TurnerNet

AI consulting for leaders who ship, not committees that study.

[TurnerNet @TurnerNetTech]

@NVIDIAGeForce #RTXOn

[Peché Africa 🇿🇦 @pmcafrica]

Bro said... hold my glasses 👓

[Spencer Pratt @spencerpratt]

If that addict on your street were your own son, what would you do? That is the defining question that guides my 5 step plan to fix the homelessness problem in LA. We *must* end this evil racket of corrupt politicians and NGOs who profit off the misery of these poor souls. They launder money and feed them more drugs, so they can keep their customers locked in this hell on our streets. We have a moral obligation from God to help them and make our city safe and clean for everyone. Karen Bass and Nithya Raman have forsaken this city. Time for real leadership. Time for real compassion.

[🚨 AI News | TestingCatalog @testingcatalog]

GOOGLE 🔥: Gemini desktop app will get Gemini Live, Gemini Spark, Gemini Omni, and a new "Stream to Cursor" feature.

What we know so far 👀
- "Stream to Cursor" feature will allow Gemini to have something similar to "Magic Pointer" announced last week during Android Show.
- Gemini Spark Agent will be able to operate local files from attached folders.
- Gimini Omni is referred to as "Veo4 Omni" internally.
- Skills will be supported too.
- Gemini Live feature is WIP and not functional yet.

A short demo from testers ⚡

[TurnerNet @TurnerNetTech]

@vivoplt @karpathy @fchollet @ylecun @AndrewYNg @rasbt @dair_ai @lilianweng @jeremyphoward @simonw @_akhaliq @ID_AA_Carmack @gwern @goodside @drfeifei @demishassabis @TurnerNetTech

[TurnerNet @TurnerNetTech]

@msurguy @jessegenet @useTRMNL She is using a 32" display. If I am reading this right, the largest here is 10.3". Is that correct?

[₩₳Ɽ ₱₳₮Ⱨ @WarPath2pt0]

HE. is. RISEN.

✝️

[TurnerNet @TurnerNetTech]

@iruletheworldmo Enterprise only???

[TurnerNet @TurnerNetTech]

@iruletheworldmo Done

[TurnerNet @TurnerNetTech]

https://t.co/9lLlaH4LUB

[TurnerNet @TurnerNetTech]

Interface: CLI, Python API, Web UI, Docker.
Extensible: plugin system via Python entry points for custom detectors and restorers.
Install: pip install artefex[all]

MIT licensed. Good first issues labeled. Contributions welcome.

Docs: https://t.co/JfcAD0gqbR

#OpenSource #Python #ComputerVision #MediaForensics #ONNX #DevTools #ImageProcessing

[TurnerNet @TurnerNetTech]

Introducing Artefex -- open-source neural forensic restoration for images.

Most tools blindly upscale or denoise. Artefex diagnoses first, then reverses each degradation step specifically.

Diagnosis before treatment. Every time.

https://t.co/NWk04ngQ6w

[TurnerNet @TurnerNetTech]

The problem with every existing restoration tool: they treat all images the same.

Got a blurry photo? Upscale it. Got noise? Denoise it. Never mind that the blur came from a 4x re-JPEG, the noise is sensor pattern from a phone camera, and someone also watermarked it twice and ran it through Instagram's compression pipeline.

One-size-fits-all filters don't fix that. They make it worse.

Artefex runs 13 forensic detectors before it touches a single pixel:

Compression: JPEG artifact detection via 8x8 block boundary analysis, plus multi-recompression detection using double quantization and ringing analysis.

Resolution: Upscaling/loss detection via high-frequency spectral analysis and autocorrelation.

Color: Color shift detection via channel imbalance and clip ratio analysis.

Artifacts: Screenshot remnant detection via border uniformity, aspect ratio, and dimension analysis.

Noise: Sensor and added noise via Laplacian MAD estimation.

Overlay: Watermark detection via tile correlation, histogram peaks, and alpha channel analysis.

Metadata: EXIF stripping detection via metadata presence and completeness checks.

Provenance: Platform fingerprinting that identifies whether your image was processed by Twitter, Instagram, WhatsApp, Facebook, Telegram, Discord, or Imgur -- from dimension, compression, and EXIF signatures alone.

Provenance: AI-generated content detection via frequency spectrum, histogram smoothness, noise uniformity, and patch consistency.

Security: Steganography detection via LSB analysis, chi-square test, entropy, and pairs analysis.

Provenance: Camera and device ID via sensor noise PRNU analysis (DSLR, smartphone, webcam, scanner).

Forgery: Copy-move detection via patch-based feature matching for cloned regions.

The output is a ranked degradation chain, graded A-F by severity. Then and only then does restoration begin -- neural (ONNX) models first, plugin restorers second, classical fallbacks third. Each step targeted to what was actually found.

[TurnerNet @TurnerNetTech]

@aaalexhl @grok How would I prompt you to build this?

[TurnerNet @TurnerNetTech]

@TheAhmadOsman Please!

[Ahmad @TheAhmadOsman]

Many are asking for the GPU giveaway to be for an RTX PRO 6000 Blackwell

How about this, if this tweet gets:

> 5k likes
> 1k retweets
> 200+ replies

I will make sure the giveaway announced on Monday will be for the RTX PRO 6000 Blackwell with 96GB of VRAM

It’s up to you guys

[Elon Musk @elonmusk]

It is

[OpenAI @OpenAI]

GPT-5.3-Codex-Spark is now in research preview.

You can just build things—faster.

[TurnerNet @TurnerNetTech]

@fmdz387 @trq212 This is awesome!

[Divam Gupta @divamgupta]

Introducing Kitten TTS, a SOTA tiny text-to-speech model

- Just 15M parameters
- Runs without a GPU
- Model size less than 25 MB
- Multiple high-quality voices
- Ultra-fast - even runs on low-end edge devices

Github and HF links below