I asked Google if MA does LLM tutoring and got back this answer:
> Math Academy does not offer Large Language Model (LLM) tutoring. While the company advertises itself as "AI-powered," this is in reference to a machine-learning-based adaptive learning system, not an interactive LLM tutor.
And here is a HN comment that indicates LLMs are a complement to MA, not part of it: https://news.ycombinator.com/item?id=43281240"},"story_title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["llm"],"value":"LLMs are the ultimate demoware"},"story_url":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["llm"],"value":"https://blog.charliemeyer.co/llms-are-the-ultimate-demoware/"}},"_tags":["comment","author_getnormality","story_45437113"],"author":"getnormality","children":[45438922],"comment_text":"Everything described there sounds like old-school adaptive algorithms. I don't see anything about generative AI or LLMs.
I asked Google if MA does LLM tutoring and got back this answer:
> Math Academy does not offer Large Language Model (LLM) tutoring. While the company advertises itself as "AI-powered," this is in reference to a machine-learning-based adaptive learning system, not an interactive LLM tutor.
And here is a HN comment that indicates LLMs are a complement to MA, not part of it: https://news.ycombinator.com/item?id=43281240","created_at":"2025-10-01T15:26:57Z","created_at_i":1759332417,"objectID":"45438868","parent_id":45438791,"story_id":45437113,"story_title":"LLMs are the ultimate demoware","story_url":"https://blog.charliemeyer.co/llms-are-the-ultimate-demoware/","updated_at":"2026-03-05T22:47:55Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"mncharity"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["adaptive","learning","llm","tutoring"],"value":"Years ago I was watching so-called "best practices" videos on teaching estimation in early primary. I was astonished. Often the skill being coached seemed to be participative performance in a collaborative pretense of understanding. What to do, and not do, so we can both pretend learning has occurred and move on. With the teachers themselves largely unclear on the concepts.
Ongoing formative assessment is usually closely associated with instruction, with attendant conflicts of interest. I wonder if say LLMs, might transformatively permit fine-grain and adaptive assessment. So a "what have you been learning?" dialog for objective identification, and then assessment across the objective neighborhood. With potential for tutoring of course. But here emphasizing a possibility for rapid verification of learning."},"story_title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["learning"],"value":"Lots of people in education disagree with the premise of maximizing learning"},"story_url":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["learning"],"value":"https://www.justinmath.com/maximizing-learning-vs-other-things/"}},"_tags":["comment","author_mncharity","story_40916904"],"author":"mncharity","children":[40921804,40922012],"comment_text":"Years ago I was watching so-called "best practices" videos on teaching estimation in early primary. I was astonished. Often the skill being coached seemed to be participative performance in a collaborative pretense of understanding. What to do, and not do, so we can both pretend learning has occurred and move on. With the teachers themselves largely unclear on the concepts.
Ongoing formative assessment is usually closely associated with instruction, with attendant conflicts of interest. I wonder if say LLMs, might transformatively permit fine-grain and adaptive assessment. So a "what have you been learning?" dialog for objective identification, and then assessment across the objective neighborhood. With potential for tutoring of course. But here emphasizing a possibility for rapid verification of learning.","created_at":"2024-07-09T22:00:31Z","created_at_i":1720562431,"objectID":"40921700","parent_id":40921090,"story_id":40916904,"story_title":"Lots of people in education disagree with the premise of maximizing learning","story_url":"https://www.justinmath.com/maximizing-learning-vs-other-things/","updated_at":"2024-09-20T17:23:43Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"fraggler"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["adaptive","learning","llm","tutoring"],"value":"The core idea is this:
Truly general intelligence requires the ability to build an unbounded number of solutions. For a finite system to achieve this, it needs a mechanism for unbounded generation, like recursion (similar to how a Turing machine operates). General intelligence also requires constant adaptation. So how do you get both? The paper proposes it arises from the dynamic interaction between an adaptive continuous substrate (like the human brain or an ANN) and an internalized symbolic framework (like human language).
The "engine" of this process, according to the ESC framework, is recursive symbolic generation. The substrate learns to:\n1. Sequentially generate symbolic sequences (like words forming thoughts or sentences).\n2. Process these sequences.\n3. Evaluate them based on internal rules and goals.
This recursive loop allows the system to effectively function as a powerful, discrete symbolic processor, capable of navigating vast combinatorial spaces and constructing structured solutions for diverse problems\u2014essentially, to think and reason in a general-purpose way.
Why this might be interesting:\n- It tries to bridge the gap between connectionist learning (like in ANNs) and symbolic competence (rule-based reasoning).\n- It offers a lens on why language seems so crucial for human thought.\n- It sheds light on the surprising abilities emerging in LLMs (which learn only from text) as a key piece of evidence.\n- It defines GI functionally, focusing on what it does (generates novel information to solve problems across unbounded domains)."},"story_title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["llm"],"value":"Beyond \"stochastic parrots\": LLMs reveal language's role in general intelligence"},"story_url":{"matchLevel":"none","matchedWords":[],"value":"https://osf.io/preprints/psyarxiv/86xsj_v24"}},"_tags":["comment","author_fraggler","story_44161689"],"author":"fraggler","comment_text":"The core idea is this:
Truly general intelligence requires the ability to build an unbounded number of solutions. For a finite system to achieve this, it needs a mechanism for unbounded generation, like recursion (similar to how a Turing machine operates). General intelligence also requires constant adaptation. So how do you get both? The paper proposes it arises from the dynamic interaction between an adaptive continuous substrate (like the human brain or an ANN) and an internalized symbolic framework (like human language).
The "engine" of this process, according to the ESC framework, is recursive symbolic generation. The substrate learns to:\n1. Sequentially generate symbolic sequences (like words forming thoughts or sentences).\n2. Process these sequences.\n3. Evaluate them based on internal rules and goals.
This recursive loop allows the system to effectively function as a powerful, discrete symbolic processor, capable of navigating vast combinatorial spaces and constructing structured solutions for diverse problems\u2014essentially, to think and reason in a general-purpose way.
Why this might be interesting:\n- It tries to bridge the gap between connectionist learning (like in ANNs) and symbolic competence (rule-based reasoning).\n- It offers a lens on why language seems so crucial for human thought.\n- It sheds light on the surprising abilities emerging in LLMs (which learn only from text) as a key piece of evidence.\n- It defines GI functionally, focusing on what it does (generates novel information to solve problems across unbounded domains).","created_at":"2025-06-02T21:04:39Z","created_at_i":1748898279,"objectID":"44163022","parent_id":44161689,"story_id":44161689,"story_title":"Beyond \"stochastic parrots\": LLMs reveal language's role in general intelligence","story_url":"https://osf.io/preprints/psyarxiv/86xsj_v24","updated_at":"2025-06-03T09:00:28Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"Aeyxen"},"comment_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["adaptive","learning","llm","tutoring"],"value":"I understand your perspective as a marketer, but I think you're creating a false dichotomy. Yes, persuasion tech has stronger financial incentives, but that doesn't prevent beneficial applications from emerging simultaneously.
The "super tutor" isn't some distant fantasy - millions already use ChatGPT, Claude and similar tools daily for personalized learning. They're imperfect but genuinely helpful for programming, languages, math, and countless other topics.
Look at what happened with YouTube: millions of people transformed themselves into programmers, musicians, mechanics, and countless other professions through free video tutorials. Khan Academy revolutionized math education. Coursera and edX brought university courses to anyone with internet. This wasn't utopian thinking - it was practical technology solving real educational problems at scale.
What's different now is that LLMs enable the missing piece: personalization. The one-on-one adaptive experience that was previously limited to those who could afford human tutors at $50-100/hour is now available to anyone at negligible marginal cost.
Your skepticism about cancer applications too ignores the technological trajectory we've been on for decades. Just as YouTube and online platforms democratized education, technology has been steadily dismantling bottlenecks in medical research.
The human genome project initially cost $3 billion and took 13 years. Today you can sequence a genome for under $1,000 in days. This wasn't utopian thinking; it was technological progress following its natural course.
Think what LLMs will do here."},"story_title":{"fullyHighlighted":false,"matchLevel":"partial","matchedWords":["llm"],"value":"LLMs are more persuasive than incentivized human persuaders"},"story_url":{"matchLevel":"none","matchedWords":[],"value":"https://arxiv.org/abs/2505.09662"}},"_tags":["comment","author_Aeyxen","story_44016621"],"author":"Aeyxen","comment_text":"I understand your perspective as a marketer, but I think you're creating a false dichotomy. Yes, persuasion tech has stronger financial incentives, but that doesn't prevent beneficial applications from emerging simultaneously.
The "super tutor" isn't some distant fantasy - millions already use ChatGPT, Claude and similar tools daily for personalized learning. They're imperfect but genuinely helpful for programming, languages, math, and countless other topics.
Look at what happened with YouTube: millions of people transformed themselves into programmers, musicians, mechanics, and countless other professions through free video tutorials. Khan Academy revolutionized math education. Coursera and edX brought university courses to anyone with internet. This wasn't utopian thinking - it was practical technology solving real educational problems at scale.
What's different now is that LLMs enable the missing piece: personalization. The one-on-one adaptive experience that was previously limited to those who could afford human tutors at $50-100/hour is now available to anyone at negligible marginal cost.
Your skepticism about cancer applications too ignores the technological trajectory we've been on for decades. Just as YouTube and online platforms democratized education, technology has been steadily dismantling bottlenecks in medical research.
The human genome project initially cost $3 billion and took 13 years. Today you can sequence a genome for under $1,000 in days. This wasn't utopian thinking; it was technological progress following its natural course.
Think what LLMs will do here.","created_at":"2025-05-18T16:49:58Z","created_at_i":1747586998,"objectID":"44022635","parent_id":44022349,"story_id":44016621,"story_title":"LLMs are more persuasive than incentivized human persuaders","story_url":"https://arxiv.org/abs/2505.09662","updated_at":"2025-05-18T21:15:43Z"}],"hitsPerPage":20,"nbHits":4,"nbPages":1,"page":0,"params":"query=adaptive+learning+LLM+tutoring&advancedSyntax=true&analyticsTags=backend","processingTimeMS":28,"processingTimingsMS":{"_request":{"roundTrip":18},"afterFetch":{"merge":{"total":2},"total":2},"fetch":{"query":22,"scanning":2,"total":25},"total":29},"query":"adaptive learning LLM tutoring","serverTimeMS":30}