Indy Nagpal’s Post

🌟 Attended the Kong Developer Day: AI + APIs webinar on June 13, 2024! 🌟 In this era of generative AI and large language models, it's crucial to establish robust practices for leveraging AI capabilities responsibly and at scale. The AI Gateway pattern is a critical solution for this, and today's webinar was packed with valuable insights and practical strategies. Here's a quick recap of the sessions: 1️⃣ What is an AI Gateway? by Marco Palladino, CTO & Co-Founder of Kong Introduction to the AI Gateway pattern for managing and controlling AI models, applications, and services. Engaging fireside chat covering challenges, best practices for AI governance, risk management, and future trends. 2️⃣ Down the AI Rabbit Hole: Leveraging AI in Your Projects Without Ending Up Lost in Wonderland by Shane Utt, Staff Software Engineer at Kong Exploring the complexities and uncertainties of the AI/ML landscape. Practical strategies for experimenting with AI and transitioning from experimental to production phases. Emphasizing the importance of API management in delivering AI features and projects. 3️⃣ AI Gateway Demo by Jack Tysoe, Field Engineer at Kong Live demonstration of the AI Gateway in action. The webinar highlighted the transformative power of generative AI while emphasizing the need for governance and responsible adoption. As someone deeply interested in AI and APIs, I found the discussions incredibly insightful and inspiring. Kudos to the Kong team for organizing such an informative event! 🎉 Marco Palladino Jack T. #KongDeveloperDay #AI #APIs #GenerativeAI #AIGateway #TechInnovation #AIgovernance

#GenerativeAI and #LLMs (large language models) can help biotechs move faster, smarter, and more efficient. To get real ROI with this new tech, biotechs need a built-for-science approach. That’s why Benchling created a guide for how, where, and when to deploy LLMs throughout the R&D lifecycle. https://lnkd.in/dkdGukXb

Discover the cutting-edge world of Retrieval Augmented Generation (RAG), revolutionizing AI language models. 🔍 By integrating knowledge sources, RAG empowers models to retrieve info and generate contextually precise responses. Learn more about this technique, its benefits, and how Prism’s platform simplifies advanced AI software development. 🌐 RAG's Key Benefits: Customization: Easily tailor language models for specific needs. Enhanced Context: Access a wealth of information for more accurate responses. 🚀 Prism's Alpha Release: A Game Changer! Enterprise-Grade API: It has truly never been easier to integrate RAG into your application. Whether you want to build a chatbot for a website, an internal search engine, or just want to make more powerful models, Prism has what you need! 🔗 Join Prism’s Alpha Release! Embark on a transformative journey in AI innovation. Sign up today to experience the simplicity and power of building advanced AI software with Prism, offering an enterprise-grade API and user-friendly tools. 🚀✨ #AI #Innovation #RAG #PrismAlphaRelease https://lnkd.in/g4Fy3bQ8

🚀 The Future of AI is Open, and It's Here! 🌐 In a world where AI's potential seems boundless, the conversation around open-source language models is more relevant than ever. A recent article on HackerNoon delves into why the future of AI might just be rooted in open-source initiatives. Here's a glimpse into what it covers, and how we at GAI are aligning with this future: - The Shift to Open-Source: Unlike the proprietary models that dominate today's landscape, the future of AI is envisioned to be built openly, alongside vibrant communities. This shift promises a more inclusive and innovative approach to AI development. - H2O-Danube-1.8B: A shining example of this open-source future is the H2O-Danube-1.8B model. With 1.8 billion parameters, it showcases remarkable capabilities and is freely available for experimentation. This model represents a step towards democratizing AI, making powerful tools accessible to all. - Beyond Danube: The ecosystem of open-source AI is rapidly expanding. From Falcon's 180-billion parameter model to Mistral's competitive 7B model, the landscape is rich with initiatives aiming to break down the walls around AI knowledge. - Why It Matters: Open-source models are not just about accessibility; they're about creating a more equitable future. They allow for collaboration across borders, enabling developers to tailor AI tools to specific needs, from healthcare to finance. At GAI, we're excited about this open future. Our workshops are designed to empower you with the skills needed to navigate this landscape. The future of AI is open, and it's a journey we're excited to embark on together. Dive into the full article to explore the possibilities: https://smpl.is/8ml68 #AI #OpenSourceAI #Innovation #GAIWorkshops #futureofAI #openfuture #opensourceinitiatives #democratizingAI #collaborationiskey

The Journey to GPT-5: Expectations and Speculations What can we truly expect from GPT-5? The development team has been cautiously optimistic, hinting at a "significant leap forward" compared to its predecessors. Yet, the road to GPT-5 is fraught with challenges. The current iterations, like GPT-4, still stumble in areas like complex reasoning and often make glaring errors that even a child wouldn’t. This suggests that while we can expect improvements, perfecting these aspects will require substantial innovation and rigorous testing. Is GPT-5 aiming to bridge these gaps? Or is there a more radical transformation in store? Exploring further, one wonders about the nature of these improvements. Comments indicate that enhanced capabilities in reasoning and natural interaction might be key focus areas. The advent of new voice and video modes in GPT-4o hints at a trend toward more multimodal AI, which could become more pronounced in GPT-5. Are we looking at a model that not only processes text with greater nuance but also integrates seamlessly with audio and visual inputs? This multi-sensory approach could revolutionize user interaction, making AI feel even more intuitive and lifelike. But how feasible is this leap within the current technological constraints? Finally, the question of timeline and readiness looms large. It has been made clear that there is "still a lot of work to be done." This implies that while the vision for GPT-5 is ambitious, its execution is still in its nascent stages. The scale and complexity of developing such a model are enormous, and the path is fraught with algorithmic and data challenges. Can the development team meet these challenges head-on and deliver GPT-5 in the near future? Or will the development stretch further, as the team works meticulously to refine every aspect? The anticipation builds, but so does the uncertainty surround the specifics of GPT-5's capabilities and release. #GPT5 #AI #ArtificialIntelligence #TechInnovation #FutureOfAI #OpenAI #MachineLearning #AIAdvancements #TechTrends #AIRevolution #NextGenAI #AIFuture #InnovativeAI #SmartTech #AIUpdates

📢 The highlight of 2024 is Small Language Models(SLMs).💥 📍While Large Language Models (LLMs) are powerful, they come with big challenges - high compute needs, costly inference, slower response times, and more. 📍Enter Small Language Models (SLMs)! These compact AI models can be fine-tuned for specific tasks, delivering high quality at low costs. 📍SLMs won't replace LLMs, but will offer a flexible portfolio approach. Companies can pick the right model for their use case - go big with an LLM, or opt for a nimble, cost-effective SLM. 📍Companies like Google, Microsoft, Meta, and more rigorously launching open-source SLMs like #gemma, #phi3, #llama3, #mixtral, and more. 📍2024 could see a rise of these "little language models that could" - transforming how we build and deploy AI solutions across industries. An exciting era of model diversity awaits! Will SLMs rewrite the AI playbook? Let me know your thoughts in the comments!!

🚀 2024 is already shaping up to be a monumental year for Large Language Models (LLMs)! Late last year, MIT made waves with a solution to process ultra-long text inputs (over 4 million tokens) at 22.2x the previous speed. Now, the Colossal-AI team has taken it a step further, achieving a 46% boost in speed with their reimplementation of the algorithm! This is a giant leap forward for LLMs, removing a major bottleneck to processing vast amounts of data And guess what? Wow AI is right there fueling this progress! With our massive pool of ready-to-use data in over 120 languages, backed by 100,000+ contributors worldwide, and customizable options to fit your specific needs, Wow AI empowers you to develop cutting-edge AI products. Contact us now! -------------------------- 𝐖𝐎𝐖 𝐀𝐈 - 𝘌𝘮𝘱𝘰𝘸𝘦𝘳𝘪𝘯𝘨 𝘎𝘭𝘰𝘣𝘢𝘭 𝘚𝘶𝘤𝘤𝘦𝘴𝘴: 𝘠𝘰𝘶𝘳 𝘌𝘯𝘥-𝘵𝘰-𝘌𝘯𝘥 𝘈𝘐 𝘛𝘳𝘢𝘪𝘯𝘪𝘯𝘨 𝘗𝘢𝘳𝘵𝘯𝘦𝘳 🌎 Website: https://wow-ai.com/ 📩 Email: contact@wow-ai.com 🔔 Discord: https://lnkd.in/ghcYNBYW 📮 200 Continental Dr Suite 401, Newark, DE 19713, US #WowAI #DataCollection #AItraining #MachineLearningModels #OTSData #Datatraining #AIModels #AIData #high-qualitydata #Ethical

The rapid evolution of Large Language Models (LLMs) has greatly transformed the technological landscape, disrupting the norms of how we interact with AI. It is evident these models have advanced from mere novelty and are actively being integrated into practical applications to tackle real business problems. Yet, the lack of clear guidance on effective implementation of LLMs poses challenges. Organizations continue to struggle with deploying these models and optimizing their resources for the best outcomes. To access the full potential of LLMs for enterprise use, careful consideration and the right approach are key. LLMs offer many benefits, but their integration into enterprise workflows requires a strategic approach. 🚀 Join our exciting panel discussion with industry tech experts to gain unique perspectives on successfully implementing LLMs into your business! 🔑 Key discussion points: - Enterprise LLM adoption and benefits - Using existing models vs. prompt engineering vs. fine-tuning - Fine-Tuning LLMs on custom datasets - Tools and platforms to facilitate LLM implementation - Addressing the challenges associated with adopting LLMs - Exploring emerging trends, advancements, etc. 🗓️ Tue, Aug 22 at 11 AM PST 📍 Virtual RSVP for free below! Animesh Singh Harrison Chase Ketan U. Nalin Dadhich Stefan Lindall #LLMs #LargeLanguageModels #Panel #ML #AI #Data

Janakiram MSV interviewed our Co-Founder & Co-CEO Ori Goshen for Forbes about AI21 Labs' strategic shift towards building smaller, more specialized Task-Specific Models that solve specific business challenges for the enterprise. "As someone who closely tracks the emerging technology space, I found [this shift] particularly compelling. The advantages of this strategy are manifold. Specialized models are not only more accurate but also offer benefits in terms of cost, speed and ease of integration. This marks a significant evolution in AI development, emphasizing efficiency and purpose-built solutions over the pursuit of larger, more complex models."

Look who popped up on my YouTube feed, being interviewed by Bloomberg's tech duo of Caroline Hyde and Edward Ludlow. "There are 1500 LLMs, and they can the MCAT and the LSAT. If LLMs were the answer, everyone would have the generative AI program of their dreams, but that's not the case." May Habib shared the the following key insights in her interview: - Writer has been successful in building a differentiated platform that helps enterprises with the last mile, which is 90% of the work. - The rate of change in the AI industry has been incredible, with hundreds of enterprise customers, hundreds of thousands of users, and thousands of applications in production. - Writer has introduced vision as a capability into the platform and launched a translation feature, supporting 32 languages. - Large language models (LLMs) need more context about the business to be able to do what customers need them to do. - There's a lot of opportunity for startups in the AI industry despite the dominance of big tech companies. - Writer has made a small acquisition, which will be announced in the future Key quotes - "The way we stand out, I think, is with a really differentiated platform that helps enterprises with the last mile, which is 90% of the work." - "We now say if you can write it, you can build it, because AI is not just the technology, it's the way to build new technology." - "There's so much work to get the data and the context and the workflow from the business user into the application, and that is what our platform does." - "We have made a small acquisition that we'll announce soon and I think we'll make others." ...and if you had not guessed already, 90% of the above summary and quotes above were generated in 5 seconds using Writer's "Recap App", all I had to do was provide it with the link to the YouTube clip. Check out the full interview below. https://lnkd.in/egTB8dbM #LLMs #AI #SanFrancisco #Bloomberg #LargeReasoningModels