#neuralnet — Public Fediverse posts

Ah, the digital equivalent of watching paint dry... but with more jargon and less satisfaction! 🎨🤖 Behold, the majestic neural net, valiantly failing to entertain as it "learns" to slither on a grid, proving once and for all that even #AI can have an existential crisis. 🐍💻
https://ppo.gradexp.xyz/ #Failures #NeuralNet #ExistentialCrisis #TechHumor #DigitalArt #HackerNews #ngated

Ah, the digital equivalent of watching paint dry... but with more jargon and less satisfaction! 🎨🤖 Behold, the majestic neural net, valiantly failing to entertain as it "learns" to slither on a grid, proving once and for all that even #AI can have an existential crisis. 🐍💻
https://ppo.gradexp.xyz/ #Failures #NeuralNet #ExistentialCrisis #TechHumor #DigitalArt #HackerNews #ngated

Ah, the digital equivalent of watching paint dry... but with more jargon and less satisfaction! 🎨🤖 Behold, the majestic neural net, valiantly failing to entertain as it "learns" to slither on a grid, proving once and for all that even #AI can have an existential crisis. 🐍💻
https://ppo.gradexp.xyz/ #Failures #NeuralNet #ExistentialCrisis #TechHumor #DigitalArt #HackerNews #ngated

Ah, the digital equivalent of watching paint dry... but with more jargon and less satisfaction! 🎨🤖 Behold, the majestic neural net, valiantly failing to entertain as it "learns" to slither on a grid, proving once and for all that even #AI can have an existential crisis. 🐍💻
https://ppo.gradexp.xyz/ #Failures #NeuralNet #ExistentialCrisis #TechHumor #DigitalArt #HackerNews #ngated

Ah, the digital equivalent of watching paint dry... but with more jargon and less satisfaction! 🎨🤖 Behold, the majestic neural net, valiantly failing to entertain as it "learns" to slither on a grid, proving once and for all that even #AI can have an existential crisis. 🐍💻
https://ppo.gradexp.xyz/ #Failures #NeuralNet #ExistentialCrisis #TechHumor #DigitalArt #HackerNews #ngated

Watch a neural net learn to play Snake

https://ppo.gradexp.xyz/

#HackerNews #neuralnet #AI #Snake #gameplay #machinelearning #reinforcementlearning

Watch a neural net learn to play Snake

https://ppo.gradexp.xyz/

#HackerNews #neuralnet #AI #Snake #gameplay #machinelearning #reinforcementlearning

Watch a neural net learn to play Snake

https://ppo.gradexp.xyz/

#HackerNews #neuralnet #AI #Snake #gameplay #machinelearning #reinforcementlearning

Watch a neural net learn to play Snake

https://ppo.gradexp.xyz/

#HackerNews #neuralnet #AI #Snake #gameplay #machinelearning #reinforcementlearning

Watch a neural net learn to play Snake

https://ppo.gradexp.xyz/

#HackerNews #neuralnet #AI #Snake #gameplay #machinelearning #reinforcementlearning

Geting 6DOF with older 3DOF XR glasses

Breezy can now turn a 3DOF (degree of freedom) device into a 6DOF device by augmenting the missing positional data from a webcam. Spoiler! It is not the cam strapped to my face – this is just for the demo you can watch here, on PeerTube or YouTube.

The cam, that I used for this task, is sitting on my monitor. How this works? Well not with magic! This requires a somewhat decent webcam – really anything from the last decade should suffice – and OpenTrack, of course.

OpenTrack is a head-tracking application with multiple tracker plugins. One of it’s plugins is the Neuralnet Tracker, an AI powered extension that comes with a bunch of different head pose models to choose from. With a webcam connected this can now locally run the detection model with very low latency – so it’s usually blazing fast on most systems!

This alone is already 6DOF and is used a lot for gaming already – so what does Breezy do with this? Simple! It reads the forwarded data via an UDP listener, a very quick way to transmit data on a local network or system [and complements it’s own rotational data with the missing positional data].

With this a Breezy user still gets the rotational data from the XR’s very sensitive IMU, that is short for Inertial Measurement Unit btw, and the not so important positional data sent from OpenTrack.

This works of course only while the webcam can still see the user. So sadly no walking around while using this.

And the best thing? It can also send the data back! This means that the very same combined values can be forwarded – e.g. to a computer game – benefiting from the best available data sources for rotation and position.

That’s not the main use case, of course, and only of importance for some nerds like myself. This is mostly relevant for the productivity features of Breezy, because sometimes a text may be too small to read with the glasses on. We do no longer have to increase the font size – we can now simply lean in! That is a feature that is usually only available with glasses, that come with little cameras of their own, so they can have native 6DOF support. And when I say native I mean that such glasses usually also outsource exactly this calculation to the connected computer. It’s my understanding that this seems to require a lot of computation power, which is something many XR users with the more modern devices complain about.

Well not so much with OpenTrack and the Neuralnet tracker, that utilizes the ONNX runtime under the hood. That’s a high-performance, cross-platform engine to power exactly such models locally. The runtime automatically makes use of the best available hardware acceleration, if there is any.

Overall I’m rather hyped about this feature – especially because I’m using the OpenTrack output option of Breezy for quite some time now, to get a VR like experience with stereoscopic 3D rendering in Side-By-Side mode. I can now keep using my older XR glasses and still enjoy this more modern 6DOF feature. This is rather expensive hardware after all.

And all that on Linux PC!

Breezy xr_driver: https://github.com/wheaney/breezy-desktop by https://www.youtube.com/@WayneHeaney

Official Announcement XR desktop with 6DoF + multiple displays: https://www.youtube.com/watch?v=eFLmjpjF-rA

Music “Life’s Worth Dying For” CC BY-SA 3.0 “LostDrone”. Licensed to the public under https://creativecommons.org/licenses/by-sa/3.0/ Verify at https://soundcloud.com/lostdrone/rock-lostdrone-lifes-worth-dying-for-free-download-and-creative-commons-license

This content is licensed under a Creative Commons Attribution 4.0 International license.

https://beko.famkos.net/2026/02/06/geting-6dof-with-older-3dof-xr-glasses/

#3DOF #6DoF #AR #Breezy #gaming #Neuralnet #opentrack #Viture #ViturePro #VR #XR

Geting 6DOF with older 3DOF XR glasses

Breezy can now turn a 3DOF (degree of freedom) device into a 6DOF device by augmenting the missing positional data from a webcam. Spoiler! It is not the cam strapped to my face – this is just for the demo you can watch here, on PeerTube or YouTube.

The cam, that I used for this task, is sitting on my monitor. How this works? Well not with magic! This requires a somewhat decent webcam – really anything from the last decade should suffice – and OpenTrack, of course.

OpenTrack is a head-tracking application with multiple tracker plugins. One of it’s plugins is the Neuralnet Tracker, an AI powered extension that comes with a bunch of different head pose models to choose from. With a webcam connected this can now locally run the detection model with very low latency – so it’s usually blazing fast on most systems!

This alone is already 6DOF and is used a lot for gaming already – so what does Breezy do with this? Simple! It reads the forwarded data via an UDP listener, a very quick way to transmit data on a local network or system [and complements it’s own rotational data with the missing positional data].

With this a Breezy user still gets the rotational data from the XR’s very sensitive IMU, that is short for Inertial Measurement Unit btw, and the not so important positional data sent from OpenTrack.

This works of course only while the webcam can still see the user. So sadly no walking around while using this.

And the best thing? It can also send the data back! This means that the very same combined values can be forwarded – e.g. to a computer game – benefiting from the best available data sources for rotation and position.

That’s not the main use case, of course, and only of importance for some nerds like myself. This is mostly relevant for the productivity features of Breezy, because sometimes a text may be too small to read with the glasses on. We do no longer have to increase the font size – we can now simply lean in! That is a feature that is usually only available with glasses, that come with little cameras of their own, so they can have native 6DOF support. And when I say native I mean that such glasses usually also outsource exactly this calculation to the connected computer. It’s my understanding that this seems to require a lot of computation power, which is something many XR users with the more modern devices complain about.

Well not so much with OpenTrack and the Neuralnet tracker, that utilizes the ONNX runtime under the hood. That’s a high-performance, cross-platform engine to power exactly such models locally. The runtime automatically makes use of the best available hardware acceleration, if there is any.

Overall I’m rather hyped about this feature – especially because I’m using the OpenTrack output option of Breezy for quite some time now, to get a VR like experience with stereoscopic 3D rendering in Side-By-Side mode. I can now keep using my older XR glasses and still enjoy this more modern 6DOF feature. This is rather expensive hardware after all.

And all that on Linux PC!

Breezy xr_driver: https://github.com/wheaney/breezy-desktop by https://www.youtube.com/@WayneHeaney

Official Announcement XR desktop with 6DoF + multiple displays: https://www.youtube.com/watch?v=eFLmjpjF-rA

Music “Life’s Worth Dying For” CC BY-SA 3.0 “LostDrone”. Licensed to the public under https://creativecommons.org/licenses/by-sa/3.0/ Verify at https://soundcloud.com/lostdrone/rock-lostdrone-lifes-worth-dying-for-free-download-and-creative-commons-license

This content is licensed under a Creative Commons Attribution 4.0 International license.

https://beko.famkos.net/2026/02/06/geting-6dof-with-older-3dof-xr-glasses/

#3DOF #6DoF #AR #Breezy #gaming #Neuralnet #opentrack #Viture #ViturePro #VR #XR

Geting 6DOF with older 3DOF XR glasses

Breezy can now turn a 3DOF (degree of freedom) device into a 6DOF device by augmenting the missing positional data from a webcam. Spoiler! It is not the cam strapped to my face – this is just for the demo you can watch here, on PeerTube or YouTube.

The cam, that I used for this task, is sitting on my monitor. How this works? Well not with magic! This requires a somewhat decent webcam – really anything from the last decade should suffice – and OpenTrack, of course.

OpenTrack is a head-tracking application with multiple tracker plugins. One of it’s plugins is the Neuralnet Tracker, an AI powered extension that comes with a bunch of different head pose models to choose from. With a webcam connected this can now locally run the detection model with very low latency – so it’s usually blazing fast on most systems!

This alone is already 6DOF and is used a lot for gaming already – so what does Breezy do with this? Simple! It reads the forwarded data via an UDP listener, a very quick way to transmit data on a local network or system [and complements it’s own rotational data with the missing positional data].

With this a Breezy user still gets the rotational data from the XR’s very sensitive IMU, that is short for Inertial Measurement Unit btw, and the not so important positional data sent from OpenTrack.

This works of course only while the webcam can still see the user. So sadly no walking around while using this.

And the best thing? It can also send the data back! This means that the very same combined values can be forwarded – e.g. to a computer game – benefiting from the best available data sources for rotation and position.

That’s not the main use case, of course, and only of importance for some nerds like myself. This is mostly relevant for the productivity features of Breezy, because sometimes a text may be too small to read with the glasses on. We do no longer have to increase the font size – we can now simply lean in! That is a feature that is usually only available with glasses, that come with little cameras of their own, so they can have native 6DOF support. And when I say native I mean that such glasses usually also outsource exactly this calculation to the connected computer. It’s my understanding that this seems to require a lot of computation power, which is something many XR users with the more modern devices complain about.

Well not so much with OpenTrack and the Neuralnet tracker, that utilizes the ONNX runtime under the hood. That’s a high-performance, cross-platform engine to power exactly such models locally. The runtime automatically makes use of the best available hardware acceleration, if there is any.

Overall I’m rather hyped about this feature – especially because I’m using the OpenTrack output option of Breezy for quite some time now, to get a VR like experience with stereoscopic 3D rendering in Side-By-Side mode. I can now keep using my older XR glasses and still enjoy this more modern 6DOF feature. This is rather expensive hardware after all.

And all that on Linux PC!

Breezy xr_driver: https://github.com/wheaney/breezy-desktop by https://www.youtube.com/@WayneHeaney

Official Announcement XR desktop with 6DoF + multiple displays: https://www.youtube.com/watch?v=eFLmjpjF-rA

Music “Life’s Worth Dying For” CC BY-SA 3.0 “LostDrone”. Licensed to the public under https://creativecommons.org/licenses/by-sa/3.0/ Verify at https://soundcloud.com/lostdrone/rock-lostdrone-lifes-worth-dying-for-free-download-and-creative-commons-license

This content is licensed under a Creative Commons Attribution 4.0 International license.

https://beko.famkos.net/2026/02/06/geting-6dof-with-older-3dof-xr-glasses/

#3DOF #6DoF #AR #Breezy #gaming #Neuralnet #opentrack #Viture #ViturePro #VR #XR

Geting 6DOF with older 3DOF XR glasses

Breezy can now turn a 3DOF (degree of freedom) device into a 6DOF device by augmenting the missing positional data from a webcam. Spoiler! It is not the cam strapped to my face – this is just for the demo you can watch here, on PeerTube or YouTube.

The cam, that I used for this task, is sitting on my monitor. How this works? Well not with magic! This requires a somewhat decent webcam – really anything from the last decade should suffice – and OpenTrack, of course.

OpenTrack is a head-tracking application with multiple tracker plugins. One of it’s plugins is the Neuralnet Tracker, an AI powered extension that comes with a bunch of different head pose models to choose from. With a webcam connected this can now locally run the detection model with very low latency – so it’s usually blazing fast on most systems!

This alone is already 6DOF and is used a lot for gaming already – so what does Breezy do with this? Simple! It reads the forwarded data via an UDP listener, a very quick way to transmit data on a local network or system [and complements it’s own rotational data with the missing positional data].

With this a Breezy user still gets the rotational data from the XR’s very sensitive IMU, that is short for Inertial Measurement Unit btw, and the not so important positional data sent from OpenTrack.

This works of course only while the webcam can still see the user. So sadly no walking around while using this.

And the best thing? It can also send the data back! This means that the very same combined values can be forwarded – e.g. to a computer game – benefiting from the best available data sources for rotation and position.

That’s not the main use case, of course, and only of importance for some nerds like myself. This is mostly relevant for the productivity features of Breezy, because sometimes a text may be too small to read with the glasses on. We do no longer have to increase the font size – we can now simply lean in! That is a feature that is usually only available with glasses, that come with little cameras of their own, so they can have native 6DOF support. And when I say native I mean that such glasses usually also outsource exactly this calculation to the connected computer. It’s my understanding that this seems to require a lot of computation power, which is something many XR users with the more modern devices complain about.

Well not so much with OpenTrack and the Neuralnet tracker, that utilizes the ONNX runtime under the hood. That’s a high-performance, cross-platform engine to power exactly such models locally. The runtime automatically makes use of the best available hardware acceleration, if there is any.

Overall I’m rather hyped about this feature – especially because I’m using the OpenTrack output option of Breezy for quite some time now, to get a VR like experience with stereoscopic 3D rendering in Side-By-Side mode. I can now keep using my older XR glasses and still enjoy this more modern 6DOF feature. This is rather expensive hardware after all.

And all that on Linux PC!

Breezy xr_driver: https://github.com/wheaney/breezy-desktop by https://www.youtube.com/@WayneHeaney

Official Announcement XR desktop with 6DoF + multiple displays: https://www.youtube.com/watch?v=eFLmjpjF-rA

Music “Life’s Worth Dying For” CC BY-SA 3.0 “LostDrone”. Licensed to the public under https://creativecommons.org/licenses/by-sa/3.0/ Verify at https://soundcloud.com/lostdrone/rock-lostdrone-lifes-worth-dying-for-free-download-and-creative-commons-license

This content is licensed under a Creative Commons Attribution 4.0 International license.

https://beko.famkos.net/2026/02/06/geting-6dof-with-older-3dof-xr-glasses/

#3DOF #6DoF #AR #Breezy #gaming #Neuralnet #opentrack #Viture #ViturePro #VR #XR

Geting 6DOF with older 3DOF XR glasses

Breezy can now turn a 3DOF (degree of freedom) device into a 6DOF device by augmenting the missing positional data from a webcam. Spoiler! It is not the cam strapped to my face – this is just for the demo you can watch here, on PeerTube or YouTube.

The cam, that I used for this task, is sitting on my monitor. How this works? Well not with magic! This requires a somewhat decent webcam – really anything from the last decade should suffice – and OpenTrack, of course.

OpenTrack is a head-tracking application with multiple tracker plugins. One of it’s plugins is the Neuralnet Tracker, an AI powered extension that comes with a bunch of different head pose models to choose from. With a webcam connected this can now locally run the detection model with very low latency – so it’s usually blazing fast on most systems!

This alone is already 6DOF and is used a lot for gaming already – so what does Breezy do with this? Simple! It reads the forwarded data via an UDP listener, a very quick way to transmit data on a local network or system [and complements it’s own rotational data with the missing positional data].

With this a Breezy user still gets the rotational data from the XR’s very sensitive IMU, that is short for Inertial Measurement Unit btw, and the not so important positional data sent from OpenTrack.

This works of course only while the webcam can still see the user. So sadly no walking around while using this.

And the best thing? It can also send the data back! This means that the very same combined values can be forwarded – e.g. to a computer game – benefiting from the best available data sources for rotation and position.

That’s not the main use case, of course, and only of importance for some nerds like myself. This is mostly relevant for the productivity features of Breezy, because sometimes a text may be too small to read with the glasses on. We do no longer have to increase the font size – we can now simply lean in! That is a feature that is usually only available with glasses, that come with little cameras of their own, so they can have native 6DOF support. And when I say native I mean that such glasses usually also outsource exactly this calculation to the connected computer. It’s my understanding that this seems to require a lot of computation power, which is something many XR users with the more modern devices complain about.

Well not so much with OpenTrack and the Neuralnet tracker, that utilizes the ONNX runtime under the hood. That’s a high-performance, cross-platform engine to power exactly such models locally. The runtime automatically makes use of the best available hardware acceleration, if there is any.

Overall I’m rather hyped about this feature – especially because I’m using the OpenTrack output option of Breezy for quite some time now, to get a VR like experience with stereoscopic 3D rendering in Side-By-Side mode. I can now keep using my older XR glasses and still enjoy this more modern 6DOF feature. This is rather expensive hardware after all.

And all that on Linux PC!

Breezy xr_driver: https://github.com/wheaney/breezy-desktop by https://www.youtube.com/@WayneHeaney

Official Announcement XR desktop with 6DoF + multiple displays: https://www.youtube.com/watch?v=eFLmjpjF-rA

Music “Life’s Worth Dying For” CC BY-SA 3.0 “LostDrone”. Licensed to the public under https://creativecommons.org/licenses/by-sa/3.0/ Verify at https://soundcloud.com/lostdrone/rock-lostdrone-lifes-worth-dying-for-free-download-and-creative-commons-license

This content is licensed under a Creative Commons Attribution 4.0 International license.

https://beko.famkos.net/2026/02/06/geting-6dof-with-older-3dof-xr-glasses/

#3DOF #6DoF #AR #Breezy #gaming #Neuralnet #opentrack #Viture #ViturePro #VR #XR

Un progetto che sviluppai negli anni '90, quando nessuno parlava di IA.

Nella simulazione una Rete Neurale Artificiale apprende le regole della tabella di payoff del Dilemma del Prigioniero Iterato (IPD) battendo tutti gli altri agenti artificiali, compreso il famoso "Tit-for-Tat" del politologo Robert Axelrod, il primo a lanciare tornei di gioco al IPD dove chiunque poteva caricare agenti non adattivi con strategie di gioco specifiche.

#GameTherory #ai #NeuralNet

---[music: Jimi Hendrix]

Un progetto che sviluppai negli anni '90, quando nessuno parlava di IA.

Nella simulazione una Rete Neurale Artificiale apprende le regole della tabella di payoff del Dilemma del Prigioniero Iterato (IPD) battendo tutti gli altri agenti artificiali, compreso il famoso "Tit-for-Tat" del politologo Robert Axelrod, il primo a lanciare tornei di gioco al IPD dove chiunque poteva caricare agenti non adattivi con strategie di gioco specifiche.

#GameTherory #ai #NeuralNet

---[music: Jimi Hendrix]

Un progetto che sviluppai negli anni '90, quando nessuno parlava di IA.

Nella simulazione una Rete Neurale Artificiale apprende le regole della tabella di payoff del Dilemma del Prigioniero Iterato (IPD) battendo tutti gli altri agenti artificiali, compreso il famoso "Tit-for-Tat" del politologo Robert Axelrod, il primo a lanciare tornei di gioco al IPD dove chiunque poteva caricare agenti non adattivi con strategie di gioco specifiche.

#GameTherory #ai #NeuralNet

---[music: Jimi Hendrix]

Un progetto che sviluppai negli anni '90, quando nessuno parlava di IA.

Nella simulazione una Rete Neurale Artificiale apprende le regole della tabella di payoff del Dilemma del Prigioniero Iterato (IPD) battendo tutti gli altri agenti artificiali, compreso il famoso "Tit-for-Tat" del politologo Robert Axelrod, il primo a lanciare tornei di gioco al IPD dove chiunque poteva caricare agenti non adattivi con strategie di gioco specifiche.

#GameTherory #ai #NeuralNet

---[music: Jimi Hendrix]

Un progetto che sviluppai negli anni '90, quando nessuno parlava di IA.

Nella simulazione una Rete Neurale Artificiale apprende le regole della tabella di payoff del Dilemma del Prigioniero Iterato (IPD) battendo tutti gli altri agenti artificiali, compreso il famoso "Tit-for-Tat" del politologo Robert Axelrod, il primo a lanciare tornei di gioco al IPD dove chiunque poteva caricare agenti non adattivi con strategie di gioco specifiche.

#GameTherory #ai #NeuralNet

---[music: Jimi Hendrix]

Dự án LLaMA 3.2 3B phát triển công cụ phân tích mới giúp quan sát các lớp transformer và token mức độ chi tiết, hỗ trợ điều chỉnh kích hoạt kết nối theo thời gian thực. Tính năng đáng chú ý: nhãn chiều nổi bật khi hoạt động mạnh, giao diện điều hướng token linh hoạt. Cơ hội học hỏi đáng ngạc nhiên từ người không phải phát triển Godot.
#AI #MachineLearning #LLaMA32 #FMRI #PhânTíchToken #NeuralNet

https://www.reddit.com/r/LocalLLaMA/comments/1pnhi27/llama_32_3b_fmri/

This #NeuralNet2025 conference seems interesting:
https://neuralnet2025.sciencesconf.org/resource/page/id/1

where: Bordeaux Neurocampus (France)
when: Wednesday 26 noon to Friday 28 noon
preceded by: minischool on spike sorting (Tuesday 25 - Wed.26).

#NeuralNet #NeuroConf #Neuroscience #SpikeSorting

This #NeuralNet2025 conference seems interesting:
https://neuralnet2025.sciencesconf.org/resource/page/id/1

where: Bordeaux Neurocampus (France)
when: Wednesday 26 noon to Friday 28 noon
preceded by: minischool on spike sorting (Tuesday 25 - Wed.26).

#NeuralNet #NeuroConf #Neuroscience #SpikeSorting

This #NeuralNet2025 conference seems interesting:
https://neuralnet2025.sciencesconf.org/resource/page/id/1

where: Bordeaux Neurocampus (France)
when: Wednesday 26 noon to Friday 28 noon
preceded by: minischool on spike sorting (Tuesday 25 - Wed.26).

#NeuralNet #NeuroConf #Neuroscience #SpikeSorting

This #NeuralNet2025 conference seems interesting:
https://neuralnet2025.sciencesconf.org/resource/page/id/1

where: Bordeaux Neurocampus (France)
when: Wednesday 26 noon to Friday 28 noon
preceded by: minischool on spike sorting (Tuesday 25 - Wed.26).

#NeuralNet #NeuroConf #Neuroscience #SpikeSorting

This #NeuralNet2025 conference seems interesting:
https://neuralnet2025.sciencesconf.org/resource/page/id/1

where: Bordeaux Neurocampus (France)
when: Wednesday 26 noon to Friday 28 noon
preceded by: minischool on spike sorting (Tuesday 25 - Wed.26).

#NeuralNet #NeuroConf #Neuroscience #SpikeSorting

🤯OMG, someone actually thinks converting a neural net to C is the key to unlocking the secrets of the universe—who knew swapping activation functions for logic gates would be the 🚀 to a 1,744× speedup? Clearly, this coder spent 25 minutes bragging about reinventing the wheel—next up, they'll try to prove water is wet! 💧🔧
https://slightknack.dev/blog/difflogic/ #neuralnet #Cconversion #speedup #techinnovation #codinghumor #unlocksecrets #HackerNews #ngated

Dunno if you heard of #BeamEyeTracker before. It's positioning itself next to #Tobii but uses just a webcam and #Opentrack, so probably just #Neuralnet tracker on steroids - but I'd still appreciate if you could chime in for a #Linux build at https://steamcommunity.com/app/2375780/discussions/0/4757578278664103829/ too as it seems to be read by the dev|s.

#LinuxGaming #GamingOnLinux #HeadTracker #HeadTracking #TrackIR

-𝟘: The Power of Negative Zero: Datatype Customization for Quantized Large Language Models

(... they get an amazing boost in performance from this!)

https://arxiv.org/abs/2501.04052

#ai #ml #cs #neuralnet #math #efficiency #goodnews

🧠 Selecting a model for semantic search at Dropbox scale

https://dropbox.tech/machine-learning/selecting-model-semantic-search-dropbox-ai

#ai #search #ir #neuralnet #programing #dropbox

It has been a while that I tried #StarCitizen. With the new #Neuralnet Tracker plugin (AI haha) for #OpenTrack we get head tracking without annoying IR LEDs or reflecting stripes just by reading the webcam video feed. This is apparently fast enough to try #headTracking without a dedicated #headTracker nowadays. And all that on a #Linux PC. Took some fiddling but the concept still works. What a time to be alive.

Demo: https://makertube.net/w/groS1wpAhP8XYE75vJwX32

HowTo: https://simpit.dev/systems/opentrack/

#Gaming

https://beko.famkos.net/2024/09/02/15629325/

#gaming #headtracker #Headtracking #linux #Neuralnet #opentrack #StarCitizen

Updated https://simpit.dev/ - home of the Space Pew Pew #SimPit inspired by a VF-1 Valkyrie cockpit (#Macross)

That's a glorified #DIY joystick controller with an LCD ('MFD') and plenty of RGB for my #Linux PC

Newest additions are my videos for #X4Foundations, #EliteDangerous and #FlightOfNova (all also on https://makertube.net/a/bekopharm) and instructions how to compile #OpenTrack with the #neuralnet tracker using #ONNX runtime.

Best viewed WITH an ad-blocker and patience (slow).

#HomeCockpit

Google DeepMind's New AI Model Can Help Soccer Teams Take the Perfect Corner https://www.wired.com/story/deepmind-is-helping-soccer-teams-take-the-perfect-corner/ #Business/ArtificialIntelligence #NeuralNet #Science

DeepMind Is Helping Soccer Teams Take the Perfect Corner - A soccer AI model created by Google DeepMind makes predictions about where corners will g... - https://www.wired.com/story/deepmind-is-helping-soccer-teams-take-the-perfect-corner/ #business/artificialintelligence #neuralnet #science

@scottmiller42 @emovulcan @acute_distress @thomasfuchs

Hey Scott, I have not decided what to think about LLMs and copyrights.

I saw the word Data analyst in your Bio, so I suppose you have some knowledge in #DataScience and #DataEngineering.

I am myself trained in #MachineLearning and a bit in #neuralnetworks but I am far far far far far away from being any close to an expert. I can use them, efficiently sometimes. Sometimes not: there are problems I am still bad at solving with them.

I am still learning the Transformers stuffs and other types of layers used in Deep Learning. That's huge stuff. For me at least.

Could you clear that doubt I have when I read your messages:
when you talk about "MEMORIZING" data

It conflicts with my poor understanding of #machinelearning #neuralnet #transformer

At my level of understanding: memorizing == overfitting
that means that the model cannot extrapolate or even interpolate between values of the training set.

This is something that I have categorized as a real flaw. If any of my models overfits, I consider it broken. I throw it away, it will not perform good on any unexpected input.

Could you explain me how "memorizing" would differ in your vision?

Don't hesitate to simplify things, I am not an expert yet at #transformer and #LLM

In advance thanks. I would not like to be fooled by my apriori.

[AI Coffee Break with Letitia] explains the #transformer architecture behind #LargeLanguageModels
https://youtu.be/ec9IQMiJBhs
#LLM #NeuralNet #ArtificialIntelligence

See and hear how an AI learns the shape of sinus curves: https://youtu.be/0T46pTfCSsE #ai #ki #neuralnet #sinus

Where might I find the most accurate breakdown of all the sources of text used to train GPT-4?

#ML #LLM #GPT4 #neuralnet #linguistics

Anyone in the #ML or #neuralnet or #design spaces seen any examples of models that have been trained on graphic design exemplars that can recognize typefaces and content hierarchies on a screenshot or page?

I'm interested in trying to build a Stockfish-like model that operates on classic principles of layout, composition, and typography.

Endlich mal ein sinnvoller Einsatz von KI: Översetter, die erste Übersetzungs-App von Hochdeutsch zu Plattdüütsch. Jetzt endlich auch für iOS.

Weil es weder „das Platt“ noch allgemeine Rechtschreibregeln gibt, sind die digitalen Übersetzungstools bisher wenige, mit überschaubarem Wortschatz und regional begrenzt. Ohne KI sind das kaum zu lösende Probleme.

#Plattdeutsch #Plattdüütsch #NeuralNet #KI
https://www.översetter.de

[ Disclosure: I have done contract work on the product being advertised, but reposting this ad is not part of that. I just think it's a neat demonstration of AI being used responsibly. ]

#AIDungeon, once again, showing us a safe use of #AI which the #NeuralNet / #LLM model is actually well suited for. #GPT and similar #Transformer programs will likely never be good at reliably simulating a therapist, a friend, or even an honest person, but they're great at outputting stories.

This time, the #Latitude PR team has the AI #writing a #surreal "#FeverDream" adventure, where we follow #anthropomorphic rabbits into a neon forests, and ride glittering unicorns away from glowing beasts.

https://youtu.be/aywL3l7VCMo

Acabei de assistir uma bela introdução à redes neurais. Andrej nos conduz passo a passo no cálculo da derivada de cada peso da rede neural individualmente para demonstrar backpropagation antes de abstrair todo o código para uma classe de forma mais enxuta.

https://www.youtube.com/watch?v=VMj-3S1tku0

#neuralnet #pytorch #redesneurais #InteligenciaArtificial

Creating training data for the neural net that will enable visual search in #TinyUX.

About 220 icons, 100 drawings / icon.

I've been doing this for many many hours in the evening while watching a football match or something.

I don't know if the feature will be used much, but wanted to get experience in embedding a neural net in an app that was actually used. Not just a demo.

Https://tinyux.app for more about the app.

#ux #wires #wireframes #ai #neuralNet #icons #reactNative

Creating training data for the neural net that will enable visual search in #TinyUX.

About 220 icons, 100 drawings / icon.

I've been doing this for many many hours in the evening while watching a football match or something.

I don't know if the feature will be used much, but wanted to get experience in embedding a neural net in an app that was actually used. Not just a demo.

Https://tinyux.app for more about the app.

#ux #wires #wireframes #ai #neuralNet #icons #reactNative

Creating training data for the neural net that will enable visual search in #TinyUX.

About 220 icons, 100 drawings / icon.

I've been doing this for many many hours in the evening while watching a football match or something.

I don't know if the feature will be used much, but wanted to get experience in embedding a neural net in an app that was actually used. Not just a demo.

Https://tinyux.app for more about the app.

#ux #wires #wireframes #ai #neuralNet #icons #reactNative

Creating training data for the neural net that will enable visual search in #TinyUX.

About 220 icons, 100 drawings / icon.

I've been doing this for many many hours in the evening while watching a football match or something.

I don't know if the feature will be used much, but wanted to get experience in embedding a neural net in an app that was actually used. Not just a demo.

Https://tinyux.app for more about the app.

#ux #wires #wireframes #ai #neuralNet #icons #reactNative

Creating training data for the neural net that will enable visual search in #TinyUX.

About 220 icons, 100 drawings / icon.

I've been doing this for many many hours in the evening while watching a football match or something.

I don't know if the feature will be used much, but wanted to get experience in embedding a neural net in an app that was actually used. Not just a demo.

Https://tinyux.app for more about the app.

#ux #wires #wireframes #ai #neuralNet #icons #reactNative

Making good progress with my visual search feature in TinyUX.

The simple neural net is stored on the device. It is now only trained on letters and numbers. Will need to train for all icons.

I use the same interface to draw content for the neural network to train on. Still quite number of hours of work ahead for creating that training content.

#neuralnet #ux #icons #pytorch #reactnative #tinygrad #tinyux

Making good progress with my visual search feature in TinyUX.

The simple neural net is stored on the device. It is now only trained on letters and numbers. Will need to train for all icons.

I use the same interface to draw content for the neural network to train on. Still quite number of hours of work ahead for creating that training content.

#neuralnet #ux #icons #pytorch #reactnative #tinygrad #tinyux

Making good progress with my visual search feature in TinyUX.

The simple neural net is stored on the device. It is now only trained on letters and numbers. Will need to train for all icons.

I use the same interface to draw content for the neural network to train on. Still quite number of hours of work ahead for creating that training content.

#neuralnet #ux #icons #pytorch #reactnative #tinygrad #tinyux