Saharsh Sharma’s Post

🚀🌌 𝐈𝐧𝐭𝐞𝐫𝐚𝐜𝐭𝐢𝐨𝐧𝐬 𝐰𝐢𝐭𝐡 𝐆𝐄𝐌𝐈𝐍𝐈: Ushering in the New Era of Multi-Modal Transformer Models 🌌🚀 Big news in the AI world, yet again! Google has unveiled GEMINI, a groundbreaking family of 𝐌𝐮𝐥𝐭𝐢-𝐌𝐨𝐝𝐚𝐥 𝐓𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐞𝐫 𝐌𝐨𝐝𝐞𝐥𝐬 (MM-TLMs) This marks a significant shift from the age of Large Language Models (LLMs) to an exciting new era where AI understands more than just text. 🎉✨ 🧠 The Legacy of LLMs: For the last year, LLMs like GPT-4 have been at the forefront of AI, mastering the art of text. From writing essays to coding, these models have reshaped how we interact with digital content. But as innovative as they were, LLMs had their limits, confined mostly to the realms of text. 🌐 The Rise of natively integrated Multi-Modal AI with GEMINI: Enter GEMINI. Unlike its predecessors, GEMINI isn't just about text; it's about integrating multiple forms of data - text, images, and possibly more. This means an AI that doesn't just read and write but one that sees, interprets, and understands a broader spectrum of human interaction. 🤖👀 🔗 Why This Matters: In a world inundated with diverse data types, the ability of AI to process and correlate information across text, images, and other mediums is revolutionary. It's not just an advancement; it's a paradigm shift in how we expect AI to interact with our complex world. 👁️💡 The Future of AI: With GEMINI, we're looking at potential applications that range from more immersive educational tools to advanced healthcare diagnostics, enhanced accessibility features, and even more creative AI in arts and media. The possibilities are as limitless as the data types GEMINI can process! 🤔 Your Thoughts?: How do you see GEMINI reshaping your field? What possibilities or challenges do you anticipate with the rise of Multi-Modal AI? Let's discuss the future shaped by these AI advancements! #GEMINI #GoogleAI #MultiModalAI #AIRevolution #FutureOfTechnology source: https://lnkd.in/gmgENEH9 🌐 Speed up your #DigitalizationJourney with the support of #SchopfMetaConsult.

🚀 𝗔𝗻𝘁𝗵𝗿𝗼𝗽𝗶𝗰’𝘀 𝗡𝗲𝘄 𝗔𝗜 𝗕𝗿𝗲𝗮𝗸𝘁𝗵𝗿𝗼𝘂𝗴𝗵: 𝗖𝗹𝗮𝘂𝗱𝗲 𝟯.𝟱 𝗦𝗼𝗻𝗻𝗲𝘁! 🚀 Anthropic is setting new standards in the AI world with its latest model, Claude 3.5 Sonnet! This powerful AI not only rivals OpenAI's GPT-4o and Google's Gemini but also introduces a clever new way to interact with chatbots. ✨ 𝐖𝐡𝐚𝐭’𝐬 𝐍𝐞𝐰? • 𝗦𝗽𝗲𝗲𝗱 𝗮𝗻𝗱 𝗘𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝗰𝘆: Claude 3.5 Sonnet is faster and more capable than ever. • 𝗜𝗻𝘁𝗲𝗿𝗮𝗰𝘁𝗶𝘃𝗲 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀: The new Artifacts feature allows users to see, interact with, and edit their AI-generated results in real-time. • 𝗩𝗲𝗿𝘀𝗮𝘁𝗶𝗹𝗲 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀: Whether it’s for customer support, content creation, or complex problem-solving, Claude 3.5 Sonnet excels across the board. 📈 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝘆 𝗜𝗺𝗽𝗮𝗰𝘁 Anthropic’s advancements promise to revolutionize how businesses leverage AI for operational efficiency and customer interaction. 🔗 Read the full article on The Verge https://lnkd.in/gg5jfZYd At Echoes, we're excited about these innovations and how they can enhance your business operations. Ready to elevate your customer service with AI? Try our Echoes extension today! 👉 Download Echoes here: https://echoes.r2bits.com/ #ClaudeAI #Anthropic #AI #TechInnovation #Echoes #CustomerService #GenerativeAI

Inflection AI unveils Inflection-2.5, rivaling GPT-4 and Gemini. #AIinnovation 🤝 Follow us on Discord 🔜: https://lnkd.in/gt823Zd3 🤝 Follow us on Whatsapp 🔜 https://wapia.in/wabeta _ ❇️ Summary: Inflection AI introduces Inflection-2.5, a highly efficient large language model (LLM) that aims to match the performance of leading LLMs like GPT-4 while using only 40% of the computational resources. This advancement makes Inflection-2.5 accessible for various applications, including personal AI assistants like Pi. The model's efficiency and performance are achieved through advanced algorithms, optimizations in model architecture, and real-time web search capabilities. Inflection-2.5 has been validated through industry benchmarks and has shown significant impact on user sentiment, engagement, and retention, driving organic user growth. Hashtags: #chatGPT #InflectionAI #AIupgrade

{ST-LLM: An Effective Video-LLM Baseline with Spatial-Temporal Sequence Modeling Inside LLM https://lnkd.in/dvrYpZNV The Impact of ST-LLM in Video Understanding Introduction Artificial intelligence has made significant progress in Large Language Models (LLMs) like GPT, PaLM, and LLaMA, showing their potential for understanding and generating natural language. However, applying these capabilities to videos with rich temporal information has been a challenge. The Challenge Current methods for video understanding in LLMs have limitations, such as difficulty in capturing dynamic temporal sequences and requiring extensive computational resources. The Solution: ST-LLM A team of researchers from Peking University and Tencent proposed ST-LLM, which uses LLMs to process raw spatial-temporal video tokens directly. This approach addresses the limitations of existing methods and enhances the model’s ability to handle varying video lengths during inference. Key Features of ST-LLM – ST-LLM feeds all video frames into the LLM, effectively modeling spatial-temporal sequences. – It introduces a dynamic video token masking strategy and masked video modeling during training. – For long videos, it employs a unique global-local input mechanism, preserving the modeling of video tokens within the LLM. Effectiveness of ST-LLM Extensive experiments have shown the remarkable effectiveness of ST-LLM, demonstrating superior temporal understanding and state-of-the-art performance in various video benchmarks. Practical AI Solutions To advance your company with AI, consider using ST-LLM for video understanding. Additionally, explore practical AI solutions like the AI Sales Bot from itinai.com/aisalesbot, designed to automate customer engagement and manage interactions across all customer journey stages. For more information and insights into leveraging AI, connect with us at hello@itinai.com or stay tuned on our Telegram t.me/itinainews or Twitter @itinaicom. List of Useful Links: AI Lab in Telegram @aiscrumbot – free consultation ST-LLM: An Effective Video-LLM Baseline with Spatial-Temporal Sequence Modeling Inside LLM MarkTechPost Twitter – @itinaicom #ai #ainews #llm #ml #startup #innovation #itinai #uxproduct

🚀 The AI revolution is rewriting the internet! 🌐 Major players like Microsoft with Copilot, Google with Gemini, and OpenAI with GPT-4 are bringing advanced AI chatbot technology from test labs to the public. Here's how it's changing the game: 🔍 How LLMs Work: - Large Language Models (LLMs) like GPT-3 operate as sophisticated autocomplete systems. - They analyze statistical properties of language to predict word sequences. - While they generate coherent text, they can sometimes present plausible but false information due to the lack of a hard-coded fact database. 🌟 Impact and Evolution: - AI chatbot technology is now more accessible than ever. - Tools like Bing and Bard have rebranded, highlighting the fast-paced evolution in the AI landscape. 🌐 The Future: AI is revolutionizing our interactions with technology, blending innovation with daily applications. As the landscape unfolds, it's crucial to understand both the capabilities and limitations of these powerful tools. Stay tuned for more insights and transformations in the world of AI! https://lnkd.in/dw2wEvdj #AI #DigitalTransformation #Innovation #FutureOfWork #Technology

Ever wondered how AI models handle long pieces of text? It’s all about context size! 📜 #SimplifyingLLMs #Post5 Context size is a crucial aspect of how Large Language Models (LLMs) process and generate text. It determines how much text the model can consider at once, which impacts its ability to understand and generate coherent, contextually accurate responses. Context size refers to the amount of text an LLM can take into account when making predictions. A larger context size allows the model to understand and retain more information, leading to more accurate and relevant outputs. Context Size: Context size, often measured in tokens, is the window of text the model uses to generate predictions. For example, if an LLM has a context size of 1,024 tokens, it can consider up to 1,024 words (or word pieces) at a time. Larger context sizes enable the model to handle longer and more complex texts more effectively. Why It Matters: A larger context size allows the model to better understand the nuances and dependencies within a text. For instance, in a long document, understanding references made several paragraphs apart requires a large context size. This is particularly important in applications like document summarization, legal text analysis, and generating coherent long-form content. Technical Insight: Technological advancements have allowed newer models to increase their context sizes significantly. For instance, early models might handle a few hundred tokens, while modern LLMs can manage thousands up to a million tokens and more. This expansion is made possible by improvements in computational power and model architectures. Real-Life Application: Consider a customer service AI that needs to understand an entire email thread to provide a meaningful response. With a larger context size, the AI can process the entire conversation, resulting in more accurate and contextually appropriate replies. #AI #MachineLearning #LLMs #ContextSize #SimplifyingLLMs

Hello Connections! 🌐 Introducing the Future of Voice Interaction: Voice Assistant Powered by OpenAI GPT-3  and IBM Watson 🎙️ In the realm of conversational AI, I'm thrilled to unveil my latest project – A Voice Assistant enriched with the groundbreaking capabilities of OpenAI's GPT-3. This endeavor marks a significant leap forward in redefining user interactions, offering a level of sophistication and natural language understanding that transforms the way we engage with technology. 🚀 🔍 Key Features: Conversational Brilliance ,Speech-to-Text Excellence, Customizable Commands 🚀 Pushing the Boundaries of Interaction: This project represents a culmination of my passion for AI, voice technology, and pushing the boundaries of what's possible. The intersection of OpenAI's GPT-3 and voice interfaces opens up exciting possibilities for creating truly intelligent and responsive systems. It's not just about following commands; it's about having meaningful, dynamic conversations with technology. 🌱 The Future of AI Collaboration: I invite fellow enthusiasts, developers, and AI aficionados to explore the project on GitHub. Your insights, suggestions, and contributions can help shape the future of this Voice Assistant, making it even more intuitive, adaptive, and powerful. GitHub Repository Link: https://lnkd.in/gVmnpYBj Let's embark on this journey together, where technology meets conversation in a symphony of innovation. Join the conversation, share your thoughts, and let's shape the future of AI-driven voice interactions! 🗣️✨ #AI #VoiceAssistant #GPT3 #ConversationalAI #TechInnovation #OpenAI #IBMSkillsNetwork #cognitiveclass

Integrating AI profitably into business workflow processes has a very high hit and miss rate. This is largely dependent upon the user's ability to effectively compose prompts. AI marketing assures us that we can use natural language to query AI models, but there are limitations and issues. Natural language, as spoken by many real user’s, can be vague and heavily nuanced. This leads to poor AI responses and the user may spend more time prompting the AI model than they would have spent just creating the content themselves. The truth is that to get the best results from our AI models we need to structure our use of language to help our AI models deliver high value responses. Over the past few months, this has led to the emergence of prompt engineering – a way of structuring our use of language to get better responses from AI. At GreatIdeaz, we have been looking into how to successfully integrate AI technology into customer workflow to consistently deliver high value responses. Our research team has collated some of the best articles and thoughts on prompt engineering into this blog: https://lnkd.in/gKz9DhXm #AI #PromptEngingeering #greatideaz #trellispark

Exciting news from Anthropic! The new Claude 3 AI models are here to outperform GPT-4 and Gemini 1.0 Ultra! 💡📈 #AI #Innovation #TechTrends 🔹 Enhanced accuracy and recall: Over 99% accuracy in complex scenarios 🔹 Large context window: Supports up to 1 million tokens for deep analysis 🔹 Vision capabilities: Processes photos, diagrams, and technical drawings 🔹 Cost-effective: Affordable options for different needs --- 📊 Benchmark highlights: 🔹 MMLU: 86.8% vs. GPT-4's 86.4% 🔹 HumanEval: 84.9% vs. GPT-4's 67% 🔹 HellaSwag: 95.4% vs. GPT-4's 95.3% 🔹 Enhanced coding and language capabilities for diverse applications 💼 Tailored for enterprises with advanced analysis, content creation, and forecasting needs https://lnkd.in/gbHXsp4p

👀 𝐘𝐞𝐬𝐭𝐞𝐫𝐝𝐚𝐲 𝐰𝐚𝐬 𝐭𝐡𝐞 𝐎𝐩𝐞𝐧𝐀𝐈 𝐃𝐞𝐯𝐞𝐥𝐨𝐩𝐞𝐫 𝐃𝐚𝐲   🆕 𝐓𝐡𝐞𝐬𝐞 𝐚𝐫𝐞 𝐭𝐡𝐞 𝐊𝐞𝐲 𝐓𝐚𝐤𝐞𝐚𝐰𝐚𝐲𝐬 𝐟𝐫𝐨𝐦 𝐭𝐡𝐞 𝐞𝐯𝐞𝐧𝐭:     ✅ GPT-4 Turbo Unleashed: Experience a massive leap in AI with the capability to process contexts as extensive as entire books, thanks to a quadrupled context limit. ✅ Precision Perfected: OpenAI's RAG system accuracy has soared from 45% to an astonishing 98%, showcasing a significant enhancement in AI reliability. ✅ Custom GPT Agents: Now you can craft and customize your own GPT-powered agents using straightforward natural language. ✅ AI Marketplace: Get ready for the upcoming GPT store – an innovative marketplace akin to the App Store for AI, enabling revenue sharing for creators. ✅ New API Capabilities: Explore the horizons with DALL·E 3 for generating images, improved Text-to-Speech functions, and Whisper V3 for superior speech recognition.    These advancements are not just technological leaps; they are the keys to unlocking unprecedented potential in your business.    At WeConnectAI, we specialize in integrating these cutting-edge innovations seamlessly into your operational workflow.  Want to dive deeper into these updates and discover how they can transform your daily tasks? Reach out to us and let's explore the future of AI together.    #OpenAI #AI #TechUpdate #WeConnectAI    Philipp Seiter  Marco Zöller  Tobias Hetfleisch