Hey AI Explorers,

Here’s what’s in store for you today:
📰 AI NEWS

• 🎥 Google Unveils Veo 3.1 and Adds It to Flow Video Editor

• ⚡ Apple Loses Key AI Executive to Meta, Signaling Talent Shift

• 🧠 Why AI Startups Are Taking Data Into Their Own Hands

LATEST DEVELOPMENT

🎥 Google Unveils Veo 3.1 and Adds It to Flow Video Editor

Google has launched Veo 3.1, an upgraded version of its AI video generation model, and integrated it into its Flow video editor. The update brings better audio support, more precise editing controls, and stronger blending when converting images into video.

With Veo 3.1, users can insert new objects into videos and have them blend naturally into the scene style. Support for removing objects is coming soon. All of Veo’s existing features—like using reference images, extending video through AI, and generating new scenes—now work with synchronized audio, making results feel more alive.

The rollout spans Flow, the Gemini app, and via Vertex and Gemini APIs. Since Flow’s launch in May, users have already created over 275 million videos, making this upgrade a timely boost to its capabilities.

⚡ Apple Loses Key AI Executive to Meta, Signaling Talent Shift

In the latest sign of shifting fortunes in AI talent, Apple has lost another senior AI executive, who is now joining Meta. While the specifics or name weren’t initially confirmed, the move marks yet another departure from Apple’s AI ranks to a rival investing aggressively in the space.

Apple, long revered for its hardware and software integration, has faced repeated exits from its AI teams—some to Meta, some to startups. The trend suggests that talented researchers and engineers are being drawn by the freedom, ambition, and resources available at companies pushing harder into generative AI, especially in social media, mixed reality, and platform-wide intelligence.

Meta, for its part, has been on a hiring spree and acquisition drive to solidify its AI capabilities. This move underscores the company’s intention to compete not just in new devices or wearables, but also at the model and research level—directly challenging the likes of Apple, Google, and OpenAI for the top brainpower.

For Apple, the loss raises questions about whether it can retain and inspire AI talent in an era where agility, risk-taking, and “moonshot thinking” are prized. The true cost may not just be one exec leaving, but deeper erosion in its AI roadmaps, culture, and momentum.

🧠 Why AI Startups Are Taking Data Into Their Own Hands

As the AI landscape matures, startups are increasingly recognizing that proprietary data is as valuable as the models they build. No longer relying solely on publicly scraped datasets or low-cost annotators, companies are investing heavily in curated, high-quality training data to gain a competitive edge.

For instance, Fyxer, an AI-driven email management platform, has shifted from using generic models to developing a suite of specialized models trained on meticulously labeled data. Founder Richard Hollingsworth discovered that this approach not only improved performance but also allowed for more customized and efficient solutions tailored to specific user needs.

This trend reflects a broader industry move towards vertical AI, where companies focus on niche applications and build their own datasets to enhance accuracy and reliability. By controlling both the data and the models, startups can create more robust and adaptable AI systems that better serve their target markets.

As the demand for specialized AI solutions grows, startups that prioritize data ownership and quality are positioning themselves to lead in their respective domains.

QUICK HITS

📰 Everything else in AI today

• 🗣️ ElevenLabs drops Conversational AI 2.0

• 🧠 OpenAI teases “ambient” hardware devices

• 💰 Anthropic hits $3B annualized revenue

• 🔐 Meta automating 90% safety reviews

• 🎥 Veo 3 used in millions of videos

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