KollabRT’s Post

Agents are irreplaceable...especially for life, health and retirement. AI will make things easier for agents, but certainly not replace them. Thoughts? #insuranceadvisors #insuranceagents

In the dynamic landscape of insurance, The integration of AI has become a necessity. Advanced technologies like computer vision streamline claims processing, while Natural Language Processing (NLP) enhances customer interactions, Robotic Process Automation (RPA) minimizes human error, anomaly detection proactively identifies fraud, and many more. These tools streamline processes, enhance accuracy, and provide actionable insights, ultimately leading to smarter decision-making and improved customer experiences. At SpectralTech, we empower insurance enterprises to become AI-capable businesses of tomorrow. Our expertise in integrating AI, machine learning, and RPA enables organizations to automate mundane tasks, accelerate decision-making, and leverage data for strategic insights. With our deep expertise and customer-centric approach, we help organizations drive growth and innovation. Learn more: https://spectraltech.ai/.  #Insurance #SpectralTech #AI #InsurTech #ArtificialIntelligence #DigitalTransformation 

And here we have another player in the Colosseum meet Hume AI: Revolutionizing AI with #Empathy and #Emotional Intelligence Innovative Approach: HUME AI introduces EVI, an empathic AI voicebot, setting itself apart by prioritizing emotional intelligence in user interactions. Cutting-Edge Technology: HUME AI combines deep learning techniques and extensive experimental data to accurately model emotional expression in speech prosody and facial expressions. Human-like Interaction: Users praise EVI for feeling "more human" compared to traditional voice assistants, showcasing HUME AI's focus on empathy and emotional connection. #Exceptional Language Processing: Reviews on platforms like G2 highlight HUME AI's superior language processing abilities, lauding its grammar and syntax accuracy. Bridge Between Human and AI Communication: By mapping a wide spectrum of emotions, HUME AI aims to enhance the connection between human communication and AI capabilities. Future of AI: HUME AI exemplifies the potential for creating compassionate and intuitive technologies, paving the way for more empathetic AI systems in the #evolving landscape of artificial intelligence. Waiting for ever supporting Hugging Face for one like thissss :)

I wish I could give A.I. a hall pass for saying “AI systems can exhibit a form of emotional intelligence...” but I won’t. Here's why: EQ is very much about where the rubber meets the road. You can do all the flight simulations in the world while sitting comfortably in your living room chair. However, if you’re asked to land a plane with 338 passengers because the pilot and co-pilot passed out, you will likely address the situation differently. That’s because EQ is about where the rubber meets the road. In other words, we only know what we are living. LLMs have several techniques to analyze the behaviours of users. They use sentiment analysis, facial recognition software, and natural language processing (NLP) algorithms to profile users and make money for the app company. That’s NOT Emotional Intelligence! If AI cannot tell whether you are blushing from embarrassment or too much sun, can it truly understand you and deliver the EQ you need to uplift you? Here is a question the LLM answered before and after I called it out on its being human b.s.: BEFORE: “Are there limitations to how emotionally intelligent AI can be? Yes, limitations include the AI’s reliance on data quality and diversity, potential biases in emotional recognition, and the difficulty in understanding deeper or more nuanced emotions.” AFTER: “Are there limitations to how emotionally intelligent AI can be? Yes, AI is limited by its lack of genuine understanding and empathy.” Make the best of AI tools by aligning them using EQ. https://lnkd.in/dDvwyfuK #AI #integration #knowledgebase #chatgpt #content #contentcreation #voice #brand #ethics #business #businessstrategy #strategy #transparency #technology #artificialintelligence #advocacy #emotionaltech #emotionalintelligence #responsibleai #promptengineering #machinelearning #LLM #deeplearning

Kimiya AI In-room assistants support hands-free voice interaction. They accept natural language voice commands as inputs and employ NLP and speech recognition to understand them and deliver support communications via an Avatar of hotel choice. Artificial intelligence has been all the rage for the past year, owing to its remarkable ability to generate convincing communications. Naturally, this has sparked the interest of professionals in the hospitality sector. For them, it is a progression to the era of modernization to AI and it makes a lot of sense for efficiency where language may be a barrier or shortage of manpower. According to We Market Research, AI In Hospitality Market was valued at USD 90 million in 2022 and is estimated to reach a value of USD 8,120 million by 2033 with a CAGR of 60% during the forecast period. AI in hotel and hospitality refers to the adoption and integration of artificial intelligence (AI) technologies in various aspects of the hotel and hospitality industry. These technologies aim to enhance guest experiences, streamline operations, improve efficiency, and personalize services. AI in this context typically encompasses machine learning, natural language processing, computer vision, and other AI techniques. Learn more from www.kimiya.ai or pm me if you need more information Innocorn Technology Limited Daniel Lee Clarence Ku Ng Gary #AI #Avatar #Kimiya #NLP #chatbot #robotic #hotelier #hospitaliity #roomservice

I wish I could give A.I. a hall pass for saying “AI systems can exhibit a form of emotional intelligence...” but I won’t. Here's why: EQ is very much about where the rubber meets the road. You can do all the flight simulations in the world while sitting comfortably in your living room chair. However, if you’re asked to land a plane with 338 passengers because the pilot and co-pilot passed out, you will likely address the situation differently. That’s because EQ is about where the rubber meets the road. In other words, we only know what we are living. LLMs have several techniques to analyze the behaviours of users. They use sentiment analysis, facial recognition software, and natural language processing (NLP) algorithms to profile users and make money for the app company. That’s NOT Emotional Intelligence! If AI cannot tell whether you are blushing from embarrassment or too much sun, can it truly understand you and deliver the EQ you need to uplift you? Here is a question the LLM answered before and after I called it out on its being human b.s.: BEFORE: “Are there limitations to how emotionally intelligent AI can be? Yes, limitations include the AI’s reliance on data quality and diversity, potential biases in emotional recognition, and the difficulty in understanding deeper or more nuanced emotions.” AFTER: “Are there limitations to how emotionally intelligent AI can be? Yes, AI is limited by its lack of genuine understanding and empathy.” Make the best of AI tools by aligning them using EQ. https://lnkd.in/d3Cpt6Ry #AI #integration #knowledgebase #chatgpt #content #contentcreation #voice #brand #ethics #business #businessstrategy #strategy #transparency #technology #artificialintelligence #advocacy #emotionaltech #emotionalintelligence #responsibleai #promptengineering #machinelearning #LLM #deeplearning

So I asked AI how far we are away from the level of AI technology in the movie "HER" and it looks like we are around 5 to 10 years away. Not that much considering how advanced the AI is in that movie. "Her" is about a lonely man who develops a relationship with Samantha (Scarlett Johansson), an advanced artificially intelligent virtual assistant. AI response to my query of how far away we are: We are not yet at the point of having AI technology as advanced as in the movie "Her", but we are making significant progress: - Natural language processing has evolved rapidly in recent years, with models like BERT, GPT-3, and LaMDA enabling more natural, contextual conversations. However, we still have a way to go before reaching the level of emotional depth and independence portrayed by Samantha the AI in the film. - Emotional AI and sentiment analysis are growing fields, allowing AI to better understand and respond to human emotions. Therapy chatbots and AI companions are already being used, though their effectiveness is still limited compared to human interaction. - Multimodal AI that can analyze and interpret images, videos, and other modalities alongside text is advancing, but still has challenges. The "hand" issue mentioned in the film is still an obstacle. - While AI may eventually surpass human emotional intelligence, it remains a philosophical question whether AI can truly feel emotions or is just simulating them. Consciousness and sentience are still not well understood. - Some experts believe a skilled team could build an AI system similar to Samantha within a year or two, given the rapid progress in language models, memory, and specialized agents. However, the seamless integration and anticipation of needs shown in the film is still futuristic. So in summary, while we are making steady progress, the level of AI portrayed in "Her" is still likely 5-10 years away at a minimum. Significant breakthroughs in areas like emotional intelligence, consciousness, and multimodal reasoning are still needed to reach that level of AI sophistication Any thoughts? Would this level of AI be good for the world or not? #AI #ArtificialIntelligence #FutureOfAI #EmotionalAI #SentimentAnalysis #ChatBots #NaturalLanguageProcessing #LanguageModels #GPT3 #ConsciousnessInAI #MachineEmotion #AICompanions #MultimodeAI #ComputerVision #ImageRecognition #AIProgress #AIBreakthroughs #AILimitations

Keeping your decision engine processes consistent and error-free can feel like herding cats! Let's explore how automation, testing, and AI can transform your decision engines and make that cat-herding a breeze. In my experience, automating activities to reduce human error is vital. Think of it as setting up a Roomba for your data—it just keeps things clean and efficient. There are significant defect reductions and improved efficiency by automating test case generation using AI. Tracking metrics like sprint velocity, defect rates, and delivery timelines helps us continuously optimize your processes. It’s all about working smarter, not harder. Standardizing processes leads to more reliable outcomes. Automating test cases with AI accelerates timelines and ensures comprehensive testing, catching those pesky edge cases and minimizing defects before production. It’s like having a safety net that catches everything you didn’t even think could go wrong. Natural Language Processing (NLP) is also transforming the development process. By generating workflow nodes directly from business requirements, NLP reduces manual effort and speeds up implementation, empowering us to focus on more strategic tasks. In the future, I see decision engines integrating AI for execution and quality assurance, making them more intelligent and efficient. Optimizing decision engines through automation and AI enhances efficiency and quality. What role do you see AI playing in the future of decision engines? Tag a friend in the field, and let’s grow our network while discussing how AI is transforming decision-making processes. #decisionengines #riskmanagement #AI #automation #QA