Imhex: A hex editor for reverse engineers
457 by wsc981 | 97 comments on Hacker News.
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New best story on Hacker News: Show HN: I made a puzzle game that gently introduces my favorite math mysteries
Show HN: I made a puzzle game that gently introduces my favorite math mysteries
652 by MCSP | 127 comments on Hacker News.
This is the first iteration of a short game I’m making that tries to interactively explain some of my favorite math questions / ideas. My goal is mostly to get the player curious and not necessarily to explain absolutely everything. There were a lot of fun technical parts to building this: - For implementation reasons, it’s much easier if the lines all have integer intersection points with each other. To do this, when a new line is added I “cheat” by rounding intersections to integers and then splitting the old lines at the intersection into new linds (with potentially different slopes) going through the rounded point - I had to draw semi accurate maps of actual places (UK, South America, US west coast) in the HTML canvas using just line segments. I tried a few different solutions, including using SVG data. I ended up using the topojson library to give nice line approximations to GeoJSON maps - I use a simple backtracking algorithm to handle the live coloring of graphs - I use turf.js’s polygonize function to handle finding polygons from line segments (very happy I didn’t have to implement this myself!) - I wanted to make the game as mobile friendly as possible (don’t think I’ve nailed this quite yet) There were also a few tradeoffs I made: - I wanted give links earlier in the game for players to learn more, but I decided to wait until the end to maintain the flow of the game - In order to make the game more mobile-friendly, I generally stuck to maps with a small number of regions (at least for maps people have to interact with them). So for the most part all of the instances in the game are “easy”
652 by MCSP | 127 comments on Hacker News.
This is the first iteration of a short game I’m making that tries to interactively explain some of my favorite math questions / ideas. My goal is mostly to get the player curious and not necessarily to explain absolutely everything. There were a lot of fun technical parts to building this: - For implementation reasons, it’s much easier if the lines all have integer intersection points with each other. To do this, when a new line is added I “cheat” by rounding intersections to integers and then splitting the old lines at the intersection into new linds (with potentially different slopes) going through the rounded point - I had to draw semi accurate maps of actual places (UK, South America, US west coast) in the HTML canvas using just line segments. I tried a few different solutions, including using SVG data. I ended up using the topojson library to give nice line approximations to GeoJSON maps - I use a simple backtracking algorithm to handle the live coloring of graphs - I use turf.js’s polygonize function to handle finding polygons from line segments (very happy I didn’t have to implement this myself!) - I wanted to make the game as mobile friendly as possible (don’t think I’ve nailed this quite yet) There were also a few tradeoffs I made: - I wanted give links earlier in the game for players to learn more, but I decided to wait until the end to maintain the flow of the game - In order to make the game more mobile-friendly, I generally stuck to maps with a small number of regions (at least for maps people have to interact with them). So for the most part all of the instances in the game are “easy”
New best story on Hacker News: Show HN: We Made The World's Smallest and Cheapest Network Switch
Show HN: We Made The World's Smallest and Cheapest Network Switch
500 by Hello9999901 | 138 comments on Hacker News.
Hello, we're Max and Byran from MUREX Robotics, a high school robotics team from Exeter, New Hampshire. We are super proud to have made this open source piece of technology! It is only 6.9 dollars (actually!) from JLCPCB :) I hope you like it. You can find us at byran@mrx.ee and max@mrx.ee as well if you have any questions. We will be putting a small run of these boards for sale somewhere (we have <25 units of stock), probably for $10+shipping. Let us know if you're interested in more! Board files for everything we make is here: https://github.com/murexrobotics/electrical-2024
500 by Hello9999901 | 138 comments on Hacker News.
Hello, we're Max and Byran from MUREX Robotics, a high school robotics team from Exeter, New Hampshire. We are super proud to have made this open source piece of technology! It is only 6.9 dollars (actually!) from JLCPCB :) I hope you like it. You can find us at byran@mrx.ee and max@mrx.ee as well if you have any questions. We will be putting a small run of these boards for sale somewhere (we have <25 units of stock), probably for $10+shipping. Let us know if you're interested in more! Board files for everything we make is here: https://github.com/murexrobotics/electrical-2024
New best story on Hacker News: ARC Prize – a $1M+ competition towards open AGI progress
ARC Prize – a $1M+ competition towards open AGI progress
459 by mikeknoop | 211 comments on Hacker News.
Hey folks! Mike here. Francois Chollet and I are launching ARC Prize, a public competition to beat and open-source the solution to the ARC-AGI eval. ARC-AGI is (to our knowledge) the only eval which measures AGI: a system that can efficiently acquire new skill and solve novel, open-ended problems. Most AI evals measure skill directly vs the acquisition of new skill. Francois created the eval in 2019, SOTA was 20% at inception, SOTA today is only 34%. Humans score 85-100%. 300 teams attempted ARC-AGI last year and several bigger labs have attempted it. While most other skill-based evals have rapidly saturated to human-level, ARC-AGI was designed to resist “memorization” techniques (eg. LLMs) Solving ARC-AGI tasks is quite easy for humans (even children) but impossible for modern AI. You can try ARC-AGI tasks yourself here: https://ift.tt/RtGi5Ho ARC-AGI consists of 400 public training tasks, 400 public test tasks, and 100 secret test tasks. Every task is novel. SOTA is measured against the secret test set which adds to the robustness of the eval. Solving ARC-AGI tasks requires no world knowledge, no understanding of language. Instead each puzzle requires a small set of “core knowledge priors” (goal directedness, objectness, symmetry, rotation, etc.) At minimum, a solution to ARC-AGI opens up a completely new programming paradigm where programs can perfectly and reliably generalize from an arbitrary set of priors. At maximum, unlocks the tech tree towards AGI. Our goal with this competition is: 1. Increase the number of researchers working on frontier AGI research (vs tinkering with LLMs). We need new ideas and the solution is likely to come from an outsider! 2. Establish a popular, objective measure of AGI progress that the public can use to understand how close we are to AGI (or not). Every new SOTA score will be published here: https://x.com/arcprize 3. Beat ARC-AGI and learn something new about the nature of intelligence. Happy to answer questions!
459 by mikeknoop | 211 comments on Hacker News.
Hey folks! Mike here. Francois Chollet and I are launching ARC Prize, a public competition to beat and open-source the solution to the ARC-AGI eval. ARC-AGI is (to our knowledge) the only eval which measures AGI: a system that can efficiently acquire new skill and solve novel, open-ended problems. Most AI evals measure skill directly vs the acquisition of new skill. Francois created the eval in 2019, SOTA was 20% at inception, SOTA today is only 34%. Humans score 85-100%. 300 teams attempted ARC-AGI last year and several bigger labs have attempted it. While most other skill-based evals have rapidly saturated to human-level, ARC-AGI was designed to resist “memorization” techniques (eg. LLMs) Solving ARC-AGI tasks is quite easy for humans (even children) but impossible for modern AI. You can try ARC-AGI tasks yourself here: https://ift.tt/RtGi5Ho ARC-AGI consists of 400 public training tasks, 400 public test tasks, and 100 secret test tasks. Every task is novel. SOTA is measured against the secret test set which adds to the robustness of the eval. Solving ARC-AGI tasks requires no world knowledge, no understanding of language. Instead each puzzle requires a small set of “core knowledge priors” (goal directedness, objectness, symmetry, rotation, etc.) At minimum, a solution to ARC-AGI opens up a completely new programming paradigm where programs can perfectly and reliably generalize from an arbitrary set of priors. At maximum, unlocks the tech tree towards AGI. Our goal with this competition is: 1. Increase the number of researchers working on frontier AGI research (vs tinkering with LLMs). We need new ideas and the solution is likely to come from an outsider! 2. Establish a popular, objective measure of AGI progress that the public can use to understand how close we are to AGI (or not). Every new SOTA score will be published here: https://x.com/arcprize 3. Beat ARC-AGI and learn something new about the nature of intelligence. Happy to answer questions!
New best story on Hacker News: Show HN: I made a tiny camera with super long battery life
Show HN: I made a tiny camera with super long battery life
388 by davekeck | 156 comments on Hacker News.
Hey HN! A few years ago someone kept trying to steal my motorcycle, so I decided to make a small camera with really long battery life to catch them. The hardware/software is totally open source, but the companion app only supports macOS currently. (I'm a big fan of native apps, and didn't want to block releasing on Linux/Windows support.) I wrote some blog posts about the process: PCB design: https://ift.tt/vqZSR39 Enclosure design: https://ift.tt/q6zMiBu Image pipeline: https://ift.tt/8buOkid Rainproofing: https://ift.tt/DucUrHs Source: https://ift.tt/j9ayFH2
388 by davekeck | 156 comments on Hacker News.
Hey HN! A few years ago someone kept trying to steal my motorcycle, so I decided to make a small camera with really long battery life to catch them. The hardware/software is totally open source, but the companion app only supports macOS currently. (I'm a big fan of native apps, and didn't want to block releasing on Linux/Windows support.) I wrote some blog posts about the process: PCB design: https://ift.tt/vqZSR39 Enclosure design: https://ift.tt/q6zMiBu Image pipeline: https://ift.tt/8buOkid Rainproofing: https://ift.tt/DucUrHs Source: https://ift.tt/j9ayFH2
New best story on Hacker News: Show HN: Every mountain, building and tree shadow mapped for any date and time
Show HN: Every mountain, building and tree shadow mapped for any date and time
608 by tppiotrowski | 179 comments on Hacker News.
I've been working on this project for about 4 years. It began as terrain only because world wide elevation data was publicly available. I then added buildings from OpenStreetMap (crowd sourced) and more recently from Overture Maps data. Some computer vision/machine learning advancements [1] in the past few years have made it possible to estimate tree canopy heights using satellite imagery alone making it possible to finally add trees to the map. The data isn't perfect, but it's within +/- 3 meters of so. Good enough to give a general idea for any location on Earth. Happy to answer any questions. [1] https://ift.tt/U1V8lDr
608 by tppiotrowski | 179 comments on Hacker News.
I've been working on this project for about 4 years. It began as terrain only because world wide elevation data was publicly available. I then added buildings from OpenStreetMap (crowd sourced) and more recently from Overture Maps data. Some computer vision/machine learning advancements [1] in the past few years have made it possible to estimate tree canopy heights using satellite imagery alone making it possible to finally add trees to the map. The data isn't perfect, but it's within +/- 3 meters of so. Good enough to give a general idea for any location on Earth. Happy to answer any questions. [1] https://ift.tt/U1V8lDr
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