Google AI strategy, AI Mode in search, Gecko QC AI Images

Google AI’s “Era of Experience” Strategy

*The Era of Experience paper – Credits: Google*

This is pretty cool. There is a research paper co-authored by Google DeepMind’s David Silver that talks about an “Era of Experience.” In simple terms (for dummies: imagine AI agents learning by doing things on their own instead of just reading a textbook), this means moving away from the old model of passively learning from huge datasets (like the texts and images scraped off the web) and instead having AI agents actively explore and generate their own training data. I mean, who wouldn’t want an AI that’s self-starting, right?

The idea is similar to how AlphaGo learned by playing millions of games against itself using reinforcement learning (that’s just a fancy way of saying the AI gets rewards for good moves). This move is going to help AI researchers and developers make tools that can better handle new, unexpected situations – and let’s be honest, that’s something tech enthusiasts like you and me can really appreciate.

For more details, check out this piece from A New Google AI Strategy Could Disrupt OpenAI’s Dominance.

Fun fact: Did you know that AlphaGo’s self-play technique set a new benchmark in AI research by showing that machines can learn complex strategies just from playing against themselves?

Google Trials “AI Mode” in Search

Google AI mode — *Google AI Mode release blog*

A few weeks back I received an email about Google releasing an “AI Mode”, and I was “lucky enough” to be able to try it out. It comes out automatically when I make a search, and to clarify, I am not a Google One AI Premium subscriber. Basically, it’s an experiment to bring generative AI directly into your search results – so you’re not just getting a list of links, but real-time synthesized information.

By combining Gemini with their massive data systems like the Knowledge Graph and shopping data, Google is setting the stage for a search experience that’s a lot more conversational and task-oriented. The implications for SEO and digital marketing are huge, which makes this experiment even more interesting.

If you’re curious for more, head over to Expanding AI Overviews and introducing AI Mode.

Did you know? Integrating AI into search isn’t just a gimmick—it’s a fundamental shift that could eventually change the way we interact with the internet.

Gecko: Google’s New Image/Video Prompt Adherence Metric

Gecko models

Original paper – Credits arXiv

This is pretty cool because Google is now showing off Gecko—a new model designed to check how well AI-generated images and videos stick to the original text prompts. In layman’s terms it’s like a quality-control robot making sure the picture really matches the description. Gecko works by comparing what the user requested with what actually got created.

In my job we do a lot of QC of data, to make sure that not only we can get results out, but that the results we get are based on good, high quality, and reliable data. This is similar. But applied to AI-generated images and videos.

The implications are huge for anyone working on image and video generation because knowing exactly why a generated output might be off can help improve these systems. It’s a neat little trick that might just be what we need to see more accurate and trustworthy AI outputs in creative tools.

Curious to dive deeper? Check out the paper titled Gecko: A Method for Evaluating Text-to-Image and Text-to-Video Generation Faithfulness on arXiv.

Fun fact: Gecko is one of the latest tools aiming to bridge the gap between human intent and machine output—a crucial step as AI-generated content becomes more prevalent.

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