by Greggory Elias | Aug 29, 2024 | Enterprise AI, LLMs / NLP, Prompt Engineering
Large Language Models (LLMs) demonstrate remarkable capabilities in natural language processing (NLP) and generation. However, when faced with complex reasoning tasks, these models can struggle to produce accurate and reliable results. This is where Chain-of-Thought...
by Greggory Elias | Aug 29, 2024 | Generative AI, LLMs / NLP, Prompt Engineering
Chain-of-Thought (CoT) prompting has been hailed as a breakthrough in unlocking the reasoning capabilities of large language models (LLMs). This technique, which involves providing step-by-step reasoning examples to guide LLMs, has garnered significant attention in...
by Greggory Elias | Aug 29, 2024 | Enterprise AI, Generative AI, Prompt Engineering
The art of crafting effective large language model (LLM) prompts has become a crucial skill for AI practitioners. Well-designed prompts can significantly enhance an LLM’s performance, enabling more accurate, relevant, and creative outputs. This blog post...
by Greggory Elias | Aug 19, 2024 | Enterprise AI, Generative AI, LLM Integration
In AI, the ability to learn efficiently from limited data has become crucial. Enter Few Shot Learning, an approach that’s improving how AI models acquire knowledge and adapt to new tasks. But what exactly is Few Shot Learning? Defining Few Shot Learning Few Shot...
by Greggory Elias | Aug 19, 2024 | Enterprise AI, Generative AI, LLMs / NLP
The true potential of large language models (LLMs) lies not just in their vast knowledge base, but in their ability to adapt to specific tasks and domains with minimal additional training. This is where the concepts of few-shot prompting and fine-tuning come into...
by Greggory Elias | Aug 19, 2024 | Generative AI, LLMs / NLP, Research / Stats
Few-shot learning has emerged as a crucial area of research in machine learning, aiming to develop algorithms that can learn from limited labeled examples. This capability is essential for many real-world applications where data is scarce, expensive, or time-consuming...
by Greggory Elias | Aug 19, 2024 | Generative AI, LLMs / NLP, Newsletter
Stat of the Week: 72% of surveyed organizations have adopted AI in 2024, a significant jump from around 50% in previous years. (McKinsey) Meta’s recent release of Llama 3.1 has sent ripples through the enterprise world. This latest iteration of the Llama models...
by Greggory Elias | Aug 19, 2024 | Enterprise AI, Generative AI, LLM Integration
Stat of the Week: Using smaller LLMs like GPT-J in a cascade can reduce overall cost by 80% while improving accuracy by 1.5% compared to GPT-4. (Dataiku) As organizations increasingly rely on large language models (LLMs) for various applications, the operational costs...
by Greggory Elias | Aug 4, 2024 | Enterprise AI, Generative AI, LLMs / NLP
As organizations increasingly rely on large language models (LLMs) for various applications, from customer service chatbots to content generation, the challenge of LLM cost management has come to the forefront. The operational costs associated with deploying and...
by Greggory Elias | Aug 4, 2024 | Enterprise AI, LLM Integration
For enterprise AI strategies, understanding large language model (LLM) pricing structures is crucial for effective cost management. The operational costs associated with LLMs can quickly escalate without proper oversight, potentially leading to unexpected cost spikes...
by Greggory Elias | Aug 4, 2024 | Enterprise AI, Generative AI, LLMs / NLP
Meta has recently announced Llama 3.1, its most advanced open-source large language model (LLM) to date. This release marks a significant milestone in the democratization of AI technology, potentially bridging the gap between open-source and proprietary models. Llama...
by Greggory Elias | Aug 4, 2024 | Enterprise AI, LLM Integration, Project Management
Meta’s recent release of Llama 3.1 has sent ripples through the enterprise world. This latest iteration of the Llama models represents a significant leap forward in the realm of large language models (LLMs), offering a blend of performance and accessibility that...
by Greggory Elias | Aug 4, 2024 | Enterprise AI, LLM Integration
The landscape of large language models (LLMs) has become a battleground between open-weight models like Meta’s Llama 3.1 and proprietary offerings from tech giants like OpenAI. As enterprises navigate this complex terrain, the decision between adopting an open...
by Greggory Elias | Aug 4, 2024 | Enterprise AI, LLM Integration
Meta’s Llama 3.1 has emerged as an impressive LLM option, offering a unique blend of performance, flexibility, and cost-effectiveness. As enterprises navigate the complex world of AI implementation, Llama 3.1 presents compelling reasons for serious...
by Greggory Elias | Aug 3, 2024 | Advertising & Marketing, Newsletter
Stat of the Week: In May 2024, Perplexity AI received 67.42 million visits with an average session duration of 10 minutes 51 seconds. Traffic increased by 20.71% compared to April. (Semrush) In digital marketing, staying ahead is crucial. As online research evolves,...
by Greggory Elias | Aug 2, 2024 | Uncategorized
In this article, we are going to break down an important research paper that addresses one of the most pressing challenges facing large language models (LLMs): hallucinations. The paper, titled “ChainPoll: A High Efficacy Method for LLM Hallucination...
by Greggory Elias | Aug 2, 2024 | Enterprise AI, Generative AI, LLMs / NLP
Large language models (LLMs) are transforming enterprise applications, offering unprecedented capabilities in natural language processing and generation. However, before your enterprise jumps on the LLM bandwagon, there’s a critical challenge you need to...
by Greggory Elias | Aug 2, 2024 | Enterprise AI, Generative AI, LLMs / NLP
As large language models (LLMs) continue to disrupt nearly every field and industry, they bring with them a unique challenge: hallucinations. These AI-generated inaccuracies pose a significant risk to the reliability and trustworthiness of LLM outputs. What are LLM... 
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