Buy, Borrow, Die – Explained
23 by nkurz | 9 comments on Hacker News.
Saturday, 31 August 2024
Friday, 30 August 2024
Man accused of child sex offense worked with vulnerable students at a local SC school
from Yahoo News - Latest News & Headlines https://ift.tt/TOnwdXy
Thursday, 29 August 2024
New top story on Hacker News: Show HN: A discovery-focused search engine for Hacker News
Show HN: A discovery-focused search engine for Hacker News
20 by skeptrune | 5 comments on Hacker News.
We (Nick, Dens, Denzell, Fede, Drew, Aaryan, and Daniel) have been building HN Discovery, a discovery-focused search engine for Hacker News, in our spare time for the past 6 months and are excited to show it! It adds the following features relative to the existing keyword search interface and preserves the existing ones: - no-JS version (hnnojs.trieve.ai) - site:{required_site} and site:{negated-site} filters - public analytics - LLM generated query suggestions based on random stories - recommendations - dense vector semantic search - SPLADE fulltext search - RAG AI chat - order by descendant count client code (FOSS self-hostable) - https://ift.tt/p8Ritoj engine code (BSL source-available) - https://ift.tt/t6DRS5N There is an extended about page with detailed information on features, how much it costs to run, etc. here - https://ift.tt/N3zgJuw .
20 by skeptrune | 5 comments on Hacker News.
We (Nick, Dens, Denzell, Fede, Drew, Aaryan, and Daniel) have been building HN Discovery, a discovery-focused search engine for Hacker News, in our spare time for the past 6 months and are excited to show it! It adds the following features relative to the existing keyword search interface and preserves the existing ones: - no-JS version (hnnojs.trieve.ai) - site:{required_site} and site:{negated-site} filters - public analytics - LLM generated query suggestions based on random stories - recommendations - dense vector semantic search - SPLADE fulltext search - RAG AI chat - order by descendant count client code (FOSS self-hostable) - https://ift.tt/p8Ritoj engine code (BSL source-available) - https://ift.tt/t6DRS5N There is an extended about page with detailed information on features, how much it costs to run, etc. here - https://ift.tt/N3zgJuw .
Wednesday, 28 August 2024
New top story on Hacker News: Show HN: Shed Light on Your Go Binary Bloat with Go Size Analyzer
Show HN: Shed Light on Your Go Binary Bloat with Go Size Analyzer
12 by zxilly | 1 comments on Hacker News.
I've created a powerful tool to help Go developers uncover the hidden giants in their compiled binaries. Go Size Analyzer is like an X-ray machine for your Go executables, revealing: Which dependencies are eating up your binary size Unexpected bloat from standard library or vendor packages Size changes between binary versions with a visual diff Key features that set it apart: Interactive treemap visualizations (check out the demo: https://gsa.zxilly.dev ) Slick terminal UI for deep diving into package hierarchies Cross-platform support (works on Linux, macOS, and Windows binaries) Export to SVG for easy sharing and documentation or just visualize the CI process Whether you're optimizing for edge devices, reducing Docker image sizes, or just curious about what's really inside your Go binaries, this tool provides detailed insights. .
12 by zxilly | 1 comments on Hacker News.
I've created a powerful tool to help Go developers uncover the hidden giants in their compiled binaries. Go Size Analyzer is like an X-ray machine for your Go executables, revealing: Which dependencies are eating up your binary size Unexpected bloat from standard library or vendor packages Size changes between binary versions with a visual diff Key features that set it apart: Interactive treemap visualizations (check out the demo: https://gsa.zxilly.dev ) Slick terminal UI for deep diving into package hierarchies Cross-platform support (works on Linux, macOS, and Windows binaries) Export to SVG for easy sharing and documentation or just visualize the CI process Whether you're optimizing for edge devices, reducing Docker image sizes, or just curious about what's really inside your Go binaries, this tool provides detailed insights. .
Tuesday, 27 August 2024
Monday, 26 August 2024
This former Credit Suisse exec says Americans should ‘never quit’ their jobs if they’re unhappy — do this instead
from Yahoo News - Latest News & Headlines https://ift.tt/2RcVtlg
Sunday, 25 August 2024
Saturday, 24 August 2024
Friday, 23 August 2024
Woman in Southern California goes on violent rampage against firefighter, police
from Yahoo News - Latest News & Headlines https://ift.tt/pRbsL8E
Thursday, 22 August 2024
Surfer Tackled and Arrested in New Jersey for Not Displaying Beach Tag, Reports Say
from Yahoo News - Latest News & Headlines https://ift.tt/2j5GHoM
Wednesday, 21 August 2024
Tuesday, 20 August 2024
Monday, 19 August 2024
New top story on Hacker News: Launch HN: Sorcerer (YC S24) – Weather balloons that collect more data
Launch HN: Sorcerer (YC S24) – Weather balloons that collect more data
75 by tndl | 30 comments on Hacker News.
Hey HN! We’re Max, Alex, and Austin, the team behind Sorcerer ( https://sorcerer.earth ). Sorcerer builds weather balloons that last for over six months, collecting 1000x more data per dollar and reaching previously inaccessible regions. In 1981, weather disasters caused $3.5 billion in damages in the United States. In 2023, that number was $94.9 billion ( https://ift.tt/MXtdyrJ ). The National Weather Service spends billions annually on its network of weather balloons, satellites, and aircraft sensors – generating hundreds of terabytes of data every day. This data, called observation data, is fed into massive supercomputers running advanced physics to produce global weather forecasts. Despite this cost, there are still places in the US where we don't know what the temperature will be two days from now: https://ift.tt/8oMeNbq... . And for the rest of the world that lacks weather infrastructure? There’s always the Weather Rock: https://ift.tt/uS7ECbQ . The most important data for these forecasts come from vertical data ‘slices’ of the atmosphere, called soundings. Every day 2,500 single-use latex radiosondes are launched across the globe to collect these soundings. They stay aloft for about two hours before popping and falling back to Earth. Launch sites for these systems are sparse in Latin America and Africa, and they’re completely non-existent over oceans. This leaves about 80% of the globe with inadequate weather data for accurate predictions. The coverage gap became painfully evident to Max and Alex during their time at Urban Sky. While building balloons for high-altitude aerial imaging, they kept running into a problem: no matter what weather forecast they used, they couldn’t get accurate wind predictions for the upper atmosphere. They tried all of the free and commercial forecast products, but none of them were accurate enough. Digging into it more, we learned that a big part of the problem was the lack of high-quality in-situ data at those altitudes. To solve this problem, our systems ascend and descend between sea level and 65,000ft several times a day to collect vertical data soundings. Each vehicle (balloon + payload) weighs less than a pound and can be launched from anywhere in the world, per the FAA and ICAO reg. Here’s one we launched from Potrero Hill in SF, https://youtu.be/75fN5WpRWH0 and here’s another near the Golden Gate Bridge, https://youtu.be/7yLmzLPUFVQ . Although we can’t “drive” these balloons laterally, we can use opposing wind layers to target or avoid specific regions. Here’s what a few simulated flight paths look like, to give you an idea: https://youtu.be/F_Di8cjaEUY Our payload uses a satellite transceiver for communications and a small, thin film solar panel array to generate power. In addition to the weather data, we also get real-time telemetry from the vehicles, which we use to optimize their flight paths. This includes maintaining the optimal spacing between balloons and steering them to a recovery zone at the end of their lifespan so we can recycle them. These systems spend most of their time in the stratosphere which is an extremely unforgiving environment. We’ll often see temperatures as low as -80°C while flying near the equator. Throughout the day, we experience extreme temperature cycling as they ascend and descend through the atmosphere. We’ll often encounter 100mph+ wind shears near the boundary with the troposphere (the tropopause) that can rip apart the balloon envelope. These conditions make the stratosphere a very difficult place to deploy to prod. The real magic of what we’re building will come into play when we have hundreds of these systems in the air over data-sparse regions. But even now, we can do useful and interesting things with them. Some of our early customers are companies who fly very big, very expensive things into the stratosphere. They use our balloons to give them a clear idea of what conditions are ahead of their operations, and we’re working on a forecast product specifically designed for the stratosphere. The combination of long duration and low cost is novel. We can theoretically maintain thousands of balloons in the atmosphere at any given time for a tenth of the cost of one useful weather satellite. We’re also using the data we collect to train AI models that produce forecasts with better accuracy than existing numerical (supercomputer) forecasts. Because we’re collecting totally unique data over areas that lack observation, our models will maintain a consistent edge versus models that are only trained on open data. We’re really excited to be launching Sorcerer here with you! We’d love to hear what you think. And if you find one of our balloons in the Bay Area: Sorry! It’s still a work in progress (and please get it back to us). I’ll leave you all with a bonus video of Paul Buchheit launching one of our balloons, which we thought was pretty cool: https://www.youtube.com/watch?v=-sngF9VvDzg
75 by tndl | 30 comments on Hacker News.
Hey HN! We’re Max, Alex, and Austin, the team behind Sorcerer ( https://sorcerer.earth ). Sorcerer builds weather balloons that last for over six months, collecting 1000x more data per dollar and reaching previously inaccessible regions. In 1981, weather disasters caused $3.5 billion in damages in the United States. In 2023, that number was $94.9 billion ( https://ift.tt/MXtdyrJ ). The National Weather Service spends billions annually on its network of weather balloons, satellites, and aircraft sensors – generating hundreds of terabytes of data every day. This data, called observation data, is fed into massive supercomputers running advanced physics to produce global weather forecasts. Despite this cost, there are still places in the US where we don't know what the temperature will be two days from now: https://ift.tt/8oMeNbq... . And for the rest of the world that lacks weather infrastructure? There’s always the Weather Rock: https://ift.tt/uS7ECbQ . The most important data for these forecasts come from vertical data ‘slices’ of the atmosphere, called soundings. Every day 2,500 single-use latex radiosondes are launched across the globe to collect these soundings. They stay aloft for about two hours before popping and falling back to Earth. Launch sites for these systems are sparse in Latin America and Africa, and they’re completely non-existent over oceans. This leaves about 80% of the globe with inadequate weather data for accurate predictions. The coverage gap became painfully evident to Max and Alex during their time at Urban Sky. While building balloons for high-altitude aerial imaging, they kept running into a problem: no matter what weather forecast they used, they couldn’t get accurate wind predictions for the upper atmosphere. They tried all of the free and commercial forecast products, but none of them were accurate enough. Digging into it more, we learned that a big part of the problem was the lack of high-quality in-situ data at those altitudes. To solve this problem, our systems ascend and descend between sea level and 65,000ft several times a day to collect vertical data soundings. Each vehicle (balloon + payload) weighs less than a pound and can be launched from anywhere in the world, per the FAA and ICAO reg. Here’s one we launched from Potrero Hill in SF, https://youtu.be/75fN5WpRWH0 and here’s another near the Golden Gate Bridge, https://youtu.be/7yLmzLPUFVQ . Although we can’t “drive” these balloons laterally, we can use opposing wind layers to target or avoid specific regions. Here’s what a few simulated flight paths look like, to give you an idea: https://youtu.be/F_Di8cjaEUY Our payload uses a satellite transceiver for communications and a small, thin film solar panel array to generate power. In addition to the weather data, we also get real-time telemetry from the vehicles, which we use to optimize their flight paths. This includes maintaining the optimal spacing between balloons and steering them to a recovery zone at the end of their lifespan so we can recycle them. These systems spend most of their time in the stratosphere which is an extremely unforgiving environment. We’ll often see temperatures as low as -80°C while flying near the equator. Throughout the day, we experience extreme temperature cycling as they ascend and descend through the atmosphere. We’ll often encounter 100mph+ wind shears near the boundary with the troposphere (the tropopause) that can rip apart the balloon envelope. These conditions make the stratosphere a very difficult place to deploy to prod. The real magic of what we’re building will come into play when we have hundreds of these systems in the air over data-sparse regions. But even now, we can do useful and interesting things with them. Some of our early customers are companies who fly very big, very expensive things into the stratosphere. They use our balloons to give them a clear idea of what conditions are ahead of their operations, and we’re working on a forecast product specifically designed for the stratosphere. The combination of long duration and low cost is novel. We can theoretically maintain thousands of balloons in the atmosphere at any given time for a tenth of the cost of one useful weather satellite. We’re also using the data we collect to train AI models that produce forecasts with better accuracy than existing numerical (supercomputer) forecasts. Because we’re collecting totally unique data over areas that lack observation, our models will maintain a consistent edge versus models that are only trained on open data. We’re really excited to be launching Sorcerer here with you! We’d love to hear what you think. And if you find one of our balloons in the Bay Area: Sorry! It’s still a work in progress (and please get it back to us). I’ll leave you all with a bonus video of Paul Buchheit launching one of our balloons, which we thought was pretty cool: https://www.youtube.com/watch?v=-sngF9VvDzg
Sunday, 18 August 2024
Saturday, 17 August 2024
Friday, 16 August 2024
Thursday, 15 August 2024
One of Honolulu’s oldest roads speaks of a significant battle
from Yahoo News - Latest News & Headlines https://ift.tt/G5VKJyE
Wednesday, 14 August 2024
Tuesday, 13 August 2024
Monday, 12 August 2024
Sunday, 11 August 2024
Community members mourn loss of Arkansas Drug Task Force agent who leaves behind infant daughter
from Yahoo News - Latest News & Headlines https://ift.tt/qklC7h8
Saturday, 10 August 2024
Friday, 9 August 2024
Assemi family member trying to block sale of $2 billion California farming empire
from Yahoo News - Latest News & Headlines https://ift.tt/OE19wsA
Thursday, 8 August 2024
Wednesday, 7 August 2024
Tuesday, 6 August 2024
New top story on Hacker News: Show HN: Datoviz – Vulkan-based GPU scientific visualization (C/C++/Python)
Show HN: Datoviz – Vulkan-based GPU scientific visualization (C/C++/Python)
16 by rossant | 0 comments on Hacker News.
I'm excited to announce the release of Datoviz 0.2.0, an open-source, high-performance GPU scientific visualization library built on Vulkan. It targets the interactive visualization of large 2D/3D datasets. This version includes tentative precompiled Python wheels for Linux, macOS (ARM and Intel), and Windows. Datoviz is a key part of the CZI-funded Vispy 2.0 project and will serve as its main GPU backend. Datoviz provides core GPU visualization capabilities while VisPy 2.0 will provide high-level plotting functionality (a bit similar to NumPy vs SciPy). What I'm looking for from the community: 1. Compatibility feedback: I'd appreciate quick feedback on how these precompiled Python wheels perform across different operating systems and graphics hardware. 2. Library feedback: Datoviz is still in its early stages and actively evolving. The API is subject to change, and I'd appreciate any feedback on its functionality and design. Please report issues on GitHub. Since the initial 2021 v0.1 release, the underlying technology has matured significantly. The internal architecture is now more robust and modular, paving the way for support for other rendering technologies like WebGPU and WebAssembly in the medium term. While still somewhat limited, the focus is on ensuring stability, performance, and visual quality. Available visuals include points, markers, line segments, paths, glyphs, images, spheres, 3D meshes, and basic volume rendering. Some important features, like axes and picking, are planned for v0.3 and later. Please give it a try, report any issues on GitHub, and feel free to ask questions. You're also welcome to contribute. I'm looking forward to your feedback!
16 by rossant | 0 comments on Hacker News.
I'm excited to announce the release of Datoviz 0.2.0, an open-source, high-performance GPU scientific visualization library built on Vulkan. It targets the interactive visualization of large 2D/3D datasets. This version includes tentative precompiled Python wheels for Linux, macOS (ARM and Intel), and Windows. Datoviz is a key part of the CZI-funded Vispy 2.0 project and will serve as its main GPU backend. Datoviz provides core GPU visualization capabilities while VisPy 2.0 will provide high-level plotting functionality (a bit similar to NumPy vs SciPy). What I'm looking for from the community: 1. Compatibility feedback: I'd appreciate quick feedback on how these precompiled Python wheels perform across different operating systems and graphics hardware. 2. Library feedback: Datoviz is still in its early stages and actively evolving. The API is subject to change, and I'd appreciate any feedback on its functionality and design. Please report issues on GitHub. Since the initial 2021 v0.1 release, the underlying technology has matured significantly. The internal architecture is now more robust and modular, paving the way for support for other rendering technologies like WebGPU and WebAssembly in the medium term. While still somewhat limited, the focus is on ensuring stability, performance, and visual quality. Available visuals include points, markers, line segments, paths, glyphs, images, spheres, 3D meshes, and basic volume rendering. Some important features, like axes and picking, are planned for v0.3 and later. Please give it a try, report any issues on GitHub, and feel free to ask questions. You're also welcome to contribute. I'm looking forward to your feedback!
Monday, 5 August 2024
Sunday, 4 August 2024
19 Signs From The Past Week That Made Me Laugh So Hard, I Forgot How To Breathe
from Yahoo News - Latest News & Headlines https://ift.tt/uVCB3sS
Saturday, 3 August 2024
Trump shooter autopsy reveals cause of death after attempted assassination
from Yahoo News - Latest News & Headlines https://ift.tt/oXKA4Fr
Friday, 2 August 2024
Thursday, 1 August 2024
Fyre Festival 2.0: California music festival-goers struck down by deadly fungus outbreak
from Yahoo News - Latest News & Headlines https://ift.tt/O5eUCGl
Subscribe to:
Posts (Atom)