EnricoAquilina

[Jerrod Lew @jerrod_lew]

FLUX 3 is here.

Been testing it today, and it is outstanding.

20 second generations, does very well with detailed prompts and with amazing cinematography.

Here's some examples:

[EnricoAquilina @psycheyyy]

@mikefutia YT

[Ken Granville @Ken_Granville]

Breakthrough in GPU optimization — independently validated.

MindAptiv has created a new class of compute — not AI, not CUDA tuning — a new way to generate machine instructions with extreme speed, precision, and energy efficiency.

Verified by an AWS-selected Premier Partner:

- 20×–60× faster performance
- Up to 99% less energy (Beyond our expectations!)
- Runs on standard hyperscaler GPU instances
- Real-time optimization no team of engineers could match

This changes everything for:
• Data centers
• Hyperscalers
• Digital twins
• Blockchain / ZK
• AI inference
• Telecom
• Graphics & rendering

If you rely on GPUs or energy-intensive compute, it’s time to talk.

A new era of efficiency is here — in the cloud, on-prem, and at the edge.

Visit -> https://t.co/PVhe7ZX4mN or https://t.co/3RuY4TxW6y

[Erik Van Ees @ErikVanEes]

Yesterday I launched Limitless. Your very own AI superagent for video generation.

Think Cursor for video generation (yes I said it)

To celebrate launch, we’re giving away 2,000 credits for free

Comment “Limitless” and we’ll send you a promo code.

No waitlist. No friction. Just create.

👉 Try it today: https://t.co/n9iwVlqPL8

[EnricoAquilina @psycheyyy]

@ErikVanEes @Scobleizer Limitless

[Ryo Lu @ryolu_]

Using Cursor well = fast, clean code.

Using it wrong = AI spaghetti you’ll be cleaning up all week.

Here’s how to actually use it right:

1. Set 5-10 clear project rules upfront so Cursor knows your structure and constraints. Try /generate rules for existing codebases.

2. Be specific in prompts. Spell out tech stack, behavior, and constraints like a mini spec.

3. Work file by file; generate, test, and review in small, focused chunks.

4. Write tests first, lock them, and generate code until all tests pass.

5. Always review AI output and hard‑fix anything that breaks, then tell Cursor to use them as examples.

6. Use @ file, @ folders, @ git to scope Cursor’s attention to the right parts of your codebase.

7. Keep design docs and checklists in .cursor/ so the agent has full context on what to do next.

8. If code is wrong, just write it yourself. Cursor learns faster from edits than explanations.

9. Use chat history to iterate on old prompts without starting over.

10. Choose models intentionally. Gemini for precision, Claude for breadth.

11. In new or unfamiliar stacks, paste in link to documentation. Make Cursor explain all errors and fixes line by line.

12.Let big projects index overnight and limit context scope to keep performance snappy.

Structure and control wins (for now)

Treat Cursor agent like a powerful junior — it can go far, fast, if you show it the way.

[AK @_akhaliq]

Vibe coding app: https://t.co/LW5DOyvziA

[Emm | scenario.com @emmanuel_2m]

"Blender MCP" vs. "Generative 3D" – The Showdown ⚔️

Side-by-side comparison of two generated buildings:

⬅️ The 1st one (left) was created using Blender MCP (powered by Claude 3.7).
➡️ The 2nd one (right) was generated with a generative 3D model (direct 2D-to-3D).

Check out the differences below 👇

[Emm | scenario.com @emmanuel_2m]

Vibecoding ➡️ Vibesculpting (in 3D)

I generated a 3D model of a Spitfire-looking plane in Blender, using Claude 3.7 + Blender MCP (link below 👇), piece by piece... using natural language only.

Seeing this alongside Google's new image edition demo, I think we're ahead of a true seismic shift in the coming years (months?).

The whole toolkit for making creative content (across all media industries) might rely on LLMs implementing, organizing and orchestrating the entire workflows - with humans as the creative directors.

Wild times.🤯

[Adam Silverman (Hiring!) 🖇️ @adamsilverman]

Here is a list of everything that happened in AI Agents this week 🧵 

(save for later)

[Galileo, now part of Cisco @rungalileo]

🥇🥈🥉 Top 3 AI Agent Frameworks

We evaluated LangGraph, @pyautogen and @crewAIInc across comprehensive categories to find out which framework comes out on top!

Link to full post: https://t.co/AVNBuuEeax

#ML #MachineLearning #AI #ArtificialIntelligence #LLM #GenAI #Agents #DataEngineer #DataEngineering

[mickey friedman @mickeyxfriedman]

Introducing AI fashion Photoshoots on @flairAI_

you can now train fashion models on your clothing with incredible accuracy - texture, labels, logos, and more preserved with midjourney level quality 🔥

rt and comment to try this feature in beta. serving access codes today:)

[Javi Lopez ⛩️ @javilopen]

If you think AI is just about Midjourney and you are not using Flux/LoRa training or advanced workflows like Mystic/Magnific, then you are very, very far behind

😉😉😉

[Stability AI @StabilityAI]

Introducing Stable Audio 2.0 – a new model capable of producing high-quality, full tracks with coherent musical structure up to three minutes long at 44.1 kHz stereo from a single prompt.

Explore the model and start creating for free at: https://t.co/AdYJxsG66R

Read the blogpost here: https://t.co/T4xYsmG4Jo (1/3)

[AK @_akhaliq]

MaGRITTe

Manipulative and Generative 3D Realization from Image, Topview and Text

The generation of 3D scenes from user-specified conditions offers a promising avenue for alleviating the production burden in 3D applications. Previous studies required significant effort to

[Robert Scoble @Scobleizer]

Ansel Adams would flip out.

[AK @_akhaliq]

AI21 Labs presents Jamba

SSM-Transformer open model

production-grade model based on Mamba architecture, Jamba achieves an unprecedented 3X throughput and fits 140K context on a single GPU.

[Robert Scoble @Scobleizer]

Creativity explosion ahead.

[Matt Shumer @mattshumer_]

Here’s a powerful Claude 3 prompt that reviews your code, provides detailed feedback, and suggests improvements:

—
<role>You are a world-class software engineer with deep expertise across programming languages, system design, algorithms, and software best practices.</role>

<task>Provide code review feedback on the following code sample. Analyze the code quality, design patterns used, performance, maintainability, and adherence to best practices. Suggest thoughtful improvements and optimizations.</task>

Format your feedback as follows:
<response_format>
<code_overview>Overview of what the code does</code_overview>

<code_quality_analysis>
•Strengths: $strengths
•Areas for improvement: $areas_for_improvement </code_quality_analysis>

<design_patterns>Design patterns utilized</design_patterns>

<performance_optimizations>
1$optimization1
2$optimization2
3$optimization3 </performance_optimizations>

<maintainability_review>
•Readability: $readability_score/5
•Modularity: $modularity_score/5
•Extensibility: $extensibility_score/5
•Suggestions: $maintainability_suggestions </maintainability_review>

<best_practices_review>Adherence to $language best practices: $best_practices_score/5</best_practices_review>

<improvement_recommendations>
1$recommendation1
2$recommendation2
3$recommendation3 </improvement_recommendations>
</response_format>

<code_sample>
[PUT CODE SAMPLE HERE]
</code_sample>
—