World’s First AI-Native Social Feed📲

AI is breaking boundaries across entertainment, conservation, and biomedical research.

• Character.AI has unveiled Feed, an AI-native social hub turning chats into shareable creative content.

• Google DeepMind’s upgraded Perch AI is supercharging wildlife protection with cutting-edge bioacoustic analysis.

• MIT & Harvard researchers have introduced PUPS, a breakthrough model predicting protein locations in human cells to accelerate disease research.

Let’s dive into the innovations shaping the future. 👇️ 

Character.AI Turns Users into Creators with Innovative Social Feed

Character.AI has launched Feed, the world's first AI-native social feed, transforming its platform from just a chat app into a dynamic, interactive hub for AI-powered entertainment. Now available on the mobile app, Feed lets users create and share multimodal short-form content like chat snippets, Character Cards, Streams for debates and battles, Avatar FX videos, and AI-generated backgrounds. The platform encourages remixing and collaboration—users can interact, rewrite stories, and build on each other’s creations. Community safety is ensured through moderation tools and its Trust & Safety team, making Character.AI a leading destination for creative AI-driven content and social experiences.

Google DeepMind Upgrades Perch AI to Boost Wildlife Conservation

Google DeepMind has released an updated version of its Perch AI model to help conservationists analyze massive amounts of bioacoustic data and protect endangered species, such as Hawaiian honeycreepers and coral reefs. Trained on nearly twice as much data as before—including birds, mammals, amphibians, and human-made noise—from sources like Xeno-Canto and iNaturalist, the new Perch offers state‑of‑the‑art species recognition, improved adaptation to varied environments, and the ability to analyze millions of hours of audio. Open-sourced and available on Kaggle, Perch supports agile modeling, allowing scientists to create custom classifiers in under an hour, even with limited training data. Already integrated into popular tools like Cornell’s BirdNet Analyzer, Perch has aided in discoveries such as new populations of the endangered Plains Wanderer and sped up honeycreeper monitoring in Hawaiʻi by nearly 50x, showcasing the transformative role AI can play in biodiversity conservation.

MIT and Harvard Researchers Develop AI to Predict Protein Locations in Human Cells

Researchers from MIT, Harvard, and the Broad Institute have developed a new AI-based computational method, called PUPS, that can predict the location of any protein within any human cell line—even for proteins and cells never seen before. This approach uniquely localizes proteins at the single-cell level, providing precise images highlighting predicted protein locations inside cells based on input amino acid sequences and three stained cellular images (nucleus, microtubules, endoplasmic reticulum). PUPS combines a protein language model (capturing protein sequence and 3D structural features) with an image inpainting computer vision model (analyzing the cell’s state), enabling it to generalize across proteins and cell types with enhanced accuracy compared to baseline AI methods. The model is further trained to name cellular compartments explicitly, improving its predictive understanding. Validated by laboratory experiments, this method promises to accelerate disease diagnosis and drug development by efficiently screening protein localization patterns without requiring extensive lab work. Future plans include extending PUPS to predict protein-protein interactions and applying it to living tissues rather than cultured cells.

Hand Picked Video

In this video, we’ll look at real-world GPT-5 use cases from coding and writing to reasoning and research to see if it truly lives up to the hype and how it stacks up in everyday tasks.

Top AI Products from this week

• Simular Pro - Simular is building the world’s first autonomous computers—systems that can use software like humans do. From browsing websites and filling out spreadsheets to running creative tools and managing workflows, Simular enables a new era of human.

• Yummery - Meet Steve, your 24/7 AI financial coach that turns everyday money habits into real progress with zero judgment. Forget spreadsheets and pricey advisors. Get science-backed nudges and goal guidance to build lasting confidence on your path to financial freedom.

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• Prexist - Validate your startup idea in seconds. Prexist searches 8 platforms like Product Hunt, Y Combinator, GitHub, Crunchbase & App Stores (iOS and Android) using AI to find similar products — all in one place. Save weeks on research and build smart.

• iGrow - Meet iGrow — a gamified, AI-powered microlearning app for Gen Z & early pros that builds real-life skills (negotiation, leadership, time & money). Interactive simulations, habit loops, and a personal AI coach. Try the MVP free and tell us what to build next!

This week in AI

• Open Source NuMarkdown-8B-Thinking - First reasoning OCR VLM for accurate document-to-Markdown conversion, excelling at complex layouts/tables; ideal for RAG and structured data extraction.

• MiniMax Speech 2.5- Advanced AI speech with 40 languages, ultra‑realistic voice cloning, and precise accent, age, and emotion preservation for truly human‑like expression.

• GPT-5 in Cursor - OpenAI’s most powerful, highly steerable model now boosts coding in Cursor, excelling at complex bugs, multi-module tasks, and customizable responses.

• AI Targets Students - OpenAI’s new ChatGPT “study mode” rivals Chegg, Quizlet with Socratic tutoring, quizzes, and study plans as edtech adapts to generative AI’s rise in classrooms.

• Microsoft Adds GPT-5 - Microsoft integrates OpenAI’s most advanced model across Copilot, GitHub, and Azure, boosting reasoning, coding, and productivity with strong safety safeguards

Paper of The Day

The paper "A 'good regulator theorem' for embodied agents" by Virgo, Biehl, Baltieri, and Capucci addresses and extends the classical Conant and Ashby good regulator theorem, which states that every good regulator must be a model of the system it regulates. The authors show that for embodied agents performing regulation tasks, it is possible for an external observer to interpret the agent as having "beliefs" about its environment that update based on sensory input. This leads to a new, more general theorem connecting regulation with the presence of such interpretable models, even in embodied, dynamical systems beyond classical control theory.

To read the whole paper, go to here.