Happy Birthday DNSimple

DNSimple logoApril 2015 brings the fifth year of service for DNSimple. ManyMedia sends wishes for a very happy birthday to Anthony and the crew!

ManyMedia was one of their first paying customers, and with five years of their excellent service to their credit we intend to continue. Why? Trust.

I met Anthony, the founder, through a project of mutual interest and found him to have solid technical perspectives. I liked his thinking generally about teaching people and sharing his expertise. He became a trusted guide in my social network. When he offered DNS routing services, I moved several of my domains to DNSimple. One might ask why I use an outside DNS routing company when my hosting companies will do domain routing for free. Among my reasons are domains that get routed to more than one host, and the quick flexibility to switch routing to a different provider as needed.

My recognition, loyalty and support are the most valuable things I offer to a company—for solid business practices, and when I personally believe in them to do the right things going forward. Domains are an important part of my communication with the world. DNSimple is my preferred personal agent for domain routing.

 

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iacsf: What’s Next? Shaping the Future

Panel:
Mark Yahiro, Intel
Timothy Tuttle, Expect Labs
Liesl Capper, IBM
Roberto Pieraccini, Jibo

Intel offers platform and foundation to use speech, motion, who you are, to use data in intelligent ways.

Jibo (a male character) is not humanoid, but has stereo camera, mic, speaker identification, motion or facial expression detection, display, touch points. Just got big crowned sourced funds. Japanese trend is to more humanoid, is creepy, uncanny valley. farthing can express feelings (teapot in beauty and beast).

Ongoing conversations? Watson uses experts systems, known data sets, to develop ranked diagnosis of medical conditions.

Movie Her and anticipatory agents? Tim suggests we’re not as far off as we think. We are going to starts seeing intelligence in new devices. Recent breakthroughs from IBM in deep learning remarkably reduce error rate within a couple of years.

What is the future? Cognitive glue working across other agents. Holy grail is all human interaction. There are already a lot of agents, interacting between and across them is learning a new language. Filter the right data specific usage, depending on the usage do we filter before or after? Where is context? What makes sense.

Speech recognition is about 60, 65 years old. Big problem is that once you understand how to did it, depends on the language and what you are talking about. Can’t create a closed loop.

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iacsf: Michael Bowers, Coca Cola

Offering perspectives as an operator. They used early virtual agent, not effective. Thecoca-cola company.com and mycokerewards.com

Spikes in volume, can’t economically staff for this. How they planned and executed new agents: planning: choose a provider, interaction with site owners and consumer care (avatars, content that is relevant). Execution: apply project management rigor, be ready to add and modify content based on user experience, steward results (data) to site stewards. Graphs show traffic. Mycokerewards is about points, 30,000 visitors vs 15000 at other site. Super Bowl ad traffic story with spike for reasons they didn’t anticipate. User-created ad on YouTube also impacted. For them, saves money. Product locator now on Sprite site.

No perfect, lessons learned when hackers found their way in.

Intelligent channeling: be available, be where consumers prefer, architect experience to drive customers thoughtfully. Learn from the IVA.

Why is virtual agent below the fold? Marketing decisions, also IVA is America-centric and company is global.

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iacsf: Norman Winarsky and Bill Mark, SRI

SRI started work with Calo, funded through DARPA, probably largest AI project in 1953. Focus on learning in the wild, the way a real human personal assistant would learn. Still quite a frontier. Biggest challenge is user experience, when things in the interface change, he’s out of control. Wants something that does the right thing every time. Calo was most major project before Siri. People who worked on Siri came out of Calo team.

sRI is very financially pragmatic about what they fund, must be relatively certain. We start with a market problem, not technology.

How important was natural speech? Global conversations with telephone ecosystem, most people don’t talk to a phone for service but Bill thought that wasn’t a future predictor. Is rare that customer expresses their intent in first sentence. W are learning what we want as we talk. One Question might lead to another.

Tempo, a smart calendar, offers insights into your daily life, predictive intent. Destiny is a travel company, bought by Nokia. Quantum game about math. Open question do we need verticals or can we use one? Different kinds of personal assistants. On kind is general, other is really about me.

There will be millions of assistants, but two layers. APIs to talk to each other? Th hard part is how to have this multi-term part conversation between all. Won’t stay mobile device centered, internet of things will help with simple intents that happen all the time. Which decisions are contingent on emotional responses or other timely options? Language, interacting, is not the future that is learning and understanding. Mobile will be center of interactions related to where, when…

Genderization is also a complex issue. Real world: not homogeneous, will be a variety in personas.

Personalization in retail, for example, can recommend, but puts you in a category. Difference between, and we need both little data as well as big.

Eliza, from 1960s, tried to emulate a psychologist. People really engaged, some went on for hours. Touring test of thinking machines… Some people want a human interaction, some dont.

What technologies need to improve before it’s conversational? Deep knowledge, represents fundamental things that are known to us (e.g., bank account), also context for human interactions and how we remember things. The way we deal with this now is through verticals, where context and intents are more established. Across market verticals not possible today. Shallow vs deep.

Tooling and analytics are useful to people buying them. Problems with deep knowledge, structuring the representations, and how it all works together.

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