Amiga Games Released in 2024 Index
5 by doener | 0 comments on Hacker News.
Tuesday, December 31, 2024
Monday, December 30, 2024
New top story on Hacker News: Tell HN: John Friel my father, internet pioneer and creator of QModem, has died
Tell HN: John Friel my father, internet pioneer and creator of QModem, has died
173 by AaronFriel | 17 comments on Hacker News.
If you knew him in life or remember his contribution to the world, please share your stories.
173 by AaronFriel | 17 comments on Hacker News.
If you knew him in life or remember his contribution to the world, please share your stories.
Sunday, December 29, 2024
New top story on Hacker News: Show HN: Kando – A cross-platform pie menu for your desktop
Show HN: Kando – A cross-platform pie menu for your desktop
47 by schneegans | 15 comments on Hacker News.
Kando is a cross-platform open source pie menu which I am currently developing! It offers an unconventional, fast, highly efficient, and fun way of interacting with your computer! You can use it to launch applications, simulate keyboard shortcuts, open files, and much more. Let me know what you think about it!
47 by schneegans | 15 comments on Hacker News.
Kando is a cross-platform open source pie menu which I am currently developing! It offers an unconventional, fast, highly efficient, and fun way of interacting with your computer! You can use it to launch applications, simulate keyboard shortcuts, open files, and much more. Let me know what you think about it!
Saturday, December 28, 2024
Friday, December 27, 2024
Thursday, December 26, 2024
Wednesday, December 25, 2024
Tuesday, December 24, 2024
Monday, December 23, 2024
New top story on Hacker News: Show HN: Otto-m8 – A low code AI/ML API deployment Platform
Show HN: Otto-m8 – A low code AI/ML API deployment Platform
3 by farhan0167 | 0 comments on Hacker News.
Hi all, so I've been working on this low to no code platform that allows you to spin up deep learning workloads(I'm talking LLM's, Huggingface models, etc), interconnect a bunch of them, and deploy them as API's. The idea essentially came up early in September, when experimenting with combining a Huggingface based BERT model with an LLM at work, and I realized it would be cool if I could do that instantly(especially since it was a prototype). At the time, I was considering a platform that could essentially help you train deep learning models without any code. It was my observation that much of the code required to train or even run inference on HF models have matured significantly. But before I solved that problem, I wanted to solve inference. Initially inspired by n8n and AWS Cloudformation, I built out otto-m8 (translates to automate). Given a json payload that lists out all the resources, and how each model is interconnected, launch it as one-off API the user can query. And thanks to Reactflow, the UI was just something I couldn't just not implement. And as I built it out, I did not want to miss out on the LLM and Agent bit. With otto-m8, today, you can launch complex workflows by interconnecting HF models and LLM's(currently it supports OpenAI and Ollama only). But I like to see it being more than that. At the core, every workflow is an input process output model. Inputs get processed and there's an output. Therefore, with the way things are setup, one can integrate almost anything and make it interconnectable. Project Link: https://ift.tt/EjKgifC Let me know what you guys think. I really would love feedback!
3 by farhan0167 | 0 comments on Hacker News.
Hi all, so I've been working on this low to no code platform that allows you to spin up deep learning workloads(I'm talking LLM's, Huggingface models, etc), interconnect a bunch of them, and deploy them as API's. The idea essentially came up early in September, when experimenting with combining a Huggingface based BERT model with an LLM at work, and I realized it would be cool if I could do that instantly(especially since it was a prototype). At the time, I was considering a platform that could essentially help you train deep learning models without any code. It was my observation that much of the code required to train or even run inference on HF models have matured significantly. But before I solved that problem, I wanted to solve inference. Initially inspired by n8n and AWS Cloudformation, I built out otto-m8 (translates to automate). Given a json payload that lists out all the resources, and how each model is interconnected, launch it as one-off API the user can query. And thanks to Reactflow, the UI was just something I couldn't just not implement. And as I built it out, I did not want to miss out on the LLM and Agent bit. With otto-m8, today, you can launch complex workflows by interconnecting HF models and LLM's(currently it supports OpenAI and Ollama only). But I like to see it being more than that. At the core, every workflow is an input process output model. Inputs get processed and there's an output. Therefore, with the way things are setup, one can integrate almost anything and make it interconnectable. Project Link: https://ift.tt/EjKgifC Let me know what you guys think. I really would love feedback!
Sunday, December 22, 2024
Saturday, December 21, 2024
Friday, December 20, 2024
Thursday, December 19, 2024
Wednesday, December 18, 2024
Tuesday, December 17, 2024
Monday, December 16, 2024
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Friday, December 13, 2024
Thursday, December 12, 2024
New top story on Hacker News: Show HN: Gentrace – connect to your LLM app code and run/eval it from a UI
Show HN: Gentrace – connect to your LLM app code and run/eval it from a UI
10 by dsaffy | 0 comments on Hacker News.
Hey HN - Doug from Gentrace here. We originally launched via Show HN in August of 2023 as evaluation and observability for generative AI: https://ift.tt/TymWan7 Since then, everyone from the model providers to LLM ops companies built a prompt playground. We had one too, until we realized this was totally the wrong approach: - It's not connected to your application code - They don't support all models - You have to rebuild evals for just this one prompt (can't use your end-to-end evals) In other words, it was a ton of work and time to use these to actually make your app better. So, we built a new experience and are relaunching around this idea: Gentrace is a collaborative LLM app testing and experimentation platform that brings together engineers, PMs, subject matter experts, and more to run and test your actual end-to-end app. To do this, use our SDK to: - connect your app to Gentrace as a live runner over websocket (local) / via webhook (staging, prod) - wrap your parameters (eg prompt, model, top-k) so they become tunable knobs in the front end - edit the parameters and then run / evaluate the actual app code with datasets and evals in Gentrace We think it's great for tuning retrieval systems, upgrading models, and iterating on prompts. It's free to trial. Would love to hear your feedback / what you think!
10 by dsaffy | 0 comments on Hacker News.
Hey HN - Doug from Gentrace here. We originally launched via Show HN in August of 2023 as evaluation and observability for generative AI: https://ift.tt/TymWan7 Since then, everyone from the model providers to LLM ops companies built a prompt playground. We had one too, until we realized this was totally the wrong approach: - It's not connected to your application code - They don't support all models - You have to rebuild evals for just this one prompt (can't use your end-to-end evals) In other words, it was a ton of work and time to use these to actually make your app better. So, we built a new experience and are relaunching around this idea: Gentrace is a collaborative LLM app testing and experimentation platform that brings together engineers, PMs, subject matter experts, and more to run and test your actual end-to-end app. To do this, use our SDK to: - connect your app to Gentrace as a live runner over websocket (local) / via webhook (staging, prod) - wrap your parameters (eg prompt, model, top-k) so they become tunable knobs in the front end - edit the parameters and then run / evaluate the actual app code with datasets and evals in Gentrace We think it's great for tuning retrieval systems, upgrading models, and iterating on prompts. It's free to trial. Would love to hear your feedback / what you think!
Wednesday, December 11, 2024
Tuesday, December 10, 2024
Monday, December 9, 2024
Sunday, December 8, 2024
New top story on Hacker News: Show HN: Grow Bluesky – A curated collection of the best tools for Bluesky users
Show HN: Grow Bluesky – A curated collection of the best tools for Bluesky users
8 by skaplich | 0 comments on Hacker News.
If you're building a service for Bluesky, share it in the comments, and I'll add it to Grow Bluesky
8 by skaplich | 0 comments on Hacker News.
If you're building a service for Bluesky, share it in the comments, and I'll add it to Grow Bluesky
Saturday, December 7, 2024
Friday, December 6, 2024
Thursday, December 5, 2024
Wednesday, December 4, 2024
Tuesday, December 3, 2024
Monday, December 2, 2024
Sunday, December 1, 2024
New top story on Hacker News: Show HN: Vicinity – Fast, Lightweight Nearest Neighbors with Flexible Back Ends
Show HN: Vicinity – Fast, Lightweight Nearest Neighbors with Flexible Back Ends
9 by Pringled | 0 comments on Hacker News.
We’ve just open-sourced Vicinity, a lightweight approximate nearest neighbors (ANN) search package that allows for fast experimentation and comparison of a larger number of well known algorithms. Main features: - Lightweight: the base package only uses Numpy - Unified interface: use any of the supported algorithms and backends with a single interface: HNSW, Annoy, FAISS, and many more algorithms and libraries are supported - Easy evaluation: evaluate the performance of your backend with a simple function to measure queries per second vs recall - Serialization: save and load your index for persistence After working with a large number of ANN libraries over the years, we found it increasingly cumbersome to learn the interface, features, quirks, and limitations of every library. After writing custom evaluation code to measure the speed and performance for the 100th time to compare libraries, we decided to build this as a way to easily use a large number of algorithms and libraries with a unified, simple interface that allows for quick comparison and evaluation. We are curious to hear your feedback! Are there any algorithms that are missing that you use? Any extra evaluation metrics that are useful?
9 by Pringled | 0 comments on Hacker News.
We’ve just open-sourced Vicinity, a lightweight approximate nearest neighbors (ANN) search package that allows for fast experimentation and comparison of a larger number of well known algorithms. Main features: - Lightweight: the base package only uses Numpy - Unified interface: use any of the supported algorithms and backends with a single interface: HNSW, Annoy, FAISS, and many more algorithms and libraries are supported - Easy evaluation: evaluate the performance of your backend with a simple function to measure queries per second vs recall - Serialization: save and load your index for persistence After working with a large number of ANN libraries over the years, we found it increasingly cumbersome to learn the interface, features, quirks, and limitations of every library. After writing custom evaluation code to measure the speed and performance for the 100th time to compare libraries, we decided to build this as a way to easily use a large number of algorithms and libraries with a unified, simple interface that allows for quick comparison and evaluation. We are curious to hear your feedback! Are there any algorithms that are missing that you use? Any extra evaluation metrics that are useful?
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