Pinecone’s Post

Really looking forward to this webinar. Jacky is going to show how he built a multi-modal search and recommendation sample app. If anyone wants more detail about this sample app, let me know!

🔥 my webinar on multimodal search will be happening in under 2 hrs come learn about the future of searching through multiple modalities! cc: Holt S. Paige Bailey Google Cloud

I reversed engineer the AI Agents Workflow, and created a Super Simpler Open Source AI Agent Framework for anyone to play and learn with! BOOKMARK FOR LATER! You can create AI Agents in 3 lines of code Here is the GitHub Repo: https://lnkd.in/e4V_WbK3

Will streaming revolutionise LLMs as it did with digital video? and what about applying streaming to both in synch perhaps using Mpeg interleaving for agents? We would end up having a live understanding and generation of video channels vs batch processing and insights generation... thanks Lior S. for sharing.

This is the future of LLMs. A new technique named "StreamingLLM" can handle infinite text input without any drop in accuracy. It works finding key tokens that guide the model's decisions and caching recent tokens. The result: It delivers up to 22x faster inference than vanilla LLMs. Link in comments. ♻️ Repost this if you found it useful. ↓ Are you technical? Check out https://AlphaSignal.ai to get a daily summary of breakthrough models, repos and papers in AI. Read by 200,000+ devs.

This week, I stumbled upon an exciting breakthrough in the field of Large Language Models (LLMs) called StreamingLLM. This innovative approach allows models to handle infinite text input without compromising accuracy, marking a significant advancement in how we utilize LLMs. 𝗞𝗲𝘆 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀 𝗼𝗳 𝗦𝘁𝗿𝗲𝗮𝗺𝗶𝗻𝗴𝗟𝗟𝗠 -  𝟭. 𝘼𝙩𝙩𝙚𝙣𝙩𝙞𝙤𝙣 𝙎𝙞𝙣𝙠𝙨: StreamingLLM identifies key tokens, referred to as "attention sinks," which guide the model's decisions. This mechanism allows the model to retain critical information over long sequences, enhancing its performance. 𝟮. 𝘾𝙖𝙘𝙝𝙞𝙣𝙜 𝙍𝙚𝙘𝙚𝙣𝙩 𝙏𝙤𝙠𝙚𝙣𝙨: By caching recent tokens, StreamingLLM efficiently manages memory and processing requirements, enabling it to model texts of up to 4 million tokens. 𝟯. 𝙎𝙥𝙚𝙚𝙙 𝘽𝙤𝙤𝙨𝙩: The results are remarkable, with StreamingLLM achieving inference speeds up to 22 times faster than traditional LLMs, making it a game-changer for applications requiring real-time processing. 𝗥𝗲𝗰𝗲𝗻𝘁 𝗘𝘅𝗰𝗶𝘁𝗶𝗻𝗴 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁𝘀 In addition to the StreamingLLM announcement, several other noteworthy advancements have emerged this week: 𝟭. 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝗠𝗮𝗷𝗼𝗿 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺𝘀: StreamingLLM has been integrated into various platforms, including NVIDIA TensorRT-LLM and HuggingFace Transformers, which enhances its accessibility and usability for developers. 𝟮. 𝗡𝗲𝘄 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 𝗼𝗻 𝗔𝗜 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀: Recent studies have shown that AI systems are being developed to create simulations using video and photos, which can train robots to function effectively in real-world environments. This could lead to significant improvements in robotics and automation. 𝟯. 𝗔𝗜 𝗶𝗻 𝗛𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲: There's a growing trend of using AI and LLMs to personalize patient care and improve medical research outcomes. Innovations in AI are transforming healthcare delivery, making it more efficient and tailored to individual needs. 𝟰. 𝗘𝘁𝗵𝗶𝗰𝗮𝗹 𝗔𝗜 𝗙𝗼𝗰𝘂𝘀: A notable shift towards creating unbiased and ethically aligned AI systems is gaining traction, ensuring responsible technology use across various sectors. These developments highlight the rapid evolution of AI technologies and their transformative impact across industries. ♻️ Feel free to repost this if you found it useful! #repost #viral #explorepage #likes #share #AI #LLM #GenAI #ML #News

Impressive. Alternative to #groq possibly. I wonder if this supports ports multimodal inputs? If so, I wonder if this is how #openai is performing advance voice mode and possiblynthe upcoming screen sharing feature?

Breakthrough in AI: Infinite Text Processing 🚀 StreamingLLM is revolutionizing how language models handle text input. This innovative technique: • Processes unlimited text without accuracy loss • Identifies crucial decision-guiding tokens • Caches recent information efficiently • Achieves up to 22x faster inference than traditional LLMs This advancement opens doors for real-time language processing in unprecedented ways. Imagine chatbots that never lose context or AI assistants that can analyze entire books instantly. What applications do you envision for this technology? Share your ideas below! 👇 #genAI #MachineLearning #FutureOfTech

There's a new model going viral on Github. It allows you to generate a live-stream deepfake from a SINGLE image. It's incredible. You just have to: 1. Select a face 2. Click live 3. Wait for a few seconds https://lnkd.in/gyRDE-dV ↓ Are you technical? Check out https://AlphaSignal.ai to get a daily summary of breakthrough models, repos and papers in AI. Read by 200,000+ devs.

"Gluing together some LLMs, APIs, and a database has saved GTM teams around 2k hours so far" That's exactly why I am building https://aicamp.so End goal is to serve world's all LLMs at your fingertips and then bring all your API connections to talk internally.