OpenAI is implementing watermarks in images generated by DALL-E 3, following standards from the Coalition for Content Provenance and Authenticity (C2PA), to include invisible metadata and a visible CR symbol for provenance verification.
Microsoft's AI-driven Copilot for Sales and Service is now generally available. It integrates with CRM systems like Salesforce to enhance productivity for sales and service professionals. The tools automate repetitive tasks and provide insights directly within Microsoft 365 apps, aiming to improve customer interactions and streamline business workflows. Early adopters like Avanade report significant time savings and better customer engagement using these AI capabilities.
The removal of large-scale datasets such as LAION, along with valid copyright concerns, makes training large-scale image models challenging. This work shows that you can train a powerful CLIP model with 30 million synthetically generated images.
Addressing the critical issue of hallucinations in Multimodal Large Language Models (MLLMs), researchers have developed MHaluBench, a new benchmark for evaluating hallucination detection methods.
Bria AI has open sourced (non-commercial) its background removal model and tools, including training data mixture and performance metrics. It is a significant improvement over alternative open models.
InteractiveVideo introduces a novel way of making videos where users can dynamically interact with the creation process. Unlike traditional methods, this user-friendly framework allows for real-time modifications using text, images, painting, and even drag-and-drop.
DeepSeekMath 7B is a language model specifically designed to tackle complex mathematical problems. It's been trained on a massive amount of math-focused content.
Advanced AIs like GPT-5 could have significant impacts across markets, real estate, labor, energy, national economies, geopolitics, and the economy's inflationary dynamics, leading to a reevaluation of value accrual, global power shifts, and changes in employment and economic structures.
As AI tooling and business use cases become more sophisticated, we’ll start to see more and more real-world applications of the tech. One lens to look at the opportunity here is how AI will make processes cheaper and more efficient whilst growing margins substantially. This might unlock a whole new way of doing things that previously didn’t make economic sense because margins were too thin. This article explores a few of these examples.
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