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495 by talonx | 126 comments on Hacker News.
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New best story on Hacker News: Show HN: I made a cheap alternative to college-level math & physics tutoring
Show HN: I made a cheap alternative to college-level math & physics tutoring
360 by eltonlin | 163 comments on Hacker News.
Hi everyone! I’m the founder of Explanations (https://ift.tt/Nsb2em6). I’m building a website where students can get college level math & physics help for 1/10th the cost of private tutoring. You’d type a question, and your teacher replies by drawing a Youtube/KhanAcademy-style video; and this happens asynchronously throughout the week. When I was studying at MIT, I often had to wait 40-60 minutes in line just to get 5 minutes of “help” from a TA - when I needed 1-2 hours. I understood that TAs can’t spend all their time helping me. That’s understandable. But what made me bitter was that, the school went the extra mile to ensure I don’t have the resources to learn on my own, 1. Blocking access to solutions for past problems (to prevent cheating) 2. Purposely not recording explanations to increase attendance: https://ift.tt/lWA26sV 3. Insisting that Office Hours is a 1-by-1 format even when crowded (to prevent solutions from leaking) These policies have good intentions - it’s to encourage a synchronous, in-person learning experience. But in practice, it had side-effects: 1. Help resources become inefficient - because so much material is restricted, and so much time is spent on delivering live lectures, there’d often be 40 students competing for help from 2 TAs in a 2-hour Office Hours 2. Because help resources are inefficient, it’s very hard to catch-up: once you fall behind, you have no way to review past material efficiently enough to compensate the difference - like credit card debt 3.Every day, I’d wake up, go to a lecture I don’t understand, go to Office Hours so I can hopefully ask for a review (which’d would take a few hours), realize TAs aren’t willing to do that, then realize there is nothing I can do to recover. I fell into a depression for many years, and my bitterness fueled me to work on the early versions of explanations.app It turns out that universities succeed by being prestigious, not by teaching well. To win at prestige, be highly selective (by keeping supply low), keep a huge endowment (because it affects school rankings), and hire the best researchers (not teachers). This is actually the fundamental reason for the odd incentives in higher education, and something felt wrong. So explanations.app is completely inspired by KhanAcademy and Youtube. The mystery to me was - why weren’t there more Youtube teachers & KhanAcademy videos? I believe it’s a combination of: 1. People who teach college subjects well often have better opportunities e.g. work, research 2. Lack of rewards: even Youtubers with 100K views and 10K subscribers would have at most 1-5 paying members on Patreon On the one hand, there are all these free resources, where teachers changed the world way more than they ever got rewarded for. Then on the other hand, there is private tutoring - very effective - but very expensive e.g. $100/hour for college level subjects. I believe the balanced solution is a system where lots of students pay $10/week to a few teachers who make videos, like a paid, Q&A Youtube/KhanAcademy, so it’s personalized, effective, but still affordable. There are currently 2 teachers on explanations.app - Ben & Esther - both MIT grads, teaching physics & math for subjects like linear algebra and electromagnetism. 3 students - Laquazia, Lidija and Chandra from US, Serbia and Korea joined this month following r/physicsStudents launch: [https://ift.tt/SPlH7Tt] While explanations.app is focused on college-level math and physics, the platform is completely open for anyone to learn and/or teach. I hope you can try it :^) and give me the chance to work with you.
360 by eltonlin | 163 comments on Hacker News.
Hi everyone! I’m the founder of Explanations (https://ift.tt/Nsb2em6). I’m building a website where students can get college level math & physics help for 1/10th the cost of private tutoring. You’d type a question, and your teacher replies by drawing a Youtube/KhanAcademy-style video; and this happens asynchronously throughout the week. When I was studying at MIT, I often had to wait 40-60 minutes in line just to get 5 minutes of “help” from a TA - when I needed 1-2 hours. I understood that TAs can’t spend all their time helping me. That’s understandable. But what made me bitter was that, the school went the extra mile to ensure I don’t have the resources to learn on my own, 1. Blocking access to solutions for past problems (to prevent cheating) 2. Purposely not recording explanations to increase attendance: https://ift.tt/lWA26sV 3. Insisting that Office Hours is a 1-by-1 format even when crowded (to prevent solutions from leaking) These policies have good intentions - it’s to encourage a synchronous, in-person learning experience. But in practice, it had side-effects: 1. Help resources become inefficient - because so much material is restricted, and so much time is spent on delivering live lectures, there’d often be 40 students competing for help from 2 TAs in a 2-hour Office Hours 2. Because help resources are inefficient, it’s very hard to catch-up: once you fall behind, you have no way to review past material efficiently enough to compensate the difference - like credit card debt 3.Every day, I’d wake up, go to a lecture I don’t understand, go to Office Hours so I can hopefully ask for a review (which’d would take a few hours), realize TAs aren’t willing to do that, then realize there is nothing I can do to recover. I fell into a depression for many years, and my bitterness fueled me to work on the early versions of explanations.app It turns out that universities succeed by being prestigious, not by teaching well. To win at prestige, be highly selective (by keeping supply low), keep a huge endowment (because it affects school rankings), and hire the best researchers (not teachers). This is actually the fundamental reason for the odd incentives in higher education, and something felt wrong. So explanations.app is completely inspired by KhanAcademy and Youtube. The mystery to me was - why weren’t there more Youtube teachers & KhanAcademy videos? I believe it’s a combination of: 1. People who teach college subjects well often have better opportunities e.g. work, research 2. Lack of rewards: even Youtubers with 100K views and 10K subscribers would have at most 1-5 paying members on Patreon On the one hand, there are all these free resources, where teachers changed the world way more than they ever got rewarded for. Then on the other hand, there is private tutoring - very effective - but very expensive e.g. $100/hour for college level subjects. I believe the balanced solution is a system where lots of students pay $10/week to a few teachers who make videos, like a paid, Q&A Youtube/KhanAcademy, so it’s personalized, effective, but still affordable. There are currently 2 teachers on explanations.app - Ben & Esther - both MIT grads, teaching physics & math for subjects like linear algebra and electromagnetism. 3 students - Laquazia, Lidija and Chandra from US, Serbia and Korea joined this month following r/physicsStudents launch: [https://ift.tt/SPlH7Tt] While explanations.app is focused on college-level math and physics, the platform is completely open for anyone to learn and/or teach. I hope you can try it :^) and give me the chance to work with you.
New best story on Hacker News: Launch HN: Aqua Voice (YC W24) – Voice-driven text editor
Launch HN: Aqua Voice (YC W24) – Voice-driven text editor
373 by the_king | 127 comments on Hacker News.
Hey HN! We’re Jack and Finn from Aqua Voice ( https://withaqua.com/ ). Aqua is a voice-native document editor that combines reliable dictation and natural language commands, letting you say things like: “make this a list” or “it’s Erin with an E” or “add an inline citation here for page 86 of this book”. Here is a demo: https://youtu.be/qwSAKg1YafM . Finn, who is big-time dyslexic, has been using dictation software since the sixth grade when his dad set him up on Dragon Dictation. He used it through school to write papers, and has been keeping his own transcription benchmarks since college. All that time, writing with your voice has remained a cumbersome and brittle experience that is riddled with painpoints. Dictation software is still terrible. All the solutions basically compete on accuracy (i.e. speech recognition), but none of them deal with the fundamentally brittle nature of the text that they generate. They don't try to format text correctly and require you to learn a bunch of specialized commands, which often are not worth it. They're not even close to a voice replacement for a keyboard. Even post LLM, you are limited to a set of specific commands and the most accurate models don’t have any commands. Outside of these rules, the models have no sense for what is an instruction and what is content. You can’t say “and format this like an email” or “make the last bullet point shorter”. Aqua solves this. This problem is important to Finn and millions of other people who would write with their voice if they could. Initially, we didn't think of it as a startup project. It was just something we wanted for ourselves. We thought maybe we'd write a novel with it - or something. After friends started asking to use the early versions of Aqua, it occurred to us that, if we didn't build it, maybe nobody would. Aqua Voice is a text editor that you talk to like a person. Depending on the way that you say it and the context in which you're operating, Aqua decides whether to transcribe what you said verbatim, execute a command, or subtly modify what you said into what you meant to write. For example, if you were to dictate: "Gryphons have classic forms resembling shield volcanoes," Aqua would output your text verbatim. But if you stumble over your words or start a sentence over a few times, Aqua is smart enough to figure that out and to only take the last version of the sentence. The vision is not only to provide a more natural dictation experience, but to enable for the first time an AI-writing experience that feels natural and collaborative. This requires moving away from using LLMs for one-off chat requests and towards something that is more like streaming where you are in constant contact with the model. Voice is the natural medium for this. Aqua is actually 6 models working together to transcribe, interpret, and rewrite the document according to your intent. Technically, executing a real-time voice application with a language model at its core requires complex coordination between multiple pieces. We use MoE transcription to outperform what was previously thought possible in terms of real-time accuracy. Then we sync up with a language model to determine what should be on the screen as quickly as possible. The model isn't perfect, but it is ready for early adopters and we’ve already been getting feedback from grateful users. For example, a historian with carpal tunnel sent us an email he wrote using Aqua and said that he is now able to be five times as productive as he was previously. We've heard from other people with disabilities that prevent them from typing. We've also seen good adoption from people who are dyslexic or simply prefer talking to typing. It’s being used for everything from emails to brainstorming to papers to legal briefings. While there is much left to do in terms of latency and robustness, the best experiences with Aqua are beginning to feel magical. We would love for you to try it out and give us feedback, which you can do with no account on https://withaqua.com . If you find it useful, it’s $10/month after a 1000-token free trial. (We want to bump the free trial in the future, but we're a small team, and running this thing isn’t cheap.) We’d love to hear your ideas and comments with voice-to-text!
373 by the_king | 127 comments on Hacker News.
Hey HN! We’re Jack and Finn from Aqua Voice ( https://withaqua.com/ ). Aqua is a voice-native document editor that combines reliable dictation and natural language commands, letting you say things like: “make this a list” or “it’s Erin with an E” or “add an inline citation here for page 86 of this book”. Here is a demo: https://youtu.be/qwSAKg1YafM . Finn, who is big-time dyslexic, has been using dictation software since the sixth grade when his dad set him up on Dragon Dictation. He used it through school to write papers, and has been keeping his own transcription benchmarks since college. All that time, writing with your voice has remained a cumbersome and brittle experience that is riddled with painpoints. Dictation software is still terrible. All the solutions basically compete on accuracy (i.e. speech recognition), but none of them deal with the fundamentally brittle nature of the text that they generate. They don't try to format text correctly and require you to learn a bunch of specialized commands, which often are not worth it. They're not even close to a voice replacement for a keyboard. Even post LLM, you are limited to a set of specific commands and the most accurate models don’t have any commands. Outside of these rules, the models have no sense for what is an instruction and what is content. You can’t say “and format this like an email” or “make the last bullet point shorter”. Aqua solves this. This problem is important to Finn and millions of other people who would write with their voice if they could. Initially, we didn't think of it as a startup project. It was just something we wanted for ourselves. We thought maybe we'd write a novel with it - or something. After friends started asking to use the early versions of Aqua, it occurred to us that, if we didn't build it, maybe nobody would. Aqua Voice is a text editor that you talk to like a person. Depending on the way that you say it and the context in which you're operating, Aqua decides whether to transcribe what you said verbatim, execute a command, or subtly modify what you said into what you meant to write. For example, if you were to dictate: "Gryphons have classic forms resembling shield volcanoes," Aqua would output your text verbatim. But if you stumble over your words or start a sentence over a few times, Aqua is smart enough to figure that out and to only take the last version of the sentence. The vision is not only to provide a more natural dictation experience, but to enable for the first time an AI-writing experience that feels natural and collaborative. This requires moving away from using LLMs for one-off chat requests and towards something that is more like streaming where you are in constant contact with the model. Voice is the natural medium for this. Aqua is actually 6 models working together to transcribe, interpret, and rewrite the document according to your intent. Technically, executing a real-time voice application with a language model at its core requires complex coordination between multiple pieces. We use MoE transcription to outperform what was previously thought possible in terms of real-time accuracy. Then we sync up with a language model to determine what should be on the screen as quickly as possible. The model isn't perfect, but it is ready for early adopters and we’ve already been getting feedback from grateful users. For example, a historian with carpal tunnel sent us an email he wrote using Aqua and said that he is now able to be five times as productive as he was previously. We've heard from other people with disabilities that prevent them from typing. We've also seen good adoption from people who are dyslexic or simply prefer talking to typing. It’s being used for everything from emails to brainstorming to papers to legal briefings. While there is much left to do in terms of latency and robustness, the best experiences with Aqua are beginning to feel magical. We would love for you to try it out and give us feedback, which you can do with no account on https://withaqua.com . If you find it useful, it’s $10/month after a 1000-token free trial. (We want to bump the free trial in the future, but we're a small team, and running this thing isn’t cheap.) We’d love to hear your ideas and comments with voice-to-text!
New best story on Hacker News: Show HN: Glossarie – a new, immersive way to learn a language
Show HN: Glossarie – a new, immersive way to learn a language
346 by jonathanb88 | 150 comments on Hacker News.
Hi HN, For over two years I've been working on an App to learn languages (currently French, Italian and Spanish), together with my partner, a language teacher. I think it is finally ready to share with this community! The idea is to introduce vocabulary and grammar whilst you read eBooks in your own language. I've found that it is easier to remember vocabulary 'in context' and with regular repetition. Plus you don't have to carve out dedicated time for language learning. Other apps require you to build a habit around various exercises or ‘games’, whereas lots of people already read books. From testing with early users so far it's proving effective for building a basic understanding of a language and quickly getting to the point where you can read and broadly understand text in the target language. It’s even better in combination with other apps that help with listening/speaking like Pimsleur. There were lots of technical challenges making this. It turned out to be (reassuringly) hard to get accuracy to an acceptable level, requiring a rabbit-hole into machine translation. There was a lot of testing required to optimise the engine that chooses the translations to show and to reduce the friction when reading books. And the backend to support uploading books is a beast in itself. I’d love to share details if there is interest. Roadmap - Accuracy - 100% accuracy is the target, but at present there can be errors. Feedback from users will be important here so that accuracy issues can be generalised and solved at scale. Errors can be reported within the app - please do so if you spot anything! - Dynamic difficulty - rather than have a progression of difficulty levels I’d prefer to introduce vocabulary and grammar automatically in response to user progress, balancing against the friction of seeing unfamiliar words. There’s a lot ‘under the hood’ to manage this today, but plenty of room to improve. - More practice features - to reinforce vocabulary/grammar and support writing, listening and speaking. - Better eBook support - improving the formatting of eBooks within the app and providing more methods for finding good books to read. Use of AI - LLMs provided a step change in accuracy and have enabled a feature that explains translations and grammar to the user - vastly improving the utility versus a year ago. - I believe apps like this, which use AI to enhance or scale functionality rather than simply acting as a wrapper over APIs, will be the major beneficiaries as LLMs improve. Take a look, and let me know your thoughts or questions!
346 by jonathanb88 | 150 comments on Hacker News.
Hi HN, For over two years I've been working on an App to learn languages (currently French, Italian and Spanish), together with my partner, a language teacher. I think it is finally ready to share with this community! The idea is to introduce vocabulary and grammar whilst you read eBooks in your own language. I've found that it is easier to remember vocabulary 'in context' and with regular repetition. Plus you don't have to carve out dedicated time for language learning. Other apps require you to build a habit around various exercises or ‘games’, whereas lots of people already read books. From testing with early users so far it's proving effective for building a basic understanding of a language and quickly getting to the point where you can read and broadly understand text in the target language. It’s even better in combination with other apps that help with listening/speaking like Pimsleur. There were lots of technical challenges making this. It turned out to be (reassuringly) hard to get accuracy to an acceptable level, requiring a rabbit-hole into machine translation. There was a lot of testing required to optimise the engine that chooses the translations to show and to reduce the friction when reading books. And the backend to support uploading books is a beast in itself. I’d love to share details if there is interest. Roadmap - Accuracy - 100% accuracy is the target, but at present there can be errors. Feedback from users will be important here so that accuracy issues can be generalised and solved at scale. Errors can be reported within the app - please do so if you spot anything! - Dynamic difficulty - rather than have a progression of difficulty levels I’d prefer to introduce vocabulary and grammar automatically in response to user progress, balancing against the friction of seeing unfamiliar words. There’s a lot ‘under the hood’ to manage this today, but plenty of room to improve. - More practice features - to reinforce vocabulary/grammar and support writing, listening and speaking. - Better eBook support - improving the formatting of eBooks within the app and providing more methods for finding good books to read. Use of AI - LLMs provided a step change in accuracy and have enabled a feature that explains translations and grammar to the user - vastly improving the utility versus a year ago. - I believe apps like this, which use AI to enhance or scale functionality rather than simply acting as a wrapper over APIs, will be the major beneficiaries as LLMs improve. Take a look, and let me know your thoughts or questions!
New best story on Hacker News: Show HN: Memories – FOSS Google Photos alternative built for high performance
Show HN: Memories – FOSS Google Photos alternative built for high performance
690 by radialapps | 201 comments on Hacker News.
Memories is a FOSS Google Photos alternative that you can self-host (it runs as a Nextcloud plugin). Website: https://ift.tt/0ZCt5yF GitHub: https://ift.tt/GcopjPy Demo Server: https://ift.tt/L7xDe5U (demo runs in San Francisco on a free-tier cloud vm) Memories has been built ground-up for high performance and is extremely fast when configured correctly. In our testing environment, it can load a timeline view with 100k photos in under 500ms, including query and rendering time! Some features to highlight: * A timeline similar to Google Photos where you can skip to any time in history instantly. * AI-based tagging that runs locally on your server, identifying and tagging people and objects. * Albums and external sharing. * Metadata editing support * A world map of your photos, supported both on mobile and the web * Did I mention it's extremely fast? Would love to hear feedback from the HN community! :)
690 by radialapps | 201 comments on Hacker News.
Memories is a FOSS Google Photos alternative that you can self-host (it runs as a Nextcloud plugin). Website: https://ift.tt/0ZCt5yF GitHub: https://ift.tt/GcopjPy Demo Server: https://ift.tt/L7xDe5U (demo runs in San Francisco on a free-tier cloud vm) Memories has been built ground-up for high performance and is extremely fast when configured correctly. In our testing environment, it can load a timeline view with 100k photos in under 500ms, including query and rendering time! Some features to highlight: * A timeline similar to Google Photos where you can skip to any time in history instantly. * AI-based tagging that runs locally on your server, identifying and tagging people and objects. * Albums and external sharing. * Metadata editing support * A world map of your photos, supported both on mobile and the web * Did I mention it's extremely fast? Would love to hear feedback from the HN community! :)
New best story on Hacker News: Ask HN: Do you also marvel at the complexity of everyday objects?
Ask HN: Do you also marvel at the complexity of everyday objects?
423 by parpfish | 297 comments on Hacker News.
A few weeks ago I was doing some soldering and I started using a spool of insulated 22-gauge wire. Maybe it was the solder fumes, but I started thinking about what it actually took to create that spool of wire -- everything from the geologists and miners extracting ore, through all the metallurgy, industrial engineering, and plastics work. And I started to marvel at all the work and expertise it took to make something that I normally would've just considered a semi-disposable consumable item. It made me wonder whether that spool of wire was actually a piece of technology on par in sophistication with all the software that I build every day. It was such an odd moment, but it's has caused a lasting perspective shift. almost every day I'll look at some commonplace object I took for granted and think "this is actually so complex, no single human has all the knowledge or expertise to create it". I'm curious if anybody else has had a similar experience and/or what are some simple everyday objects that give you pause when you stop to think about their complexity
423 by parpfish | 297 comments on Hacker News.
A few weeks ago I was doing some soldering and I started using a spool of insulated 22-gauge wire. Maybe it was the solder fumes, but I started thinking about what it actually took to create that spool of wire -- everything from the geologists and miners extracting ore, through all the metallurgy, industrial engineering, and plastics work. And I started to marvel at all the work and expertise it took to make something that I normally would've just considered a semi-disposable consumable item. It made me wonder whether that spool of wire was actually a piece of technology on par in sophistication with all the software that I build every day. It was such an odd moment, but it's has caused a lasting perspective shift. almost every day I'll look at some commonplace object I took for granted and think "this is actually so complex, no single human has all the knowledge or expertise to create it". I'm curious if anybody else has had a similar experience and/or what are some simple everyday objects that give you pause when you stop to think about their complexity
New best story on Hacker News: Fine tune a 70B language model at home
Fine tune a 70B language model at home
606 by jph00 | 146 comments on Hacker News.
Jeremy from Answer.AI here. This is our first project since launching our new R&D lab at the start of this year. It's the #1 most requested thing I've been hearing from open source model builders: the ability to use multiple GPUs with QLoRA training. So that's why we decided to make it our first project. Huge thanks to Tim Dettmers for helping us get started to this -- and of course for creating QLoRA in the first place! Let me know if you have any questions or thoughts.
606 by jph00 | 146 comments on Hacker News.
Jeremy from Answer.AI here. This is our first project since launching our new R&D lab at the start of this year. It's the #1 most requested thing I've been hearing from open source model builders: the ability to use multiple GPUs with QLoRA training. So that's why we decided to make it our first project. Huge thanks to Tim Dettmers for helping us get started to this -- and of course for creating QLoRA in the first place! Let me know if you have any questions or thoughts.
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