How Technology is Giving Customers Their Power Back

When it comes to emerging technology, most consumers are often quite fearful of this kind of change. Many are concerned that automation will eliminate thousands of jobs in the near future. Others fear that their private data can be bought and sold, putting them in danger or removing any sense of privacy from the internet.

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The Rise of Chatbots (And Why Your Business Needs Them)

It’s hard to believe we’re living in the year 2020.
And while it may not quite be the space age that many predicted decades ago, it’s pretty cool nonetheless. We have cars that can park themselves, powerful computers that are as small as wristwatches, and robots that can do our business bidding for us.
We’re talking about chatbots, of course.

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AI the Perfect Solution to the Identity Fraud Epidemic

Fraud has been an ongoing problem for quite some time now. Our technology may have become more sophisticated but so are criminals. It feels more secure now that we have several modes of verification but it’s still unsettling to see news of big companies like Facebook or Yahoo getting their data compromised.
Fraud is not a small problem. The global cost of it is $4.2 trillion.

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Vendor Mistake

Here’s a problem, quite possibly caused by the vendor responsible for email marketing at Final Draft … maybe not, but quite possibly yes.I once had a boss who told me that I was free to pick and choose vendors and when my vendor messed up badly I’d lose my job as a consequence. Is that a fun work environment? Nah. Is that the way the world works? Oftentimes yes.

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Predictive Analytics Advances Rewrite Rules On Corporate Conferences

In years past, it was quite the cumbersome task to put together corporate conferences for the dissemination of important information and trends among industry stakeholders. It was only within the last few years that advancements in technology have provided efficient ways to bring large groups of stakeholders together for them to share information.

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Everything you wanted to know about chatbot platforms, and some things you didn’t

It’s quite overwhelming how many chatbot platforms there are. How
should I know which one to choose? I created
ChatbotTech to solve this problem. It’s a
site that reviews and rates all* the chatbot platforms so you don’t
have to.
*some. In fact it’s quite hard to know which ones to review, there are
so many.

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Disney, Caltech

As many of you know, I was kept quite busy on the faculty job market this past spring, when I spent three months traveling almost non-stop. My time as a postdoc at Carnegie Mellon University was a very stimulating and productive one, but it is now coming to a close. Many thanks to my supervisors, Carlos and Krishnan, as well as all my other colleagues and collaborators.

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Making AI Interpretable with Generative Adversarial Networks

It has been quite awhile since I have posted, largely because soon after I started my job at Square I had a child! I hope to have some newer blog post soon. But along those lines I want to share a blog post I did with a coworker (Juan Hernandez) for Square that gives a taste of some of the cool data science work we have been up to.

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ICML has 3(!) Real World Reinforcement Learning Workshops

The first is Sunday afternon during the Industry Expo day. This one is meant to be quite practical, starting with an overview of Contextual Bandits and leading into how to apply the new Personalizer service, the first service in the world functionally supporting general contextual bandit learning.
The second is Friday morning. This one is more academic with many topics.

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So You Want to Start a Podcast

Podcasting has gotten quite a bit easier over the past 10 years, due in part to improvements to hardware and software. I wrote about both how I edit and record both of my podcasts about 2 years ago and, while not much has changed since then, I thought it might be helpful if I organized the information in a better way for people just starting out with a new podcast.

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What is Empirical Risk Minimization

Even though it has an ornate name, the underlying concept is actually quite simple and intuitive. The concept of Empirical Risk Minimization becomes relevant in the world of supervised learning. The actual goal of supervised learning is to find a model that solves a problem as opposed to finding a model that best fits the given dataset.

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