No, RAG is probably not going to rescue the current situation
We recorded 11 claims from this post. 7 were checked against evidence. 4 can’t be checked. 2 more are held. Read the post at its source.
Claims from this post (11)
In the order they appear in the post. Each quotation is the speaker’s words in this post. A label such as “Supported” or “Can’t be checked” is the claim’s current assessment; its page has the evidence and the reasons.
Assessment: UnresolvedSaid
Observation
“Investors put in over $100 billion into the driverless car industry, and so far have little to show far it.”
Our reading: Investors have put over $100 billion into driverless cars and so far have little to show for it.
No horizon Evidence as of
Limitation: Deployment is not revenue, profit, or investor return.
Assessment: SupportedSaid
Observation
“The trouble is that so far RAG has been hit and miss.”
Our reading: So far retrieval-augmented generation has produced inconsistent results.
No horizon Evidence as of
Limitation: Citation correctness is narrower than overall factual accuracy.
Assessment: Can’t be checkedSaid
Recommendation or value judgment
“Honestly, every LLM, with RAG or without, probably ought to have on of those old movie disclaimers after every response:”
Our reading: Every LLM, with or without RAG, should probably carry a disclaimer after each response.
No horizon
Qualifier: with RAG or without
Assessment: SupportedSaid
Observation
“Reality is that RAG is still in its infancy, a work in progress much as LLMs themselves are, an no more guaranteed to be correct. Like LLMs, RAG can appear spectacular at times, but there is no evidence that it is a cure-all.”
Our reading: RAG is immature, not guaranteed correct, and there is no evidence it is a cure-all for LLM problems.
No horizon Evidence as of
Limitation: The evidence does not give 'infancy' an objective maturity threshold or show that every RAG application was immature.
Assessment: UnresolvedSaid
Forecast
“RAG may reduce hallucinations somewhat, but it certainly won’t come close to eliminating them.”
Our reading: RAG may somewhat reduce hallucinations but will not come close to eliminating them.
No deadline stated Evidence as of
Limitation: The claim supplies no deadline or numerical definition of near-elimination.
Assessment: SupportedSaid
Observation
“The road from research idea to reliable production remains steep.”
Our reading: Getting RAG from a research idea to reliable production remains difficult.
No horizon Evidence as of
Limitation: The implementation report covers three cases, not a representative industry survey.
Assessment: UnresolvedSaid
Observation
“There’s no reason to think that any such thing yet exists, nor that building such a comparison tool is any easier than solving AGI itself.”
Our reading: There is no reason to think that a technology yet exists for comparing an LLM's output with the text of a reliable source and determining with very high accuracy whether they say the same thing, nor that building such a comparison tool is any easier than solving AGI.
No horizon Evidence as of
Limitation: The compound claim combines an empirical existence question with an undefined difficulty comparison.
Assessment: SupportedSaid
Observation
“That’s exactly what classical AI has been trying to do for decades, with only limited success. And what systems like Gemini still struggle with.”
Our reading: Classical AI has had only limited success in turning input into checkable logical form and reasoning over it, and systems like Gemini still struggle with it.
No horizon Evidence as of
Limitation: Limited success is a qualitative judgment about general coverage.
Assessment: Can’t be checkedSaid
Rhetoric
“Waiting on RAG to fix what ails LLM is just waiting on another miracle.”
Our reading: Expecting RAG to fix LLMs' problems is like waiting for a miracle.
No horizon
Assessment: Can’t be checkedSaid
Conditional forecast
“Some great-grandchild of RAG, perhaps extended, revised, and elaborated, might even help — if people seriously embrace neurosymbolic AI in coming years.”
Our reading: Some great-grandchild of RAG, perhaps extended, revised, and elaborated, might help AI work reliably if people seriously embrace neurosymbolic AI in coming years.
No horizon
Only if: if people seriously embrace neurosymbolic AI in coming years
Assessment: Can’t be checkedSaid
Conditional forecast
“Making it work is very likely going to require a whole new technology, one that is unlikely to arrive until the tech industry gets over its infatuation with LLMs and quick fixes.”
Our reading: Reliable AI will very likely require a whole new technology, which is unlikely to arrive until the tech industry moves past its infatuation with LLMs and quick fixes.
No horizon
Only if: new technology unlikely until industry gets over LLM infatuation and quick fixes
Held from this post (2)
These records did not pass every check, so nothing about them is published. Held is not a finding.
- The criteria are ambiguous. Our reading, not assessed: By about February 2025, one year after the post, there will be no perfectly reliable, hallucination-free chatbots.
- The two reviews read the claim differently