#generativesearch

Michael Martinez :verified:michael_martinez@c.im
2025-06-03

"Search With Stateful Chat" patent (Cf. patents.google.com/patent/US20 ) - appears to describe the Gemini app for smartphones.

"Method for Text Ranking with Pairwise Ranking Prompting" (Cf. patents.google.com/patent/US20 ) - documents an experimental process described in this research paper titled "Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting" (Cf. arxiv.org/pdf/2306.17563 ). There is no indication this was introduced into a live agentic system like Gemini.

"User Embedding Models for Personalization of Sequence Processing Models" (Cf. patents.google.com/patent/WO20 ) - documents an experimental process for improving recommender (sub-)systems (like movie searches) that incorporate large language models. The process is described in this research paper titled "User Embedding Model for Personalized Language Prompting" (Cf. arxiv.org/pdf/2401.04858 ).

"Systems and methods for prompt-based query generation for diverse retrieval" (Cf. patents.google.com/patent/WO20 ) - updates a 2022 patent for a process named PROMPTAGATOR that generates queries more efficiently based on a small number of examples, as described in this research paper titled "Promptagator - Few-shot Dense Retrieval from 8 Examples" (Cf. arxiv.org/pdf/2209.11755 ). This could be used to generate query fan-outs (but query fan-out has been used in multiple systems at least since the 1990s, so there are many implementations).

"Instruction Fine-Tuning Machine-Learned Models Using Intermediate Reasoning Steps" (Cf. patents.google.com/patent/US20 ) - documents an older method for fine-tuning instructions submitted to LLMs, as described in this 2022 research paper titled "Scaling Instruction-Finetuned Language Models" (Cf. jmlr.org/papers/volume25/23-08 ). The work has been superseded by this paper titled "Mixture-of-Experts Meets Instruction Tuning: A Winning Combination for Large Language Models" (Cf. arxiv.org/pdf/2305.14705 ).

This is the AI Overviews patent, titled "Generative summaries for search results" (Cf. patents.google.com/patent/US11 )

#google #aioverviews #aimode #machinelearning #search #searchengines #generativesearch #seo #searchengineoptimization #webmarketing #digitalmarketing #ai #patents

Mat Nelsonmatnelsonppc
2025-04-25

AI Overviews & Copilot are pushing organic results down, making a key strategy for brand visibility in the age of

Investing in paid will help companies stay prominent on

šŸ‘‰ searchengineland.com/us-search

Mat Nelsonmatnelsonppc
2025-02-03

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Mat Nelsonmatnelsonppc
2025-01-06

is here! Learn how AI-driven search & ads could reshape . From affiliate strategies to local services, it’s time to prepare for the shift. Are you ready?

Read more: open.substack.com/pub/matnelso

2024-12-16

We need a conceptual framework for LLMs and social visibility

As a literary executor I promised to maximise diffusion of my mentor’s work to extent I could without damaging its integrity. Now receiving requests from publisher to license training on the books. This certainly aids diffusion by increasing visibility within the model but does it damage integrity? We still lack a conceptual framework for thinking about how existing hierarchies of attention will be restructured by visibility or its absence within a model. I find it easy to see how the implications could be complex and multifaceted, in ways we urgently need to understand for higher education.

For example my blog now gets lots of traffic via Perplexity & ChatGPT because it’s clearly identified as a high authority source. ChatGPT can answer questions about me with sufficient detail that I suspect it was trained on my blog. These have non-trivial implications for academic visibility/status. It’s hard to explore these issues conceptually and empirically if the debate is polarised into abolitionists and solutionists, such that if you’re not one you are immediately suspected of being the other.

#attentionEconomy #celebrity #generativeAI #generativeSearch #heirarchy #LLMs #SocialMedia #socialPlatforms #stratification #visibility

2024-11-21

The psuedo-singularity of generative search answers

Given how transfixed I am by Rings of Power season 2 (so much better than the original) I’ve been asking Perplexity background information about Tolkien lore to address my uncertainty about elements of the show e.g. if Sauron is a spirit then why does he turn into Venom-esque black goo when he dies? There’s no question too obscure for Perplexity to provide an answer, with ā€˜suggested questions’ rapidly spiralling off into hyper-obscurity as you go down a rabbit hole. It satisfies my curiosity without leading me to spend hours lost in fan wikis, even though it poses obvious question about the ethics of what generative search trained on those wikis will be doing to their visibility.

So I thought I’d test it in an area where I know the lure inside and out. In Jon Hickman’s epic Secret Wars there were lots of threads which I know were never fully elaborated. I’ve been asking Perplexity questions about this unresolved plot threads and it will consistently provide a singular and definitive answer for each one, even when they weren’t actually shown in the story arc. The problem as far as I can see isn’t hallucination in the classic GAI sense but rather stitching together partial inferences in sources access through retrieval-augmented generation.

There’s a hole in knowledge, part of a story that was gestured to but never actually told, which various people have filled in through more or less speculative means. Their speculative answers are drawn upon by Perplexity in order to provide a singular answer to a question which is in reality unanswerable. It resides as a unrealised creative intention in Jon Hickman’s mind rather than something out there in the world which can be veridically described. Yet Perplexity treats every question as having an answer, generating those answers in a way that papers over the fractures and gaps in the knowledge system.

The combination of GAI hallucination and the combinatorial dynamics of RAG is very interesting. I feel like I’ve not got the language to adequately describe this yet, but this was a first attempt to put this dynamic into words, because I believe it is inherent in generative search and will manifest in different ways in other RAG systems.

#generativeSearch #knowledge #lore #perplexity

2024-09-28

I was initially extremely sceptical but this rapidly improving. This was the result for the slightly niche query ā€œuniversity of manchester two-step I don’t have a smart phoneā€ and it was exactly what I was looking for:

This is exactly the page I needed from the university website, which is ironically the sort of specific information which legacy search is increasingly unable to reliably locate. Obviously the problem is that this encourages people to not look at the site, not least of all to check the information. The hallucinations will continue, even if they are reduced.

But if the utility of generative search increases while legacy search continues to get worse, it could get normalised very quickly.

https://markcarrigan.net/2024/09/28/will-google-crack-generative-search/

#generativeSearch #google

Scott ClarkScottclark
2023-05-27

h/t Lily Ray for the screenshot - So as we all suggest to clients that a brand-first strategy might be one important area of emphasis for succeeding with , this kind of result emerges for a branded, navigational query. WTH?

What % of people type exact match "REI" to get the info about the the company?

2023-05-19

Haystack US 2023 - Keynote - Trey Grainger - Relevance in the Age of Generative Search

40two.tube/videos/watch/4f6a34

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