Mindy Support’s Post

Large language models (LLMs) are transforming data science with their ability to automate text and generate images. However, putting them into practice in organizations is tricky, and we're still unsure if they can do all human tasks. What do you think LLMs will do to jobs in the future? #MachineLearning #LLM #Technology #DigitalTransformation https://lnkd.in/gpqSpCZk

Large language models (LLMs) are transforming data science with their ability to automate text and generate images. However, putting them into practice in organizations is tricky, and we're still unsure if they can do all human tasks. What do you think LLMs will do to jobs in the future? #MachineLearning #LLM #Technology #DigitalTransformation https://lnkd.in/dp5Xr4Zp

Large language models (LLMs) are transforming data science with their ability to automate text and generate images. However, putting them into practice in organizations is tricky, and we're still unsure if they can do all human tasks. What do you think LLMs will do to jobs in the future? #MachineLearning #LLM #Technology #DigitalTransformation https://lnkd.in/ea3grNPB

Large Language Models (LLMs) are revolutionizing data processing and analysis, offering a more comprehensive understanding of structured and unstructured data. By leveraging advanced language processing techniques, LLMs can provide nuanced and context-aware insights for sentiment analysis, trend identification, and risk assessment. At Nort Labs, we understand the potential of LLMs in enhancing business intelligence and informed decision-making. The integration of LLMs with data analytics unlocks the potential of unstructured data, providing a more comprehensive analysis and deeper insights. Let's embrace the power of LLMs and take our data analysis to the next level! #LLMs #DataProcessing #BusinessIntelligence #NortLabs #Technology #DataAnalytics

"LLMs complete the picture." Derek du Preez sits down with newly appointed ThoughtSpot CEO Ketan Karkhanis, to hear why Large Language Models (LLMs) are the missing piece in helping get data into the hands of as many business users as possible: bit.ly/4fyFuRN #LLMs #BusinessIntelligence #DataAnalysis

🚀Check out our latest blog, "Automating Insight: The Fusion of Topic Modeling and LLMs," where Sayali Pophale explores the powerful synergy between topic modeling algorithms and Large Language Models (LLMs). Discover how this convergence is revolutionizing automated insights, with profound implications for industries such as finance and healthcare.💹👩⚕️ Read the blog here: https://lnkd.in/dtjnebZ4 #TopicModeling #Insights #LLM #LargeLanguageModels #Finance #Healthcare #AlgoFabric

The articles explore the limitations and failure modes of large language models (LLMs), which despite their impressive capabilities, still struggle with seemingly simple tasks for unclear reasons. LLMs are statistical predictors that perform well in specialized domains with abundant data, but lack the depth of understanding and logical reasoning abilities of human cognition. The author compares this to the limitations of university students early in their studies, who only see the surface of literature without grasping the deeper structure. While LLMs have surpassed many previously impossible challenges, they remain very different from human intelligence, unable to demonstrate even basic propositional logic theorems. #LargeLanguageModels #LLMs #AIvsHuman

The power and limitations of Large Language Models (LLMs) 🧠💻 We did a webinar with Unstract CEO where he discussed: 📈 Current challenges in extracting data from charts and graphs 📈 Why LLMs aren't yet reliable for processing visual data 📈 The vast potential of LLMs in solving manual, time-consuming tasks Watch the full replay: https://lnkd.in/gapuukTg #Milvus #Vectordatabase #LLMs

Understanding user behavior is key to gathering implicit feedback. This type of feedback is inferred from actions like clicking on items or watching videos. While it's easier to collect, interpreting implicit feedback can be challenging. For instance, when a user watches a movie, it's not always clear if they genuinely enjoyed it or simply had it playing in the background. #UserBehavior #ImplicitFeedback #recommenders #recommendationsystems #ai #datascience

GPT vs BERT: Which is better❓❓ Not really sure… that’s why I chose to use both 💡 BERT is extremely powerful for text classification tasks, and its performance is excellent even in multi-class classification problems. However, like any other classifier, it requires sufficient text data for proper training. Utilizing a GPT model can be an effective solution to generate additional text data to address data scarcity and balance the training set. I tested this approach, and the BERT classification accuracy increased by more than 10% after augmenting the data with GPT-3.5 Turbo 🚀