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Today:

• Anthropic to Unveil New Hybrid AI Model

• Musk Threatens OpenAI Bid Withdrawal

• Apple Teams with Baidu, Alibaba

• YouTube Adds Veo 2 to Shorts

• Musk Unveils Grok 3 AI Model

Anthropic to Unveil New Hybrid AI Model

Anthropic is set to release a new AI model within weeks, blending "deep reasoning" with fast responses. This hybrid model will feature a sliding scale for cost control, as deep reasoning demands more computing power. The model is expected to outperform OpenAI’s o3-mini-high on certain tasks, including programming and business analysis. CEO Dario Amodei emphasized the company’s focus on creating distinct reasoning models that challenge traditional approaches.

Musk Threatens OpenAI Bid Withdrawal

Elon Musk has threatened to withdraw his $97.4 billion takeover bid for OpenAI’s nonprofit controlling entity unless the board halts its planned shift to a for-profit model. Musk claims the nonprofit’s value would be compromised during the conversion. OpenAI’s CEO, Sam Altman, responded by stating that the board would reject Musk’s offer. The situation is part of Musk's ongoing legal efforts to prevent OpenAI’s transition.

Apple Teams with Baidu, Alibaba

Apple is continuing its partnership with Baidu to develop AI features for iPhones in China, including an AI-powered search tool and improvements to Siri. Despite challenges with Baidu, Apple has also onboarded Alibaba to enhance AI capabilities in the Chinese market, where local regulations require partnerships with domestic companies. This dual collaboration reflects Apple’s strategy of working with multiple AI partners to strengthen its position in China amid growing competition from local smartphone brands.

YouTube Adds Veo 2 to Shorts

YouTube is integrating Google's Veo 2 AI video model with its Dream Screen tools for Shorts, allowing creators to generate AI-generated video clips. The new feature enables video creation from text prompts, offering options for styles, effects, and length. This update, now available in the U.S., Canada, Australia, and New Zealand, improves video realism, especially human movement and physics. Generated content will be tagged with visual labels and AI watermarks for transparency.

Musk Unveils Grok 3 AI Model

Elon Musk introduced Grok 3, the latest AI chatbot from his company xAI, claiming it outperforms all rivals in reasoning. Set for release in one to two weeks, Grok 3 improves accuracy by analyzing its own mistakes. Musk criticized OpenAI for shifting from a nonprofit to a profit-driven model and revealed his group’s $97.4 billion bid to acquire OpenAI’s nonprofit entity. Grok 3 will compete with major AI models like ChatGPT, Gemini, and Claude.

🧠RESEARCH

TextAtlas5M: A Large-scale Dataset for Dense Text Image Generation

TextAtlas5M is a new dataset designed for evaluating long-text rendering in text-conditioned image generation. With 5 million images and a curated 3000-test set, it offers a comprehensive benchmark for large-scale models. Evaluations highlight significant challenges even for advanced models, positioning it as a valuable resource for future development.

BenchMAX: A Comprehensive Multilingual Evaluation Suite for Large Language Models

BenchMAX is a multilingual evaluation benchmark designed to assess large language models' advanced abilities like reasoning, code generation, and instruction following across 17 languages. It includes machine-translated data annotated by native speakers. Experiments reveal performance gaps between languages, highlighting that scaling model size alone doesn't bridge these issues.

Light-A-Video: Training-free Video Relighting via Progressive Light Fusion

Light-A-Video is a training-free method for video relighting that ensures temporal consistency in lighting. By introducing the Consistent Light Attention (CLA) module and Progressive Light Fusion (PLF), it smooths lighting transitions between frames, overcoming issues like flickering and appearance inconsistency. The approach improves video quality without excessive training costs.

CineMaster: A 3D-Aware and Controllable Framework for Cinematic Text-to-Video Generation

CineMaster is a 3D-aware, controllable framework for text-to-video generation that allows precise placement and manipulation of objects and cameras in 3D space. It uses an interactive workflow to generate videos based on user-defined 3D signals and a text-to-video diffusion model, outperforming existing methods in cinematic video generation.

Scaling Pre-training to One Hundred Billion Data for Vision Language Models

This paper investigates the impact of pre-training vision-language models on 100 billion examples, finding performance saturation on standard benchmarks. However, models show significant gains in culturally diverse tasks and low-resource languages. The study emphasizes that scaling data to this size is crucial for developing inclusive multimodal systems despite challenges with noisy data.

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📲SOCIAL MEDIA

🗞️MORE NEWS

• Baidu will offer its AI chatbot, Ernie Bot, for free starting April 1, 2025, citing improved technology and cost reductions. This move comes as Baidu faces stiff competition from rivals like DeepSeek and ByteDance in China’s AI sector.

• Apptronik has raised $350 million in Series A funding, co-led by B Capital, Capital Factory, and Google. The funds will accelerate the development of Apollo, its AI-powered humanoid robot, and expand production to meet rising demand across industries like logistics, manufacturing, and healthcare.

• Simon Kohl, a former DeepMind scientist, raises $50mn to launch Latent Labs for AI drug discovery. Latent Labs aims to revolutionize drug discovery using generative AI to design synthetic proteins for pharmaceutical industry. Latent Labs plans to provide a generative AI platform as a service to cut drug development time and costs.

• Google has signed a memorandum of understanding with Poland to accelerate AI adoption, focusing on driving economic growth and transforming sectors like cybersecurity, health, and energy, according to CEO Sundar Pichai.

• NVIDIA's experiment with the DeepSeek-R1 model demonstrates how inference-time scaling can improve the automatic generation of optimized GPU kernels for attention operations, achieving faster and more efficient results, surpassing manually optimized code in some cases.