LLMs in 2024

2024 was a great year in terms of LLM progress.

Here are some of the notable progress. It’s primarily based on the summary written by Simon Willison

🔥 Biggest Changes:

• LLM prices crashed dramatically (up to 27x cheaper)
• Powerful models can now run on laptops (Llama 3.3 70B, Qwen2.5)
• Voice/camera interactions is becoming mainstream. It’s not science friction anymore
• Open Source models are on par with proprietary AI models. Unlike last year, OpenAI doesn’t seem to competitive advantage with current progress

💪 Key Improvements:

• Multimodal became standard (vision, audio, video support) and almost all the new models supports them
• Context lengths increased massively (up to 2M tokens)
• Training efficiency improved significantly (DeepSeek v3 trained for ~$6M)
• Inference-scaling models emerged (like OpenAI’s o1/o3 series)
  • It uses Chain of Thoughts under the hood

⚠️ Ongoing Challenges:

• “Agents” still haven’t materialized meaningfully. And similar to fine-tuning in 2023, everyone started using “Agents” as next big thing (buzz word)
• Models remain difficult to use effectively
• Environmental concerns shifted from per-prompt cost to infrastructure

🔮 Notable Trends:

• Synthetic training data proved highly effective
• Prompt-driven app generation became commonplace
  • Apps like Bolt.new, Vercel’s v0, etc becoming more and more popular

References

• Things we learned about LLMs in 2024
• https://huggingface.co/spaces/reach-vb/2024-ai-timeline
• https://genai2024.replit.app/