https://lnkd.in/gWNNkjpa Want a crash-course on the technical capabilities Large Language Models when looking at using them at full-scale? This is a great overview from Ben Lorica 罗瑞卡 from Neo4j's conference this week.
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Yesterday, I fine-tuned a microsoft/Phi-3.5-mini-instruct model using Unsloth AI. Initially, I faced some slow inference times in Colab, but I switched to a Runpod + TGI setup, which made a world of difference! With this new configuration, I successfully processed 100,000 samples in just 50 minutes, all for under $0.50. This setup proves to be incredibly effective for large-scale inference tasks. I've created a detailed step-by-step tutorial for anyone interested in replicating this process. Thank you to the RunPod and Hugging Face teams for building fantastic products that enable efficient and scalable solutions! #MachineLearning #Inference #Runpod #TGI #Unsloth #AI #DataScience
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Vice President of Marketing at U.S. Legal Support | B2B | Marketing Strategy | Branding | Digital Marketing | Content | Demand Generation ⭐️
This is a great resource for legal professionals looking to dive into the world of Generative AI and Large Language Models. Download a copy today to: 🔎 Uncover the fundamental concepts of GenAI and LLMs, including how these cutting-edge technologies work 🔒 Secure your workflow with expert insights on data protection and preventing AI hallucinations ⚙ Explore practical uses of GenAI for legal professionals, including optimized document review, comprehensive analysis, and transcript summarization ➡ Download a copy now! https://lnkd.in/gW897GGj
🌟 Introducing our latest white paper, GenAI for Smart Legal Professionals! 🌟 Co-authored by John Tredennick and Dr. William Webber of Merlin Search Technologies, it's your essential guide to harnessing AI’s power to transform your discovery workflows and enhance efficiency. 🧠 Understand Generative AI and Large Language Models (LLMs) 🔎 Discover how these groundbreaking technologies operate and grasp essential concepts 🔒 Gain peace of mind with insights on data security and the mitigation of AI hallucinations ⚙ Learn real-world applications of GenAI for legal professionals, from streamlining document review and in-depth analysis to efficient transcript summarization ➡ Download a copy now! https://lnkd.in/gW897GGj
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Just finished the course “RAG and Fine-Tuning Explained” by Morten Rand-Hendriksen! An excellent short course and a brilliant idea to present it as a 20-minute session, addressing the challenge of defining RAG and clarifying the capabilities and limitations of LLMs. Check it out: https://lnkd.in/eZggXdZ5 #generativeai #aisoftwaredevelopment #retrievalaugmentedgeneration.
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Understand Generative AI and Large Language Models (LLMs)
🌟 Introducing our latest white paper, GenAI for Smart Legal Professionals! 🌟 Co-authored by John Tredennick and Dr. William Webber of Merlin Search Technologies, it's your essential guide to harnessing AI’s power to transform your discovery workflows and enhance efficiency. 🧠 Understand Generative AI and Large Language Models (LLMs) 🔎 Discover how these groundbreaking technologies operate and grasp essential concepts 🔒 Gain peace of mind with insights on data security and the mitigation of AI hallucinations ⚙ Learn real-world applications of GenAI for legal professionals, from streamlining document review and in-depth analysis to efficient transcript summarization ➡ Download a copy now! https://lnkd.in/gW897GGj
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This guide is your key to leveraging AI to revolutionize discovery workflows and boost efficiency. Don't miss out—download a copy today!
🌟 Introducing our latest white paper, GenAI for Smart Legal Professionals! 🌟 Co-authored by John Tredennick and Dr. William Webber of Merlin Search Technologies, it's your essential guide to harnessing AI’s power to transform your discovery workflows and enhance efficiency. 🧠 Understand Generative AI and Large Language Models (LLMs) 🔎 Discover how these groundbreaking technologies operate and grasp essential concepts 🔒 Gain peace of mind with insights on data security and the mitigation of AI hallucinations ⚙ Learn real-world applications of GenAI for legal professionals, from streamlining document review and in-depth analysis to efficient transcript summarization ➡ Download a copy now! https://lnkd.in/gW897GGj
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When it comes to applying Large Language Models (LLMs) in real-world scenarios, open-source offerings such as Mixtral (for those requiring larger models) and Mistral 7B stand out for their unparalleled performance. Despite the influx of new models, these remain superior in terms of their capabilities, offering longer context lengths without the need for adopting new tools for effective utilization. Mistral AI remains unbeaten in the open-source space, imo.
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Open-weight models are catching up with closed-source commercial models. This is great news for all the researchers and developers who don't possess the resources to access commercial models or build their own. The irony is that the organization founded to promote "Open" AI is now closed-source. However, they seem to overlook the fact that in the software industry, most innovations happen in the open-source community. Hopefully, we will soon witness open-weight models matching or even surpassing closed-source models (Mark Zuckerberg Is that too much to ask? 🤔 ). #AI #MetaAI #LLAMA #405B #LLAMA3_1 #LLAMA3_1_405B #Open_Weight_Models #GenAI
NVIDIA Senior Research Manager & Lead of Embodied AI (GEAR Group). Stanford Ph.D. Building Humanoid robot and gaming foundation models. OpenAI's first intern. Sharing insights on the bleeding edge of AI.
The power of GPT-4o in the palm of our hands. It's a monumental day - for the first time in history, open weights catch up with the latest frontier models. This figure charts the historic run of open models against the closed ones. The former starts humble, but rise with a much higher gradient and a much more diverse ecosystem. Research like multimodal LM and robot foundation models wouldn't have been possible without white box access to a strong base LM. Llama-3.1 release includes more than just weights: - "Open Source AI is the Path Forward" - a manifesto that clearly lays out Zuckerberg's vision. It explains the commercial strategies, ecosystem positioning, and even geopolitical concerns, basically answering FAQs for OSS LLM in general: https://lnkd.in/gJt_nYZp - A 71-page long paper that treats all LLM researchers to a buffet of training details and analysis. They even discuss large-scale cluster failures and remedies - issues that only emerge with 16K H100s! It's literally early Christmas for my team ;) GPT-4o and Claude-3.5 are great, but I would easily rank Llama-3.1 the No. 1 highlight in the 2024 LLM landscape.
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Let's take a step back and recognize that this diagram of the evolutionary techno-revolution represents just over 2 years and in the time it took us to reflect on this, they've moved forward 10 steps.
NVIDIA Senior Research Manager & Lead of Embodied AI (GEAR Group). Stanford Ph.D. Building Humanoid robot and gaming foundation models. OpenAI's first intern. Sharing insights on the bleeding edge of AI.
The power of GPT-4o in the palm of our hands. It's a monumental day - for the first time in history, open weights catch up with the latest frontier models. This figure charts the historic run of open models against the closed ones. The former starts humble, but rise with a much higher gradient and a much more diverse ecosystem. Research like multimodal LM and robot foundation models wouldn't have been possible without white box access to a strong base LM. Llama-3.1 release includes more than just weights: - "Open Source AI is the Path Forward" - a manifesto that clearly lays out Zuckerberg's vision. It explains the commercial strategies, ecosystem positioning, and even geopolitical concerns, basically answering FAQs for OSS LLM in general: https://lnkd.in/gJt_nYZp - A 71-page long paper that treats all LLM researchers to a buffet of training details and analysis. They even discuss large-scale cluster failures and remedies - issues that only emerge with 16K H100s! It's literally early Christmas for my team ;) GPT-4o and Claude-3.5 are great, but I would easily rank Llama-3.1 the No. 1 highlight in the 2024 LLM landscape.
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Paving the way in innovation once again ❄ Today Snowflake and our AI Research Division released Arctic ☃ a Fully Open, Enterprise-Grade LLM, that disrupts the current cost/performance matrix for training ultra large language models. Check out documentation and benchmarking here: https://lnkd.in/e7tSXYN8 Cannot wait to dive into this with our customers / partners and to watch the world of enterprise data put Arctic to use 🚀
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