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Fast Compilation: 100k classes compile in ~888ms (Single-pass).
Lightweight: The VM is designed for a ~2ms startup target.
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I\u2019d love to hear your thoughts on using Arena-restart for autonomous scripts and any advice on optimizing dispatch without bloating the startup time."},"title":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["autolane"],"value":"Show HN: Autolang-A C++ VM with 2ms startup time and arena-restart memory model"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["autolane"],"value":"https://autolang.vercel.app/docs/introduction"}},"_tags":["story","author_hoansdz","story_47206397","show_hn"],"author":"hoansdz","created_at":"2026-03-01T13:11:47Z","created_at_i":1772370707,"num_comments":0,"objectID":"47206397","points":2,"story_id":47206397,"story_text":"Hi HN, I\u2019m a student and I\u2019ve spent the last few months building Autolang\u2014an embedded language and VM from scratch in C++.
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Here's a 2 minute video that shows it off: https://www.youtube.com/watch?v=S4R1gtmM-Lo
How/why does it work?\nWe believe that with the rise of foundation vision models, computer vision will fundamentally change. These powerful models will let any devs \u201ccompile\u201d a model ahead of time with a subset of the foundation model\u2019s characteristics, using only text and a web-tool. The days of teams of MLEs building complex models and pipelines are ending.
Zeroshot works by using two powerful pre-trained models, CLIP and DINOv2 together. The web-app allows users to quickly create our training sets via text search. Using pre-cached DINOv2 features, we generate a simple linear model that can be trained and deployed without any fine-tuning. Since you can see what\u2019s going into your training set, you can tune your prompts to get the type of performance or detail you want.
CLIP Small -- Size: 335 MB, Latency: 35ms
CLIP Large -- Size: 891 MB, Latency: 276ms
Zeroshot -- Size: 85 MB, Latency: 20ms
What\u2019s next?\nWe wanna see how people use or would use the tool before deciding what to do next. On the list: clients for iOS and NodeJS, speeding up GPU inference times via TensorRT, offering larger Zeroshot models for better accuracy, easier results refining, support for bringing your own data lake, model refinement using GPT-V, we\u2019ve got plenty of ideas."},"title":{"matchLevel":"none","matchedWords":[],"value":"Show HN: Build an open-source computer vision model in seconds using text"},"url":{"matchLevel":"none","matchedWords":[],"value":"https://usezeroshot.com/"}},"_tags":["story","author_nharada","story_38450690","show_hn"],"author":"nharada","children":[38453194,38453544,38455066,38458138,38458535],"created_at":"2023-11-28T20:18:32Z","created_at_i":1701202712,"num_comments":14,"objectID":"38450690","points":64,"story_id":38450690,"story_text":"Hello HN! I want to share something me and a few friends have been working on for a while now \u2014 Zeroshot, a web tool that builds image classifiers using text-image models and autolabeling. What does this mean in practice? You can put together an image classifier in about 30 seconds that\u2019s faster and more accurate than CLIP, but that you can deploy yourself however you\u2019d like. It\u2019s open source, commercially licensed, and doesn\u2019t require you to pay anyone per API call.
Here's a 2 minute video that shows it off: https://www.youtube.com/watch?v=S4R1gtmM-Lo
How/why does it work?\nWe believe that with the rise of foundation vision models, computer vision will fundamentally change. These powerful models will let any devs \u201ccompile\u201d a model ahead of time with a subset of the foundation model\u2019s characteristics, using only text and a web-tool. The days of teams of MLEs building complex models and pipelines are ending.
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CLIP Small -- Size: 335 MB, Latency: 35ms
CLIP Large -- Size: 891 MB, Latency: 276ms
Zeroshot -- Size: 85 MB, Latency: 20ms
What\u2019s next?\nWe wanna see how people use or would use the tool before deciding what to do next. On the list: clients for iOS and NodeJS, speeding up GPU inference times via TensorRT, offering larger Zeroshot models for better accuracy, easier results refining, support for bringing your own data lake, model refinement using GPT-V, we\u2019ve got plenty of ideas.","title":"Show HN: Build an open-source computer vision model in seconds using text","updated_at":"2024-09-20T15:49:02Z","url":"https://usezeroshot.com/"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"c1yd3i"},"story_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["autolane"],"value":"!PHL 01/165 PHL AD AP RDO ALTIMETER UNREL. AUTOLAND, HUD TO TOUCHDOWN, ENHANCED FLT VISION SYSTEMS TO TOUCHDOWN, HEL OPS REQUIRING RDO ALTIMETER DATA TO INCLUDE HOVER AUTOPILOT MODES AND CAT A/B/PERFORMANCE CLASS TKOF AND LDG NOT AUTHORIZED EXC FOR ACFT USING APPROVED ALTERNATIVE METHODS OF COMPLIANCE DUE TO 5G C-BAND INTERFERENCE PLUS SEE AIRWORTHINESS DIRECTIVES 2021-23-12, 2021-23-13 2201190501-2401190501"},"title":{"matchLevel":"none","matchedWords":[],"value":"NOTAM: Radio Altimeter Unreliable Due to 5G C-Band Interference"}},"_tags":["story","author_c1yd3i","story_29938406","ask_hn"],"author":"c1yd3i","children":[29938660],"created_at":"2022-01-14T18:46:19Z","created_at_i":1642185979,"num_comments":2,"objectID":"29938406","points":3,"story_id":29938406,"story_text":"!PHL 01/165 PHL AD AP RDO ALTIMETER UNREL. AUTOLAND, HUD TO TOUCHDOWN, ENHANCED FLT VISION SYSTEMS TO TOUCHDOWN, HEL OPS REQUIRING RDO ALTIMETER DATA TO INCLUDE HOVER AUTOPILOT MODES AND CAT A/B/PERFORMANCE CLASS TKOF AND LDG NOT AUTHORIZED EXC FOR ACFT USING APPROVED ALTERNATIVE METHODS OF COMPLIANCE DUE TO 5G C-BAND INTERFERENCE PLUS SEE AIRWORTHINESS DIRECTIVES 2021-23-12, 2021-23-13 2201190501-2401190501","title":"NOTAM: Radio Altimeter Unreliable Due to 5G C-Band Interference","updated_at":"2024-09-20T10:14:40Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"hammock"},"story_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["autolane"],"value":"In aviation we already have planes that can and regularly do land themselves without any pilot touching the controls. Landing being the most dangerous part of flying (don\u2019t try to compare it to auto-parallel park) It\u2019s called autoland. The plane\u2019s sensors gather left-right and up-down info and then control the plane down into the runway. We do this with planes carrying as many as 350+ souls on board. You would never even know if a pilot was using autoland, and you\u2019ve probably never heard of an autoland accident the way you have with self-driving.
The difference is, for a plane to do an auto-land (Cat III Landing) you need six things. The airport has to be certified, the crew needs to be certified, the aircraft needs to be certified, the company you are working with must be certified with its home civil aviation authority, the airport/country you are doing the cat III must certify the company as well, AND the weather should actually be low vis (meaning other types of landings like visual, VNAV and standard ILS are more difficult/impossible).
If you have just one of these items not certified, then the pilot can\u2019t do an auto-land.
Until we have the same rigor in self-driving, I would not anticipate much success, for safety reasons."},"title":{"matchLevel":"none","matchedWords":[],"value":"Tell HN: Biggest self-driving challenge is not technology"}},"_tags":["story","author_hammock","story_39790764","ask_hn"],"author":"hammock","children":[39791122,39793361],"created_at":"2024-03-22T13:51:16Z","created_at_i":1711115476,"num_comments":2,"objectID":"39790764","points":2,"story_id":39790764,"story_text":"In aviation we already have planes that can and regularly do land themselves without any pilot touching the controls. Landing being the most dangerous part of flying (don\u2019t try to compare it to auto-parallel park) It\u2019s called autoland. The plane\u2019s sensors gather left-right and up-down info and then control the plane down into the runway. We do this with planes carrying as many as 350+ souls on board. You would never even know if a pilot was using autoland, and you\u2019ve probably never heard of an autoland accident the way you have with self-driving.
The difference is, for a plane to do an auto-land (Cat III Landing) you need six things. The airport has to be certified, the crew needs to be certified, the aircraft needs to be certified, the company you are working with must be certified with its home civil aviation authority, the airport/country you are doing the cat III must certify the company as well, AND the weather should actually be low vis (meaning other types of landings like visual, VNAV and standard ILS are more difficult/impossible).
If you have just one of these items not certified, then the pilot can\u2019t do an auto-land.
Until we have the same rigor in self-driving, I would not anticipate much success, for safety reasons.","title":"Tell HN: Biggest self-driving challenge is not technology","updated_at":"2024-09-20T16:42:26Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"ramacastro"},"story_text":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["autolane"],"value":"Hey everyone!
I created a startup with a friend to make it easier for anyone to create AIs without any prior experience or knowledge in the field. We started with computer vision, specifically object detection, but we plan to add all subfields of AI eventually, like natural language processing, speech and all the cool generative stuff.
You can do everything inside the platform: create datasets, train artificial neural networks and use them to give intelligence to your web apps, mobile apps, machines, security cameras, robots, drones, cars and everything else.
It is free to use forever without any credit card required. You can connect google colab notebooks to our platform and use their free GPUs for training. Forget about all the different labeling file formats and running complex code yourself, just connect colab to Theos, click the Start Training button and the metrics will stream directly to your browser, and we will automatically upload weights checkpoints every epoch so you don't have to worry about colab shutting down and losing all your AI training progress. Also, we have an autolabeler feature to let your current AI's version help you make a better version of itself 100 times faster than labeling manually. Finally, you can deploy your AI as a rest API and use it in your software with simple http requests.
Here's the getting started guide for object detection:
https://docs.theos.ai/get-started/object-detection
Please let me know if you find it helpful and what subfield of AI you think we should tackle next.
(the landing page is not finished yet, soon we will release a way better version, but for now you can sign up and use the app for free)
Thanks!"},"title":{"matchLevel":"none","matchedWords":[],"value":"Show HN: Theos AI - development platform for AI"}},"_tags":["story","author_ramacastro","story_32038181","show_hn"],"author":"ramacastro","created_at":"2022-07-09T18:56:03Z","created_at_i":1657392963,"num_comments":0,"objectID":"32038181","points":1,"story_id":32038181,"story_text":"Hey everyone!
I created a startup with a friend to make it easier for anyone to create AIs without any prior experience or knowledge in the field. We started with computer vision, specifically object detection, but we plan to add all subfields of AI eventually, like natural language processing, speech and all the cool generative stuff.
You can do everything inside the platform: create datasets, train artificial neural networks and use them to give intelligence to your web apps, mobile apps, machines, security cameras, robots, drones, cars and everything else.
It is free to use forever without any credit card required. You can connect google colab notebooks to our platform and use their free GPUs for training. Forget about all the different labeling file formats and running complex code yourself, just connect colab to Theos, click the Start Training button and the metrics will stream directly to your browser, and we will automatically upload weights checkpoints every epoch so you don't have to worry about colab shutting down and losing all your AI training progress. Also, we have an autolabeler feature to let your current AI's version help you make a better version of itself 100 times faster than labeling manually. Finally, you can deploy your AI as a rest API and use it in your software with simple http requests.
Here's the getting started guide for object detection:
https://docs.theos.ai/get-started/object-detection
Please let me know if you find it helpful and what subfield of AI you think we should tackle next.
(the landing page is not finished yet, soon we will release a way better version, but for now you can sign up and use the app for free)
Thanks!","title":"Show HN: Theos AI - development platform for AI","updated_at":"2024-09-20T11:30:57Z"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"wilonth"},"title":{"matchLevel":"none","matchedWords":[],"value":"Show HN: An \u201cautomatic\u201d way to learn Chinese"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["autolane"],"value":"https://play.google.com/store/apps/details?id=gupik.autolang.zh"}},"_tags":["story","author_wilonth","story_18463886","show_hn"],"author":"wilonth","children":[18464421,18465365,18465683,18465824,18465985,18466333,18467409,18467513,18467894,18468491,18468755,18468864,18469700,18469796,18470070,18472357,18473550,18473795,18476076],"created_at":"2018-11-15T22:04:32Z","created_at_i":1542319472,"num_comments":38,"objectID":"18463886","points":57,"story_id":18463886,"title":"Show HN: An \u201cautomatic\u201d way to learn Chinese","updated_at":"2024-09-21T17:04:19Z","url":"https://play.google.com/store/apps/details?id=gupik.autolang.zh"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"Nycto"},"story_text":{"matchLevel":"none","matchedWords":[],"value":""},"title":{"matchLevel":"none","matchedWords":[],"value":"A radically new type of engine"},"url":{"fullyHighlighted":false,"matchLevel":"full","matchedWords":["autolane"],"value":"http://www.autoblog.com/2009/11/30/autoline-on-autoblog-with-john-mcelroy/"}},"_tags":["story","author_Nycto","story_972846"],"author":"Nycto","children":[973089,973178,973248,973729,973806,973925,974088],"created_at":"2009-12-02T20:28:19Z","created_at_i":1259785699,"num_comments":14,"objectID":"972846","points":56,"story_id":972846,"story_text":"","title":"A radically new type of engine","updated_at":"2023-09-06T20:17:05Z","url":"http://www.autoblog.com/2009/11/30/autoline-on-autoblog-with-john-mcelroy/"},{"_highlightResult":{"author":{"matchLevel":"none","matchedWords":[],"value":"Shivetya"},"title":{"matchLevel":"none","matchedWords":[],"value":"The race for autonomous cars is over. 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