Rakuten’s Post

🚀 Excited to share a new milestone in my AI journey! I've successfully deployed the Llama 2 model locally on my system with just 8 GB RAM core-i5! 💻✨ Using the powerful Langchain framework for seamless model integration and Streamlit for an interactive UI, I've created a robust and efficient setup. This showcases the potential of running sophisticated AI models on modest hardware, opening up new avenues for innovation and experimentation. If you're interested in AI, ML, or local model deployment, let's connect and discuss! 🌐 #AI #MachineLearning #Langchain #Streamlit #LocalDeployment #TechInnovation #SanwalKhan

As the AI landscape rapidly evolves, it’s fascinating to see how emerging players are challenging established giants. The competitive pricing and performance of DeepSeek and 01.AI indicate a shift towards more accessible and efficient AI solutions. This could democratize AI technology further, allowing smaller companies to leverage powerful models without prohibitive costs. Recent Updates (Week of August 12-18, 2024): 1. #DeepSeek's New Model Release: This week, DeepSeek announced the launch of its latest model, which reportedly surpasses previous benchmarks set by both Mistral and Meta. This model is expected to further disrupt the pricing strategies in the market. 2. #ClaudeOpus3.5 Announcement: Claude has confirmed that its Opus 3.5 model will be available in the next couple of months, promising enhancements that could make it a formidable contender against both Mistral and DeepSeek. 3. #Mistral's Strategic Developments: Mistral is reportedly working on a new model that aims to leverage unique architectures to improve efficiency and performance, although specific details remain under wraps.

Building AI agents used to be 𝐜𝐨𝐦𝐩𝐥𝐞𝐱 𝐚𝐧𝐝 𝐝𝐞𝐦𝐚𝐧𝐝𝐞𝐝 𝐡𝐮𝐠𝐞 𝐫𝐞𝐬𝐨𝐮𝐫𝐜𝐞𝐬. You were expected to: • 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐞 𝐦𝐮𝐥𝐭𝐢𝐩𝐥𝐞 𝐭𝐞𝐜𝐡𝐧𝐨𝐥𝐨𝐠𝐢𝐞𝐬 like speech recognition, natural language processing, and text-to-speech. • 𝐌𝐚𝐧𝐚𝐠𝐞 𝐞𝐱𝐭𝐞𝐧𝐬𝐢𝐯𝐞 𝐢𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 to support real-time interactions and scalability. • 𝐈𝐧𝐯𝐞𝐬𝐭 𝐬𝐢𝐠𝐧𝐢𝐟𝐢𝐜𝐚𝐧𝐭 𝐭𝐢𝐦𝐞 𝐚𝐧𝐝 𝐦𝐨𝐧𝐞𝐲 in development and maintenance. But now, it’s (actually) really simple with 𝐄𝐥𝐞𝐯𝐞𝐧𝐋𝐚𝐛𝐬: • Create complete conversational AI agents in minutes using 𝐜𝐮𝐬𝐭𝐨𝐦𝐢𝐳𝐚𝐛𝐥𝐞 𝐭𝐞𝐦𝐩𝐥𝐚𝐭𝐞𝐬. • Enjoy 𝐥𝐨𝐰 𝐥𝐚𝐭𝐞𝐧𝐜𝐲 𝐚𝐧𝐝 𝐟𝐮𝐥𝐥 𝐜𝐨𝐧𝐟𝐢𝐠𝐮𝐫𝐚𝐛𝐢𝐥𝐢𝐭𝐲 without heavy infrastructure • Access powerful features, including:🗣️𝐕𝐨𝐢𝐜𝐞 𝐜𝐥𝐨𝐧𝐢𝐧𝐠 with instant and professional options.🧠 Integration of 𝐜𝐮𝐬𝐭𝐨𝐦 𝐤𝐧𝐨𝐰𝐥𝐞𝐝𝐠𝐞 𝐛𝐚𝐬𝐞𝐬. 🔄 𝐂𝐨𝐦𝐩𝐚𝐭𝐢𝐛𝐢𝐥𝐢𝐭𝐲 with multiple LLMs (𝐆𝐞𝐦𝐢𝐧𝐢, 𝐆𝐏𝐓, 𝐂𝐥𝐚𝐮𝐝𝐞). Revolutionizing how we interact with technology isn’t a challenge anymore—it’s your chance to: 𝐈𝐧𝐧𝐨𝐯𝐚𝐭𝐞, 𝐂𝐫𝐞𝐚𝐭𝐞 𝐚𝐧𝐝 𝐈𝐧𝐬𝐩𝐢𝐫𝐞. 👇 #AI #ConversationalAI #ElevenLabs

Live from Jam AI Night: Janak Agrawal is showing us how to build AI apps with Adapt. You can chain multimodal models together, fine tune it and scale it on their infra w/ observability built in 🔥so cool!

Portkey is now a first class provider in the Vercel AI SDK. When should you use Portkey's AI gateway with the AI SDK? 1. You're routing requests to multiple models & providers. 2. You're going to production and need metrics on cost, performance and accuracy 3. You want to build & manage on-line guardrails without adding latency 4. You have multiple teams building with AI and need to manage usage and budgets.

We did some tests on Rakuten AI 7B. Click on the link to view the video! 🔬 💻 ➡️ https://lnkd.in/gxfR-hfg #RakutenAI7B #LLM #AI #GenerativeAI

PaliGemma, Google's latest vision language model (VLM), is a game-changer in the world of AI. Developed alongside other cutting-edge products at the 2024 Google I/O event, it boasts multimodal capabilities that outshine its predecessors. Unlike other VLMs like GPT-4o and Google Gemini, PaliGemma stands out with its robust object detection and segmentation abilities, thanks to its fusion of SigLIP and Gemma models. With 3 billion parameters, PaliGemma offers commercial usability and comes pre-trained on diverse datasets like WebLI and OpenImages. What sets PaliGemma apart is its flexibility. It's not just a ready-made solution; rather, it's a platform for customization. Through fine-tuning, users can tailor PaliGemma for specific tasks like image and video captioning, visual question answering, object detection, and segmentation. This adaptability opens up a world of possibilities, allowing for innovative applications in various domains. While benchmarking provides insights into its capabilities, the true potential of PaliGemma lies in its versatility through fine-tuning. Google's decision to release an open multimodal model with this level of customization is a significant breakthrough for AI. It empowers users to create bespoke models that cater to their unique needs, whether it's in the cloud or on edge devices like NVIDIA Jetsons. In essence, PaliGemma represents a new frontier in AI, where flexibility and performance converge to drive innovation. It's not just about what the model can do out of the box; it's about unlocking its full potential through fine-tuning, making it a powerful tool for tackling real-world challenges. Reference: https://lnkd.in/g2iHvb63

#Topics Llama 3.1 on Vertex AI [ad_1] Today, we’re excited to announce the addition of the Llama 3.1 family of models, including a new 405B model – Meta's most powerful and versatile model to date — to Vertex AI Model Garden. These additions continue Google Cloud’s commitment to open and flexible AI ecosystems that help you build solutions best-suited to your needs.  Vertex AI provides a curated collection of first-party, open-source, and third-party models, many of which — including the new Llama models — can be delivered as fully-managed Model-as-a-service (MaaS) offerings. With MaaS, you can choose the foundation model that fits your requirements, access it simply via an API, tailor it with robust development tools, and deploy on our fully-managed infrastructure — all with the simplicity of a single bill and hassle-free infrastructure. Meta's Llama 3.1 represents a paradigm shift in open-weight models, boasting unparalleled performance and versatility in its class. This release features a family of models tailored for diverse applications: Llama 3.1 405B: The largest openly available foundation model to date, Llama 3.1 405B sets a new standard among open models for flexibility, control, and innovation. This model opens an array of new possibilities, from generating...

I saw the LinkedIn post below from Gradio and followed the link to the webpage, as an experiment I then used LlamaIndex to parse the blog post and return the content of the blog post as markdown, then I pushed the markdow into ChatGPT and asked it to write a LinkedIn post about the announcement, all that took more or less 5 minutes because I was doing it adhoc, I wanted to see how fast it would be. Interesting points of note, LlamaIndex correctly identified the tables in the blog post and rendered them as tables in the final markdown file, not to mention it picked up on the the parts of text that were written in Korean. For those that want to try out the LG models you can find them here on the LG AI Research on HuggingFace 🤗 . The 2.4B ultra lightweight model is interesting, built for on device use, could we be seeing a an LG phone on the market soon that comes preloaded? https://lnkd.in/gqj-SHH7 Everything below was written using ChatGPT ..... 🚀 Exciting News in AI Innovation! 🎉 LG AI Research has officially open-sourced EXAONE 3.5, unveiling three cutting-edge models that redefine AI performance: 2.4B Model: Perfect for on-device and low-infrastructure use. 7.8B Model: Versatile and lightweight with superior performance. 32B Model: Frontier-level model for those demanding top-tier AI. 💡 What Makes EXAONE 3.5 Stand Out? 1️⃣ Unmatched Long Context Understanding: Handles up to 32K tokens effectively, excelling in real-world applications. 2️⃣ Top Instruction Following Capabilities: Dominates global benchmarks in multiple languages, enhancing productivity. 3️⃣ Competitive in General Domains: Achieves state-of-the-art results in mathematical and coding benchmarks. 🛠️ Training Efficiency & Ethics: The models were crafted with a focus on affordability, ethical AI practices, and meticulous decontamination processes to ensure high-quality outputs. Transparency in ethical assessments ensures responsible AI deployment. 🌐 These open-source models are ready to accelerate AI research and innovation, inviting feedback from researchers worldwide. Let’s shape the future of AI together! 🔗 Try EXAONE 3.5 Models Now! 🔗 Read the Full Technical Report #AI #OpenSource #EXAONE3_5 #Innovation

A very informative blog post by Chip Huyen on "Building A Generative AI Platform". It clearly explains how to start simple and then gradually add complexity to the GenAI system or platform that one is building. The building blocks are 🔸Start with a simple LLM call 🔸Enhance the context for LLM models using additional information like RAG 🔸Implement guardrails for both input and output to reduce AI risks 🔸Add model router and gateway to enable experimentation with different models and better model management 🔸Reduce latency with caching and also save costs 🔸Add complex logic and write actions 🔸Bonus - Observability and Orchestration Blog: https://lnkd.in/gdeJ898Z #GenAI