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Is there a better way to ask AI better questions? Well there always is. Sheila Teo, winner of Singapore's first ever GPT-4 Prompt Engineering competition has a quite interesting approach. It's called the COSTAR Framework. Crafting effective prompts is key to unlocking the full potential of ChatGPT, Bard, Claude2 etc.. But with so many factors to consider, it can be easy to get lost in the weeds. That's why I believe the COSTAR framework might help you to get over the hump. COSTAR is not just effective, but it is also easy to remember. COSTAR stands for: Context: Set the scene and provide background information. Objective: Clearly define what result you want from the AI assistant. Specificity: Specify the desired style, tone, and level of detail. Task: Indicate the type of task you want the AI assistant to do. Audience: Consider who will be reading or consuming the output. Response: Specify the format of the desired response (e.g., text, code, etc.). Brilliant. Especially because it puts Context at the very beginning, how you would do in a regular conversation with somebody. So easy to remember, so clearly defined. By following these six steps, I can create my prompts in a clear, concise way that is tailored to my specific needs. This will result in more relevant, creative, and effective outputs from AI assistant. Ready to put COSTAR into action? Try it out with your next prompt and see the difference! @Jake George

Advice - read this before you plunge into the wild world of Smart Techs of Future.

What's happening today in the AI world? Let me tell you: 🔥 Marketing mavens, imagine fueling your business's growth engine without being an expert. Meet Evercopy, the AI genie that conjures up tailored marketing strategies, fine-tunes campaigns, and designs captivating ads, all while juggling your channels. It's like having a marketing whiz on your team at the touch of a button. Discover Evercopy here: https://buff.ly/3viUP6N 🛠️ Now, who doesn’t like a little secret sauce for success? OpenAI serves up a six-step recipe for getting top-notch results with ChatGPT. Their prompt engineering guide is the GPS you need to navigate the world of effective prompts and fully harness the smarts of ChatGPT and GPT-4. Get your guide here: https://buff.ly/47fMfmC 🌟 But wait, there's more! Feast your eyes on these standout AI tools: - Stackbear, your own digital helper for sprucing up websites: https://buff.ly/47itUFs - Booknotes, your fast track to knowledge through book summaries: https://buff.ly/41ISJcy - Knowbase, the key to an organized conversational knowledge base: https://buff.ly/48zCq3L - Pulze, smoothing out language model deployment: https://lnkd.in/dhRnyVmA - Wave AI Note Taker, your personal scribe for transcription and summarization: https://lnkd.in/dRws-eiF Stay informed and inspired: Twitter: https://lnkd.in/dK53iysg LinkedIn: https://lnkd.in/d8XvjAvj YouTube: https://lnkd.in/dN8piWpr Until next time, leverage AI to elevate your strategy, simplify tasks, and stay ahead. #ArtificialIntelligence #MarketingStrategy

Say goodbye to overpriced tools Try this FREE alternative for better results Read Here:⬇️ _______________________________ Let Me introduce you to Buffup.ai ▶️ AI Copilot of ChatGPT4 & Claude3 with 1K+ bots ▶️ Buffup (dot) AI is an innovative and extremely user-friendly AI assistant. ▶️ The most advanced AI model, and you can freely use thousands of Buffup (dot) AI Bots released by users worldwide. Try it: buffup.ai Some of its important features: 1. Chat Pdf 2. Processing webpage content 3. Text to image 4. Chatbot Why Buffup.ai? ▶️Ease of Use: Designed for simplicity, ready to use right out of the box. ▶️Versatile AI Assistant: Chat Smarter, Search Faster, Read Easier, Write Brighter, Translate Freely ▶️Global Buffup Bots Library:Freely use thousands of Buffup.AI Bots released by users worldwide ▶️Custom Bot：Customize the AI bot and share it easily ▶️Text-to-image generation：Generate the picture you want in one sentence ▶️ChatPDF: quick summarization, and parsing of PDF content ▶️File Assistant: Support analysis of various types of files ▶️Strongest model: Chat with ChatGPT4 & Claude3 Interesting? Try it for FREE Link: buffup.ai ________________________ GIFT 🧧 Top 12 AI Tools FREE Tutorial is here 🔽 •Click the link • Get it download for FREE 🔗 https://lnkd.in/dX96sUMn #ai #prompt #buffupai #tools

Fakhre Alam, Thank you for sharing this insightful post about Buffup.ai as a free alternative to overpriced tools. It's always great to discover new AI assistants that can enhance our productivity and deliver better results. Buffup.ai seems like an innovative and user-friendly AI assistant, especially with its advanced AI models and a vast library of Buffup.AI Bots released by users worldwide. The versatility of this tool, from chat smarter to search faster, read easier, write brighter, and even translate freely, is impressive. I particularly find the customizable bot feature intriguing. Being able to personalize the AI bot according to our specific needs and easily share it is definitely a valuable asset. The ability of Buffup.ai to generate images based on one sentence is fascinating. Text-to-image generation can save a lot of time and effort in visual content creation. Additionally, the features like ChatPDF for quick summarization and parsing of PDF content, as well as File Assistant supporting analysis of various file types,

Save this for future reference. 𝗖𝗵𝗮𝘁𝗚𝗣𝗧: 𝗧𝗵𝗲 𝗯𝗶𝗴𝗴𝗲𝘀𝘁 𝘁𝗵𝗶𝗻𝗴 𝘀𝗶𝗻𝗰𝗲 𝘁𝗵𝗲 𝗜𝗻𝘁𝗲𝗿𝗻𝗲𝘁 is the webinar I just held with ~500 registrations. Next steps: 1. ChatGPT for Work: The Interactive Course https://lnkd.in/df8PCKwZ 2. Prompting PDF https://lnkd.in/dTD-E5XE 3. Top 10 Things you need to know about ChatGPT https://lnkd.in/d_KjE_KG 4. Top 100 Use Cases for ChatGPT (and how to ask them) https://lnkd.in/d7-8V2UR 5. ChatGPT Adoption Methodology https://lnkd.in/dHaYHwK2 6. Honest Review of OpenAI DevDay https://lnkd.in/dV7QWcEP 7. From 0 to 10K users | Team-GPT Getting Ready to Scale https://lnkd.in/em4sPtnm 8. What we do at Team-GPT https://lnkd.in/dPxfq2bS 9. Team-GPT https://team-gpt.com/ 10. Team-GPT (5-min demo) https://lnkd.in/drBEtxFk 11. Team-GPT Enterprise (deploy on your own server) https://lnkd.in/d8gPab4Z --- Other people's amazing resources: 12. Generative AI: This is how it works https://lnkd.in/dYifzyzi 13. What Is ChatGPT Doing ... and Why Does It Work? https://lnkd.in/dPEbKDXi 14. How to Research and Write Using Generative AI Tools https://lnkd.in/deNd2hiv 15. ChatGPT Complete Guide: Learn Midjourney, ChatGPT 4 & More https://lnkd.in/dYVpN6PV 16. AI and the Illusion of Intelligence https://lnkd.in/dVVh--cF 17. Prompt Engineering Guide https://lnkd.in/dqehqwGB 18. The state of AI in 2023: Generative AI’s breakout year https://lnkd.in/dPSjZrUs 19. The economic potential of generative AI: The next productivity frontier https://lnkd.in/dxBz-mzQ 20. Humans need not apply https://lnkd.in/dih2ummj - Save it 🔖 Then click my photo + follow + 🔔

Is synthetic data good or bad for marketing and #insights? 🤔 I'm a skeptic, but there are some undeniable benefits: 💨 Speed -> Instead of running a study that takes days (or, god forbid, weeks or months), you can just use AI and other tools to generate insights for you. 💰 Costs -> No need to hire an agency, pay an employee, or subscribe to a #restech or survey tool to engage your customers ⚙️ Automation -> This is how Mark Ritson explains it for Marketing Week: "AI could automate the process of analysis and decision making. Rather than discrete stages between data collection, analysis, strategy and execution, imagine the ability of AI to simply go to work and formulate the optimum targeting, positioning, objectives, media mix, pricing and so on, in real time." Just like AI, synthetic data is here to stay and it will definitely change the game in market research and insights. But unlike Ritson (and with all due respect), I believe the concerns around it are valid and worth talking about. This includes: 🧐 Where is the data coming from? And are those datasets accurate and timely? (Keep in mind, for example, that if you're using ChatGPT to generate some of this synthetic data, you're using data from whatever the current cutoff date is.) 🧐 What's behind the algorithm? 🧐 Are there biases in the algorithm? What I do agree with is that triangulation is key. Primary research can help with this, but also in providing more context, color—and, just as important—confidence that the insights are correct. My recommendation? Start experimenting with synthetic data now, but definitely keep in mind its potential risks and challenges. And run parallel studies to validate what you're seeing. #MRXPros: What do you think? P.S. Ritson's article is worth checking out. Link in the comments. 👇

Here is my special curation this week for you: It consists of the latest AI breakthroughs, insightful guides, and must-have tools I’m eager for you to explore. From OpenAI's innovative developments to strategies that will take your digital footprint to the next level, we’ve got a lot to dive into. 🔍 Inside This Edition: The Voice Engine Innovation: OpenAI's new model is transforming synthetic voices. Instant Access to ChatGPT: Explore AI without the hassle of signing up and enjoy the experience. DALL·E Mobile Editing: Discover easy-to-use editing features for your AI artworks. 💡 Featured Guide: I share a comprehensive guide on crafting content calendars with ChatGPT. Plus, don't miss out a great video on the ChatGPT Memory feature and a tailored prompt designed to improve your social media interactions. 🔗 Spotlight on Tools: Meet Taplio, the tool that promises to change your LinkedIn strategy, offering everything from content inspiration to analytics. Every Wednesday, it's delivered directly to your inbox. 1. Please comment on this post. 2. I will send you the sign-up link. 3. Share this post to spread AI knowledge and update your network. _____________________________ I'm Tim Cakir Like this post? 👍 Subscribe to my weekly newsletter for AI tools, systems, and technology to grow your business.

🌟 𝗠𝗮𝗸𝗶𝗻𝗴 𝗔𝗜 𝗦𝗺𝗮𝗿𝘁𝗲𝗿: 𝗜𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝗳𝗿𝗼𝗺 𝗠𝘆 𝗥𝗲𝗰𝗲𝗻𝘁 𝗖𝗼𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 Hello everyone! At a recent conference, I had some enlightening discussions with experts from CrateDB and DataStax (AstraDB). One standout topic was about a new way to make AI systems smarter and more informed. Here's the gist: 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗔𝘂𝗴𝗺𝗲𝗻𝘁𝗲𝗱 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 pattern, or what many are calling the "RAG" approach. 𝗧𝗵𝗶𝗻𝗸 𝗼𝗳 𝗔𝗜 𝗮𝘀 𝗮 𝗦𝘁𝘂𝗱𝗲𝗻𝘁: Just like a student uses books and the internet to find answers, our AI systems are now being equipped with a similar ability to "look up" information from vast digital libraries. 𝗕𝗲𝘁𝘁𝗲𝗿 𝗔𝗻𝘀𝘄𝗲𝗿𝘀, 𝗙𝗲𝘄𝗲𝗿 𝗠𝗶𝘀𝘁𝗮𝗸𝗲𝘀, 𝗟𝗲𝘀𝘀 𝗛𝗮𝗹𝘂𝗰𝗶𝗻𝗮𝘁𝗶𝗼𝗻: We've all experienced moments where voice assistants or chatbots give unexpected replies. This new approach helps reduce those moments by allowing AI to cross-check its answers. 𝗔𝗹𝘄𝗮𝘆𝘀 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴: Just as we're constantly learning and updating our knowledge, this new method ensures AI does the same, using the latest and most relevant information. 𝗪𝗵𝘆 𝗜𝘁'𝘀 𝗘𝘅𝗰𝗶𝘁𝗶𝗻𝗴: As we interact more with AI in our daily lives, it's crucial that it understands and assists us accurately. This new approach is a big step towards that goal. 𝗟𝗲𝘁'𝘀 𝗖𝗵𝗮𝘁: Have you had any memorable interactions with AI? How do you feel about technology that's constantly learning and improving? Share your thoughts! ================================================================================ PS. This post was automatically written by a tool that I wrote myself, using an AI copilot - agent, powered by ChatGPT LLM, Langchain agent and a knowledge base consisted of: 𝗚𝗼𝗼𝗴𝗹𝗲 𝘀𝗲𝗮𝗿𝗰𝗵, 𝗪𝗶𝗸𝗶𝗽𝗲𝗱𝗶𝗮, 𝗭𝗮𝗽𝗶𝗲𝗿 and few articles about RAG, indexed by OpenAI embeddings and an internal vector store. 𝗖𝗼𝗼𝗹, 𝗶𝘀𝗻𝘁 𝗶𝘁.

ChatGPT drinks 1.7 billion gallons water. Equal to 2,500 Olympic-sized pools 👇 As we rush to AI tools, the environmental impact of AI is beginning to come to light. Building LLM requires analyzing patterns across a huge trove of data. All of that computing takes a lot of electricity and generates a lot of heat. To keep it cool, data centers need to pump in lot of water. How much? In the latest environment report, Microsoft revealed a 34% jump in their global water consumption last year. That's 1.7 billion gallons, about the size of 2,500 Olympic-sized pools. Why? OpenAI ties this increase to AI research. Microsoft's partnership with OpenAI undoubtedly plays a part too. In fact, Iowa, the home of their data centers, is already feeling the water squeeze. Consider this, ChatGPT sips a full 16-ounce water bottle for answering 5 to 50 questions. Outrageous, isn't it? Google, too, noted a 20% increase in water use, mostly because of AI. As we brace ourselves for GPT-4, Bard and Claude upgrades, we must also prepare for an even thirstier AI. But the question is - how much are we willing to let AI drink? P.S. Share ♻️ this to spread the awareness. Thank you!