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Today:

• OpenAI’s Deep Research Transforms Productivity

• OpenAI Powers 23 California Campuses

• ByteDance OmniHuman AI Creates Realistic Videos

• Physical Intelligence Launches π0 for Robots

• Figure Ditches OpenAI for In-House Models

• OpenAI Expands with Kakao Partnership

• AI Transforming Breast Cancer Detection

Deep Research STUNNING Performance REPLACES Human Labor, Paves Way for Agents

A new AI research tool, OpenAI’s Deep Research, is gaining attention for its ability to conduct complex, multi-source research in minutes. Users, including early-access experts, are calling it a game-changer for fields like medicine, law, and scientific publishing. 

The AI can analyze vast datasets, compile detailed reports, and even provide personalized insights, such as health recommendations based on uploaded medical records. Some estimates suggest it could automate 10–18% of economically valuable tasks worldwide.

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OpenAI Powers 23 California Campuses

OpenAI and the California State University system have launched the largest deployment of ChatGPT, providing over 500,000 students, faculty, and staff access to an AI-powered educational platform. This initiative offers personalized learning, AI coaching, and workforce readiness programs, aiming to equip students with essential AI skills for the future. The rollout, which spans 23 campuses, sets a global precedent for integrating AI into higher education, enhancing learning outcomes and career prospects.

ByteDance OmniHuman AI Creates Realistic Videos 

ByteDance has developed OmniHuman, an AI system that creates realistic full-body videos from a single photo, including natural movements and gestures. Trained on over 18,700 hours of video data, OmniHuman can generate videos of people speaking, singing, and performing actions like playing instruments. This breakthrough surpasses previous models by animating entire bodies, not just faces. While it promises advancements in entertainment and education, it also raises concerns about the potential misuse of synthetic media.

Physical Intelligence Launches π0 for Robots

Physical Intelligence has released π0, a general-purpose robotic foundation model that can be fine-tuned for diverse tasks like folding laundry or cleaning, and supports various robots. The openpi repository offers code, model weights, and pre-trained checkpoints for platforms like ALOHA and DROID. This release aims to advance robotic learning and contribute to the development of broadly capable physical intelligence. Researchers are encouraged to experiment with the model and share feedback for further improvements.

Figure Ditches OpenAI for In-House Models

Figure AI, a robotics company focused on humanoid robots for residential and commercial use, announced it is ending its partnership with OpenAI. Instead, it will develop in-house AI models after achieving a significant breakthrough. Figure's CEO, Brett Adcock, stated that integrating AI specific to their robots is crucial for scaling real-world applications. Despite OpenAI’s involvement in humanoid robotics, Figure believes that vertical integration of both hardware and software is essential to solving embodied AI challenges.

OpenAI Expands with Kakao Partnership

OpenAI has partnered with Kakao to develop AI products in South Korea, marking its second major alliance in Asia. CEO Sam Altman emphasized Korea's significance for AI growth, citing demand from energy, semiconductor, and internet sectors. Altman also discussed potential contributions from Korean firms to OpenAI’s Stargate project, a U.S.-based AI data center initiative. He met with leaders from SoftBank, Samsung, and SK Group during his Asia tour, further exploring AI collaborations.

AI Transforming Breast Cancer Detection

A major NHS trial will recruit nearly 700,000 women to test five AI platforms for breast cancer screening across 30 sites in the UK. Starting in April, the £11 million Edith trial aims to speed up diagnoses and relieve pressure on radiologists by allowing AI to assist in reviewing mammograms. The trial could significantly impact radiology workloads, improving efficiency and reducing waiting lists. However, experts warn that addressing the ongoing shortage of radiologists remains urgent.

🧠RESEARCH

The Differences Between Direct Alignment Algorithms are a Blur

The paper examines Direct Alignment Algorithms (DAAs), comparing one-stage and two-stage methods for improving language model alignment. It finds that incorporating a Supervised Fine-Tuning (SFT) phase boosts performance, especially in Alpaca Eval 2. The study emphasizes the importance of evaluating alignment techniques to avoid premature conclusions about their effectiveness.

OmniHuman-1: Rethinking the Scaling-Up of One-Stage Conditioned Human Animation Models

The paper introduces OmniHuman, a Diffusion Transformer-based framework for scaling human animation models. It improves data handling by mixing motion-related conditions in training, enhancing video realism and flexibility. OmniHuman supports various portrait contents, human-object interactions, and multiple input modalities, outperforming existing audio-driven methods in realism and versatility.

Process Reinforcement through Implicit Rewards

The paper introduces PRIME (Process Reinforcement through Implicit Rewards), which addresses challenges in training large language models with dense process rewards. PRIME allows online updates using only policy rollouts and outcome labels, eliminating the need for expensive reward model training. It demonstrates significant performance improvements in math and coding tasks, achieving higher reasoning accuracy with less training data.

MM-IQ: Benchmarking Human-Like Abstraction and Reasoning in Multimodal Models

The paper presents MM-IQ, a benchmarking framework for evaluating human-like abstraction and reasoning in multimodal models. With 2,710 test items across 8 reasoning paradigms, MM-IQ highlights the limitations of current models, showing that even the best systems perform only slightly better than random chance. This reveals a significant gap in cognitive capabilities between AI and humans.

DeepRAG: Thinking to Retrieval Step by Step for Large Language Models

The paper introduces DeepRAG, a framework that models retrieval-augmented reasoning as a Markov Decision Process (MDP) to improve retrieval efficiency and answer accuracy in large language models. By decomposing queries iteratively, DeepRAG adapts whether to retrieve external knowledge or use parametric reasoning, boosting accuracy by 21.99%.

🛠️TOP TOOLS

PhotoAI - AI-powered platform that transforms ordinary photos into personalized, high-quality images for various purposes.

ChatCSV - AI-powered personal data analyst tool that enables users to interact with CSV files through natural language queries.

FormWise -No-code platform that enables marketers, agencies, and coaches to create custom AI-powered tools without programming skills.

FreeImage AI - AI-driven tool designed to help webmasters and entrepreneurs create high-quality visuals for their online marketing needs.

TLDR This - Web-based tool designed to simplify the process of consuming lengthy online content.

📲SOCIAL MEDIA

🗞️MORE NEWS

• Adobe's new Acrobat AI Assistant helps users understand complex contracts by summarizing key terms, comparing versions, and highlighting changes. It acts as a guide for document analysis, not legal advice, ensuring privacy and security.

• Ola founder Bhavish Aggarwal is investing $230 million in Krutrim, an AI startup focused on developing large language models for Indian languages. Krutrim aims to raise $1.15 billion and build India's largest supercomputer with Nvidia.

• Quantinuum has introduced a Generative Quantum AI framework, harnessing quantum-generated data to solve complex problems in sectors like medicine, finance, and logistics. This breakthrough enables new AI capabilities beyond classical computing's limitations, with vast commercial potential.

• Hugging Face researchers have developed an open-source version of OpenAI's deep research tool, called Open Deep Research. It autonomously navigates the web, processes data, and offers an open framework for building advanced AI applications.

• Google has lifted its previous ban on using its AI for weapons and surveillance, reversing guidelines established in 2018. The company now allows the development of AI technologies with potential military and surveillance applications.

• Snap has introduced a new AI text-to-image model for mobile devices, capable of generating high-resolution images in 1.4 seconds on an iPhone 16 Pro Max. This model, running entirely on-device, aims to power Snapchat features like AI Snaps and Bitmoji Backgrounds while lowering operational costs.

• Microsoft has hired former DeepMind researchers Marco Tagliasacchi, Zalán Borsos, and Matthias Minderer to work on advanced AI features. Their work, including the AI podcast tool "Audio Overviews," will contribute to Microsoft's efforts in developing interactive AI agents like Copilot.