How Will the LLM Hallucination Problem Be Solved?
29
1kṀ9402029
11%
9%
Vector Embeddings (as with Pinecone https://www.pinecone.io/)
1.2%
Filtering (as with Deepmind AlphaCode https://www.deepmind.com/blog/competitive-programming-with-alphacode)
0.1%
Ensemble Combined with Fine Tuning
0.5%
Joint Embedding Predictive Architecture (https://arxiv.org/pdf/2301.08243.pdf)
0.3%
Feed Forward Algorithms (https://www.cs.toronto.edu/~hinton/FFA13.pdf)
9%
Bigger model trained on more data + RL
1.6%
Vigger models + prompt engineering
53%
It won't be
15%
Giving all LLMs access to the internet and databases of scientific papers
By the year 2028, how will the Hallucination Problem have been solved for the vast majority of applications out there?
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