ShepHyken
APRIL 28, 2024
Years ago, the term “Big Data” became popular. I came up with the concept of “Micro Data,” which is about very personalized information about a smaller set of customers. From chatbots and voice assistants to recommendation engines, brands are integrating AI wherever they can, and for good reason.
Connect
APRIL 18, 2024
It is costly and complex to build out Gen AI capabilities as creating the modelling needed to derive insights from AI engines is intensive, requiring scarce and expensive resources like data scientists and other technical experts. As such, the journey to Gen AI requires careful planning and implementation.
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TechSee
OCTOBER 9, 2018
Use AI-based virtual assistants – Millennials are very open to communication with virtual entities – chatbots – including voice-based assistants and visual virtual technician. According to a Retale poll, 86% of Millennials said that brands should use chatbots to promote products and services. Pay attention.
AWS Machine Learning
OCTOBER 6, 2023
Large language models (LLMs) are revolutionizing fields like search engines, natural language processing (NLP), healthcare, robotics, and code generation. Another essential component is an orchestration tool suitable for prompt engineering and managing different type of subtasks. A feature store maintains user profile data.
TechSee
FEBRUARY 1, 2021
This data is culled from devices, networks, mobile applications, geolocations, detailed customer profiles, services usage and billing data. Another Vodafone chatbot — TOBi – has already launched in 11 markets and handles a range of customer service-type questions.
Aspect
DECEMBER 27, 2017
2016 saw an explosion of interest and investments in chatbots, as I wrote in my last annual recap. Much like in 2016, this year I’ve had countless conversations about chatbot needs with numerous customers, prospects, and partners around the globe, and it’s clear to me that as an industry we have made progress. Let’s have a look.
AWS Machine Learning
JANUARY 26, 2024
The goal of this post is to empower AI and machine learning (ML) engineers, data scientists, solutions architects, security teams, and other stakeholders to have a common mental model and framework to apply security best practices, allowing AI/ML teams to move fast without trading off security for speed.
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