Himanshu Gupta’s Post

Framework and Benchmark for AI agents...

OpenAI just announced their new line of models - o1! Why would this be useful? It’s early yet, but as an example, new o1 models are perfect for complex reasoning tasks in workflows within n8n and Clay. Instead of using GPT-4o, pull your data from a website with ZenRows or using a Claygent to enrich data, then leveraging o1-preview for advanced decision-making right inside your Clay tables. These models can bring more accuracy and efficiency to your automation processes. If you're working with complex workflows, give these new reasoning models a try! #OpenAI #n8n #Clay #Automation #AI

OpenAI o1: A GAME-CHANGER FOR AI AUTOMATION ⠀ For those of you who don't know, OpenAI’s o1 model dropped, and it’s changing the game for AI automation. If you're working with APIs, this model is a must. ⠀ With 83.3% accuracy in Math Olympiad-level tasks, 89.0% in competitive coding, and outperforming human experts in science, o1 is built for serious problem-solving. ⠀ What sets GPT-o1 apart is its ability to think through its answers, thanks to advanced reinforcement learning. ⠀ It doesn’t just spit out results—it reflects, adapts, and delivers more thoughtful, accurate outputs, making it a powerful tool for automated systems that require high-level reasoning. ⠀ This model is available now for trusted API users, and its integration into your AI workflows will enable a new level of precision and intelligence.

𝘞𝘰𝘶𝘭𝘥 𝘺𝘰𝘶 𝘵𝘳𝘶𝘴𝘵 𝘓𝘓𝘔𝘴 𝙧𝙚𝙖𝙨𝙤𝙣𝙞𝙣𝙜 𝘵𝘰 𝘮𝘢𝘯𝘢𝘨𝘦 𝘺𝘰𝘶𝘳 𝘣𝘢𝘯𝘬 𝘢𝘤𝘤𝘰𝘶𝘯𝘵 𝘰𝘳 𝘥𝘦𝘵𝘦𝘳𝘮𝘪𝘯𝘦 𝘺𝘰𝘶𝘳 𝘤𝘰𝘶𝘳𝘵 𝘳𝘶𝘭𝘪𝘯𝘨? 👻 [🙂]: What do you think? [🤖]: I don't think, I just predict the next word. [😵] Most LLMs excel at predicting the next word. However, this very strength paradoxically may lead to 𝗵𝗮𝗹𝗹𝘂𝗰𝗶𝗻𝗮𝘁𝗶𝗼𝗻𝘀. 𝘚𝘰, 𝘤𝘢𝘯 𝘸𝘦 𝘵𝘳𝘶𝘴𝘵 𝘓𝘓𝘔𝘴 𝘪𝘯 𝘩𝘪𝘨𝘩𝘭𝘺 𝘳𝘦𝘨𝘶𝘭𝘢𝘵𝘦𝘥 𝘴𝘦𝘤𝘵𝘰𝘳𝘴 𝘭𝘪𝘬𝘦 𝘧𝘪𝘯𝘢𝘯𝘤𝘦 𝘢𝘯𝘥 𝘭𝘢𝘸? The landscape is changing with the intro of OpenAI's 𝗼𝟭 𝗺𝗼𝗱𝗲𝗹, which revolutionizing AI 𝗿𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴. Unlike previous models focused on efficient word prediction, the 𝗼𝟭 𝗺𝗼𝗱𝗲𝗹 is designed to think through problems step-by-step, mirroring human-like 𝗿𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴. This advanced "𝗰𝗵𝗮𝗶𝗻 𝗼𝗳 𝘁𝗵𝗼𝘂𝗴𝗵𝘁" approach significantly reduces hallucinations and enhances accuracy, delivering PhD-level 𝗰𝗼𝗴𝗻𝗶𝘁𝗶𝗼𝗻. Imagine solving a puzzle: instead of guessing the next move, 🤖 carefully consider each piece and how it fits. It unlocks new potential for problem-solving across fields like science, coding, and beyond. [🤔]: Is this another step towards AGI? [🤖]: Let me think about that for a moment…  [🫠] #AI #ArtificialIntelligence #MachineLearning #OpenAI #AIInnovation #AIReasoning https://lnkd.in/dn6hjFtp

OpenAI just dropped its new O1 model, and it's seriously impressive! It’s faster, more efficient, and still delivers top-notch results. What really stands out is how much better it handles different types of inputs and how customizable it is for different tasks. This is going to shake things up in so many industries. Exciting times for AI! https://lnkd.in/g4tNCNNa

𝐔𝐧𝐥𝐨𝐜𝐤𝐢𝐧𝐠 𝐀𝐈’𝐬 𝐅𝐮𝐥𝐥 𝐏𝐨𝐭𝐞𝐧𝐭𝐢𝐚𝐥: 𝐇𝐨𝐰 𝐌𝐞𝐦𝐨𝐫𝐲 𝐁𝐞𝐜𝐨𝐦𝐞𝐬 𝐀 𝐊𝐞𝐲 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐜 𝐀𝐬𝐬𝐞𝐭 𝐰𝐢𝐭𝐡 𝐂𝐡𝐚𝐭𝐆𝐏𝐓 𝟏.𝟎 𝐏𝐫𝐞𝐯𝐢𝐞𝐰 In the ever-evolving landscape of AI, memory isn’t just a tool—it’s a strategic asset. As we embrace the release of OpenAI’s 𝐨𝟏-𝐩𝐫𝐞𝐯𝐢𝐞𝐰 𝐚𝐧𝐝 𝐨𝟏-𝐦𝐢𝐧𝐢, understanding how to fully utilize memory is key to unlocking the system’s potential for advanced reasoning and more efficient interactions. 💡 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞: While the models are designed to excel in complex tasks, AI systems sometimes face challenges recalling contextual details—particularly when handling numerous variables across multiple interactions. This doesn’t stem from a lack of knowledge but from limitations in how the model processes and retrieves stored information over time. 💡 𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧: By using memory as a repository for key reminders, similar to how developers use GitHub repositories, we can ensure the AI remains aligned with specific user needs and retrieves critical information without backtracking. This approach allows memory to: • Store important context: Whether for formatting tasks or recalling pre-installed libraries, memory reduces friction in complex workflows. • Enhance AI functionality: Just as GitHub serves as a collaborative platform for open and closed-source projects, AI memory can store essential documentation and technical details, ensuring smoother communication between users and the system. By leveraging memory as a tool for reminders, not subjective interpretation, we can achieve higher efficiency and maximized performance in interactions—just as the 𝐨𝟏 𝐩𝐫𝐞𝐯𝐢𝐞𝐰 and 𝐨𝟏-𝐦𝐢𝐧𝐢 models help AI refine reasoning capabilities in coding, mathematics, and strategic tasks. This strategic use of memory is a powerful approach that Plus, Team, and Enterprise users can adopt, especially with the new model capabilities. It aligns with the larger trend in AI innovation—storing information in repositories ensures accuracy and efficiency across multiple sectors, whether for API-driven teams or general users. Check out more details on the new 𝐨𝟏 𝐚𝐧𝐝 𝐨𝟏-𝐦𝐢𝐧𝐢 𝐦𝐨𝐝𝐞𝐥𝐬 here: https://lnkd.in/gagQxPSx Explore how this can be applied through my BookmarkGPT here: https://lnkd.in/g7XC49RW

Analytics India Magazine writes "OpenAI Introduces Swarm, a Framework for Building Multi-Agent Systems - OpenAI has also released MLE-bench, a benchmark designed to assess how effectively AI agents can perform machine learning engineering tasks." https://lnkd.in/eUreDrrR. #openai #framework #swarm #aiagent #multiagent #generativeai #artificialintelligence #analyticsindiamagazine

🌊 Interested in the new wave of AI in observability? Last week, our CTO and Co-Founder, Asaf Yigal, delivered an in-depth presentation during a webinar on The Linux Foundation on this trending topic! Watch the webinar here to gain insights into the future of AI observability! https://buff.ly/4ayb3rA #observability #ai #chatgpt #llm

Beyond basic LLM apps: dive into Retrieval Augmented Generation (RAG) This week's tech breakdown: - What RAG is & why it matters for AI apps - 3 key RAG architectures explained - How RAG solves hallucination & knowledge updates challenges From basic RAG to Retrieval-Enhanced Transformers, unpack the tech behind smarter AI.

#Xenon7Insights - Can #AI truly reason like humans? With OpenAI's latest breakthrough suggests we're getting closer. The company has unveiled its new #o1Model, designed to "think before it speaks" using advanced reinforcement learning techniques. This development marks a significant step towards more thoughtful and reliable #AISystems. Unlike previous models that sometimes rush to conclusions, #o1 takes time to consider problems carefully before responding. In a striking demonstration, #o1 successfully reasoned through a multi-step problem involving strawberries and algebraic equations, showcasing its ability to handle complex, interconnected concepts. Key points about #o1: 1️⃣ Trained to solve problems independently, mimicking human reasoning processes. 2️⃣ Capable of breaking down complex tasks into smaller, manageable steps. 3️⃣ Demonstrates improved performance in math, coding, and analytical reasoning. As industries move toward smarter automation, o1 is setting a new standard for AI-powered solutions that drive tangible business results. Want to see how this might impact your bottom line? Let’s talk about how #ArtificialIntelligence can work for your business. Follow us for more insights & breakthroughs from Xenon Seven.