It’s been a busy week for AI enthusiasts. OpenAI has released a mini version of their GPT-4o model, priced at 15 cents per million input tokens and 60 cents per million output tokens, making it over 60% cheaper than GPT-3.5 Turbo.
At the same time, Meta introduced Llama 3.1, an open-source AI model with performance benchmarks comparable to proprietary models from OpenAI, Google, and Anthropic. Llama 3.1, with its 405 billion parameters, is less compute-intensive than OpenAI’s GPT-4 and is free to use.
France’s Mistral also released an updated model, Mistral Large 2, which is cost-effective but requires a license for commercial use, unlike the fully open-source Llama.
Future Vision and Industry Impact
OpenAI envisions a future where AI models are seamlessly integrated into every app and website. For this to happen, models need to be smaller, more efficient, and affordable for large-scale deployment. Mark Zuckerberg recently argued that open-source AI models will surpass proprietary ones, predicting Llama 3.1’s release as a turning point for developers.
Benefits for Developers
The push towards affordable, open-source models benefits developers, especially in India. Tanusree De, executive director & responsible AI leader at EY Global Delivery Services, highlights that lower costs allow developers to experiment and build applications without financial constraints. These models offer capabilities comparable to leading models, enabling sophisticated AI features in applications and accelerating innovation across industries.
Debdoot Mukherjee, chief data scientist at Meesho, points out that large open-source models allow for the generation of vast amounts of training data, facilitating the fine-tuning of smaller models.
Rahul Lodhe, global head of engineering for SAP Business AI Copilot Joule, advises Indian developers to gain proficiency in programming languages like Python, work with AI frameworks and tools, and stay updated with the latest AI research. Engaging in open-source projects and AI communities is also crucial for advancing skills and contributing to the global AI ecosystem.
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