New AI and ChatGPT books by Valentina Alto

Now you know which scores represent "Quality" in your AI agent. But next: Applying it to every AI call in production? That’s the real game. You can’t check thousands of user interactions manually.
You need automation. 3 fundamental ways: 1. Human Annotation → Ground truth. Small sample, deep accuracy. 2. Rule-based Checks → Black-and-white. Fast. Cheap. Every call. 3. LLM-as-a-Judge → Scales nuance (e.g. helpfulness, relevance). Combine all 3 → Continuous, reliable, scalable evals. That’s how you stop hoping your AI works… and know it does. Diving into AI Observability & Evals (5/6) #AIObservability #Tracing #LLM #AI

Ever thought about how AI agents like ChatGPT and Alexa are reshaping our daily lives? I came across an insightful article that explores the evolving world of AI, shedding light on how these technologies are more than just tools; they are revolutionizing the way we interact and accomplish tasks. Understanding these innovations is key to unlocking their potential in both personal and professional settings. It’s incredible to see how AI can enhance our productivity, allowing us to focus on what truly matters. What’s your experience with AI solutions? Are they helping you achieve your goals? Share your thoughts! #AI #Innovation #Productivity #FutureOfWork #Technology https://lnkd.in/g6npzWAV -to-know-about-chatgpt-alexa-and-more Brain Pod AI

The rapid adoption of AI tools is creating a fragmentation challenge for businesses, as individual teams pick different models, datasets and AI architectures to work with.  In turn, this introduces risks due to inconsistent a quality control, oversight and accuracy levels in AI responses.   Learn how AI Knowledge Bases can addresses these challenges, by providing a shared memory for agents & AI chat: https://ow.ly/8sNu50WUryq #AI #TungstenAutomation #Blog #AIAdoption #BusinessIntelligence #AIEthics #DataManagement #MachineLearning

The rapid adoption of AI tools is creating a fragmentation challenge for businesses, as individual teams pick different models, datasets and AI architectures to work with.  In turn, this introduces risks due to inconsistent a quality control, oversight and accuracy levels in AI responses.   Learn how AI Knowledge Bases can addresses these challenges, by providing a shared memory for agents & AI chat: https://ow.ly/9nhR30sPvYM #AI #TungstenAutomation #Blog #AIAdoption #BusinessIntelligence #AIEthics #DataManagement #MachineLearning

With AI still really in its infancy, we need to view AI-powered tech with a critical eye. In this Acuity article, Heather Smith FCA unpacks the apps that are getting AI right: https://ow.ly/1YlQ30sPHNo #SmallerPractices #DifferenceMakers #CAANZ #AI

The rapid adoption of AI tools is creating a fragmentation challenge for businesses, as individual teams pick different models, datasets and AI architectures to work with.  In turn, this introduces risks due to inconsistent a quality control, oversight and accuracy levels in AI responses.   Learn how AI Knowledge Bases can addresses these challenges, by providing a shared memory for agents & AI chat: https://ow.ly/wUvC30sPy4H #AI #TungstenAutomation #Blog #AIAdoption #BusinessIntelligence #AIEthics #DataManagement #MachineLearning

With AI still really in its infancy, we need to view AI-powered tech with a critical eye. In this Acuity article, Heather Smith FCA unpacks the apps that are getting AI right: https://ow.ly/RUAq30sPG2V #SmallerPractices #DifferenceMakers #CAANZ #AI

The rapid adoption of AI tools is creating a fragmentation challenge for businesses, as individual teams pick different models, datasets and AI architectures to work with.  In turn, this introduces risks due to inconsistent a quality control, oversight and accuracy levels in AI responses.   Learn how AI Knowledge Bases can addresses these challenges, by providing a shared memory for agents & AI chat: https://ow.ly/e7My30sPxHP #AI #TungstenAutomation #Blog #AIAdoption #BusinessIntelligence #AIEthics #DataManagement #MachineLearning

The rapid adoption of AI tools is creating a fragmentation challenge for businesses, as individual teams pick different models, datasets and AI architectures to work with.  In turn, this introduces risks due to inconsistent a quality control, oversight and accuracy levels in AI responses.   Learn how AI Knowledge Bases can addresses these challenges, by providing a shared memory for agents & AI chat: https://ow.ly/z5BW30sPw48 #AI #TungstenAutomation #Blog #AIAdoption #BusinessIntelligence #AIEthics #DataManagement #MachineLearning