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With Generative AI Advances, The Time to Tackle Responsible AI Is Now

Unite.AI

AI models in production. Today, seven in 10 companies are experimenting with generative AI, meaning that the number of AI models in production will skyrocket over the coming years. As a result, industry discussions around responsible AI have taken on greater urgency. In 2022, companies had an average of 3.8

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Decoding Opportunities and Challenges for LLM Agents in Generative AI

Unite.AI

We are seeing a progression of Generative AI applications powered by large language models (LLM) from prompts to retrieval augmented generation (RAG) to agents. In my previous article , we saw a ladder of intelligence of patterns for building LLM powered applications. Let's look in detail. Sounds exciting!?

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All You Need to Know About Gemma, the Open-Source LLM Powerhouse

Analytics Vidhya

Google has been a frontrunner in AI research, contributing significantly to the open-source community with transformative technologies like TensorFlow, BERT, T5, JAX, AlphaFold, and AlphaCode. What is Gemma LLM?

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Considerations for addressing the core dimensions of responsible AI for Amazon Bedrock applications

AWS Machine Learning Blog

The rapid advancement of generative AI promises transformative innovation, yet it also presents significant challenges. Concerns about legal implications, accuracy of AI-generated outputs, data privacy, and broader societal impacts have underscored the importance of responsible AI development.

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Learn Generative AI With Google

Unite.AI

The Artificial Intelligence (AI) ecosystem has evolved rapidly in the last five years, with Generative AI (GAI) leading this evolution. In fact, the Generative AI market is expected to reach $36 billion by 2028 , compared to $3.7 However, advancing in this field requires a specialized AI skillset.

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Social Impact of Generative AI: Benefits and Threats

Unite.AI

Today, Generative AI is wielding transformative power across various aspects of society. As per eMarketer , Generative AI shows early adoption with a projected 100 million or more users in the USA alone within its first four years. Let’s discuss its positive social impact: 1. just a simple click away.

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Improve factual consistency with LLM Debates

AWS Machine Learning Blog

In this post, we demonstrate the potential of large language model (LLM) debates using a supervised dataset with ground truth. In this LLM debate, we have two debater LLMs, each one taking one side of an argument and defending it based on the previous arguments for N(=3) rounds. The arguments are saved for a judge LLM to review.

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