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The conversational nature of reality - Issue #45

The conversational nature of reality - Issue #45
By Mari from VoiceFirst Weekly • Issue #45 • View online
As I like to tinker with technology, program and design systems, I also like poetry. I even sometimes write poetry, sigh, it’s not excellent but it feeds me. The conversational nature of reality is the philosophy of David Whyte, a poet I heard on the wonderful podcast On Being with Krista Tippett. It strike me as very related to our voice technology world. If poetry it’s too far away for you, you can still listen to his theory of how everything in our nature is hold by a conversation (skip the video linked below to almost the end). But do not miss it. Achieving true conversational technology demands more understanding of human nature and as James Baldwin said:
The poets (by which I mean all artists) are finally the only people who know the truth about us. Soldiers don’t. Statesmen don’t. Priests don’t. Union leaders don’t. Only poets.
Ok, leaving the poetry aside, this issue is about why we need a new way to solve the natural language challenges we have today, how voice analytics differs from chatbot analytics, the decline of chatbots and why companies want to mine the secrets in your voice. Enjoy.
As always, much ❤️.

Virtual assistants are doomed without a new AI approach
On the flip side of the enthusiasm we share for digital assistants and the progress on natural language understanding there are people like Boris Katz, a principal research scientist at MIT that believes current AI techniques aren’t enough to make Siri or Alexa truly smart:
But on the other hand, these programs are so incredibly stupid. So there’s a feeling of being proud and being almost embarrassed. You launch something that people feel is intelligent, but it’s not even close.
Katz has made key contributions to the linguistic abilities of machines. In the 1980s, he developed START, a system capable of responding to naturally phrased queries. The ideas used in START helped IBM’s Watson win on Jeopardy! and laid the groundwork for today’s chattering artificial servants.
Katz then moves to explain why the current state of ML and DL are not the optimal to solve natural language challenges that we have today:
In language processing, like in other fields, progress was made by training models on huge amounts of data—many millions of sentences. But the human brain would not be able to learn language using this paradigm. We don’t leave our babies with an encyclopedia in the crib, expecting them to master the language.
Boris Katz suggest a new way to teach machines language through simulated physical worlds:
I have yet to see a baby whose parents put an encyclopedia in the crib and say, “Go learn.” And this is what our computers do today. I don’t think these systems will learn the way we want them to or understand the world the way we want to.
To end the article what is a better approach for building intelligent systems:
AI research needs to build on ideas from developmental psychology, cognitive science, and neuroscience, and AI models ought to reflect what is already known about how humans learn and understand the world. Real progress will come only when researchers get out of our offices and start talking to people in other fields.
Short but thought provoking article that you shouldn’t miss.
The conversational nature of reality, podcast episode On Being with Krista Tippett
There’s no single element in the world that it’s not bonded to flying away from or catalytic with another element in the world and every creature, even the smallest singled-cell creature is in a thousand different conversations with a thousands other elements and dynamics and forms in order to keep itself alive and its environment alive. And every ecosystem in the world is this astonishing meeting, this conversation between various dynamics that contribute to this central conversation of life.
How Chat Analytics Differs from Voice Analytics
A chat analytics platform and a voice analytics platform are like a screwdriver and a hammer. While both are tools aimed at solving a similar problem, they often arrive at the solution in very different ways. Just like hand tools engineered for specific applications, voice and chat analytics platforms are engineered to optimize specific customer support channels.
It’s important to note that the variables that affect the outcomes of chat and voice conversations, while important in each, are different because spoken word is different than written. People use a fundamentally different language for different channels. The challenge regardless of channel is to move beyond just the words to understand tone, emotions, and cadence in alignment with customer expectations.
Each customer support channel, whether it’s voice, email, chat, etc holds unique potential for optimization. Voice and chat analytics platforms like those mentioned in this article continue to make huge gains in this area. As you evaluate the tools that are right for your business, it’s important to adopt a platform that aligns with your specific channel mix. It’s also essential to understand the variables in communication for the different support channels to analyze tone, cadence, and speech patterns. Once these are identified and understood, they fuel a coaching and continuous improvement process that will drive your business toward your desired outcomes and beyond.
Why companies want to mine the secrets in your voice
Voices are highly personal, hard to fake, and contain surprising information about our mental health and behaviors… Voice is not only ubiquitous; it’s highly personal, hard to fake and present in some of our most intimate environments.
Voice is powerful indicator of so many aspects of the human life, including, health, mental health, working behavior. This one goes into what voice analysis is able to predict today and what happens when the algorithms are wrong. Are there going to be regulations against data collection of your voice?
A SIRI-ous Conclusion
A check on chatbot chatter
While news and transcript mentions have declined, patent activity about chatbots has held steady. IBM leads the pack in chatbot patents, followed by Microsoft and Kik Interactive.
Funding also has shown interesting findings:
Funding to chatbots has mostly been relegated to early-stage companies (seed/angel & Series A), with few breaking out despite many receiving initial funding.
I think this is a sign that chatbots alone don’t cut it. And that the future is necessarily multimodal and multichannel.
Image credit to CBInsights.
Image credit to CBInsights.
To try
Quote of the week
Voice is not only ubiquitous; it’s highly personal, hard to fake and present in some of our most intimate environments.
Angela Chen
Did you enjoy this issue?
Mari from VoiceFirst Weekly

The ultimate resource in #VoiceFirst. Weekly digest of the most relevant news in the #VoiceFirst ecosystem. Everything from voice assistants to bots including conversational AI and published audio.

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