, - specifically in the context of call centers. We speak with Ali Azarbayejani, CTO of Cogito based in the Boston area, which works on coaching and providing feedback for call center agents in real time. We aim to focus on what our readers and business executives can do today with AI in the context of call center applications, and how they can go about seeing measurable impacts over a predetermined period of time. We speak with Ali about what is possible with analyzing voice in real-time today and what kind of ROI can businesses expect for this application. Lastly we touch-base on what factors will make AI inevitable for some companies in the next two to three years. Interested readers can see the full interview with Ail here: https://www.techemergence.com/what-industries-will-adopt-voice-related-ai-applications-first/  

Episode summary: There are many challenges to bringing AI into an enterprise for example the lack of skilled AI talent, or issues around data organization. In this week's episode, we focus on AI adoption in the enterprise from an investor’s perspective. We expect that founders looking to sell B2B enterprise AI-products and people in enterprises who are looking for the right qualities in an AI firm which would ease integration, would find this episode relatable. We speak with Rudina Seseri from Glasswing Ventures about what are the pain points for AI integration in the enterprise and at the other end of the spectrum, some factors that are aiding AI adoption. Interested readers can see the full interview with Rudina here: https://www.techemergence.com/reducing-friction-ai-adoption-enterprise-rudina-seseri/  

Episode summary: In this week's interview on the AI in Industry podcast, we speak with Amir Konigsberg, the CEO of Twiggle, about the future of product search - and how eCommerce and retail brands can use natural language processing (NLP) to improve their user experience. Amir explains some of the factors that make eCommerce product search challenging, and the artificial intelligence approaches that can improve it today and within the next five years. Interested readers can learn more about present and future use-cases for artificial intelligence applications in retail in our full article on that topic. You can listen to the full interview with Amir Konigsberg from Twiggle here: https://www.techemergence.com/nlp-for-ecommerce-search-current-challenges-and-future-potential

Episode Summary: Machine learning (ML) can be used to identify objects and pictures or help steer vehicles, but is not best suited for text-based AI applications says Robbie Allen, founder of Automated Insights. In this episode of AI in Industry, we speak with Robbie about what is possible in generating text with AI and why rules based processes are a big part of natural language generation (NLG). We also explore which industries are likely to adopt such NLG techniques and in what ways can NLG help in business intelligence applications in the near future. You can listen to the full interview with Robbie here: https://www.techemergence.com/robbie-allen-from-automated-insights-the-use-cases-of-natural-language-generation  

Episode summary: This week’s episode explores the current possibilities in applying natural language processing for legal contract review. We speak with Andrew Antos and Nischal Nadhamuni from Klaritylaw, a Boston-based startup focused on using natural language processing (NLP) based information extraction, from non-disclosure agreements (NDAs), in a live setting. We delve into the current and future roles of AI and lawyers with respect to legal contracts. AI is currently being applied in applications like retroactive analysis and information identification in legal documents. According to Andrew and Nishchal, in the future we will see on-the-fly legal content creation from AI tools and NLP being applied to most commercial contracting. Although, one restraint that AI companies presently face in the legal domain is the lack of access to huge amounts of publicly available data. You can listen to the full interview with Andrew and Nischal here: https://www.techemergence.com/applying-ai-legal-contracts-whats-possible-now/ ‎

Episode summary: Most NLP applications we hear about involve marketing, customer service, and other customer-facing functions - but that there are NLP-related opportunities in other back-end functions as well.   In this episode of AI in industry, we speak with Talla's Chief Data Scientist, Byron Galbraith, about how businesses can leverage chatbots or other NLP applications for improving document search for internal company communication. Byron explores what is currently possible using AI to improve search operations using contextual awareness. Byron also paints a vision of what AI-enabled "knowledge sharing" and "knowledge discovery" might look like in the future. For the full article of this episode, visit: TechEmergence.com/artificial-intelligence-team-communication/

When we talk about natural language processing (NLP), applications like handling customer service or chatbots which can aid with questions, come to mind. Yet, in recent years, NLP platforms have been increasingly used in content marketing and content production applications. In this episode of AI in industry, we talk to Tomás Ratia García-Oliveros, the co-founder and CEO founder of Frase.io, a Boston based startup which focuses on NLP problems around content marketing and content creation. Tomas explores how NLP platforms are now able to summarize resources on the web, perform contextual search and language understanding applications related to this domain. See the full interview article with Tomás Ratia García-Oliveros live at: www.techemergence.com/artificial-intelligence-content-marketing-content-creation

In this episode of AI in industry, we speak with Michael Johnson, the director of research and innovation for Interactions llc, in Boston MA. Michael explores the inbound (human to machine) and outbound (machine to human) applications of voice based natural language processing (NLP) and also talks about attaching a timeframe to how soon small and medium enterprises (SMEs) would have access to this technology in a financially sensible manner.  Although NLP is often associated with chat or text interfaces, voice is important for applications in call centers, mobile phones, smart home devices, and more. In addition, Michael explains that voice involves unique challenges that text does not have to deal with - including background noise and accents, which need to be overcome to deliver a good user experience.  See the full interview article with Michael Johnston live at: www.techemergence.com/overcoming-challenges-spoken-voice-based-natural-language-processing-nlp-business-use

In order to shed more light on the growing applications of natural language processing, we speak with Vlad Sejnoha (CTO of Nuance Communications) about the current and near-term applications of NLP for voice and text across industries. In this podcast interview, Vlad breaks down real-world NLP use-cases in industries like banking, healthcare, automotive, and customer service. For the full article of this episode, visit: TechEmergence.com/natural-language-processing-current-applications-and-future-possibilities

This week on AI in Industry we interview Vito Vishnepolsky of Clickworker. Clickworker is a large microtasking marketplace that crowdsources the search optimization work for many of the world's leading search engines. So how does crowdsourced human work play a role in making sure eCommerce and media searches give users what they want? That's exactly what we explore this week. Vito’s perspective is valuable because he has a finger on the pulse of crowdsourced demand, handing business development for various crowdsourced AI support services - both for tech giants and startups. Read the full article online at TechEmergence: TechEmergence.com/how-microtasking-helps-optimize-ai-based-search