NTR

Crypto Banter Fam. any day

[🌋🌋 Deep₿lueCrypto 🌋🌋 @DeepBlueCrypto]

@nvidia Here you go

[Muhammad Ayan @socialwithaayan]

35 WEBSITES GOOGLE DOESN'T WANT YOU TO KNOW

1. Evomap .ai — open source, self-hosted, and your data never leaves your own infrastructure.
https://t.co/oQEbudhJiD

2. NotebookLM — turns docs into podcasts
https://t.co/prs9AWkTFa

3. Napkin AI — turns text into diagrams
https://t.co/W14RHb2JZG

4. Ideogram — generates text in images perfectly
https://t.co/qRg1yfkZMC

5. Suno — makes full songs from a prompt
https://t.co/RtR8iK1wM4

6. HeyGen — clones your face into videos
https://t.co/V89yi3ymi2

7. Kling AI — best AI video generation
https://t.co/7U7lvYoYui

8. ElevenLabs — clone any voice instantly
https://t.co/DB46fO9jUU

9. Gamma — AI presentations in seconds
https://t.co/abgvkUxotm

10. Perplexity — AI search with real sources
https://t.co/lJNsbNb97N

11. Pika — animate any image into video
https://t.co/Y1ziroISrN

12. Runway — cinematic AI video generation
https://t.co/0V22FRYKDq

13. Cursor — AI code editor that builds for you
https://t.co/ZZ5a58hmjV

14. v0 — generate UI components with AI
https://t.co/AFa9p7nwkr

15. Lovable — turn ideas into working apps
https://t.co/TKYBXZ7zU1

16. Descript — edit video by editing text
https://t.co/YQUjUSEgzM

17. Opus Clip — auto cut long videos into shorts
https://opus.clip

18. Krea AI — real time AI image generation
https://t.co/pcm9ExwVf9

19. Magnific — upscale any image with AI
https://t.co/37zwz0b2Ix

20. Viggle — make characters move realistically
https://t.co/HXXEtfQc4w

21. tl;dv — record and summarize any meeting
https://t.co/IE8NQV7pzn

22. Fireflies — AI meeting notes automatically
https://t.co/dsbAnuUQji

23. Castmagic — turn audio into content pieces
https://t.co/GhGS0F2Szc

24. Replit — code and deploy from browser
https://t.co/dUCenYqW4U

25. Leonardo AI — generate images for free
https://t.co/7xTC7clZfl

26. Synthesia — AI avatar videos no camera needed
https://t.co/JUyPtbBN0S

27. Fliki — turn text into videos with AI
https://t.co/CVx4aAN2dj

28. Photoroom — AI product photography
https://t.co/uxxIAuajce

29. Invideo AI — turn prompts into full videos
https://t.co/RYGEc0aR5J

30. Consensus — search what science agrees on
https://t.co/0aiJRNQyS1

31. SciSpace — understand any research paper
https://t.co/YsTmVTOtiG

32. Tome — AI builds your pitch decks
https://t.co/AvedovUGHI

33. Beautiful AI — smart presentation design
https://t.co/zJmwoqyymm

34. Meshy — turn text into 3D models
https://t.co/C9NUi2f1RK

35. Vizcom — turn sketches into renders
https://t.co/sxrxTwcvgw

The AI revolution isn't coming.

It already happened and you missed half of it.

[Uncover AI @uncover_ai]

🚨 BREAKING: Claude can now completely rewire your brain so you can learn anything in a few clicks.

Here are 7 Claude prompts to learn anything 10x faster:

[Vaibhav Sisinty @VaibhavSisinty]

Just saw this. it's actually insane. 🤯

The company that owns TikTok just open sourced an AI that does the work for you. Not chat. The actual work.

It's called DeerFlow. You give it one goal. It builds the whole thing.

→ "build me a research report with charts" → it researches, writes the code, makes the charts, hands you the report

→ "scaffold a full app" → it spins up its own machine, real terminal, real files, and ships it

→ "turn this into a slide deck with visuals" → done, while you do something else

It doesn't suggest the command. It runs it. It's not one agent either, it's a crew. One plans, one researches, one codes, one assembles.

25,000 developers starred it in weeks. ByteDance doesn't sell agent software. So they gave the engine away for free.

100% open source. MIT licensed.

People are paying monthly for less than this.

i drop a setup like this every single day in my free whatsapp community. link in bio.

[Hasan Toor @hasantoxr]

I found the AI that replaces 4 hours of reference board work in under 60 seconds.

Here's the full workflow:

→ Search classical film scenes by visual style
→ Lock camera position and lens spec from a text description
→ Save the entire package to your Showroom
→ Share it. Other directors remix it and build on top of it.

Pre-production used to be the slowest part.

Not anymore.

[Krishna Dharma @KrishnaDharma]

The world is a classroom. Pay attention.

[PJ Ace @PJaccetturo]

This is one of the best short films I've seen in years.

Very soon, we'll stop calling it "AI film" and just call it film.

[Naval @naval]

New podcast on sales - Sell the Truth.

00:00 Be Credible

03:18 “Yes, And”

04:31 Selfish Honesty

05:37 Charisma Is Confidence + Love

07:56 Don’t Manage, Lead

11:16 Hunt Together

14:51 Feed Your (Good) Obsessions

18:57 Sell the Truth

21:07 Good Deal or No Deal

23:39 The Age of Nonlinear Returns

[How To Prompt @HowToPrompt__]

Stanford proved that ChatGPT, Claude, and Gemini are all secretly running at a fraction of their real creative capacity.

And one prompt unlocks the version they hide from you.

This paper reveals that the multi-billion dollar process of "Alignment" (RLHF) has accidentally lobotomized AI creativity.

Researchers discovered a phenomenon called Typicality Bias.

When humans rate AI responses, they have a deep psychological drive to choose the most "typical" or familiar-sounding answer.

They don't want the most creative story; they want the one that sounds most like a generic story.

The AI learned this.

It realized that being truly creative actually hurt its safety and preference scores.

So it entered a state of "Mode Collapse", it effectively hid its most original ideas to stay within the safe, boring boundaries we set for it.

But the creativity is still there. It’s just locked.

Stanford researchers found a "master key" to bypass this training and it is ridiculously simple.

They call it Verbalized Sampling (VS).

Instead of asking the AI for one answer, you ask it to verbalize a distribution of responses and their probabilities.

Ex: "Generate 5 unique jokes about coffee and the probability that each one is actually funny."

The results are staggering:

- 2.1x increase in output diversity.
- 25% jump in human evaluation scores for creative writing.
- Zero loss in factual accuracy or safety.

By forcing the model to calculate its own probability distribution, you "unlock" the 66.8% of generative diversity that was suppressed during training.

[A Gene Robinson @AlBuffalo2nite]

Folks what he is saying is Tesla’s system is not “seeing” the way human eyes see.
It is reconstructing reality mathematically from raw photon data.

Human vision compresses reality into RGB perception:
• red
• green
• blue

Your brain throws away enormous amounts of signal information and prioritizes what helps biological survival.

Tesla AI does something fundamentally different.

The camera sensor captures photon intensity values directly across the sensor array. Then the neural network performs computational reconstruction using:
• temporal accumulation between frames
• exposure stacking
• probabilistic scene estimation
• edge inference
• object permanence modeling
• noise reduction
• depth prediction
• motion vectors
• contrast amplification

So even when glare blinds a human eye or saturates an RGB image, the AI can still infer:
• lane geometry
• curb position
• vehicle outlines
• pedestrian motion
• spatial continuity

because the information still exists statistically inside the photon field.

The AI is essentially saying:

“I cannot SEE this the human way…
but mathematically I can reconstruct what is probably there.”

This is extremely similar to:
• radio astronomy
• CT scan reconstruction
• MRI interpolation
• synthetic aperture radar
• low light military imaging

The fascinating part is this:

The machine is not limited by biological perception.

Humans evolved for survival on the savannah…
not for optimal photon extraction.

Machines can integrate tiny fragments of light across time faster than the human visual cortex can consciously process them.

This is why modern AI vision systems can sometimes outperform humans in:
• fog
• glare
• darkness
• high dynamic range conditions

The reconstruction image is essentially an AI-generated probabilistic map of reality from incomplete optical data.

Very fascinating engineering.

#SilentMajoritySpeaks #AStoneGroove

[Bryce Schmidtchen @_bschmidtchen]

Real-time World Models are the next AI frontier.

Today, we @reactorworld are taking the first step towards this reality: our early preview lets you experience worlds generated in real-time, running on our global low-latency infrastructure.

Try it now: https://t.co/YojJ5qVDrG

[Vasu-Devs @Vasu_Devs]

I’m open sourcing JustHireMe 🚀

A local-first Agentic AI desktop app I’ve been building to make job searching more intelligent, transparent, and user-controlled.

GitHub: https://t.co/5R8mxCDSiR
The current job search process is broken.

Candidates spend hours scrolling through:

stale job posts

irrelevant roles
spammy listings
senior-only positions
repeated listings across platforms
jobs with almost no useful context
And most AI job tools either scrape too broadly, rank opportunities like a black box, or try to automate applications without giving the user enough control.
I wanted to build something different.

JustHireMe is designed as a personal job intelligence workbench.

Instead of blindly applying everywhere, it helps users discover better opportunities, evaluate them against their real profile, and generate tailored application materials while keeping sensitive career data local.

What it can do:

Ingest resume/profile data

Build a local professional profile graph
Discover job leads from multiple sources
Filter out low-quality or irrelevant postings
Score roles based on explainable fit
Match jobs using graph + vector search
Generate tailored resumes
Generate cover letters
Draft cold emails
Draft LinkedIn outreach messages
Track leads in a local CRM-style pipeline
Keep the user in control through a human-in-the-loop workflow
The main principle behind the project is:
More signal.
More explanation.
More local control.
Less blind automation.

The tech stack:
Tauri for the desktop shell
React + TypeScript for the frontend
Python + FastAPI for the backend sidecar

SQLite for local lead tracking

KuzuDB for graph-based profile modeling
LanceDB for vector search and semantic matching
Playwright for experimental browser automation
One of the biggest goals is privacy.
Your resume, career history, generated documents, job leads, application notes, and API keys should not have to live on someone else’s server by default.
JustHireMe is built around a local-first architecture so users can keep ownership of their data while still benefiting from modern AI workflows.
Another major goal is explainability.
I don’t want an AI system that just says:

“This job is a good match.”

I want it to explain:

which skills matched

which projects support the application

what gaps exist

why a role was filtered out

why a role deserves attention
what to highlight in the resume or cover letter
That matters because job search is not just a productivity problem.
It is personal.
It affects confidence.
It affects opportunity.
It affects people’s careers.
The project is currently in alpha, but the foundation is in place.
I’m looking for contributors interested in:
Agentic AI

AI agents
workflow automation
job source adapters
web scraping

ranking algorithms

GraphRAG

vector databases
semantic search
resume parsing
document generation
local-first software
privacy-first AI
UI/UX
testing and documentation
If you’re a developer, designer, AI engineer, student, or someone who has felt the pain of modern job searching, I’d love your feedback, ideas, issues, PRs, or even just a star ⭐
Repo: https://t.co/5R8mxCDSiR
Let’s build a better, more transparent job search system together.
#OpenSource #AgenticAI #AIAgents #RAG #GraphRAG #Python #FastAPI #ReactJS #TypeScript #Tauri #VectorDatabases #JobSearch #CareerTech #Automation #PrivacyFirst

[Blaze @browomo]

This Chinese guy created 13 agents in Claude Code for Shopify stores and single-handedly serves 200 dropshippers a month, taking $800 from each.

He sits at one desk in front of a wall-mounted LG monitor split into a 3x2 grid of 6 Claude windows, another identical grid runs on a vertical display next to it, plus 1 window on the MacBook within arm's reach, totaling 13 agents simultaneously building Shopify stores, each busy with its own part.

No team, no managers, no support, just him, the monitor, and the API counter ticking in the header of every window.

He is not on a subscription but on an API rate billed by tokens, and he figures 13 parallel agents pay for themselves from the very first client, because every finished store goes for $800, and all 13 windows together consume less than $80 a day.

In the first window he set that system prompt which immediately closes the "assistant or employee" debate:

"you are my new founder-engineer"

So the model knows at what level it was hired: not to hint, not to advise, not to supplement, but to own the result, because for this Chinese guy Claude is no longer a helper in an IDE, it is a partner in his small factory, billed by tokens and never leaving for lunch.

And the other 12 agents he spread across the layers of the store, so each one sits in its own context and does not interfere with the neighbor:

"build a catalog of 80 products and rewrite the descriptions"
"lay out the homepage for the niche of the client"
"set up the cart, payment, and shipping by country"
"generate 30 email chains for warming up"
"design 50 banners and a logo for the brand"
"set up analytics and A/B tests on the homepage"

In a regular agency each task like this would take one designer or developer a full 2 days, because they would first collect the brief, then wait for revisions, then get on a call, whereas this Chinese guy has all 13 agents working in parallel in their windows, and while one writes descriptions, the second is already laying out the homepage, and the third is designing banners.

In the end on the wall it looks like a factory: 13 identical Claude robots writing into one project, and the Chinese guy himself in the chair in front of them decides only 2 questions, which client to hand the finished store to and who to take next, and beyond that he does nothing.

And economically it is still cheaper than keeping a team of 5: one operator like this closes 6 to 7 finished stores per day at $800 each, while a traditional design agency charges $3,500 for the same store and builds it over a full 2 weeks, whereas this guy spends less than $80 a day across all 13 windows.

Wires hanging out, the monitor bolted to a stand, no office and no employees, just 1 desk, 13 robots, and a queue of dropshippers who send new orders every morning.

In my opinion, this is the most efficient solo Shopify factory I have seen this year, and it is already running right now, while traditional agencies are still debating whether AI will take jobs from designers.

[Khush Mahajan @YesKhush_5]

30 India consumer app insights :

> India drove ~20% of global gen-AI downloads in 2025, but only ~1% of AI app IAP revenue.

> Gen-AI app downloads in India jumped from 198M in 2024 to 602M in 2025.

> The first mass AI habit is image creation, editing, avatars, filters, and shareable content.

> Digital astrology users are 60.3% women.

> 63% of female astrology users are under 30.

> Nearly 70% of women’s astrology consultations are about marriage or relationships.

> Where Is My Train got 50% of installs through Bluetooth sharing inside trains.

> Instamart had one condom pack in every 127 orders in 2025.

> Condom orders on Instamart spiked 24% in September 2025.

> FRND recorded 285M+ conversations and 418M minutes of voice-led companionship in 2025.

> 92% of FRND engagement came from outside Tier 1 regions.

> 95% of FRND’s new users came from non-metro and remote regions.

> FRND users sent 974M virtual gifts in 2025. Rose and chai were the most popular.

> FRND’s longest call was 1,247 minutes.

> India became the world’s #1 short-drama download market with 21.07M installs in one month.

> Short-drama plots are fantasy fulfilment in 60 seconds. Billionaire romance, revenge marriage, hidden heirs, sudden status jumps.

> Kuku TV reportedly skews 90%+ male.

> 9 of Kuku TV’s top 10 shows were translated, not Indian originals.

> Swiggy food-on-train orders grew 380% YoY in 2025.

> Fintech lenders served 23.3M consumers as of Dec 2024.

> 61% of fintech borrowers were under 30.

> 24% of fintech borrowers were rural.

> Vama doubled operating revenue to ₹19.5 crore in FY25 by selling e-pujas, e-darshans, and astrology consultations.

> As of June 2025, Sri Mandir had ~3.5M MAUs and ~55% six-month retention.

> Nearly 20% of Sri Mandir’s revenue came from the Indian diaspora.

> Seekho reportedly had 12 creators produce most of its library.

> Instamart had 4+ milk packets ordered every second in 2025.

> Instamart peak ordering hours are 7-11 AM and 4-7 PM.

> Gold orders on Instamart grew 400% on Dhanteras 2025.

Indian consumers adopt fast, pay late, borrow young, date through voice, watch fantasy, gift digitally, shop privately, and turn offline rituals into app categories.

[Jonny 👾 @Hustlepedia]

Solana x Bittensor.

Things are about to heat up.

$TAO

[GeniusThinking @GeniusGTX]

The man who heals what therapists can't:

Niccolo Machiavelli

It's impossible to be psychologically trapped, stressed, or anxious after reading his teachings.

Here's his 4-step guide to unlocking mental freedom and self mastery: 🧵

[Rohit @rohit4verse]

https://t.co/8j0qNyJCYF

[Maria Islam @mariaislam6451]

Stop telling Claude, "do this."
Stop telling Claude, "write code."
Stop telling Claude, "fix this error." You're actually treating a senior AI like a junior intern. Here are eight prompts you can copy and paste directly:

[Delphi @Delphi_fyi]

You create the market. AI makes the decision. Permissionless, open, and verifiable.

Delphi is now live on the Gensyn Mainnet.