What are Generative AI models?
Generative AI models, particularly foundation models, have garnered significant attention due to their remarkable capabilities. These models are trained on extensive amounts of unstructured data, enabling them to transfer to multiple tasks and generate new content. They can be fine-tuned using labeled data for traditional natural language processing (NLP) tasks, a process called tuning. Foundation models offer advantages such as high performance and productivity gains due to their extensive pre-training on unlabeled data. However, they come with challenges such as computing costs and concerns about trustworthiness, as they are trained on data scraped from the internet, potentially containing biases and toxic information.
What are LLMs?
Large Language Models (LLMs) are powerful machine-learning models specifically designed to understand and generate human language. Built on transformer architecture, LLMs are trained on massive text datasets. They have found applications in various tasks such as chat, copywriting, translation, and code generation. LLMs function as advanced autocomplete systems, completing text based on patterns learned during training. Prompt design plays a crucial role in guiding LLMs’ behavior, and experimentation is necessary to achieve the best results.
Spotlight: ChatGPT & BARD
Two such LLMs making waves are ChatGPT, developed by OpenAI, and Google’s BARD. ChatGPT, a variant of the Generative Pre-trained Transformer (GPT)3.5 language model, has gained widespread popularity due to its capacity to generate human-like responses. It aims to align with human values, prioritizing helpfulness, truthfulness, and harmlessness. However, it’s important to remember that while impressive, it lacks actual knowledge or sentience.
On the other hand, Google’s BARD is an LLM aimed at enhancing programming capabilities, assisting with code generation, debugging, and explaining code snippets in multiple programming languages. Developers gain from code citations, precise annotations, and improved code formatting. BARD, with its proposed future expansions, is expected to offer a more seamless programming experience.
Upcoming Models: FALCON and ORCA
FALCON AI introduces the Falcon 40B model, a powerful AI model for coding and translation. With 40 billion parameters and training on 1 trillion tokens, it outperforms other models on the open NLM leaderboard and supports multiple languages. While commercial use requires a commercial agreement for significant revenues, the model excels in translation and coding tasks. However, it struggles with math problems and restricts certain types of content. On the other hand, Microsoft’s ORCA, a 13 billion parameter model, challenges the dominance of GPT-4. ORCA learns from GPT-4’s step-by-step reasoning, offering remarkable performance and zero-shot reasoning capabilities. Microsoft plans to open source ORCA to encourage transparency, collaboration, and innovation in the AI community.
Final Thoughts:
Generative AI models, particularly LLMs, have ushered in a new era of AI capabilities, enabling machines to understand and generate human language. ChatGPT and BARD have demonstrated their prowess in their respective domains, while upcoming models like FALCON and ORCA promise further advancements. As these models continue to evolve, their impact on various industries and applications will undoubtedly grow, shaping the future of AI-driven technologies.
At Liberin Technologies, we constantly strive to incorporate the best-in-class AI models into our solutions. Our understanding of these AI technologies enables us to deliver innovative and effective solutions to our clients. Stay tuned to our blog for more insights into the ever-evolving world of AI.
Happy innovating!