Sawera Khadium’s Post

🚀 OpenAI o1 is Here, and It’s Changing the Game! 🚀 AI is advancing fast, and OpenAI’s o1 model is shaking things up! 💡 Some say o1 is the biggest AI breakthrough since GPT-3, others think it’s overrated. 🤯 So, what’s the truth? Let's dive into the real-world use cases! 👇 First up, legal work! 📝 People are using o1 to edit and improve contracts, not write them from scratch. It shines in editing existing content rather than creating new. Next, math calculations! 🔢 For large numbers, GPT models struggle, but o1 scores higher in multiplication accuracy. For 10-digit numbers, o1 gets it right 100% of the time. 🙌 Building applications is another big win! 🛠️ One impressive example is o1 building a fully functional chess game with an AI opponent! 🎮 But there’s more! o1 is perfect for strategizing. It can create detailed design documents and plan projects step by step. 💼 Pair o1 with another model for code generation, like GPT 3.5, and you’ve got a perfect workflow! ⚡ What about intelligence? 🤔 o1 ranks 120 on IQ tests, well above the average of most AI models. 📈 o1 may not solve everything, but for brainstorming and planning, it's unbeatable. 💡 Want to know more? Watch the full breakdown here 👇 https://lnkd.in/gvswfMMk 🎥

When was the last time you got what you wanted on your first prompt? 🤔 Check out 4 tactics our CTO uses for debugging complex AI prompts 🪲 #prompting #foundertalks #AIprompt

OpenAI's engineers just did something incredible. They made GPT-4 think ahead. Literally five times faster. The old way? Each word took time. Like watching paint dry. The new way uses "Predicted Outputs." Picture an AI that skips the obvious. Jumps straight to what matters. Writing a document? Flying through edits. Updating content? No waiting. OpenAI tested it with pro users. Results blew them away. Content creators cut wait times by 80%. Students got instant feedback. Teachers saved hours. All because the AI learned to predict. Skip what it knows. Focus on what's new. That's how you make AI practical. No more watching those three dots bounce 😀

Supercharge your processes with fine-tuning! 🚀 OpenAI announced that fine-tuning is now available for GPT-4o. Fine-tuning is a game-changer! 🎉 Fine-tuning allows you to customize generic models to handle specific use cases—from automating complex processes to delivering personalized customer interactions. This isn't just limited to GPT-4o; fine-tuning is available across many other models, offering flexibility to match your business needs. 📢 Learn more about Fine-Tuning GPT-4o by following the link in comment. Do you want to know more? Are ready to elevate your AI strategy? DM or comment to discover how RAG and fine-tuning can transform your use cases and automate your processes! 🔥 #𝐀𝐈𝐑𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧 #𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐨𝐧 #𝐁𝐮𝐬𝐢𝐧𝐞𝐬𝐬𝐆𝐫𝐨𝐰𝐭𝐡 #𝐅𝐢𝐧𝐞𝐓𝐮𝐧𝐢𝐧𝐠 #𝐆𝐏𝐓4𝐨

AI is now smarter than the average human!! And its name is 'o1' (the reason for the odd name is below!) OpenAI’s latest release, the o1 model series, is set to shake up the AI landscape. But what exactly makes these models, including o1-preview and o1-mini, so groundbreaking? Let's take a closer look under the hood of these AI chain-of-thought powerhouses. What makes o1 special? Supersized Context: With a staggering 128,000 token context window, o1 can grasp and process information like never before from OpenAI models. Reasoning Superpowers: o1 uses innovative "reasoning tokens" to break down complex problems step-by-step, emulating human-like thinking. Unparalleled Performance: In tests, o1 has already blown past previous models in areas like math, coding, and analytical reasoning. A peek behind the curtain! o1's secret sauce is a combination of cutting-edge reinforcement learning (learning through rewards and penalties) and those game-changing reasoning tokens. As o1 tackles a problem, it generates hidden reasoning tokens that steer its thought process. It's a bit like having a superhuman chess master, able to think multiple moves ahead, anticipate every possible scenario, and devise brilliant strategies on the fly. That's the kind of intellectual prowess o1 brings to the table, but across a vast range of complex problems, not just on the chessboard. The future of problem-solving.. o1 represents a leap in AI's ability to reason, plan, and tackle intricate challenges. It has the potential to revolutionise fields like finance, healthcare, and beyond, where complex decision-making is paramount. Thoughts.. o1's approach to problem-solving is incredibly exciting. Its ability to reason and plan could have far-reaching implications across industries. But what do you think? How do you see the inner workings of o1 being leveraged in your field? What aspects of the model intrigue you the most? Oh, and the reason for the name - by resetting the naming back to ‘1’, OpenAI aims to emphasise the distinction between this new series and previous GPT models, like GPT-4, while highlighting its unique advancements in problem-solving and safety features.

So what's hard about making modern AI systems real-time data aware? Some are solving it by giving them internet access. That's one way to do it! But what if you have a stream of, let's say... 1,000,000 events per second coming into your system, and you want your modern AI system to classify it? One way to do it is naively wrap GPT. Just route every event to GPT's API, get the results, and act on them. Write a check for a couple $million every month to OpenAI, and you're done! What if you'd prefer to spend less? We need modern LLM performance, but at traditional ML prices. This seems doable with some clever science and engineering.

What will GPT-5 bring?... Tried GPT-4 and wondering what GPT-5 will be like? ‘Agentic’ seems to be the next big thing. 📬 Old post by Andrej Karpathy (a lead AI researcher & co-founder of OpenAI): "A more complete picture is emerging of LLMs not as a chatbot, but the kernel process of a new Operating System." Consider agents as an LLM taking over your computer. Does the idea of an LLM taking over your computer seem far-fetched? We are experimenting with agents on some very specific (for now) use cases, such as desk research and optimizing work prioritization sheets. The key ingredients: - 💻 Open source locally hosted LLM (Llama 3), since the agents are VERY ‘api-call’ hungry - 🤖 Crewai for building and running the agents: defining roles, delegating tasks, and managing their performance." The outcome: “A mix of hits and misses, with low consistency from the agents leading us to integrate rule-based task management, somewhat defeating the original purpose of full autonomy." Curious what you think! Will ‘Agentic’ really be this big? Or is the ‘AI bubble’ just overly excited?

Over the past 2 months I have built over 10 AI Assistants using OpenAI's GPT builder. Surprisingly, I use 9 of these bad boys consistently. Overall I would say they have saved me an easy 50 hours in the past 2 months - I wrote two 25 page books with my Book Writing Assistant, one in 6 hours, the other in 2 days (more story intensive, less data). - I have written 4 newsletters with my Newsletter Ninja (easily saving 2 hours per email) - Built an Alex Hormozi Grand Slam Offer AI Assistant that helped me create the flagship offer for Build With AI in a day. And I'm barely scratching the surface of what's possible here. Tomorrow I drop an email on AI Assistants I have built, and more importantly, how to build one yourself (in 4 steps). You can sign up for the email here: https://lnkd.in/gpc5t2MM

OpenAI is prototyping a new search GPT. This looks similar to what Perplextity provides. You can join the waitlist using the following link. https://lnkd.in/e4mU7KnG

Repurposing the logic of Rules Based Rewards from OpenAI into your enterprise-wide meta prompts can help align your multitude of AI with company standards.