AI Engineer，Full-time open source engineer, Apache Linkis Committer, initiator of the SolidUI AI painting project.
Why Are Most Large Models Now Decoder-Only? Discover why most large language models (LLMs) are decoder-only. Explore their efficiency, performance, and the future of AI architectures in this deep dive. https://lnkd.in/gZHhjVZk #AI #Decoder #LLM
Just came across this fascinating article discussing the integration of Large Language Models (LLMs) with causal AI for better decision-making. Teaming up genAI and causal AI combines the advantages of fast and slow thinking, facilitating decision-making that is both quick and accurate. This opens up doors for more enterprise use cases and applications! #CausalAI #DecisionMaking #GenAI https://lnkd.in/gahjscVF
Are you looking to implement AI-driven solutions in your organisation but concerned about the high costs and complexity? Look no further! The combination of vector databases and large language models (LLMs) has revolutionised the development of custom generative AI solutions. Learn more: https://zurl.co/gKJF #EnterpriseSolutions #DigitalTransformation
AI/ML Programmer | Expert in Python, NLP, Deep Learning, Gen AI | Transformer/LLM Fine-Tuning Specialist | ML Ops 🚀
🚀 Exciting AI Trends for 2024: Retrieval-Augmented Generation (RAG) is set to revolutionize how businesses harness the power of large language models (LLMs)! Check out this insightful article by David Fang and Justin Haan from MoFo Tech, highlighting how RAG enhances LLM performance for domain-specific tasks without the need for extensive retraining. Dive into the future of AI with RAG and discover how it augments user prompts with relevant, high-quality information, leading to more accurate and tailored outputs. Read more: https://lnkd.in/g_bycUyk #AI #RAG #FutureTech
Multimodal Large Language Models (MLLMs), known for their ability to understand and generate content across various data types, will dominate the main story of Generative AI in 2024. maadaa.ai is working on how to prepare high quality dataset for MLLMs commercialization. Please check it here: https://lnkd.in/eb5EkTH4 #llms #multimodel #dataset
Senior Account Executive @Mulesoft | Qualified Negotiator®, Sales Advisor, Story Telling, Resilience
Generative AI 🧠 promises vast opportunities for efficiency, so naturally, businesses are rapidly looking for ways to incorporate AI into their operations. One prominent option is to use large language models (LLMs), and one of the more convenient ways to engage with LLMs is through APIs.
Embeddings are like secret codes that let AI models understand the world (and how you see it) a little better! They take words, ideas, or even images and convert them into a special code, like creating a secret handshake for each concept. Head over to the full blog post to learn more about the foundation of large language models ➡️ https://hubs.la/Q02tPQ2D0 #Embeddings #AI
Traditional methods of instruction tuning often require vast amounts of data and computational resources, leading to significant costs and time investments. Advanced instruction tuning methods offer more efficient alternatives, potentially reducing development time and costs while maintaining or even improving the quality of AI interactions. Check out the latest blog from Openstream.AI for more insight. https://hubs.li/Q02RzNR70
Creating task-specific language models that can understand and respond to a wide range of instructions is an important area of AI development. However, traditional methods of instruction tuning often require vast amounts of data and computational resources - leading to significant investments in time and money. Recent advancements in instruction tuning for large language models (LLMs) have led to new strategies that have the potential to be more efficient and effective. Check out our recent blog post to learn more: https://hubs.li/Q02RzNR70 #ai #llm #conversationalai
I am excited about the long-term prospects of Generative AI. However. It's clear that many large organizations are facing a challenge: their data infrastructure isn't quite ready for the powerful capabilities of Large Language Models (LLMs) or Structured Language Models (SLMs). As a result, they're missing out on the immediate benefits these foundational models could offer. Addressing data readiness is key to unlocking the full potential of AI in driving innovation and competitiveness. #AI #GenerativeAI #DataInfrastructure #DigitalTransformation #ML #Machinelearning
On Maternity Leave Until April 2025 #RoTheDEIPro|Top Recruiting Voice| Dallas SWN Events/VTO Chair| Dallas Impact Council| Dallas Culture Guide| DEI Advocate | Trailhead Ranger ☁️
Generative AI promises vast opportunities for efficiency, so naturally, businesses are rapidly looking for ways to incorporate AI into their operations. One prominent option is to use large language models (LLMs), and one of the more convenient ways to engage with LLMs is through APIs. #salesforce #APIs #AI
Did you know that traditional fine-tuning of large language models can be costly and time-consuming? With PEFT, you can reduce the number of trainable parameters by up to 99% while maintaining top-tier performance. In our latest blog, we dive deep into PEFT techniques like Adapters, Prefix-Tuning, and Low-Rank Adaptation (LoRA), showcasing how they can optimize AI models efficiently—even in low-resource settings. Learn how to implement PEFT and why it’s the future of AI fine-tuning: https://lnkd.in/gWDBWDcV #AI #MachineLearning #PEFT #DataScience #AIOptimization
