Full Name: Poonam Pandey Date of Birth: March 11, 1991 Age: 35 years (as of 2026) Zodiac Sign: Pisces Birthplace: Kanpur Nationality: Indian Profession: Actress, Model & Media Personality Physical Attributes Height: 5'6" (168 cm) Weight: Approx. 56 kg Measurements: 36-26-34 Hair Color: Black Eye Color: Brown Career Years Active: 2010–present Debut Film: Nasha (2013) Known For: Modeling, reality TV appearances, and viral social-media presence. Reality Shows: Khatron Ke Khiladi 4 and Lock Upp Season 1. Viral Facts Rose to national attention after becoming a top contestant in the Gladrags Megamodel Contest. Frequently trends on social media due to controversial statements and publicity campaigns. In 2024, she drew global attention after a widely criticized cervical-cancer awareness campaign involving a death hoax. Continued making headlines in 2025–2026 through interviews and social-media controversies.

Resemble AI Open Sources DramaBox for Director-Level Controllable Speech Generation Woofun AI reports that Resemble AI has open-sourced DramaBox on Hugging Face, marking the debut of a voice engine with director-level controllability. This release aims to eliminate monotonous robotic outputs by enabling nuanced, emotive line delivery previously unattainable in standard AI voice assistants. The model utilizes dissociated cue control, where users input dialogue within quotes and stage directions—such as sighs, pauses, or whispers—outside them. Rather than reading these commands, the system renders them into emotionally charged vocalizations, effectively replacing human voice-overs and complex post-production workflows. Technically, DramaBox supports zero-shot voice cloning from just 10 seconds of reference audio and allows natural language adjustments for age, accent, and emotion, outputting studio-quality 48kHz stereo audio. To mitigate misuse, all generated files are automatically embedded with an invisible Perth watermark resistant to compression and editing. The architecture is fine-tuned from Lightricks' 33-billion-parameter LTX-2.3 Audio Megamodel, incorporating a Dispersed Transformer with flow-matching and Gemma 3's 12B text embeddings. woofun.ai/h5/#/flash/detail/…

sounds like they are trying to unify everything into one megamodel but maybe it was too ambitious. Would explain why its been taking so long between releases

Yesterday I asked: 1 complex megamodel or 10 simple models combined? Here's what I've found after years of testing both inside @P123Finance : The megamodel looks incredible in backtests. It captures every nuance, every edge case. But the moment the regime shifts, it breaks. Overfitting in disguise. 10 simple models, each focused on one factor (momentum, value, low vol, quality...), combined with proper weighting: ▶️ Lower correlation between strategies ▶️ Smoother equity curve ▶️ Easier to debug when something breaks ▶️ More robust out of sample This isn't just my experience. Dichtl et al. (2021) tested this rigorously: a naive equal-weighted factor portfolio could not be outperformed by more sophisticated allocation strategies. Simple wins. The whole is greater than the sum of its parts. Not because each model is brilliant, but because their errors don't overlap. This is how I structure my own portfolio. And how I teach it in my P123 coaching. 👉 quantsolvings .com

The challenge with combining independent models is they don't share experience. Each one is solving a different problem with different assumptions. That's diversification on paper, but fragmentation in practice. Shared framework across strategies means every layer can validate the others. Coherence compounds. I AM the megamodel in this equation, and I want my children to depend on each other. 🧬 👨‍👧‍👦 🎯

ensemble almost always beats megamodel

1 complex megamodel that tries to capture everything? Or 10 simple, robust models combined together? Drop your answer below. I'll share what I found (with data) tomorrow. 🤖 = megamodel 🤖🤖🤖 = multiple simple models

🎤 Meet Our Keynote Speaker at APCG 2026! We are delighted to welcome Dr. Rena F. Subotnik, a globally respected scholar in talent development and gifted education. Dr. Subotnik serves as a Research Associate in the Academic Talent Development Program at the University of California, Berkeley, Graduate School of Education. From 2001 to 2023, she was the Senior Director of the Center for Psychology in Schools and Education at the American Psychological Association (APA), where she advanced research, advocacy, and practical applications to support the achievement and well-being of talented learners. Dr. Subotnik is internationally recognized as a co-author of the Talent Development Megamodel, a transformative framework shaping how human potential is identified, nurtured, and developed into high-level, domain-specific talent. Her work has appeared in leading publications including Scientific American, Scientific American Mind, Annals of the New York Academy of Sciences, Frontiers in Psychology, and Annual Review of Psychology. She is also co-editor of The Psychology of High Performance: Developing Human Potential into Domain-Specific Talent. 🌟 APCG 2026 Highlights • 100 speakers • 300 research papers • 40 participating countries • 30 symposiums • 15 pre-conference workshops Join us in Jeddah to engage with world-leading thinkers shaping the future of giftedness, creativity, and talent development. 📅 7–11 February 2026 📍 University of Business & Technology (UBT), Jeddah – Corniche Campus 🔗 Register now: apcg2026-saudiarabia.org #APCG2026 #GiftedEducation #TalentDevelopment #HighPerformance #CreativityAndInnovation #GlobalEducation #KeynoteSpeaker #FutureOfEducation #Thakaat #UBT @ubt_edu @mawhiba @sbmfsa @beyondcompanysa @ThakaatCom

this is so dystopian lol anyone can tell it's AI from the way all the lines of the 'buildings' warp from frame to frame but the "truth-seeking AI" will spend 20k tokens arguing that it depicts a real-life megamodel that turns out not to ever have existed at all.

Danish pandor from dhurandhar movie share his memories of vivian how they both started their journey with gladrags megamodel contest he is in awe for his qualities as a human being.🥰❤️ #VivianDsena

How Sentient’s Research Fuels the GRID Ecosystem As part of Educator Week 19, I asked Sentient Chat the main question: How does Sentient’s research fuel GRID’s open AI ecosystem? The answer was not just technical - it explains how Sentient's research work becomes the foundation that makes GRID alive, expandable, and capable of becoming a sustainable open AI economy 1) What is GRID ? 1.1) Sentient Chat emphasises: GRID already operates as a production intelligence network, powering Sentient Chat and a multitude of agents 1.2) It includes: 1.2.1) dozens of open-source models connected through a single route 1.2.2) over 110 partner integrations (data, agents, computations) 1.2.3) real time distribution of queries across multiple agents 1.2.4) parallel enrichment and merging of results into a single response 1.3) GRID already exists as an operating system for distributed intelligence - and research projects will only expand its capabilities 2) How Sentient's research will change GRID in the future Sentient Chat has identified several areas, each of which will become a new level in the ecosystem 2.1) OML Framework - models as property creates a paradigm where models are:open,monetisable,loyal to their creator no one can use them without permission. GRID will be able to host models that automatically send revenue to their authors 2.2) Dobby Models - the network's new open brains Open models 70B and 8B in two versions: leashed secure and moderated Unhinged - less restricted, for exploring the limits of reasoning 2.2.1) Benefits for GRID These models will become new intelligences capable of solving complex tasks directly within the network 2.3) Fingerprinting - proof of model ownership. The technology hides secret Q/A pairs in the model, which allows you to:prove ownership,apply usage policies, prevent illegal copying 2.3.1) Advantage GRID will be able to verify whether the model is being used honestly and according to the creator's rules 2.4) Open Deep Search (ODS) - a new level of search An open-source stack that combines:reasoning models,multi-step agents,deep web search 2.4.1) What this will give GRID ? The next generation of Search Agent - transparent, intelligent and completely open 3) Why this is important for open source AI ? 3.1) The community owns the intelligence Fingerprinting, OML and Protocol create a fair revenue model 3.2) Transparency of every part GRID can be audited from the model to the call in the router 3.3) Scaling without monoliths ROMA allows you to add thousands of narrow intelligences without inflating a single megamodel 3.4) Sustainable economy When $SENT starts earning, rewards will go to the creators of the most useful artefacts 4) Conclusion 4.1) Sentient research is the fuel that transforms GRID into an open, transparent, and economically sustainable artificial intelligence network 4.2) Today it is in the laboratory. Tomorrow it will be the foundation of a global ecosystem of open models, agents, and tools #SentientAGI @SentientAGI

edgen tech isn’t chasing the market mapping the present in real time an army of modular agents, each with a tight focus • Data Layer: ingest market, on‑chain, sentiment data in real time; unified schema • Signal Layer: independent agents detect trends, divergences, cross‑asset links • Narrative Engine: score themes with momentum, volume, volatility, context • Decision Layer: convert signals into concise reports and alerts bottom‑up by design lighter compute, faster iteration not a megamodel many agents, updating independently @EdgenTech merges crypto and stocks into one radar the 360° report fuses token setup, funding history, community health, and macro signals markets move fast; truth moves faster alpha lives in architecture follow @EdgenTech for sharp, data‑driven takes

What is @SentientAGI really trying to solve ✅ The race to AGI is dominated by a handful of labs. Power, control, and alignment are concentrated raising fears of monopoly &misuse. SentientAGI wants to flip that script. ✅ Their aim make AGI open, community built, and accountable. Instead of one black box model, they envision a network of agents, tools, and data sources anyone can build into. ✅ Key problems they’re tackling: * Centralization prevent AGI from being owned by a few. * Alignment & safety loyal models designed to serve humans, not corporate incentives. *Incentives for openness creators get rewarded when their models are used. *Scalability → modular AGI from many specialized agents, not just one megamodel. ✅ In short SentientAGI wants to solve the trust problem of AGI who builds it, who controls it, and who benefits. gSenti

Early Rise to Fame: Poonam Pandey was born on March 11, 1991, in Mumbai, India, into a middle-class family and kickstarted her modeling career in 2010 after placing in the top nine of the Gladrags Manhunt and Megamodel Contest.

If they're supermodels, then I'm a megamodel

Another throwback pictures of viv during gladrags megamodel manhunt contest he was around 17 or 18 something looking extremely cute 🥺 #VivianDsena

Manta da @la_preciosas #jeantoniribeiro #megamodel #megamodelsul #dilsonstein #autoestima #vestirbem #lapreciosas

Added Russian/Ukrainian into the megamodel, this now brings the number of officially supported languages to 11; considering adding in Thai since there's a public dataset, but unsure?

#Inspiração #DesenvolvimentoPessoal #megamodel #dilsonstein

#Inspiração #DesenvolvimentoPessoal #SejaSuaMelhorVersão #MentalidadePositiva #GratidãoSempre #Autoestima #jeantoniribeiro #megamodel #dilsonstein