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Bigger isn’t always better: How hybrid AI pattern enables smaller language models

IBM Journey to AI blog

However, there are smaller models that have the potential to innovate gen AI capabilities on mobile devices. Let’s examine these solutions from the perspective of a hybrid AI model. The basics of LLMs LLMs are a special class of AI models powering this new paradigm. Is hybrid AI the answer?

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AI Learns from AI: The Emergence of Social Learning Among Large Language Models

Unite.AI

Since OpenAI unveiled ChatGPT in late 2022, the role of foundational large language models (LLMs) has become increasingly prominent in artificial intelligence (AI), particularly in natural language processing (NLP).

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Sean Mullaney, Chief Technology Officer at Algolia – Interview Series

Unite.AI

In a nutshell, Algolia NeuralSearch integrates keyword matching with vector-based natural language processing , powered by LLMs, in a single API – an industry first. You’ve described Algolia as being the most scalable hybrid AI search engine in the world. In September 2022, Search.io

Big Data 246
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What is Artificial General Intelligence (AGI) and Why It’s Not Here Yet: A Reality Check for AI Enthusiasts

Unite.AI

Despite achieving remarkable results in areas like computer vision and natural language processing , current AI systems are constrained by the quality and quantity of training data, predefined algorithms, and specific optimization objectives.

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AI vs. Machine Learning vs. Deep Learning vs. Neural Networks: What’s the difference?

IBM Journey to AI blog

Categories of AI Three main categories of AI are: Artificial Narrow Intelligence (ANI) Artificial General Intelligence (AGI) Artificial Super Intelligence (ASI) ANI is considered “weak” AI, whereas the other two types are classified as “strong” AI.

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A Guide to Mastering Large Language Models

Unite.AI

Large language models (LLMs) have exploded in popularity over the last few years, revolutionizing natural language processing and AI. From chatbots to search engines to creative writing aids, LLMs are powering cutting-edge applications across industries.

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Amazon EC2 DL2q instance for cost-efficient, high-performance AI inference is now generally available

AWS Machine Learning Blog

With eight Qualcomm AI 100 Standard accelerators and 128 GiB of total accelerator memory, customers can also use DL2q instances to run popular generative AI applications, such as content generation, text summarization, and virtual assistants, as well as classic AI applications for natural language processing and computer vision.

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