Much like any good fiction writer dreams up the ending of their story and writes to that ending, good NLG leaves the reader with actionable information—and the creator should write to that.
Outlining the context layer for the ending works a lot like outlining the beginning, only instead of outlining all viable ledes (the shortest possible summarization of the most important facts hidden within the data), we'll be listing, prioritizing, and grouping all the potential endings.
Potential endings can take any format. That's a business decision based solely on the purpose of the content. But there are some commonalities for good endings, and that gives us a place to start.
If you're having trouble thinking up a good ending for your NLG content, remember: all good stories have meaning. In other words, all content has some purpose for its existence, whether it's to sell something, mark progress, or even provide an update until more information arrives.
read the rest at: https://automatedinsights.com/blog/defining-the-context-layer-in-nlg-part-2-what-does-it-mean
This is because NLG content is less about the words and more about the insights, the data. The context layer will help make sure the words are used to convey the data to the reader in a manner that can be absorbed quickly and easily.
So how do you define a context layer?
First and foremost, defining the context layer is a business process, not a technical process. It's akin to defining business requirements for custom software, and then translating those business requirements into technical requirements. The beauty of Wordsmith is that it allows anyone, regardless of technical aptitude, to translate their own business requirements into automated content.
But like any business initiative worth pursuing, just because the process isn't technical doesn't mean it isn't complex. In fact, when we work with customers to assist them in creating massive automated content projects, like Yahoo's Fantasy Football Recaps or the AP's Quarterly Earnings Reports, we spend the vast majority of our time working with our customer to define the context layer, and we take most of our cues from their industry experts.
The goal when creating good automated content is to unlock the story hidden within the data. And those stories can usually be boiled down to a few basic structural elements.
In this post, we'll look at the first and most important of those structural elements, and talk about building a context layer around it.
read the rest at: https://automatedinsights.com/blog/defining-context-part-1
That can be a plus
In Episode 6.7 of The Startup Show, we talk to NeuroPlus founder Jake Stauch about how his amazing brainwave tech struggled to take off until he found the right problem for his solution.
While a student a Duke University, Jake founded NeuroPlus, a company that tested audience reaction to advertising by scanning brain waves. His customers were routinely fascinated by his tech, but Jake couldn't get a lot of repeat business. A lot of customers didn't understand the data, and even when they did, they had a hard time grasping the value.
read the rest
And how to do it
In Episode 6.6 of The Startup Show, we discussed the challenges of starting up a retail product, in this case, Mati Energy, with founder and CEO Tatiana Birgisson. The beverage industry is home to some entrenched, deep-pocketed (sometimes evil) corporations, and the plucky startup has to be more than just unique and hardworking to survive in that environment.
There's almost always an element of luck involved.
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The Startup Show - Episode 6.5
Last week, during what was supposed to be the shoot for The Startup Show's 7-block (episodes 7.1, 7.2, and so on), I instead gathered the talent and crew into the WXYZ lounge at the awesome Aloft Durham Downtown and there we all discussed the future of Teaching Startup.
In short, we discussed whether or not it should have a future.
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The Great Silicon Valley Startup Debate
There's a lot of debate in this episode and it's all warranted and it's all around where you start your company and how much that matters.
When Automated Insights sought its Series A VC raise, we were offered a big check almost immediately, funding for years, provided we move our company out west. Robbie had a young family, I had a young family, it was pretty much off the table.
We got to our Series A, but it took much longer and was much more work than even we, conservative as we were, could have imagined. We didn't raise VC money locally, but we couldn't have gotten there without the support of the organizations and individuals around us for introductions, advice, and help with business development.
We wound up giving back to our community in different ways. Robbie turned to angel investing, and is involved with a number of local early startups. I hated writing checks, so I do this, and I did ExitEvent, and I advise and/or mentor anywhere from four to six local early startups at any given time.
A startup community is important, no doubt, but questions have to be asked and I think we ask most of them in this episode. How valuable is the local community? Does it need a physical, locational definition? What about digital communities (that's a big one for us)? What is support and what is just noise? Does everyone outside of the Valley need to be customer first?
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The Startup Show: Episode 6.3
Before I started my journey at Automated Insights, I had spent a couple years consulting. This is what entrepreneurs do when they finish one thing and haven't figured out what to do next. But I didn't just do consulting, I went all-in on a consulting startup.
I hired people, I built the portfolio up to over 20 clients, I was doing over $1 million in revenue each year. This was the first time I had built something completely based on service and completely based on revenue, and that would inform how I thought about startups from that point on.
The lesson learned was pretty simple. Get to money, and get there quick.
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Data variability, which is predicated upon the number and the depth of insights driven by changes in the data, is the key quality driver in Natural Language Generation (NLG). And to do NLG data variability right, you have to create a lot of scenarios.
NLG creators must always be asking: How vast is the universe of outcomes that the engine takes into account when creating a narrative?
In other words: How many ways can you say something?
It's not a coincidence that this is the same approach used when developing NLG's reverse twin, Natural Language Processing (NLP).
Words from Data meets Data from Words
People get touchy when you confuse NLG and NLP, especially those people who do either for a living (which is not a lot of people, but they still get touchy). The truth is that there is a lot of commonality between NLG and NLP. The core concept is the same: Understand the input and translate to the output.
While NLP takes in words and translates those words to data, NLG takes in data and translates that data to words. But creating words isn't the hard part of NLG. In fact, we've reached the point where machines can create complex sentences without too much trouble. In its simplest form, creating words from data is a binary proposition:
read the rest at: https://automatedinsights.com/blog/good-vs-bad-automated-content-its-in-the-context-layer
Some reasons are obvious, some less so
There are some obvious reasons why I wanted to get Tatiana Birgisson, founder of Mati Energy, and Jake Stauch, founder of Neuro Plus, on The Startup Show. And also some not-so-obvious reasons.
Tatiana is one of the most impressive people I've met over the last five years. And it's conscious decision I just made to not call her the most impressive woman or the most impressive young entrepreneur I've met over the last five years.
When I first met Tatiana, she was dragging kegs of Mati Energy to startups all over the American Tobacco campus. She was perfecting the formula, brewing the beverage, packaging, marketing, selling, and delivering. Mostly by herself.
Forward a year or so later when she was the keynote at Triangle Startup Weekend. I brought my twin daughters, around 10 years old at the time, to hear Tatiana speak and take in all the startup. Tatiana made an instant impression on both of them, more so than my own startup championing around the house.
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Building The Startup Show
I'm so freaking lucky.
I realize how cool it is that I'm in a position where I can be so open about my side project(s) at any given time. I like to think I've earned that over a 20-year career of proving I can handle, and actually benefit from, doing two things at once.
In this episode of The Startup Show, Jon, Andy and I got into the really deep topic of side projects. I'm a big believer in the necessity of side projects, something between a hobby and a job, to fuel what it is your trying to do with your life. And if your "day job" is the right job, i.e. it's the roadmap to do what you want to do with your life, a second thing can't be anything but helpful to that first thing.
Over the last week I've realized a couple things. I've never been more convinced that Teaching Startup and The Startup Show can and will work and do big things, but I'm also more and more aware of how much I need to narrow my focus.
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It's not as crazy as it sounds
The latest episode of The Startup Show is the first in which we take an actual member question from our Talk board (in the member area of the Teaching Startup website, join now and use it please).
Dawn was let go from her job due to cutbacks. This is a great excuse for her to start her own company, which she has always dreamed of doing. One small problem, she doesn't have a single idea for a product, service, or anything else to sell.
This is actually not a problem. She served us up a great, universal entrepreneur's dillema.
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Because we need to move the conversation forward too
In Episode 5.2 of The Startup Show, we talk about sexual harassment in startup culture.
The recent incident at 500 Startups isn't the first time sexual harassment has made an appearance in startup culture. Far from it, just look at all the recent issues at Uber as a starting point. Nor do we think that this is something that will magically go away anytime soon.
It sucks, and we just feel like startup culture should, and more importantly COULD, be better than corporate culture in this regard. And we think the responsibility for that falls heavily on dudes like us.
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I spent the summer thinking about how to make Teaching Startup better
I don't want The Startup Show or Teaching Startup itself to be a local thing. I've been pretty adamant about that ever since ExitEvent, my last startup, couldn't get out of the local scene and expand nationally. But I also believe there are concepts we talk about on a local level that can inform at a national level.
What works for Raleigh and Durham can work for Des Moines, Mobile, Syracuse, even Austin.
In this first-ever "local" episode of the now rebranded The Startup Show, Jon Colgan, Andy Roth and I (no Chop this week), talk about everything from beer to religion to creative writing to west coast money and how they can influence and impact local economies, and how entrepreneurs can and should be at the heart of this.
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How to make the human touch more human using natural language generation
They'll point to fees as the culprit. In other words, the robo-advisor is far less expensive, charging less than 1% of the value of one's portfolio, as opposed to the traditional 1% to 3% charged by most professional financial managers.
They'll also jump on the shift in user experience expectations from boomers to millennials. Younger people tend to do everything digitally and quickly, with as little personal contact as necessary. That's how they shop, get themselves from place to place, order food, find lodging, and so on. On-demand, push-button, machine-recommended-options are just the way the kids do things these days.
As a counter-argument, the professional managers offer a more -- pun intended -- human touch. Their experience, their ability to research, and the option to call or email or visit the local branch are all selling points.
What the professional financial managers tend to miss is that the human touch, so often lauded as their unique differentiator, isn't as human as it used to be. If professional managers want to reach and accommodate this new investor class, they need to be able to scale the human touch.
read the rest at: https://automatedinsights.com/blog/nlg-the-secret-weapon-in-the-war-between-financial-managers-and-robo-advisors
It Comes Down to Managing Expectations and Staying Agile
Two years ago, an entrepreneur came to me with a dilemma. She had been approached by another entrepreneur who was being forced to wind down his own fledgling startup as his funding dried up. He was a one-person shop, he had made a decent run of it, but time was up.
Now he wanted to go to work for her.
I walked her through the dilemma. The guy had great tech and had been able to do a lot in a short amount of time with limited funds and resources. His was a tragic and all-too-common story. He raised a small seed round, crushed his milestones, a lot of investors were saying "maybe," and he just ran out of runway.
So I asked her: Where's the dilemma? He didn't want a lot of money or equity. He wasn't looking for a specific role, but he came with ideas. He had connections, experience, and he filled a gap in a place she wasn't super strong. He came with zero baggage. He wasn't a jerk, no blemishes on his personal record.
She then explained, in a long, roundabout way, that he didn't fit the plan.
read the rest at: http://teachingstartup.com/one-bad-early-hire-can-kill-a-startup.asp
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