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3 Obstacles to the Evolution of Conversational AI

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Shaip

Thanks to ongoing advancements in the fields of artificial intelligence and machine learning, computers can perform a growing number of cognitive tasks. As a result, businesses are able to rely on machines for critical functions once thought impossible to automate. In particular, the rise of conversational AI platforms such as chatbots and virtual cognitive agents has given organizations in a wide range of industries the ability to improve customer support and HR activities — and these platforms are only getting smarter.

Interest in conversational AI skyrocketed in 2020, as did corporate investment in machine learning platforms. This was in large part due to the COVID-19 pandemic, which forced companies in nearly every sector to find ways to do more with less. The sudden spike in customer inquiries received by banks, retailers, and airlines, for instance, exposed the limitations of human customer-support teams and the urgent need for automated capabilities. Moreover, the pandemic has altered our expectations as consumers, increasing the demand for digital-first customer experiences.

1.Detecting emotions. For starters, most platforms are still relatively unsophisticated when it comes to detecting emotions. Human communication depends as much on emotion as it does on language, and a change in tone could completely alter the meaning of spoken or written dialogue. In order to train computers to detect subtle contextual cues, product teams need troves of data containing many different human voices. Finding all that data is no small challenge.

1. How Conversational AI can Automate Customer Service

2. Automated vs Live Chats: What will the Future of Customer Service Look Like?

3. Chatbots As Medical Assistants In COVID-19 Pandemic

4. Chatbot Vs. Intelligent Virtual Assistant — What’s the difference & Why Care?

2. Learning new languages. Most of the world’s population doesn’t speak English. Global organizations that hope to use conversational AI to interact with customers outside the United States would need platforms that understand not only different languages, but also various regional dialects and cultural differences. Again, this would require large amounts of multilingual speech and audio data from diverse communities and a wide range of situations (e.g., TED Talks, debates, phone conversations, monologues, etc.), and that data would need to cover a variety of topics.

3. Identifying the right voice. Training AI to detect a single speaker among a multitude of voices is another challenge, one that’s likely familiar to anyone with an in-home smart speaker such as Google Home or Amazon’s Alexa. In a crowded living room, these platforms might respond to commands not intended for them or might be unable to distinguish commands over multiple conversations. This usually creates minor frustration and perhaps some comic relief, but when business transactions involving sensitive customer data are being conducted via voice commands, it’s imperative that the AI doesn’t confuse user accounts.

Despite these obstacles, conversational AI holds immense potential for businesses of all kinds. Shaip is here to help you unlock that potential, and it all starts with data. We can provide product teams with hours of transcribed, annotated audio data in more than 50 languages. Using our proprietary data-acquisition app, we’re able to streamline the distribution of data-collection tasks to global teams of experienced data collectors. The app interface allows data collection and annotation service providers to easily view their assigned collection tasks, review detailed project guidelines including samples, and swiftly submit and upload data for approval by project auditors.

Used in conjunction with the ShaipCloud Platform, our app is just one of many tools that equip us to source, transcribe, and annotate data at virtually any scale needed to train sophisticated algorithms for use in real-world customer interactions. Want to learn what else makes us the leaders in conversational AI? Get in touch, and let’s get your AI talking.

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Source: https://chatbotslife.com/3-obstacles-to-the-evolution-of-conversational-ai-426b18bd02eb?source=rss—-a49517e4c30b—4

Artificial Intelligence

Australian ID verification startup OCR Labs raises $15M Series A to expand into UK/Turkey/Europe

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With the gig economy came the need for ID verification, thus startups like OnFido (raised $188.8 million) appeared, alongside several others. But this sector is by no means ‘done’ yet.

Now, OCR Labs, which emerged from Australia, has announced a €12.5M / $15 million Series A funding round led by Turkish investors Oyak Group, to expand its services and team to the UK, Turkey and Europe. Halkin Ventures invested in its seed round. The startup specializes in digital ID verification, customer onboarding, identity fraud, and regulatory compliance.

OCR Labs, founded in 2018 by Daniel Aiello and Matthew Adams, says its technology uses “five proprietary technologies in one solution, including identity document optical character recognition (OCR), document fraud assessment, liveness detection, video fraud assessment, and face matching”. This supports AML and KYC regulations.

Daniel Aiello, Co-Founder, and CPO of OCR Labs, commented, “The need for digital verification is growing exponentially. This past year we’ve seen more demand from new sectors as they try to navigate the pandemic and an inability to operate in person…No one wants to spend hours trying to prove who they are, whether it’s for a job or for a bank account, and we also want to know we’re protected against identity theft and fraud. Digital ID verification has a key role to play, but this year we’ve also seen the limitations if hybrid models are used. People are a barrier and a risk, but fully automated technology can have a huge impact on many industries and privacy. OCR Labs is built to be secure, frictionless and fast, and capable of recognizing ID documents the world over.”

OCR Labs is used by recruitment business REED in the UK. Russ Cohn, an early member of the Google UK leadership team, has been appointed OCR’s General Manager of International Operations, based out of London.

Cohn commented: “The technology that Matt and Dan have created is completely automated, so it doesn’t rely on any humans behind the scenes. That’s very key at the moment. We’ve seen how COVID has impacted having that hybrid solution, so automation increases the speed and delivery of the technology to our users… A lot of competitors outsource and use different vendors to put together a solution.”

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Source: https://techcrunch.com/2021/06/15/australian-id-verification-startup-ocr-labs-raises-15m-series-a-to-expand-into-uk-turkey-europe/

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Digital Onboarding: BNY Mellon and Saphyre to Leverage AI to Enhance Customer Experience

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BNY Mellon (NYSE: BK), an American investment banking services holding company headquartered in New York City with over $380 billion in assets, and Saphyre recently revealed that they’ll utilize AI tech to enhance the customer experience while also automating and expediting client onboarding.

This partnership with Saphyre supports the bank’s OMNISM strategy to work cooperatively with Fintechs to better support customers’ investment goals.

Saphyre’s platform has been developed to provide seamless communication between customers and priority stakeholders by enhancing traditional communication methods, like email, fax, and phone calls.

This latest integration between the two firms will allow for improved communication while lowering time to market, and also enabling more efficient international trading.

Caroline Butler, Global Head of Custody at BNY Mellon, stated:

“Time is a finite and precious commodity. BNY Mellon’s work with Saphyre aims to create true savings for our custody clients and truly expedite the client onboarding process. What once took days or weeks, is now near real time. This is yet another example of the digitization efforts BNY Mellon has undertaken in the past two years with a direct client benefit.”

Gabino M. Roche, Jr., CEO and Founder at Saphyre, remarked:

“Having BNY Mellon join the Saphyre endeavor is a great honor. By applying our patented technology to their leading asset servicing operations we’ve demonstrated the ability to intelligently pre-fill client custody packs, allow for digital signatures, auto-setup SWIFT Reporting, Trade Message Routing, and Corporate Action standing instruction – while intelligently and dynamically tracking market requirements and their respective document statuses. In a post-COVID world where AI and digital is paramount, BNY Mellon is fully seizing the innovation mandate.”

Earlier this year, BNY Mellon released a report in which it noted that the bank thinks there’s now real demand for Bitcoin and other cryptocurrencies. In its report, the bank clarified that it’s not attempting to derive a price target or formalize “a valuation mode” for these new forms of assets. However, they intend to look into the different “analogies” and “dissimilarities” that may be applied to Bitcoin and “potentially other areas of cryptos.”

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Source: https://www.crowdfundinsider.com/2021/06/176551-digital-onboarding-bny-mellon-and-saphyre-to-leverage-ai-to-enhance-customer-experience/

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Passengers Learn To Adapt As Airlines Adopt Dynamic Pricing

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With airlines keener than ever to maximize revenues, dynamic pricing is making inroads into the industry. Not everyone is welcoming the trend, but industry insiders say dynamic pricing can benefit both passengers and airlines.

dynamic-pricing-airline-industry
Like it or not, dynamic pricing is here to stay in the airline industry. Photo: Don Wilson / Sea-Tac Airport

Airlines know a lot about their passengers, dynamic pricing harnesses that knowledge

Dynamic pricing is a process whereby an airline will pitch a fare at you based on what they know about you or think they know about you. Airlines are masters at gathering data. They harvest your frequent flyer data and track your searches and interests online via cookies. Hand over your Amex details to buy a drink inflight or a case of wine from the airline’s wine store and that airline gets an insight into your drinking preferences. Hundreds or thousands of these tracked behaviors all add up.

Log on to the British Airways website (or any airline’s website) after cleaning up your browser, and a message like this pop up.

“By continuing to use ba.com, you will be agreeing to the website terms and conditions and the use of cookies while using the website and our services. Please also read our privacy policy under which, to the extent stated, you consent to the processing of your personal data.”

Airlines already know a lot about their passengers – we’ve largely lost or surrendered that privacy battle. Now, many airlines are harnessing that data and learning to use it to boost revenues. On an individual passenger level, dynamic pricing tries to determine what a passenger is willing to pay to fly from Madrid to Heathrow next Sunday.

dynamic-pricing-airline-industry
Your favorite airline already knows a lot about you. Photo: Don Wilson / Sea-Tac Airport

Just how much will a passenger pay to fly at a certain time on a certain day?

Justin Jander, Director of Product Management at digital commerce platform PROS  says airlines are trying harder than ever to create a sticky end-to-end passenger journey. One way they can do that is to use artificial intelligence (AI) to learn from the past behavior of a passenger. The airline can then attempt to predict what they will do next – including what they are willing to pay for an airline ticket.

“Dynamic pricing is extremely relevant to the airline industry as it allows airlines to break away from the barriers of fare classes with fixed price points,” says Jander. “Imagine a scenario where there are two filled fares, one at $100 and the other at $200. If a passenger is willing to pay $150, the airline either offers that passenger the $100 fare and loses $50 in incremental income. Or the airline can offer the $200 fare and lose the entire $150. Having this flexibility to identify an optimal price point allows airlines to be more effective in capturing revenue.”

We know airlines adjust fares according to broad seasonal factors. We also know an airline will adjust fares to a particular destination at a certain time if a big event is on in that city, say a football final. Equally, airlines will drop fares at off-peak times to stimulate travel demand. Dynamic pricing is about taking this to a more granular, individual passenger level.

dynamic-pricing-airline-industry
Passengers can stand to benefit from dynamic pricing if they learn how it works. Photo: Ontario International Airport

Dynamic pricing can work for passengers

Justin Jander says dynamic pricing can work for passengers as well as airlines. At a basic level, interested passengers can learn how dynamic pricing works and is applied. It’s like learning how frequent flyer, hotel loyalty, or shopping programs work. Once you understand the nuts and bolts of dynamic pricing, passengers can potentially work dynamic pricing to their advantage.

“It is more expensive to acquire a new customer than to retain one,” says the PROS Director. “It makes sense for airlines to prioritize getting to know their existing customers.

“For passengers that are brand loyal customers of a particular airline, they will benefit from receiving personalized flight packages based on the AI that the airline has been able to leverage to understand them and their preferences.”

Most airline insiders agree dynamic pricing is here to stay. As the AI behind it gets smarter, so to will dynamic pricing. It will become more subtle and less driven by sometimes clunky algorithms. There always has been and always will be some tension between buyer and seller. Dynamic pricing in the airline industry won’t take that away> But over time, dynamic pricing may become better at fixing the median price that satisfies both airline and passengers.

Do you agree with dynamic pricing in the airline industry? Is it here to stay? Post a comment and let us know.

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Source: https://simpleflying.com/dynamic-pricing-airlines/

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Waabi’s Raquel Urtasun explains why it was the right time to launch an AV technology startup

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Raquel Urtasun, the former chief scientist at Uber ATG, is the founder and CEO of Waabi, an autonomous vehicle startup that came out of stealth mode last week. The Toronto-based company, which will focus on trucking, raised an impressive $83.5 million in a Series A round led by Khosla Ventures. 

Urtasun joined Mobility 2021 to talk about her new venture, the challenges facing the self-driving vehicle industry and how her approach to AI can be used to advance the commercialization of AVs.


Why did Urtasun decide to found her own company?

Urtasun, who is considered a pioneer in AI, led the R&D efforts as a chief scientist at Uber ATG, which was acquired by Aurora in December. Six months later, we have Waabi. The company’s mission is to take an AI-first approach to solving self-driving technology. 

I left Uber a little bit over three months ago to start this new company, Waabi, with the idea of having a different way of solving self-driving. This is a combination of my 20-year career in AI as well as more than 10 years in self-driving. Thinking about a new company was something that was always in my head. And the more that I was in the industry, the more that I started thinking about going away from the traditional approach and trying to have a diverse view of how to solve self-driving was actually the way to go. So that’s why I decided to do this company. (Time stamp: 1:21)

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Source: https://techcrunch.com/2021/06/14/waabis-raquel-urtasun-explains-why-the-time-was-right-to-launch-an-av-technology-startup/

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