Chatting with robots absolutely fascinates me. I’ve received two telemarketing calls for secondary education that was merely voice-clips served by an algorithm based on my responses. But that wasn’t evident until about the 25 second mark. Pretty good 2015 Turing test! I got one into a 3 minute loop asking it weird things, actually.

Check this out…

Conversational modeling is an important task in natural language understanding and machine intelligence. Although previous approaches exist, they are often restricted to specific domains (e.g., booking an airline ticket) and require hand-crafted rules. In this paper, we present a simple approach for this task which uses the recently proposed sequence to sequence framework. Our model converses by predicting the next sentence given the previous sentence or sentences in a conversation.

Human: who is skywalker ?
Machine: he is a hero .
Human: who is bill clinton ?
Machine: he ’s a billionaire .
Human: is sky blue or black ?
Machine: blue .
Human: does a cat have a tail ?
Machine: yes .
Human: does a cat have a wing ?
Machine: no
Human: can a cat fly ?
Machine: no .
Human: how many legs does a cat have ?
Machine: four , i think .
Human: how many legs does a spider have ?
Machine: three , i think .
Human: how many legs does a centipede have ?
Machine: eight .
Human: what is the color of the sky ?
Machine: blue .
Human: what is the color of water ?
Machine: water .
Human: what is the color of blood ?
Machine: it is the same as a black eye .
Human: what is the usual color of a leaf ?
Machine: it is a green one .
Human: what is the color of a yellow car ?
Machine: yellow .
Human: how much is two plus two ?
Machine: four .
Human: how much is ten minus two ?
Machine: seventy – two .

via The Future of Neural Network-based Chatbots and Intelligent Virtual Agents: A Neural Conversational Model.

I think this is an amazing quote, and says a lot about what’s driving content innovation these days… Especially as Buzzfeed hires a longtime PepsiCo marketing exec, Frank Cooper, to help them blow up their approach this week…

Anyway: another thought prompted by a throwaway Ellis tidbit in relation to the news that some brands (in this case, Ballantines Whisky) after having escaped the early 2000s gravitational well of “build it and they will come”, slingshotted their way past “build it where the people are” have now set a heading for “deploy fleeting structures of content on other peoples’ networks” by commissioning a digital magazine for Instagram. I’ll get to the point, though. Ellis says this: “Used to be that porn was the vanguard of any new comms technology shift. Now it’s advertising. Has been for a while. Look at where the infomercial people are going” and he’s not wrong.

–Dan Hon quoting Warren Ellis.

via Dan Hon’s s2e04: Everything.

…my test for outsourcing human work to machines is this: any task that has an output or outcome which can be pre-stated or even guessed, should eventually be performed by a machine.

Humans should eventually be left to more or less exclusively deal with open-ended endeavors that generate new organic value (as opposed to efficiency derived value).

Alluding to Peter Drucker’s thinking, effectiveness should be a human pursuit, while efficiency should be delegated to machines.

via We Should Want Robots to Take Some Jobs – HBR.

See also:

Mary Meeker’s famous annual Internet Trends presentation was today.

Although never presented very clearly (in a creative sense), this is one of the most important milestones of aggregating trend data in our industry each year.

By this time tomorrow, you will see countless digital/advertising trades recutting and summarizing this data in their coverage. And insights held in this presentation will serve as a reference point throughout the rest of 2015.

See all 197 slides in their ugly glory here:

“Some brands — notably Red Bull, Squarespace and Converse — have found ways to partner with musicians without infiltrating their works…

So to a degree, ‘selling out’ can be creatively liberating. But there’s a difference between selling a partnership and selling part of your song’s message — the part that a listener trusts and needs to connect with. Consumers need to look at branding in lyrics with extreme skepticism. They should look to support acts that only use brands to establish an artistic identity, not solely a financial one.”

Pop Music Is More About Advertising Now Than Before — And Nobody Realizes It.

We are on the edge of change comparable to the rise of human life on Earth. — Vernor Vinge

The AI Revolution: Road to Superintelligence – Wait But Why.

All content needs to be made interesting. What you’re doing as a writer is introducing variable rewards into your story. Everything that engages us, all pieces of content are engineered to be interesting,” he said. “Movies aren’t real life, books aren’t real life, your article isn’t real life. It’s manufactured to pull us one sentence after another through mystery, through the unknown. It’s a slot machine. Your article is a slot machine. It has to be variable. So just because an experience introduces variability and mystery — that’s good!”

Slot machines perfected addictive gaming. Now, tech wants their tricks | The Verge.

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“With the legacy social networks crossing the decade mark and prioritizing monetization over organic reach, it’s time for brands to reevaluate their approach to Always-On content.

For example, “National Doughnut Day” shouldn’t be part of your content strategy this summer, unless your company sells donuts.

Instead, audience insights, corporate priorities, time of year and publisher format should all inform your editorial calendar and your paid promotion plan to ensure the right consumers will see your content.

Every action should generate measurable awareness or drive conversions beyond the vanity metrics on the mainstream social media channels.” —Greg Swan, space150

via 5 online best practices for businesses | Minnesota Business Magazine.

So instead of just seeing your shares in buckets (100 Facebook, 50 Twitter, 30 LinkedIn, etc.) you see exactly how that content spread in a tangled web from it’s original sharer to other channels.

BuzzFeed Just Cracked the Code on How Social Content Spreads, and It’s a Big Deal.

See also:
Introducing Pound: Process for Optimizing and Understanding Network Diffusion