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Today’s Headlines:
Ai4 2025 Wrap-Up: Marketing Insights, AI Ethics, and the Road Ahead - Ai4 2025 brought together the AI world’s brightest minds for sessions on generative AI, automation, and responsible human–machine collaboration. On day one, Alicia Shapiro, CMO of AiNews.com, moderated a standing-room-only panel on data-driven marketing with leaders from AEG Vision, Northwell Health, and Uniphore.
Claude Gains Selective Memory and 1M-Token Context Window - As competition in the AI space accelerates, Anthropic is adding new capabilities to its Claude platform designed to make it more powerful and adaptable for enterprise use. The company is rolling out selective chat memory and a dramatically expanded context window, updates aimed at improving both day-to-day usability and the technical performance demanded by developers.
xAI Co-Founder Igor Babuschkin Departs to Launch AI Safety-Focused VC Firm - Igor Babuschkin, a founding engineer of Elon Musk’s xAI, is leaving the company to launch a venture capital firm dedicated to AI safety and responsible innovation. His new firm, Babuschkin Ventures, will fund AI safety research and startups that, in his words, “advance humanity and unlock the mysteries of our universe.”
Create professional music tracks for projects
In this tutorial, you will learn how to generate studio-grade music from simple text prompts using the new ElevenLabs music model that supports multiple languages and gives you complete creative control.
Step-by-step:
Visit ElevenLabs and navigate to the Music section
Write a detailed prompt: “Upbeat acoustic folk song with fingerpicked guitar, warm male vocals, cheerful and inviting with cozy vibes”
Choose your desired number of variants and duration
Generate your track, then edit individual sections and download in studio quality
Pro tip: Start broad (“upbeat pop song”) then get specific (“80s synths, female vocals, catchy summer hook”) for perfect results.
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Training cutting edge AI? Unlock the data advantage today.
If you’re building or fine-tuning generative AI models, this guide is your shortcut to smarter AI model training. Learn how Shutterstock’s multimodal datasets—grounded in measurable user behavior—can help you reduce legal risk, boost creative diversity, and improve model reliability.
Inside, you’ll uncover why scraped data and aesthetic proxies often fall short—and how to use clustering methods and semantic evaluation to refine your dataset and your outputs. Designed for AI leaders, product teams, and ML engineers, this guide walks through how to identify refinement-worthy data, align with generative preferences, and validate progress with confidence.
Whether you're optimizing alignment, output quality, or time-to-value, this playbook gives you a data advantage. Download the guide and train your models with data built for performance.