Aug 14, 2018

Amazon may have to drop next-day delivery claim in UK

Observe.AI raises $8M to use artificial intelligence to improve call centers

Being stuck on the phone with call centers is painful. We all know this. Observe.AI is one company that wants to make the experience more bearable, and it’s raised $8 million to develop an artificial intelligence system that it believes will do just that.

The funding round was led by Nexus Venture Partners, with participation from MGV, Liquid 2 Ventures and Hack VC. Existing investors Emergent Ventures and Y Combinator also took part — Observe.AI was part of the YC’s winter 2018 batch.

The India-U.S. startup was founded last year with the goal of solving a very personal problem for founders Swapnil Jain (CEO), Akash Singh (CTO) and Sharath Keshava (CRO): making call centers better. But, unlike most AI products that offer the potential to fully replace human workforces, Observe.AI is setting out to help the humble customer service agent.

The company’s first product is an AI that assists call center workers by automating a range of tasks, from auto-completing forms for customers to guiding them on next steps in-call and helping find information quickly. Jain told TechCrunch in an interview that the product was developed following months of consultation with call center companies and their staff, both senior and junior. That included a stint in Manila, one of the world’s capitals for offshoring customer services and a city well known to Keshava, who helped healthcare startup Practo launch its business in the Philippines’ capital.

That effort to know call center operates directly has also shaped how Observe.AI is pitching its services. Rather than going to companies, it is tapping the root of the tree by offering its services to the call centers who manage customer support for well-known businesses behind the curtain. Uber, for example, is one of many to use Philippines-based support centers, but the Observe.AI thesis is that going directly to the source is easier than navigating large companies for business.

One such partner is Concentrix, one of the world’s largest customer support providers with over 100,000 staff and offices dotted around the globe, while the startup said it has tapped Philippines telco PLDT for infrastructure.

In addition to helping understand the problems and generating business, working directly with these companies also gives Observe.AI access to and use of data, which is essential for developing any AI and natural language processing-based systems.

Beyond improving its customer service assistant — which Jain likens to an ‘Alexa for call centers’ — Observe.AI is working to develop a virtual assistant of its own that can handle the more basic and repetitive calls from customers to help free up agents for callers who need a human on the other end of the line.

“We aim to eventually automate a large part of the call center experience,” Jain explained in an interview. “A good set [of customer calls] are complex but a large set can be fairly automated as they are simple in nature.”

The startup is aiming to introduce ‘voicebots’ before March 2020, with a beta launch targeted at the end of 2019.

“The kind of company that will disrupt call centers will come from the east — we truly understand the call center life,” Jain told TechCrunch.

He explained that, while Silicon Valley is a hotbed for tech development, understanding the problems that need to be solved requires spending time in markets like India and the Philippines.

“That knowledge is super, super valuable… someone in the U.S. can’t even think about it,” he added.

That said, Observe.AI is headquartered in the U.S., in Santa Clara. That’s where Keshava, the company CRO, is based with a growing team that is dedicated pre- and post-sales and to building relationships with major software platforms used by call center companies. The idea with the latter is that they can provide an avenue into new business by working with Observe.AI to add AI smarts to their product.

In one such example, Talkdesk, a U.S. startup that offers cloud-based contact center services, has added Observe.AI’s services to what it offers to its customers. Talkdesk CEO Tiago Paiva called the addition “a huge opportunity for call center efficiency and improving the caller experience.”

The startup’s India-based team is in Bangalore and it handles technology, which includes the machine learning component. Total headcount is 16 people right now but the founding team expects that will at least double before the end of this year.



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May 23, 2018

Bill Gates Names 5 Books You Should Read This Summer

It's something of a tradition. Every summer, philanthropist/Microsoft founder Bill Gates recommends five books to read during the slow summer months. This year's list, he tells us, wrestles with some big questions: "What makes a genius tick? Why do bad things happen to good people? Where does humanity come from, and where are we headed?"

And now, without no further ado, here's Bill's list for 2018. The text below is his, not mine:

Leonardo da Vinci, by Walter Isaacson. I think Leonardo was one of the most fascinating people ever. Although today he’s best known as a painter, Leonardo had an absurdly wide range of interests, from human anatomy to the theater. Isaacson does the best job I’ve seen of pulling together the different strands of Leonardo’s life and explaining what made him so exceptional. A worthy follow-up to Isaacson’s great biographies of Albert Einstein and Steve Jobs. [Read his blog post on the book here.]

Everything Happens for a Reason and Other Lies I’ve Loved, by Kate Bowler. When Bowler, a professor at Duke Divinity School, is diagnosed with stage IV colon cancer, she sets out to understand why it happened. Is it a test of her character? The result is a heartbreaking, surprisingly funny memoir about faith and coming to grips with your own mortality. [Read his blog post on the book here.]

Lincoln in the Bardo, by George Saunders. I thought I knew everything I needed to know about Abraham Lincoln, but this novel made me rethink parts of his life. It blends historical facts from the Civil War with fantastical elements—it’s basically a long conversation among 166 ghosts, including Lincoln’s deceased son. I got new insight into the way Lincoln must have been crushed by the weight of both grief and responsibility. This is one of those fascinating, ambiguous books you’ll want to discuss with a friend when you’re done. [Read his blog post on this book here.]

Origin Story: A Big History of Everything, by David Christian. David created my favorite course of all time, Big History. It tells the story of the universe from the big bang to today’s complex societies, weaving together insights and evidence from various disciplines into a single narrative. If you haven’t taken Big History yet, Origin Story is a great introduction. If you have, it’s a great refresher. Either way, the book will leave you with a greater appreciation of humanity’s place in the universe. [Read his blog post on this book here.]

Factfulness, by Hans Rosling, with Ola Rosling and Anna Rosling Ronnlund. I’ve been recommending this book since the day it came out. Hans, the brilliant global-health lecturer who died last year, gives you a breakthrough way of understanding basic truths about the world—how life is getting better, and where the world still needs to improve. And he weaves in unforgettable anecdotes from his life. It’s a fitting final word from a brilliant man, and one of the best books I’ve ever read. [Read his blog post on this book here.]

You can find Gate's reading lists from previous summers in the Relateds below.

via Gates Notes

Related Content:

Bill Gates Recommends Five Books for Summer 2017

5 Books Bill Gates Wants You to Read This Summer (2016)

Bill Gates, Book Critic, Names His Top 5 Books of 2015

Summer 2014

Summer 2013

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May 10, 2018

Buoy Health, CVS MinuteClinic partner to send patients from chatbot to care

Buoy Health, which offers an AI-powered tool that serves to help people understand potential health problems, announced a partnership with CVS MinuteClinic.

When users go through Buoy Health’s online or app-based chatbot interface, if the suggested possible diagnoses lend themselves to treatment at one of the 1,100 MinuteClinics around the United States, the app will do two things. First, it will use GPS to locate the nearest MinuteClinic, and second, it will offer to hold a place in line for the user.

“We’re still figuring out all the nuts and bolts of the commercial arrangement,” Dr. Andrew Le, CEO of Buoy Health, told MobiHealthNews. “This is the first small bite that we’re taking. But we really feel there are mutual benefits for us. We’re enabling a better patient experience, as is CVS. We’re helping bring affordable care to as many patients as possible. What we’re doing is trying to keep patients out of the ER when not appropriate, out of urgent care when not appropriate. So as an affordable place for those patients to land, the MinuteClinic is a really obvious and really nice place for people to get care.”

Obviously the partnership will also benefit CVS by sending individuals to the MinuteClinic who otherwise might not think of it.

“CVS Health is committed to helping people on their path to better care. We do so by providing high-quality health care services that are convenient, affordable, and accessible for patients,” Dr. Troyen A. Brennan, EVP and chief medical officer at CVS Health, said in a statement. “Entering into a relationship with a health-tech innovator like Buoy to connect their experience to our nationwide network of MinuteClinic providers gives us the opportunity to provide affordable care at times and locations that work best for the patients who utilize this innovative technology.”

Buoy Health launched in March 2017 and raised $6.7 million in August. Le says the company has seen significant traction in the meantime.

“By the end of [2017] we actually hit about two and a half million visitors to the site, which we were really excited about,” he said. “Even more exciting is our growth in 2018. This year we’re actually on pace for somewhere between 25 and 50 million visitors to the site.”

What’s more, the visitors capture an interesting segment of the market, gathering data on patients in the early stages of symptoms that can then be used to train Buoy’s machine learning algorithm to be even better.

“What’s interesting is that 65 percent of our users have had symptoms for less than 12 hours when they come to Buoy,” Le said. “Data on how symptoms evolve, that kind of data just doesn’t exist. So as we see patients we’re capturing a snapshot of suffering that’s really unique and interesting for us.”

Le says MinuteClinic is a first step: the company hopes eventually to be able to automatically refer users to a number of different services based on their particular needs.

“We’re going to continue to partner with innovative providers and payers across the country to help patients who have different severity levels find that type of care,” he said. “Whether it’s emergency care, or primary care, or a weight loss program, or behavioral health, all those other services we’re going to continue to partner such that people can really count on coming to Buoy, understanding what to do, and then enabling them to do it. So this is kind of our first step in doing so.”



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Jan 30, 2018

What If Amazon Ran Hospitals?

What if Dr. Alexa offered you the next appointment with your doctor in the Amazon Clinic? What if you could buy your prescription drugs in Amazon’s online pharmacy? What if you could get your...

Visit my blog to read the whole article and other news about the future of medicine!


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Jan 24, 2018

Comprehensive, open tutorial on using data analysis in social science research

Benjamin Mako Hill (previously) collaborated with colleagues involved in critical technology studies to write a textbook chapter analyzing the use of computational methods in social science and providing advice for social scientists who want to delve into data-based social science.

Their chapter is open access, and starts with a history of modern data-driven social science research, from its early days in social network analysis to the contemporary world of consumer analysis and public health research.

But the chapter primarily serves as a tutorial for using data methods with in your own social science research, with extensive code examples and practical advice.

You're invited to improve the paper and check your changes into the Github repo for it.

Abstract
Data from social media platforms and online communities have fueled the growth of computational social science. In this chapter, we use computational analysis to characterize the state of research on social media and demonstrate the utility of such methods. First, we discuss how to obtain datasets from the APIs published by many social media platforms. Then, we perform some of the most widely used computational analyses on a dataset of social media scholarship we extract from the Scopus bibliographic database’s API. We apply three methods: network analysis, topic modeling using latent Dirichlet allocation, and statistical prediction using machine learning. For each technique, we explain the method and demonstrate how it can be used to draw insights from our dataset. Our analyses reveal overlapping scholarly communities studying social media. We find that early social me- dia research applied social network analysis and quantitative methods, but the most cited and influential work has come from marketing and medical research. We also find that publication venue and, to a lesser degree, textual features of papers explain the largest variation in incoming citations. We conclude with some consideration of the limitations of computational research and future directions.

Introducing Computational Methods to Social Media Scientists [Benjamin Mako Hill]

A Computational Analysis of Social Media Scholarship [Jeremy Foote, Aaron Shaw and Benjamin Mako Hill]

Software and data for "A Computational Analysis of Social Media Scholarship" [Jeremy Foote, Aaron Shaw and Benjamin Mako Hill]

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