IREB’s Post

A large language model (LLM) is an artificial intelligence (AI) that can generate human-quality text. LLMs are trained on massive datasets of text and code, and they can be used for various tasks such as Text generation, Translation, Summarization, Question answering, and Classification. Examples of LLMs are ChatGPT and Bard. LLMs are still under development, but they have the potential to revolutionize the way we interact with computers. They can be used to create more natural and engaging user interfaces, and they can also be used to automate tasks that humans currently do. #technology #ai #chatgpt #bardai #llm #futureforward #automation #technologysolutions #informationtechnology #contorsolutions

Skeleton of Thought Prompting Technique Skeleton of Thought prompting shows promising ways to make chatbots faster, smarter, and more human-like. The key idea is having LLM create the skeleton of the response first - just like how people outline ideas before writing an essay. Once you have an outline or a "skeleton" of the idea, then each idea is elaborated concurrently. This Skeleton of Thought technique not only enables parallel generation, but in most cases also enhances accuracy and completeness. Early experiments applying this multi-phase approach achieved up to 2.4x faster responses on open-domain, real-world content without losing quality. In the blog post below, I explain the technique in more detail and then write the code to test it out. Through my testing, I was able to reproduce and confirm the conclusions drawn in the paper. Generations were faster, longer and more comprehensive than Vanilla prompting! At Opal AI, we seek to make leading-edge language and generative technologies accessible and impactful for organizations of all sizes. Contact us to learn more about us. https://lnkd.in/gbABcKtS #artificialintelligence #chatgpt #promptengineering

Skeleton of Thought Prompting Technique Skeleton of Thought prompting shows promising ways to make chatbots faster, smarter, and more human-like. The key idea is having LLM create the skeleton of the response first - just like how people outline ideas before writing an essay. Once you have an outline or a "skeleton" of the idea, then each idea is elaborated concurrently. This Skeleton of Thought technique not only enables parallel generation, but in most cases also enhances accuracy and completeness. Early experiments applying this multi-phase approach achieved up to 2.4x faster responses on open-domain, real-world content without losing quality. In the blog post below, I explain the technique in more detail and then write the code to test it out. Through my testing, I was able to reproduce and confirm the conclusions drawn in the paper. Generations were faster, longer and more comprehensive than Vanilla prompting! At Opal AI, we seek to make leading-edge language and generative technologies accessible and impactful for organizations of all sizes. Contact us to learn more about us. https://lnkd.in/gbABcKtS #artificialintelligence #chatgpt #promptengineering #consulting

𝐆𝐏𝐓 𝐔𝐧𝐯𝐞𝐢𝐥𝐞𝐝: 𝐓𝐡𝐞 𝐄𝐧𝐜𝐡𝐚𝐧𝐭𝐢𝐧𝐠 𝐅𝐨𝐫𝐜𝐞 𝐁𝐞𝐡𝐢𝐧𝐝 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 🌠 🤖 🔮 ChatGPT has become one of the most interesting AI applications in recent times. Most of us are amazed by its uncanny ability to deliver spot-on responses. But did you ever wonder about the fascinating technology that fuels ChatGPT's brilliance? GPT, which stands for Generative Pre-trained Transformer, for an AI network that's good at creating text. It has been trained with quite a lot of text and books to obtain human-like textual capabilities. It uses the Transformer architecture which is one of the leading architectures for these kinds of AI. Fascinated by the wonder of GPT? Here’s an overview of GPT and its evolution. #GPT #chatgpt #ai #techadvancements #technologyinnovation #bistecglobal

Did you know that both your phone’s T9 and ChatGPT work by predicting the next word in a sentence? 🧠✨ This process, called language modeling, allows these AI tools to generate coherent text word by word. Essentially, these models use complex equations to guess what comes next based on the words you’ve already typed. For example, after each word, the model reassesses the entire sentence to predict the next one accurately. This is how your phone’s autocomplete and ChatGPT can create smooth, flowing text. T9 has been enhancing our texting experience since the early 2010s. Meanwhile, ChatGPT, based on the Generative Pre-trained Transformer (GPT) architecture developed by Google researchers in 2017, takes it to the next level, creating longer and more sophisticated content. AI language models are truly transforming the way we communicate! #AI #Artificial Intelligence #LanguageModeling #T9 #ChatGPT #Autocomplete #TextPrediction #NeuralNetworks #MachineLearning

What is Artificial General Intelligence (AGI), and why are people worried about it? Artificial general intelligence (AGI) is a theoretical AI system with capabilities that rival those of a human. Many researchers believe we are still decades, if not centuries, away from achieving AGI. AGI is AI with capabilities that rival those of a human. While purely theoretical at this stage, someday AGI may replicate human-like cognitive abilities including reasoning, problem solving, perception, learning, and language comprehension. When AI’s abilities are indistinguishable from those of a human, it will have passed what is known as the Turing test, first proposed by 20th-century computer scientist Alan Turing. If you’re thinking that AI already seems pretty smart, that’s understandable. We’ve seen gen AI do remarkable things in recent years, from writing code to composing sonnets in seconds. But there’s a critical difference between AI and AGI. Although the latest gen AI technologies, including ChatGPT, DALL-E, and others, have been hogging headlines, they are essentially prediction machines—albeit very good ones. In other words, they can predict, with a high degree of accuracy, the answer to a specific prompt because they’ve been trained on huge amounts of data. This is impressive, but it’s not at a human level of performance in terms of creativity, logical reasoning, sensory perception, and other capabilities. By contrast, AGI tools could feature cognitive and emotional abilities (like empathy) indistinguishable from those of a human. Depending on your definition of AGI, they might even be capable of consciously grasping the meaning behind what they’re doing. #chatgpt #AIDevelopment #ArtificialIntelligence #artificialinteligence #aicontent #chatbot #AIApplications #AIFacts #artificialintelligence #IntelligentAutomation #AIFuture #AIForGood

Is Chat GPT getting dumber or is it just "Prompt Drift"? A recent academic research paper (link in comments) found that Chat GPT3.5 and GPT4 performance and accuracy was getting worse. This lead to headlines like “The world's most powerful AI model suddenly got 'lazier' and 'dumber.'” from the Insider, and various theories that the model had been changed to be cheaper to run, or moderation to be more politically correct was also limiting its performance In fact, it seems that Chat GPT's performance isn't getting worse, it's just that it is evolving. Prompts that used to work work less well or not as expected - a concept known as "Prompt Drift". This is why, I always recommend companies embracing AI to keep an internal prompt library - a shared collection of prompts that are utilised by you and your team. Prompt libraries allow you to: - organise prompts by use case or objective - share improved prompts between team members - monitor prompt performance and report issues - help encourage a culture of AI adoption throughout your organisation. Notion.ai is my go to platform for this, though any software with similar functionality would work just as well. #ai #promptengineering #chatgpt4 #chatgpt #midjourney BTW the picture 👇 is my imagination of a prompt library. Midjourney.

Computer vision vs common sense🧠 -_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_-_- A person asked community to look for an ai or software which can count the number of stones in a given picture. GPT-4 estimated it to be around 557 which was way off from the correct estimate...😵 When it was asked again, it said the numbers could lie between 200 to 300. This happens usually to almost all regular users of ChatGPT. But why? A very significant quality that humans have—that AI does not—is common sense. ✨ This is very important in all routine activities, and that is where humans have the upper hand. AI cannot grasp any concept on its own using reason, since it depends only on predefined facts and figures. There are many facts that exist in this world because of common sense used by humans. AI may not be able to perceive these facts if they don’t coincide with an established set of actions. AI can’t prepare models of things mentally using the environment and experience, as humans do; it can merely link the relationship in the raw data to the model that it is looking at. The AI possibly counted the cracks in the stones as separate stones, which in reality is not true, because a stone having cracks doesn't make it count as 2 stones. common sense, right?🤷 AI never experienced this situation in real life but... Defense Advanced Research Projects Agency (DARPA)'s Machine Common Sense project aims to address this gap by building computational models that learn from experience and developing a service that learns from reading the web to construct a common sense knowledge repository. Still, would it be sufficient to enrich AI with common sense? Let me know in the comments... #ai #computervision #gpt4 #chatgpt4 #chatgpt #counting #commonsense #logic Not sure about common sense, but in order to automate your daily tasks you should definitely go for ai solutions. Visit us at ASTROSIA🚀

📚 New Insights on AI Prompt Engineering! Explore "Mastering Prompt Engineering for LLMs like GPT." 🤖 In this resource, you'll dive into the world of prompt engineering, learning to optimize results from ChatGPT. Explore various approaches, from using persona patterns instead of Naive prompts to navigating the Tree of Thought for highly optimized AI outcomes. Learn strategies to optimize AI results. Find it on my LinkedIn profile. Let's drive the AI conversation forward! 💡 #ai #gpt #prompt #promptengineering #chatgpt

Juji in the #Media: #AIHallucinations and #CognitiveAI: Generative AI tools like ChatGPT are powerful in interpreting natural language and generating text responses, but they can exhibit flaws, such as "AI hallucinations," where they produce inaccurate information. These hallucinations occur due to the model's reliance on training data and patterns, often resulting in fabricated responses when data is lacking. However, this ability to synthesize information relates to human cognitive skills like learning by analogy. In this Fast Company article by Juji, Inc. CEO and co-founder Michelle Zhou, she highlights how AI’s evolution toward cognitive intelligence can benefit areas like education and healthcare by tailoring information to individual characteristics, enhancing comprehension, motivation, and personalization. Read the article: https://lnkd.in/gRP5Gnk7 #AI #Juji #JujiStudio #programming #nocode #lowcode #chatbots #ML