Which one is Google? Is it bargain basement? It's the only one I interact with, albeit involuntarily, but last night in my usual fashion of typing a question, this time a quick thumbnail for determining the yardage needed if you are trying to switch to a different yarn class for a knitting pattern, depending how I phrased the question it included in its reasoning that worsted was thicker than dk (yes) and then in quick succession, that dk was thicker than worsted (no).
I know the work on these things is all very complicated, but I'm going to go out on a limb and say that knitting is a pretty settled science, which ought to be elementary for the AI.
I am reminded of - about 25 years ago? I'm a little fuzzy - shepherding some early grade school children through an assignment they'd been given - to do a project on a favorite animal, starting with "research" in the school library.
This was around when schools were easy targets, pretty early in their bumpy, largely naive, and of course utterly wasteful and ultimately totally deleterious journey purchasing "technology". All those hundreds of CD-ROMs, destined for the trash ...
The children (maybe 2nd grade?) were struggling to use the Britannica CDs, or to find a website on the internet about otters; and also with writing their reports on the computers. The things were so trouble-prone then - imagine being a little kid and thinking as they are supposed to that this project was a *big deal* and yet being unable to do anything. The librarian* in charge of the computer room and library wasn't so good as a troubleshooter; who would be when you've got two dozen kids? (The next year the district would supply a second old lady just for the computer room, and what a turf fight erupted then in that quiet precinct; it ended in the noble sacrifice of the school's eel, which was beloved of old lady #1 and the children, and turned out to be only rented with moms' club funds, in order to secure yet more CD-ROMs.)
I was only a sub and wouldn't have cared one way or another but the kids were like a bunch of cranky frustrated people at the DMV at that point. I was no help, having scarcely ever used a computer.
I suggested to the librarian that they might use the actual, physical Britannicas - something of a skill in itself, and one they had of course skipped in their short school careers - as the library was possessed of several sets across one wall, the proud purchase of another era though in fact they had a quite recent edition.
Oh no, they must use the computer, she said. Because they must have the most up-to-date information. They must benefit from the latest science on the internet.
I mildly suggested that I didn't think our understanding of raccoons had changed that much in the last couple years.
I then steered them to wikipedia, not realizing that our fearless technology-enforcer forbade the use of wikipedia in her library. She had thoughts about it; she knew (had heard somewhere) that it was "unsourced" and illegitimate.
I'm pretty sure it's completely cribbed from the Britannica, I said.
But school ladies, like AIs, always know best.
*She was crackerjack at maintaining an orderly, attractive library; at aquarium-keeping; at remembering young children's names and taking an interest in their selections; at reading aloud to the younger children; and she was good at and very much enjoyed writing celebratory poems for retiring school or district personnel.
Which interestingly is what AI is really crackerjack at as well - writing "occasional" poems, pastiches, sonnets about the ATP cycle and such.
The frequency of false facts confidently spit out as true will continue to babble ai—and continually remind us that they are not “thinking” in the ways humans think, nor lying in the ways nor for the reasons that humans lie.
Because they don’t know they’re lying when they say false stuff, they also don’t know when they’re not lying. They literally do not “know” what they’re talking about, they are trying to probabilistically simulate knowing.
This confirms my bias, strengthens my prior that LLMs will provide an ai front end UI that accepts questions, but then breaks down the task so as to give to, limited expert systems to come up with accurate answers, or partial answers including what is not known.
Not knowing, what is known vs what is not known, remains a hard limit for LLMs.
In the meantime, ai answers to questions that have known correct answers, like code creating, those ai tools will get better and enhance productivity. A good tweet said something like:
In a job interview for coding, they need to allow ai co-pilot support in order to understand how effective that coder can crank out code.
Ai access to all the public data & databases in the country should be improving the availability of obtaining data that is relevant for making decisions—but I haven’t seen this yet.
"I now think it’s increasingly likely that the first AI systems that can do advanced STEM R&D will cost more than paying for the equivalent work from human researchers."
It's not much more than a mention at [1:00:15]; but this episode discusses using AI beneficially in genetic research. Attia has talked about using AI in medical research in other episodes too.
Regarding optimism on AI and education, the other day Joanne Jacobs blogged about AI and cheating in school, citing a Chronicle of Higher Education article:
“’"Professors in writing-intensive courses, particularly those teaching introductory or general-education classes’ say ‘AI abuse has become pervasive,’ writes McMurtrie. ‘Clukey said she feels less like a teacher and more like a human plagiarism detector, spending hours each week analyzing her students’ writing to determine its authenticity.’”
(https://www.joannejacobs.com/post/is-everybody-cheating ) (as an aside one wonders if this might be related to another Jacobs’ blog post on an EdWeek survey that found “younger educators -- district and school leaders and teachers -- were more likely to back Trump than their older colleagues. ‘Forty-nine percent of respondents who labeled themselves as 'millennial or younger' said they would vote for Trump.’" (https://www.joannejacobs.com/post/young-teachers-like-trump ).
Curious, I searched “AI in education” on the Brave browser and the Brave AI returned the following:
“AI in Education
AI is transforming the education sector, offering numerous benefits for teachers, students, and institutions alike. Here’s a summary of the key aspects:
MagicSchool - AI Built for Schools
MagicSchool is a leading AI platform for educators, providing a “one-stop-shop” for AI needs. It offers:
AI-powered tools: 70+ AI tools for lesson planning, differentiation, assessment writing, and more.
Easy-to-use interface: Intuitive design with built-in safeguards, highlighting potential bias and emphasizing factual accuracy and privacy.
Interoperability: Integrates with LMS and easy exports to Google Classroom, Microsoft, and more.
Robust training resources: Includes training with “show an exemplar” in every tool, certification courses, video walkthroughs, and more.
AI Education Trends
Personalized learning: AI helps tailor education to individual students’ needs, abilities, and learning styles.
Intelligent tutoring systems: AI-powered chatbots and virtual assistants offer one-on-one support, supplementing human teachers.
Natural Language Processing (NLP): AI-enhanced language tools improve writing, reading, and communication skills.
Data-driven decision-making: AI analytics provide insights on student performance, helping educators identify areas for improvement.
Challenges and Concerns
Teacher training: Educators require upskilling to effectively integrate AI into their teaching practices.
Bias and ethics: AI systems must be designed with fairness, transparency, and accountability to avoid perpetuating biases.
Job displacement: AI may augment, but not replace, human teachers; educators must focus on high-value tasks.
Equity and access: AI education initiatives must prioritize inclusivity, ensuring equal access to AI-enhanced learning opportunities.
Real-World Examples
AI bird feeder: Middle school students in Maine use an AI bird feeder to learn about AI, data analysis, and environmental science.
AI-powered game: A California-based project develops an online game teaching high school students university-level AI and computational thinking concepts.
AI exhibit: Researchers at the University of Southern California and University of California, Berkeley, design an interactive AI exhibit for elementary-aged children.
aiEDU: Advancing AI Literacy and Readiness
aiEDU is a non-profit organization dedicated to ensuring all students are AI-ready. They provide research-based training experiences and curriculum for teachers, administrators, and nonprofits, focusing on AI literacy and readiness.
The Future of Learning: AI in Education 4.0
AI integration in education can streamline administrative tasks, giving teachers more time for meaningful student engagement. AI-assisted assessments offer valuable insights, and AI-powered tools can enhance teaching and learning. However, AI should augment, not replace, human teachers, and educators must prioritize equity and access in AI education initiatives.”
I suppose one might consider that reason for optimism but all the AI generated DEI blather in the AI response might also give someone pause as well. One might also get the impression that the AI in the classroom use cases are all about serving the teacher rather than the student. Interestingly in one experiment, AI augmented teaching was found not to be more effective than pure AI assistance. (https://www.sciencedirect.com/science/article/pii/S0360131523002440 ). Alleged “teacher shortage” solved? Perhaps the vindication for optimism about AI in education will be when AI allows school district teacher employment and payroll to be significantly slashed.
“I now think it’s increasingly likely that the first AI systems that can do advanced STEM R&D will cost more than paying for the equivalent work from human researchers.“
I have a feeling the same might be true for Arnold’s AI-grader idea. The AI grader can work for simple* cases, but can it work for important, and difficult cases such as grading Tyler Cowen’s newest essay in which he hypothetically argues that lock-downs are prudent for DIVOC just as they were for COVID?
Can an AI grader ever be smart enough to grade Tyler Cowen’s latest essay in regard to a topic that relies on new opinions and ideas that he has quietly been working on largely by himself?
I would say, yes, but compared to what? How much would it cost to develop such a grader? Are we talking Mission-to-Moon money? If so, can we all agree that we inherently dogmatic humans can probably do better to judge Tyler’s latest essay?
Footnotes
*But cheap labor is a substitute for simple and routine cases also, I.e. Immigrant labor for example.
Which one is Google? Is it bargain basement? It's the only one I interact with, albeit involuntarily, but last night in my usual fashion of typing a question, this time a quick thumbnail for determining the yardage needed if you are trying to switch to a different yarn class for a knitting pattern, depending how I phrased the question it included in its reasoning that worsted was thicker than dk (yes) and then in quick succession, that dk was thicker than worsted (no).
I know the work on these things is all very complicated, but I'm going to go out on a limb and say that knitting is a pretty settled science, which ought to be elementary for the AI.
I am reminded of - about 25 years ago? I'm a little fuzzy - shepherding some early grade school children through an assignment they'd been given - to do a project on a favorite animal, starting with "research" in the school library.
This was around when schools were easy targets, pretty early in their bumpy, largely naive, and of course utterly wasteful and ultimately totally deleterious journey purchasing "technology". All those hundreds of CD-ROMs, destined for the trash ...
The children (maybe 2nd grade?) were struggling to use the Britannica CDs, or to find a website on the internet about otters; and also with writing their reports on the computers. The things were so trouble-prone then - imagine being a little kid and thinking as they are supposed to that this project was a *big deal* and yet being unable to do anything. The librarian* in charge of the computer room and library wasn't so good as a troubleshooter; who would be when you've got two dozen kids? (The next year the district would supply a second old lady just for the computer room, and what a turf fight erupted then in that quiet precinct; it ended in the noble sacrifice of the school's eel, which was beloved of old lady #1 and the children, and turned out to be only rented with moms' club funds, in order to secure yet more CD-ROMs.)
I was only a sub and wouldn't have cared one way or another but the kids were like a bunch of cranky frustrated people at the DMV at that point. I was no help, having scarcely ever used a computer.
I suggested to the librarian that they might use the actual, physical Britannicas - something of a skill in itself, and one they had of course skipped in their short school careers - as the library was possessed of several sets across one wall, the proud purchase of another era though in fact they had a quite recent edition.
Oh no, they must use the computer, she said. Because they must have the most up-to-date information. They must benefit from the latest science on the internet.
I mildly suggested that I didn't think our understanding of raccoons had changed that much in the last couple years.
I then steered them to wikipedia, not realizing that our fearless technology-enforcer forbade the use of wikipedia in her library. She had thoughts about it; she knew (had heard somewhere) that it was "unsourced" and illegitimate.
I'm pretty sure it's completely cribbed from the Britannica, I said.
But school ladies, like AIs, always know best.
*She was crackerjack at maintaining an orderly, attractive library; at aquarium-keeping; at remembering young children's names and taking an interest in their selections; at reading aloud to the younger children; and she was good at and very much enjoyed writing celebratory poems for retiring school or district personnel.
Which interestingly is what AI is really crackerjack at as well - writing "occasional" poems, pastiches, sonnets about the ATP cycle and such.
The frequency of false facts confidently spit out as true will continue to babble ai—and continually remind us that they are not “thinking” in the ways humans think, nor lying in the ways nor for the reasons that humans lie.
Because they don’t know they’re lying when they say false stuff, they also don’t know when they’re not lying. They literally do not “know” what they’re talking about, they are trying to probabilistically simulate knowing.
This confirms my bias, strengthens my prior that LLMs will provide an ai front end UI that accepts questions, but then breaks down the task so as to give to, limited expert systems to come up with accurate answers, or partial answers including what is not known.
Not knowing, what is known vs what is not known, remains a hard limit for LLMs.
In the meantime, ai answers to questions that have known correct answers, like code creating, those ai tools will get better and enhance productivity. A good tweet said something like:
In a job interview for coding, they need to allow ai co-pilot support in order to understand how effective that coder can crank out code.
Ai access to all the public data & databases in the country should be improving the availability of obtaining data that is relevant for making decisions—but I haven’t seen this yet.
can anyone enlighten me as to the reason why Arnold titles his posts as LLM links? merci beaucoup!
LLM = Large Language Model
See some of Arnold’s non-LLM link posts:
https://arnoldkling.substack.com/p/links-to-consider-11162024
If you’re not big on ai, it’s nice to see what’s ignorable. I’m glad to know.
"I now think it’s increasingly likely that the first AI systems that can do advanced STEM R&D will cost more than paying for the equivalent work from human researchers."
It's not much more than a mention at [1:00:15]; but this episode discusses using AI beneficially in genetic research. Attia has talked about using AI in medical research in other episodes too.
https://peterattiamd.com/fengzhang/
Regarding optimism on AI and education, the other day Joanne Jacobs blogged about AI and cheating in school, citing a Chronicle of Higher Education article:
“’"Professors in writing-intensive courses, particularly those teaching introductory or general-education classes’ say ‘AI abuse has become pervasive,’ writes McMurtrie. ‘Clukey said she feels less like a teacher and more like a human plagiarism detector, spending hours each week analyzing her students’ writing to determine its authenticity.’”
(https://www.joannejacobs.com/post/is-everybody-cheating ) (as an aside one wonders if this might be related to another Jacobs’ blog post on an EdWeek survey that found “younger educators -- district and school leaders and teachers -- were more likely to back Trump than their older colleagues. ‘Forty-nine percent of respondents who labeled themselves as 'millennial or younger' said they would vote for Trump.’" (https://www.joannejacobs.com/post/young-teachers-like-trump ).
Curious, I searched “AI in education” on the Brave browser and the Brave AI returned the following:
“AI in Education
AI is transforming the education sector, offering numerous benefits for teachers, students, and institutions alike. Here’s a summary of the key aspects:
MagicSchool - AI Built for Schools
MagicSchool is a leading AI platform for educators, providing a “one-stop-shop” for AI needs. It offers:
AI-powered tools: 70+ AI tools for lesson planning, differentiation, assessment writing, and more.
Easy-to-use interface: Intuitive design with built-in safeguards, highlighting potential bias and emphasizing factual accuracy and privacy.
Interoperability: Integrates with LMS and easy exports to Google Classroom, Microsoft, and more.
Robust training resources: Includes training with “show an exemplar” in every tool, certification courses, video walkthroughs, and more.
AI Education Trends
Personalized learning: AI helps tailor education to individual students’ needs, abilities, and learning styles.
Automated grading: AI-assisted grading reduces teacher workload, providing timely feedback and improving assessment accuracy.
Intelligent tutoring systems: AI-powered chatbots and virtual assistants offer one-on-one support, supplementing human teachers.
Natural Language Processing (NLP): AI-enhanced language tools improve writing, reading, and communication skills.
Data-driven decision-making: AI analytics provide insights on student performance, helping educators identify areas for improvement.
Challenges and Concerns
Teacher training: Educators require upskilling to effectively integrate AI into their teaching practices.
Bias and ethics: AI systems must be designed with fairness, transparency, and accountability to avoid perpetuating biases.
Job displacement: AI may augment, but not replace, human teachers; educators must focus on high-value tasks.
Equity and access: AI education initiatives must prioritize inclusivity, ensuring equal access to AI-enhanced learning opportunities.
Real-World Examples
AI bird feeder: Middle school students in Maine use an AI bird feeder to learn about AI, data analysis, and environmental science.
AI-powered game: A California-based project develops an online game teaching high school students university-level AI and computational thinking concepts.
AI exhibit: Researchers at the University of Southern California and University of California, Berkeley, design an interactive AI exhibit for elementary-aged children.
aiEDU: Advancing AI Literacy and Readiness
aiEDU is a non-profit organization dedicated to ensuring all students are AI-ready. They provide research-based training experiences and curriculum for teachers, administrators, and nonprofits, focusing on AI literacy and readiness.
The Future of Learning: AI in Education 4.0
AI integration in education can streamline administrative tasks, giving teachers more time for meaningful student engagement. AI-assisted assessments offer valuable insights, and AI-powered tools can enhance teaching and learning. However, AI should augment, not replace, human teachers, and educators must prioritize equity and access in AI education initiatives.”
I suppose one might consider that reason for optimism but all the AI generated DEI blather in the AI response might also give someone pause as well. One might also get the impression that the AI in the classroom use cases are all about serving the teacher rather than the student. Interestingly in one experiment, AI augmented teaching was found not to be more effective than pure AI assistance. (https://www.sciencedirect.com/science/article/pii/S0360131523002440 ). Alleged “teacher shortage” solved? Perhaps the vindication for optimism about AI in education will be when AI allows school district teacher employment and payroll to be significantly slashed.
“I now think it’s increasingly likely that the first AI systems that can do advanced STEM R&D will cost more than paying for the equivalent work from human researchers.“
I have a feeling the same might be true for Arnold’s AI-grader idea. The AI grader can work for simple* cases, but can it work for important, and difficult cases such as grading Tyler Cowen’s newest essay in which he hypothetically argues that lock-downs are prudent for DIVOC just as they were for COVID?
Can an AI grader ever be smart enough to grade Tyler Cowen’s latest essay in regard to a topic that relies on new opinions and ideas that he has quietly been working on largely by himself?
I would say, yes, but compared to what? How much would it cost to develop such a grader? Are we talking Mission-to-Moon money? If so, can we all agree that we inherently dogmatic humans can probably do better to judge Tyler’s latest essay?
Footnotes
*But cheap labor is a substitute for simple and routine cases also, I.e. Immigrant labor for example.