Play in GenAI is now in its applications
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There is no doubt that LLMs are advancing but now they have mainly transitioned to incremental refinements. Why will this happen? Learning for LLMs, which happens through data, is bound to plateau sooner or later, when most of unique patterns are learnt (and new info to be gained from data is marginal). There may not be a huge improvement unless there is some breakthrough like "attention is all you need" (2017) which made transformers dominant architecture. Then why is GenAI now more popular…
1Key Takeaways
- There is no doubt that LLMs are advancing but now they have mainly transitioned to incremental refinements.
- Learning for LLMs, which happens through data, is bound to plateau sooner or later, when most of unique patterns are learnt (and new info to be gained from data is marginal).
- There may not be a huge improvement unless there is some breakthrough like "attention is all you need" (2017) which made transformers dominant architecture.
2AIWedia Score
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that there is no doubt that LLMs are advancing but now they have mainly transitioned to incremental refinements.
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