Is AI progress slowing?

AI is evolving fast and dominating every sector with its capabilities. The creators of ChatGPT, OpenAI, are on the verge of releasing their new model, “Orion.” Reports are saying that AI progress is slowing down after Orion’s news. Let’s look at what the fuss is about regarding Orion.

This blog is written by Akshat Virmani at KushoAI. We're building the fastest way to test your APIs. It's completely free and you can sign up here.

What is OpenAI’s Orion?

Orion is a next-generation AI model developed by OpenAI, aimed at improving the performance of its predecessor, GPT-4. Orion is built on the GPT-4 architecture with refinements in fine-tuning, training efficiency, and task-specific optimisation. Despite these enhancements, early reports indicate that the performance leap from GPT-4 to Orion is incremental rather than groundbreaking.

For example, GPT-4 showcased substantial improvements over GPT-3.5 in reasoning, contextual understanding, and creative output but Orion’s advancements only focus on fine details and specialised use cases. 

Why AI Progress Appears To Be Slowing

1. Scaling Complexity

AI relies heavily on larger datasets, more parameters, and more computational power. While this strategy has delivered impressive results, it comes with diminishing returns. Each improvement requires more resources, making it hard and costly to achieve.

2. Data Limitations

Large language models rely on massive datasets. Future progress may require new approaches to data collection or entirely new types of datasets to improve the models' ability to be distinguished from other LLMs.

3. Shifting Goals

As AI matures, the focus shifts from performance to other priorities like safety, interpretability, and cost efficiency. 

The Broader Industry Challenge

• Energy Consumption: Training AI models requires immense computational resources, raising sustainability concerns.
• Bottlenecks: The demand for AI researchers far outpaces supply, slowing innovation in cutting-edge areas.
• Regular Inspection: Governments worldwide are introducing regulations to ensure AI is safe and ethical, potentially slowing development timelines.

Some solutions to these challenges

• Efficient Architectures: Techniques like sparsity, pruning, and low-rank adaptation are helping to reduce resource requirements while maintaining performance.
• Collaborative Research: Open-source initiatives and collaborations in research foster innovation and reduce duplication of effort.

To Conclude

The challenges highlighted by Orion’s development are not just limited to OpenAI. The broader AI industry faces a convergence of technical, economic, and ethical hurdles that slow progress.

This blog is written by Akshat Virmani at KushoAI. We're building an AI agent that tests your APIs for you. Bring in API information and watch KushoAI turn it into fully functional and exhaustive test suites in minutes.