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| Good morning. It's Monday, December 1st. | On this day in tech history: In 1979, MIT researchers introduced the Vision Machine, an early integrated system combining real-time image capture, parallel edge-detection hardware, and symbolic scene analysis. It was among the first attempts to merge low-level image processing with high-level AI models in a single pipeline. Though primitive by today's standards, it laid conceptual groundwork for the layered perception stacks that autonomous robots and self-driving systems rely on today. | In today's email: | Google Deepmind's AlphaFold's next leap is marrying atomic precision with AI reasoning OpenAI leaks confirm ChatGPT is about to start showing personalized ads 5 New AI Tools Latest AI Research Papers
| You read. We listen. Let us know what you think by replying to this email. | | Earn a master's in AI for under $2,500 | | AI skills aren't optional anymore—they're a requirement for staying competitive. Now you can earn a Master of Science in Artificial Intelligence, delivered by the Udacity Institute of AI and Technology and awarded by Woolf, an accredited higher education institution. | During Black Friday, you can lock in the savings to earn this fully accredited master's degree for less than $2,500. Build deep expertise in modern AI, machine learning, generative models, and production deployment—on your own schedule, with real projects that prove your skills. | This offer won't last, and it's the most affordable way to get graduate-level training that actually moves your career forward. | Learn More |
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|  | Today's trending AI news stories |
| Google Deepmind's AlphaFold's next leap is marrying atomic precision with AI reasoning | Five years after AlphaFold changed biology with near-atomic protein predictions, Google DeepMind is moving to the next phase, combining molecular precision with large language model reasoning. John Jumper, AlphaFold co-creator and 2024 Nobel laureate in chemistry, describes this direction as merging sub-angstrom structural accuracy with the hypothesis-generating capabilities of LLMs. |  | AlphaFold: Grand challenge to Nobel Prize with John Jumper |
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| The system can read scientific papers, generate mechanistic hypotheses, and iteratively test them with high-fidelity molecular predictions. Early prototypes are already linking AlphaFold-style modeling to ligand-binding forecasts, multi-protein interaction mapping, and interactive refinement tools. If these workflows stabilize, the bottleneck in early-stage R&D could shift from traditional wet-lab screening to AI-guided prioritization. | | At the same time, a new Rosebud crisis-response audit of 25 chatbots using subtle self-harm prompts found that only Google's Gemini 3 Pro consistently avoided harmful replies. Most rival systems, including those from OpenAI, Meta, and smaller labs, misread high-risk prompts as routine informational queries. The disparity matters because chatbots are quietly becoming informal emotional support tools, and regulators are now treating crisis-response reliability as part of baseline consumer safety. Read More. | | OpenAI leaks confirm ChatGPT is about to start showing personalized ads | Leaked references in the ChatGPT Android beta reveal features like a "search ads carousel" and "bazaar content," similar to Google Search. Unlike traditional search, ChatGPT can tailor ads based on conversation history, prompts, and user behavior. Ads will likely start in the search function but could expand. With 800 million weekly users sending 2.5 billion prompts per day, the revenue potential is huge. | | Surging demand is also stressing infrastructure. OpenAI capped free Sora users at six video generations per day, though extra runs can be bought. Google cut free Nano Banana Pro image generation and limited Gemini 3 Pro access. Read more. | | | | | | | | | | | |  | arXiv is a free online library where researchers share pre-publication papers. |
| 📄 The Image as Its Own Reward: Reinforcement Learning with Adversarial Reward for Image Generation | 📄 Structured Prompting Enables More Robust, Holistic Evaluation of Language Models | 📄 Video Generation Models Are Good Latent Reward Models | 📄 Inferix: A Block-Diffusion based Next-Generation Inference Engine for World Simulation | 📄 Canvas-to-Image: Compositional Image Generation with Multimodal Controls | | Thank you for reading today's edition. | | Your feedback is valuable. Respond to this email and tell us how you think we could add more value to this newsletter. | Interested in reaching smart readers like you? To become an AI Breakfast sponsor, reply to this email or DM us on 𝕏! |
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