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KaiMing He's team introduces **MiniT2I**, a minimalist text-to-image (T2I) model that challenges the complexity of mainstream approaches. It eliminates components commonly considered essential: the VAE encoder-decoder, AdaLN conditioning mechanisms, auxiliary losses, private training data, and post-training alignment stages like RL/DPO. Instead, it uses a pure flow-matching objective trained directly on RGB pixels. The model employs a simplified **MM-JiT** Transformer architecture. It removes AdaLN blocks for conditioning and instead prepends two lightweight text adapter blocks to a standard pre-norm Transformer, allowing frozen T5 text features to adapt to the denoiser. Training follows a two-stage, LLM-like paradigm using only public datasets: pre-training on LLaVA-recaptioned CC12M for coverage, followed by fine-tuning on ~120k high-quality image-text pairs. With just 258M parameters (B/16), MiniT2I achieves competitive scores (0.87 on GenEval, 84.2 on DPG-Bench), outperforming larger pixel-space models. Scaling to 912M parameters (L/16) yields results comparable to SD3-Medium (~2B parameters) in style, composition, and imagination, though it lags in text rendering and named entities due to public data limitations. Key advantages include lower computational cost (~570 GFLOPs vs. ~1379 for latent models) and architectural simplicity. Acknowledged limitations include patch boundary artifacts in pixel space, side effects of high CFG scales, resolution ceilings for sequences longer than 1024 tokens, and the aforementioned data bottlenecks. The work demonstrates that high-performance T2I generation is possible with a radically simplified, publicly reproducible baseline.

The SEC has appointed John Moses to lead its Office of Investor Education and Advocacy. This role is significant for the crypto industry as the office shapes public-facing messaging to warn retail investors about market risks, scams, and complex products like cryptocurrencies. While this personnel move does not signal a sudden policy shift or act as a market catalyst, it indicates that crypto risk education remains a persistent and key component of the SEC's investor protection strategy. The appointment suggests continuity in how the agency communicates its regulatory priorities to the public, ensuring crypto stays within its ongoing retail-risk conversation.

OpenAI is accelerating its roadmap, with GPT-6 rumored for imminent release and the complete abandonment of the older ~4 trillion parameter "Spud" base model. Meanwhile, the GPT-5.6 series has been officially greenlit by regulators and will launch publicly on Thursday, July 9th. This release features three specialized models: GPT-5.6 Sol (a high-performance flagship for complex coding, science, and security), GPT-5.6 Terra (a cost-effective generalist), and GPT-5.6 Luna (a high-speed, low-cost option for agents). Early testers praise Sol's relentless, "never-give-up" problem-solving approach, comparing its tenacity to a "Rottweiler" versus competitor Anthropic's Fable 5, described as a more insightful but sometimes haughty "wise owl." While some testers still favor Fable for certain creative or architectural tasks, GPT-5.6 Sol is highlighted for its dependable execution, strong sub-agent coordination, and significant improvements in coding efficiency, leading to a proposed optimal workflow: using Fable for brainstorming, Sol for execution, and Fable again for documentation.