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#AI Showdown: Perplexity vs. Google!   ✨ Revolutionary Search: Perplexity's AI summarizes, no more link lists! 👥 Copilot Guide: Get personalized search assistance! 📑 Source-Specific Searches: Target academic papers, YouTube, Reddit! 💻 Advanced AI Models: GPT-3.5, Llama 2, GPT-4 - Tailor your searches! ❓ Honesty Matters: Perplexity admits when it's unsure. No more fake info! 🔄 Best of Both Worlds: Perplexity excels in complexity, Google for specifics. Explore both! 🔮 Future Impact: Convenience vs. ethical media consumption debate!   💡 Win for Users, Challenge for Publishers: Will AI reshape how we consume info? Share your thoughts!   #PerplexityVsGoogle #AIRevolution #SearchTech #FutureMedia #DebateTime #sundarinfographicanalytics #SIA #@SNC    

#AI Showdown: Perplexity vs. Google!   ✨ Revolutionary Search: Perplexity's AI summarizes, no more link lists! 👥 Copilot Guide: Get personalized search assistance! 📑 Source-Specific Searches: Target academic papers, YouTube, Reddit! 💻 Advanced AI Models: GPT-3.5, Llama 2, GPT-4 - Tailor your searches! ❓ Honesty Matters: Perplexity admits when it's unsure. No more fake info! 🔄 Best of Both Worlds: Perplexity excels in complexity, Google for specifics. Explore both! 🔮 Future Impact: Convenience vs. ethical media consumption debate!   💡 Win for Users, Challenge for Publishers: Will AI reshape how we consume info? Share your thoughts!   #PerplexityVsGoogle #AIRevolution #SearchTech #FutureMedia #DebateTime #sundarinfographicanalytics #SIA #@SNC    

The Golem era for AI has arrived! (Ok, it is more like GOLMM) Google Gemini has launched, bringing many benefits and increased reasoning. If you have not already read about it, you can find more information here: https://lnkd.in/gw4FDrrw But as we know, with every AI model launch, another company will soon try to do a one-up. So stay calm, manage the FOMO, and understand things from first principles. Early in Q1 2023, a new term was discussed: GLLMM - referring to Generative Large Language Multimodal Models With multi-modality, GLLMM goes beyond text and can process other forms of inputs like audio, pictures, and video. This means AI can now interpret and process information like a human, with less technical data conversion or processing needed. The result? Less effort and faster results. As business leaders, finding low/no code tools to enable your team (technical + non-technical) to try and solve problems will be key to unleashing next-gen GLLMMs at scale. What's not to love? Go try it out! If you enjoy more practical AI business applications tips and insights (think pure math vs applied math), hit like and follow to go on this journey with me :) #AI #GoogleGemini #GLLMM #NextGenAI #AppliedAI Image credit: Pokemon

Demystifying the Magic: How Large Language Models Power BlinkIT #AI #MachineLearning At BlinkIT, we're obsessed with innovation, leveraging cutting-edge technology like Large Language Models (LLMs) to empower our platform. But what exactly are LLMs? Think of them as incredibly powerful AI models trained on massive amounts of text data. This allows them to: Understand complex language: LLMs can analyze and interpret information just like humans, making data retrieval and manipulation a breeze. Generate human-quality text: Need summaries, reports, or even creative content? LLMs can handle it, freeing you up for more strategic tasks. Learn and adapt continuously: As LLMs are exposed to new data, they improve, ensuring BlinkIT stays at the forefront of data intelligence. Here's how LLMs make BlinkIT shine Enhanced Data Search: Find the exact information you need quickly and efficiently with LLM-powered search functionalities. Automated Content Creation: Generate insightful reports and summaries, saving you valuable time and resources. Personalized User Experience: LLMs help us personalize your BlinkIT experience, delivering the most relevant data and insights. #BlinkIT #LLM #DataScience #FutureofWork #AIpowered

Imagine if AI could understand your questions better and give more helpful answers. That’s the magic of Retrieval Augmented Generation (RAG)! It’s like having a super-smart AI assistant that can find the right information and write a response that makes sense. Let’s dive into what RAG is all about and how it’s changing the game in AI. Read More https://lnkd.in/dsHpDy43 Asif Raza Babar Shahzad Syed Wasay Ayaz Zeeshan A. Shariq Rizvi saqib hassan Aijaz Ali Muhammad Talha W. Omer Khan #itservices #softwaresolutions #softwareengineer #qualityassurance #softwarecompany #softwareengineering #automationtesting #developers #softwareaccessibility #accessibilitytech #accessibilitytechnology #softwaremaintenance #softwareengineer #softwaredeveloper #softwaredevelopmentcompany #loadtesting #softwaredevelopmentlifecycle #softwaremaintenance #agile #outsourcingsolutions #itoutsourcing #developmentstack #technology

DISCOVER THE FUTURE OF AI 🧠 • See how Gen AI has the potential to be a force for good in business • Learn how Large Language Models (LLMs) solve today’s highly challenging issues • Find out how to use Gen AI responsibly and what safeguards are available • Explore use cases in Healthcare, Capital Markets, Sports, and Waste & Recycling With a foreword written by Matt Penton, Head of Data & Analytics at Appsbroker Download today: https://hubs.la/Q01_YJwz0 #appsbroker #googlecloud #genai #data #ai #ml #llm #ebook

🔱 Achilles heel of AI (LLM) is overwhelming! 🔆 Why it matters? I spent tons of time with different types of LLMs, multi modal and single modal and here is my feedback: No way AI is going to take any jobs in the nearest future. Here is why 👇 💯 BIG PICTURE. ACHILLES HEEEL. LLM generating output, answering the question, why LLMs are "kind of so stupid" (the prompt is a bit more complex). Here is what it comes up with, but(!!!) surprisingly enough, it is right in what is in fact an Achilles heel is. Read below. Reflecting on the rise of AI-generated content, I can't help but ponder the irony of using Large Language Models (LLMs) for crafting social media posts. While these tools offer efficiency, they often lack the spark of human creativity that ignites true commitment. 🤖✍️ The essence of social media is authenticity and novel insights—something that machines, no matter how advanced, struggle to replicate. LLMs may construct grammatically correct and coherent text, but can they match the nuanced, original thought a human brings to the table. Let's not forget that innovation stems from our unique experiences (THIS IS IT - ACHILLES HEEL) and perspectives. As we navigate the digital landscape, let's prioritize content that reflects our individuality rather than settling for the predictability of algorithms. #ai #intelligence #llm

In our daily discussions about generative AI, the fear of AI 'hallucinating'—or fabricating information—often surfaces. This conversation, however, opens the door to an exciting question: Could AI surpass human accuracy in identifying truths? Enter a groundbreaking study by #Google #DeepMind and #Stanford researchers, which introduces a novel framework called SAFE. Tested across approximately 16,000 facts, SAFE demonstrated superhuman performance, aligning with human evaluators 72% of the time and besting them in 76% of contested cases, all while being 20 times more cost-effective than traditional methods. The essence of this methodology lies in two pivotal steps. Initially, the LongFact prompt set, crafted using GPT-4, targets the comprehensive assessment of long-form content's factuality over 38 varied topics. Then, the SAFE framework takes this base further by meticulously breaking down responses into individual facts and validating each through targeted Google Search queries. The process unfolds across four critical stages: 1. 𝗣𝗿𝗼𝗺𝗽𝘁 𝗚𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝗟𝗼𝗻𝗴𝗙𝗮𝗰𝘁: Crafting varied, fact-seeking prompts to elicit detailed LLM responses. 2. 𝗗𝗲𝗰𝗼𝗺𝗽𝗼𝘀𝗶𝘁𝗶𝗼𝗻 𝗶𝗻𝘁𝗼 𝗜𝗻𝗱𝗶𝘃𝗶𝗱𝘂𝗮𝗹 𝗙𝗮𝗰𝘁𝘀: Segmenting these responses into distinct facts for precise evaluation. 3. 𝗙𝗮𝗰𝘁 𝗩𝗲𝗿𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝘃𝗶𝗮 𝗚𝗼𝗼𝗴𝗹𝗲 𝗦𝗲𝗮𝗿𝗰𝗵: Using LLMs to formulate and dispatch queries, checking each fact's accuracy against search results. 4. 𝗜𝘁𝗲𝗿𝗮𝘁𝗶𝘃𝗲 𝗥𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴 𝗮𝗻𝗱 𝗘𝘃𝗮𝗹𝘂𝗮𝘁𝗶𝗼𝗻: Applying a multi-step reasoning process to assess the support level for each fact. This innovative approach doesn't just mark a leap in evaluating LLM-generated content's factuality; it also paves the way for more trustworthy AI applications in countless fields. For a deep dive into this fascinating study, including access to the LongFact prompts and the SAFE framework, visit: https://lnkd.in/eVr4rz-u Find the full paper here: https://lnkd.in/eSjZ5Tn9 #GenAI #LLM #Hallucination #FactChecking #DeepMind #Stanford #Google #SAFE #LongFact