Elton  Bogan

Elton Bogan

1602424800

How to Build, Deploy, and Operationalize AI Assistants

Conversational AI has been experiencing a renewed focus in recent years. In the past few years, we’ve seen language models achieve state-of-the-art results, demonstrate impressive results with language understanding benchmarks like General Language Understanding (GLUE) and SuperGLUE, and lend themselves to practical applications. Even so, conversational AI is far from being solved. However, we’re moving to an AI- first world, where people expect technology to be naturally conversational, thoughtfully contextual, and intelligent – and so most companies will have to consider adopting an AI assistant sooner or later.

In this article, I’ll first discuss the five levels of AI assistants using a standard model for conversational AI maturity. Second, I’ll summarize my own recent experience building a level 3 AI assistant. Finally, I’ll outline various custom tools I built to continuously iterate upon, improve, and monitor the AI assistant in production.

The Five Levels of AI Assistants

Most AI assistants today can handle simple questions, and they often reply with prebuilt responses based on rule-based conversation processing. For instance, if a user says X, respond with Y; if a user says Z, call a REST API, and so forth. However, for AI assistants to provide value to business functions like customer service, supply chain management, and healthcare workflow processes, we need to move beyond the limitations of rule-based assistants and to a more standard maturity model for conversational AI. In this article, we’ll talk about how to model and deploy a contextual assistant and discuss real life examples of contextual assistants in production.

#chatbots #natural language processing #ai # ml & data engineering #article

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How to Build, Deploy, and Operationalize AI Assistants
Otho  Hagenes

Otho Hagenes

1619511840

Making Sales More Efficient: Lead Qualification Using AI

If you were to ask any organization today, you would learn that they are all becoming reliant on Artificial Intelligence Solutions and using AI to digitally transform in order to bring their organizations into the new age. AI is no longer a new concept, instead, with the technological advancements that are being made in the realm of AI, it has become a much-needed business facet.

AI has become easier to use and implement than ever before, and every business is applying AI solutions to their processes. Organizations have begun to base their digital transformation strategies around AI and the way in which they conduct their business. One of these business processes that AI has helped transform is lead qualifications.

#ai-solutions-development #artificial-intelligence #future-of-artificial-intellige #ai #ai-applications #ai-trends #future-of-ai #ai-revolution

Murray  Beatty

Murray Beatty

1598606037

This Week in AI | Rubik's Code

Every week we bring to you the best AI research papers, articles and videos that we have found interesting, cool or simply weird that week.

#ai #this week in ai #ai application #ai news #artificaial inteligance #artificial intelligence #artificial neural networks #deep learning #machine learning #this week in ai

This Week in AI - Issue #22 | Rubik's Code

Every week we bring to you the best AI research papers, articles and videos that we have found interesting, cool or simply weird that week.Have fun!

Research Papers

Articles

#ai #this week in ai #ai application #ai news #artificaial inteligance #artificial intelligence #artificial neural networks #deep learning #machine learning #this week in ai

George  Koelpin

George Koelpin

1602255900

Amsterdam And Helsinki Launch Open AI Registers

Amsterdam and Helsinki both launched an Open AI Register at the Next Generation Internet Summit. According to sources, these two cities are the first in the world that are aiming to be open and transparent about the use of algorithms and AI in the cities.

Currently, in the beta version, Algorithm Register is an overview of the artificial intelligence systems and algorithms used by the City of Amsterdam. The register is an effort to show where the cities are currently making use of AI and how the algorithms work.

Jan Vapaavuori, Mayor of Helsinki stated, “Helsinki aims to be the city in the world that best capitalises on digitalisation. Digitalisation is strongly associated with the utilisation of artificial intelligence. With the help of artificial intelligence, we can give people in the city better services available anywhere and at any time. In the front rank with the City of Amsterdam, we are proud to tell everyone openly what we use Artificial Intelligence for.”

#news #ai register #amsterdam ai #helsinki ai #open ai register #ai

Elton  Bogan

Elton Bogan

1602424800

How to Build, Deploy, and Operationalize AI Assistants

Conversational AI has been experiencing a renewed focus in recent years. In the past few years, we’ve seen language models achieve state-of-the-art results, demonstrate impressive results with language understanding benchmarks like General Language Understanding (GLUE) and SuperGLUE, and lend themselves to practical applications. Even so, conversational AI is far from being solved. However, we’re moving to an AI- first world, where people expect technology to be naturally conversational, thoughtfully contextual, and intelligent – and so most companies will have to consider adopting an AI assistant sooner or later.

In this article, I’ll first discuss the five levels of AI assistants using a standard model for conversational AI maturity. Second, I’ll summarize my own recent experience building a level 3 AI assistant. Finally, I’ll outline various custom tools I built to continuously iterate upon, improve, and monitor the AI assistant in production.

The Five Levels of AI Assistants

Most AI assistants today can handle simple questions, and they often reply with prebuilt responses based on rule-based conversation processing. For instance, if a user says X, respond with Y; if a user says Z, call a REST API, and so forth. However, for AI assistants to provide value to business functions like customer service, supply chain management, and healthcare workflow processes, we need to move beyond the limitations of rule-based assistants and to a more standard maturity model for conversational AI. In this article, we’ll talk about how to model and deploy a contextual assistant and discuss real life examples of contextual assistants in production.

#chatbots #natural language processing #ai # ml & data engineering #article