Neural_Sorcerer

Building UrbanFlow, Into Vision and Perception, GPU poor @huggingface 🤗

[Neural_Sorcerer @Subh_775]

RF-DETR is just amazing! 🤯

I finetuned it on a public dataset and it hit an outrageous mAP@50:95 score: 0.9650 in only 2 epochs, with faster inference on a CPU!

Thanks to @roboflow community for such an amazing release. 🙏🏻

Waiting for paper to be release at the end of October

[Movez @0xMovez]

Anthropic Head of Product:

“Fable 5 - is our best model for self-improving agentic systems. It can run for days on a single /goal.

add /loops, dynamic workflows, dreaming and you become unstoppable.”

in 11 minutes, the Anthropic team shows how to build long-running systems with Fable 5 from scratch.

Worth more than a $500 agent-building course.

Live from Anthropic’s latest stage in Japan. Unpublished.

[Claude @claudeai]

Fable 5 is state-of-the-art on nearly all tested benchmarks, with exceptional performance in software engineering, knowledge work, scientific research, and vision.

The longer and more complex the task, the larger Fable 5’s lead over our other models.

[Marco Franzon @mfranz_on]

OpenCV 5 is here!

This is the biggest update in years for computer vision:
>Brand new DNN engine with 80%+ ONNX coverage
>Built-in LLM & VLM support
>Faster performance (often beating ONNX Runtime)
>Better 3D vision, Python integration, and hardware acceleration

OpenCV is not just a computer vision library but the settle stone for millions of projects.

[NVIDIA AI @NVIDIAAI]

This #CVPR2026 paper from our research team is trending #1 on @HuggingFace 🤗

Meet LocateAnything: a vision-language detection model that rethinks bounding box prediction. For AI agents and robots, “seeing” is only useful if a model can pinpoint where something is fast enough to act.

Trained on 138M high-quality samples, LocateAnything decodes bounding boxes in parallel instead of one coordinate at a time, improving localization accuracy while dramatically increasing throughput for visual grounding and detection.

Project page: https://t.co/O7JMe8tzFM

[Neural_Sorcerer @Subh_775]

@Om_Codes_ @IRCTCofficial People don’t need PR lectures — they need a railway app that works for more than 30 seconds under load.”

[Neural_Sorcerer @Subh_775]

@Om_Codes_ @IRCTCofficial Instead of improving infrastructure, scaling servers, or building a platform that can actually handle Indian traffic, the system’s first instinct is always intimidation.

[Neural_Sorcerer @Subh_775]

@Om_Codes_ @IRCTCofficial Millions of people depend on this service daily, yet the experience still feels like beta testing forced on the public.
Stop acting offended by criticism and start acting embarrassed by the performance.

[Vatsalya @vatsalyatandon]

claude took her job too

[NeilXbt @neil_xbt]

ANDREJ KARPATHY COULD HAVE CHARGED $500 FOR THIS WALKTHROUGH.

He put it on YouTube.

Every way he personally uses LLMs in his own life. Thinking models. Deep research. File uploads. Python interpreter. Claude Artifacts.

Not theory. Not benchmarks.

The actual daily workflow of the person who built Tesla Autopilot and co-founded OpenAI.

2 hours walking through his personal LLM workflow.

The gap between people who watch this week and those who save it for later is not 2 hours.

It is everything those 2 hours quietly change about how you work for the rest of your career.

[CyrilXBT @cyrilXBT]

ANTHROPIC JUST PROVED MOST PEOPLE HAVE NO IDEA HOW TO PROMPT CLAUDE.

Their applied AI team dropped a 24 minute free workshop.

Not a creator who reverse engineered it.

Not a Reddit thread.

ANTHROPIC.

The people who wrote the weights.

And what they showed is uncomfortable.

There are 6 elements to a properly structured Claude prompt.

Most people are using 1.

Maybe 2.

That is not a skill issue.

That is an information issue.

And it has been quietly costing you every single day.

The outputs that felt slightly off.

The responses you had to rewrite 4 times.

The prompts that worked once and never again.

All of it traces back to the same 6 missing elements.

The people who watch this 24 minute workshop tonight will understand something about Claude that most daily users still do not know exists.

The people who skip it will keep getting 30% of what the tool is actually capable of and wonder why the results never quite land.

I watched it twice.

Then I built a Claude Skill that applies all 6 elements to every prompt automatically.

No more thinking about structure.

No more guessing what Claude needs.

The framework runs in the background every single time.

Full breakdown and skill setup is below.

Bookmark this now.

Watch the workshop first.

Then read the guide.

This is the one that compounds.

Follow @cyrilXBT for the exact prompt architecture, Claude skills, and systems I use to get outputs most people do not believe came from one person working alone.

[Suryansh Tiwari @Suryanshti777]

🚨 Claude Opus 4.7 just changed how coding works.

But almost no one is using it the way Andrej Karpathy thinks about it.

People are still stuck in:

“write this function”
“fix this bug”
“explain this code”

That’s outdated.

Karpathy’s idea?

You don’t code everything anymore.
You steer intelligence.

Here are 9 high-leverage, value-packed prompts inspired by his “vibe coding” mindset:

[Rahul @sairahul1]

The creator of Claude Code teaches more about vibe-coding in 30 minutes than most tutorials do in hours.

Save this — it'll change how you build forever.

[Neural_Sorcerer @Subh_775]

Truly amazing content

[Evan Luthra @EvanLuthra]

The Head of Claude Code at Anthropic said he hasn’t written code by hand in months.

In 2 days he shipped 49 full features. All written 100% by AI.

He just dropped a 30 min talk on exactly how he does it.

Worth more than any $500 vibe coding course. Bookmark it:

[Neural_Sorcerer @Subh_775]

I should benchmark this model with rfdetr and yolo26..

[Tom Dörr @tom_doerr]

Real-time object detection with DINOv3 features

https://t.co/uv7lDGPgZS

[Neural_Sorcerer @Subh_775]

@roboflow Full logs and artifacts are in:

https://t.co/CecLMW4JVV

[Neural_Sorcerer @Subh_775]

Some Glimpses of rf-detr version 1.2.1, The model jumps to a strong starting point, leading it to beat all previous SOTA on UVH-26-MV- a challenging vehicular dataset.

But seems like it is nerfed in version- 1.6.1?
Is it @roboflow ?
Any major architectural shifts or changes?

[Neural_Sorcerer @Subh_775]

@roboflow version- 1.6.1 struggled to reach the same mAP in around 12th epoch, and took 9 hrs in dual T4

[Kasif @md_kasif_uddin]

> be Dario Amodei
> science kid obsessed with physics, not startups
> studies at Stanford, gets PhD from Princeton
> starts career in research, not tech hype
> works at Google and Baidu on AI
> joins OpenAI in 2016
> leads research on GPT-2 and GPT-3
> becomes VP of research at OpenAI
> disagrees with direction of the company
> walks away from one of the hottest AI labs
> starts Anthropic in 2021 with his sister + ex-OpenAI team
> focuses on one thing: safe and controllable AI
> builds Claude to compete with ChatGPT
> Anthropic becomes one of the biggest AI companies in the world

bro helped build GPT

then left and built its biggest competitor

quietly shaping the future of AI from both sides

[0xMarioNawfal @RoundtableSpace]

Gemma 4 watches raw video, understands the scene, then directs SAM 3 & RF-DETR to segment and track everything in it

One AI orchestrating two others. Fighter jets. Crowds. Aerial footage.

All three running locally on a MacBook. No cloud.

[Neural_Sorcerer @Subh_775]

@skalskip92 I can now finally compute the exact convergence on my custom dataset in Kaggle Notebook.

YOLOv6s achieved 0.66 mAP@50:95.
Let me also share the RF-DETR score...