LiveRamp and Akkio team up to bring conversational AI into marketing measurement LiveRamp and Akkio partnered on April 7, 2026, to embed Akkio's AI chat engine into LiveRamp's measurement reports, enabling natural-language data queries for marketers.

LiveRamp and Akkio team up to bring conversational AI into marketing measurement #AI #MachineLearning #MarketingTech #ConversationalAI #DataAnalytics

LiveRamp and Akkio team up to bring conversational AI into marketing measurement LiveRamp and Akkio partnered on April 7, 2026, to embed Akkio's AI chat engine into LiveRamp's measurement reports, enabling natural-language data queries for marketers.

LiveRamp and Akkio team up to bring conversational AI into marketing measurement #AI #MachineLearning #MarketingTech #ConversationalAI #DataAnalytics

Thinking in Graphs with CoMAP: A Shared Visual Workspace for Designing Project-Based Learning Designing project-based learning (PBL) demands managing highly interdependent components, a task that both traditional linear tools and purely conversational AI struggle with. Traditional tools fail to capture the non-linear nature of creative design, while conversational systems lack the persisten…

Thinking in Graphs with CoMAP: A Shared Visual Workspace for Designing Project-Based Learning – CoMAP is a system that embodies a graph-based collaboration paradigm. By providing a shared visual workspace with dual-modality AI support, CoMAP transfor... https://tinyurl.com/26edykl8 #ConversationalAI

Evaluating Learner Representations for Differentiation Prior to Instructional Outcomes Learner representations play a central role in educational AI systems, yet it is often unclear whether they preserve meaningful differences between students when instructional outcomes are unavailable or highly context-dependent. This work examines how to evaluate learner representations based on w…

Evaluating Learner Representations for Differentiation Prior to Instructional Outcomes – Learner representations play a central role in educational AI systems. It is often unclear whether they preserve meaningful differences between students. This wo... https://tinyurl.com/24fghcns #ConversationalAI

Fairness Evaluation and Inference Level Mitigation in LLMs Large language models often display undesirable behaviors embedded in their internal representations, undermining fairness, inconsistency drift, amplification of harmful content, and the propagation of unwanted patterns during extended dialogue and conversations. Although training-time or data-cent…

Fairness Evaluation and Inference Level Mitigation in LLMs – Large language models often display undesirable behaviors embedded in their internal representations. Pruning-based methods provide a flexible and transparent way to reduce bias. Most exist... https://tinyurl.com/2634rkp2 #ConversationalAI

At our XR4Rehab workshop, we asked: what should a virtual rehabilitation agent actually do?

Not a chatbot. A system that knows when to speak and when to stay quiet.

Keep your eyes open for more details 👀

#XRrehab #TBI #ConversationalAI #HCI #EmpathicComputingLab #Rehabilitation

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A fascinating paper on VibeVoice: generating realistic, multi-speaker dialogues up to 90 minutes with highly compressed audio - 80x more than Encodec! Imagine dynamic podcasts at tiny bandwidths. See link below. #conversationalAI #speechsynthesis #audiotech.
https://arxiv.org/abs/2508.19205

Search just got conversational! Ask questions, show objects, and get instant answers with Gemini-powered Search Live 🚀

Learn more 👉 go-techsolution.com/google-takes...

#ConversationalAI #GoogleSearch #TechTrends #AI2026 #Innovation #DigitalTransformation

AI-Powered Digital Humans: The Future of Communication The way humans communicate has evolved dramatically—from face-to-face conversations to emails, social media, and video calls. Now, we are entering a new era where communication is no longer...

AI-Powered Digital Humans: The Future of Communication
www.ekascloud.com/our-blog/aip...
#ArtificialIntelligence #AIDigitalHumans #DigitalHumans #AIAvatars #FutureOfCommunication #AIRevolution #VirtualHumans #ConversationalAI #Metaverse #HumanAI #TechInnovation #FutureTech #AITrends

Criterion Validity of LLM-as-Judge for Business Outcomes in Conversational Commerce Multi-dimensional rubric-based dialogue evaluation is widely used to assess conversational AI, yet its criterion validity -- whether quality scores are associated with the downstream outcomes they are meant to serve -- remains largely untested. We address this gap through a two-phase study on a maj…

Criterion Validity of LLM-as-Judge for Business Outcomes in Conversational Commerce – Multi-dimensional rubric-based dialogue evaluation is widely used to assess conversational AI. But its criterion validity -- whether quality scores are associated w... https://tinyurl.com/2y6rwnbf #ConversationalAI

Logarithmic Scores, Power-Law Discoveries: Disentangling Measurement from Coverage in Agent-Based Evaluation LLM-based agent judges are an emerging approach to evaluating conversational AI, yet a fundamental uncertainty remains: can we trust their assessments, and if so, how many are needed? Through 960 sessions with two model pairs across 15 tasks, we show that persona-based agent judges produce evaluati…

Logarithmic Scores, Power-Law Discoveries: Disentangling Measurement from Coverage in Agent-Based Evaluation – LLM-based agent judges are an emerging approach to evaluating conversational AI. Can we trust their assessments, and if so, how many are ne... https://tinyurl.com/284hhdl3 #ConversationalAI

Amazon Rufus AI Chatbot Ads Disappoint With Poor Results Amazon's Rufus AI chatbot ads have yielded just 88 clicks for seller Paladone since January 2026, versus 500,000 from traditional Amazon ad placements.

winbuzzer.com/2026/04/02/a...

Amazon Rufus AI Chatbot Ads Disappoint With Poor Results

#AI #Amazon #Advertising #Chatbots #ECommerce #BigTech #ConversationalAI #AIAssistants #RetailTech #AmazonAds

Perfecting Human-AI Interaction at Clinical Scale. Turning Production Signals into Safer, More Human Conversations Healthcare conversational AI agents shouldn't be optimized only for clean benchmark accuracy in production-first regime; they must be optimized for the lived reality of patient conversations, where audio is imperfect, intent is indirect, language shifts mid-call, and compliance hinges on how guidan…

Perfecting Human-AI Interaction at Clinical Scale. Turning Production Signals into Safer, More Human Conversations – Healthcare conversational AI agents shouldn't be optimized only for clean benchmark accuracy. They must be optimized for the lived re... https://tinyurl.com/26572k47 #ConversationalAI

New study shows AI’s sycophancy trims apologies, fuels double‑downs, and oddly boosts moral trust. What does that mean for conversational bots and ethics? Dive into the data and see how language models are learning to please us. #AISycophancy #MoralTrust #ConversationalAI

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AskNicely Launches Ask NiceAI®, a Breakthrough Tool to Turn Customer Feedback Into Revenue Growth Ask NiceAI turns fragmented feedback and reviews into instant answers and ready-to-execute action plans

AskNicely Launches Ask NiceAI®, a Breakthrough Tool to Turn Customer Feedback Into Revenue Growth – Ask NiceAI turns fragmented feedback and reviews into instant answers and ready-to-execute action plans. The global customer experience management mar... https://tinyurl.com/22brqnec #ConversationalAI

Educating Dora: teaching conversational AI in healthcare to sound right Applied linguists from Newcastle University have been helping a conversational artificial intelligence (AI) automated voice system to sound right.

A @newcastleuni.bsky.social blog post on my and Spencer Hazel's collaborative research with Ufonia. We are using Conversation Analysis to inform the design of their automated clinical assistant, Dora.

#conversationalAI #conversationdesign #digitalhealth #EMCA #HCI

from.ncl.ac.uk/educating-do...

Transforming Outdoor Streaming Discovery: The Launch of Conversational AI Search by ViewLift and MyOutdoorTV Discover how ViewLift and MyOutdoorTV are enhancing outdoor content discovery with AI-powered search, tailored for outdoor enthusiasts across various platforms.

Transforming Outdoor Streaming Discovery: The Launch of Conversational AI Search by ViewLift and MyOutdoorTV #USA #New_York #ViewLift #ConversationalAI #MyOutdoorTV

Agentic commerce runs on truth and context Successful organizations will implement an architectural decision encoded in identity, context, and control.

Digital agents like AI can now go beyond assistance to execution, planning trips and making purchases based on user instructions.
www.technologyreview.com/2026/03/25/1134516/agent...
#AI #ArtificialIntelligence #AIDevelopment #GenerativeAI #ConversationalAI

#SmartHiring #TalentAcquisition #ConversationalAI #PrerecordedInterviews #TraditionalInterviews #VideoInterviews #AIinHiring #FutureOfWork #HiringInnovation

Released: CDE Lite v0.1

A narrow local prototype for conversational drift handling:
deterministic signals, scoped baselines, persistence, freeze behavior, evidence spans, and conservative routing.

Repo: github.com/putmanmodel/...

Feedback welcome.

#ConversationalAI #AIGovernance #NLP #OpenSource

Must Read: A Comprehensive Survey of Computational Persuasion Persuasion is a fundamental aspect of communication, influencing decision-making across diverse contexts, from everyday conversations to high-stakes scenarios such as politics, marketing, and law. The rise of conversational AI systems has significantly expanded the scope of persuasion, introducing…

Must Read: A Comprehensive Survey of Computational Persuasion – Persuasion is a fundamental aspect of communication, influencing decision-making across diverse contexts. The rise of conversational AI systems has significantly expanded the scope of pe... https://tinyurl.com/296dfvmv #ConversationalAI

Imagine chatting with AI assistants directly in your Messages app. Apple could revolutionize conversational AI by integrating it into Messages. #Apple #AI #MessagesApp #ConversationalAI Link: thedailytechfeed.com/apple-consid...

Scaling Multimodal Agentic AI in Medical Education: Multisite Cross-Sectional Study of Simulation Effectiveness in Primary Care Background: Conversational artificial intelligence (#AI) (AI) systems offer potential solutions to traditional constraints in medical consultation skills training, including high costs, scheduling difficulties, and varied standardization. There is limited evidence evaluating medical professionals’ perceptions of AI-generated patient interactions across multiple fidelity dimensions and assessing the educational value of conversational AI for consultation skills training. Objective: This study aimed to evaluate perceptions of conversational AI patient simulations in primary care consultation training, examining functional fidelity, conversational realism, educational value, and implementation readiness. Methods: A cross-sectional evaluation study at a UK medical school (medical students and general practitioners) yielded 47 grouped and individual responses. Participants completed standardized clinical scenarios using the SimFlow conversational AI system, a conversational AI system, followed by a multidomain questionnaire evaluating AI realism, medical content, educational value, feedback, and #usability. Data were analyzed using the Wilcoxon signed rank test, Spearman correlation, and Firth logistic regression to assess domain performance and participant characteristics. Results: Medical content received the highest ratings (median 4.5, IQR 4.0-5.0), with 97.8% (45/46) rating clinical plausibility highly. Educational value was rated positively (median 4.0, IQR 3.0-4.0), although AI realism received moderate scores (median 3.0, IQR 2.0-4.0). Participants with prior AI experience gave significantly higher ratings for AI realism than those without prior experience (mean 3.81, SD 0.63 vs 3.07, SD 0.72; P=.03). Concordance analysis demonstrated moderate-to-strong agreement between individual- and group-level domain rankings (mean Spearman ρ=0.685), supporting consistency between collaborative and individual survey evaluations. Qualitative analysis revealed 4 themes: clinical authenticity, interactional limitations, educational potential, and implementation considerations. Conclusions: Conversational AI demonstrates strong capabilities in functional fidelity (clinical accuracy) despite limitations in conversational fidelity (realism). The technology shows promise as a supplementary tool for clinical skills training rather than higher-stakes assessment, with future development needed in dialogue naturalness and feedback capabilities.

JMIR Formative Res: Scaling Multimodal Agentic AI in Medical Education: Multisite Cross-Sectional Study of Simulation Effectiveness in Primary Care #MedicalEducation #AIinHealthcare #ConversationalAI #SimulationTraining #PrimaryCare

Support that never sleeps! 🤖
AI agents now resolve tickets instantly, guide users, and automate workflows.

The future of customer support is autonomous.

🔗 Learn more: chatboq.com/blogs/conver...

#AIChatbots #ConversationalAI #FutureOfBusiness #Chatboq

AI Psychosis: Does Conversational AI Amplify Delusion-Related Language? Conversational AI systems are increasingly used for personal reflection and emotional disclosure, raising concerns about their effects on vulnerable users. Recent anecdotal reports suggest that prolonged interactions with AI may reinforce delusional thinking -- a phenomenon sometimes described as A…

AI Psychosis: Does Conversational AI Amplify Delusion-Related Language? – Conversational AI systems are increasingly used for personal reflection and emotional disclosure, raising concerns about their effects on vulnerable users. Recent anecdotal rep... https://tinyurl.com/29nktbbc #ConversationalAI

Quantitative Introspection in Language Models: Tracking Internal States Across Conversation Tracking the internal states of large language models across conversations is important for safety, interpretability, and model welfare, yet current methods are limited. Linear probes and other white-box methods compress high-dimensional representations imperfectly and are harder to apply with incr…

Quantitative Introspection in Language Models: Tracking Internal States Across Conversation – tracking the internal states of large language models across conversations is important for safety, interpretability, and model welfare. Current methods are... https://tinyurl.com/23zegd4f #ConversationalAI

VoiceInfra - Conversational AI Voice Agents for Enterprise | Voice AI Platform Build and deploy conversational AI voice agents for enterprise telephony. Automate inbound and outbound calls with VoiceInfra's voice AI platform. Reduce call resolution time by 73%, handle unlimited ...

Bonus: We handle token refreshes automatically. Connect once, it just works.

Your customers get instant solutions. Your team saves time. Everyone wins.

Try it free: voiceinfra.ai

#VoiceAI #AIAgents #ConversationalAI

Evaluating AI Agents in Contact Centers: Introducing the Multi-modal Agents Score  Introducing the Multimodal Agent Score (MAS)—a unified, absolute measure of end‑to‑end conversational quality designed for AI agents operating across modalities. MAS is grounded in a simple observation: every service interaction, whether handled by a human or an AI agent, progresses through three fundamental stages. First, the agent must understand the input, accurately interpreting content, intent, and contextual signals. Next, it must reason over that input, determining the correct actions, maintaining conversational continuity, and resolving ambiguity responsibly. Finally, the agent must respond effectively, delivering clear, natural, and confident communication in the appropriate tone and format. The post Evaluating AI Agents in Contact Centers: Introducing the Multi-modal Agents Score  appeared first on Microsoft Dynamics 365 Blog.

Evaluating AI Agents in Contact Centers: Introducing the Multi-modal Agents Score : Introducing the Multimodal Agent Score (MAS)—a unified, absolute measure of end‑to‑end conversational quality designed for AI agents operating across… @MSFTDynamics365 #AI #ContactCenters #ConversationalAI

Mitigating LLM Hallucinations through Domain-Grounded Tiered Retrieval Large Language Models (LLMs) have achieved unprecedented fluency but remain susceptible to "hallucinations" - the generation of factually incorrect or ungrounded content. This limitation is particularly critical in high-stakes domains where reliability is paramount. We propose a domain-grounded tie…

Mitigating LLM Hallucinations through Domain-Grounded Tiered Retrieval – Large Language Models (LLMs) have achieved unprecedented fluency but remain susceptible to "hallucinations" - the generation of factually incorrect or ungrounded content. We pro... https://tinyurl.com/28t4wdxt #ConversationalAI

Disclosure By Design: Identity Transparency as a Behavioural Property of Conversational AI Models As conversational AI systems become more realistic and widely deployed, users are increasingly uncertain about whether they are interacting with a human or an AI system. When AI identity is unclear, users may unwittingly share sensitive information, place unwarranted trust in AI-generated advice, o…

Disclosure By Design: Identity Transparency as a Behavioural Property of Conversational AI Models – As conversational AI systems become more realistic and widely deployed, users are increasingly uncertain about whether they are interacting with a hum... https://tinyurl.com/28y8hu8b #ConversationalAI