AI
- AI chat-based search for all
- An AI-powered shopping experience with virtual try on
- Gemini in Chrome
- Multi-modal search via camera
- XR glasses
- How will this change user behavior?
- How will big G monetize AI search?
- Contact list
- Company List
- Conversion
- Lead Gen Form
- Retargeting
Remember when a big deal was made about Gen Z using Instagram and TikTok to search for places to eat? Well…
Gen Z consumers are starting their purchase journeys more often on Google…
But this isn’t a Google Search comeback story:
properties, including YouTube and Gemini
While Gen Z shoppers have moved away from Google Search as their primary method of discovery, those losses have been more than offset by YouTube’s growing importance as a channel for product discovery and research
The former search company is quickly becoming the YouTube company.
via EMARKETER
What Google announced at I/O that you might want to know about
(hint: it rhymes with “hey why”)
The two main questions for marketers:
We might get some hints during Marketing Live today.
Could Google’s best anti-trust defense be to play up its coming irrelevance?
Apple SVP of Services Eddy Cue said last week that AI will one day replace search engines like Google.
Cue said he expects Safari to eventually swap out Google for AI services from up-and-comers including OpenAI, Anthropic, and Perplexity.
Which of course brings to mind the Twain-ism, “the reports of my death are greatly exaggerated.”
In the long run, Google’s 10 Blue Links™ approach is likely dead, a former monopoly. But how long is that long run?
via The Daily Upside
Eventually all large platforms become commerce platforms
When ChatGPT users search for products, the chatbot will now offer a few recommendations, present images and reviews for those items, and include direct links to web pages where users can buy the products.
The ChatGPT search update is part of OpenAI’s effort to compete with rival Google by creating a better, more personalized experience to find products and information on the internet.
Everyone is coming for Google these days.
via TechCrunch
My own personal Siri?
Apple Inc. will begin analyzing data on customers’ devices in a bid to improve its artificial intelligence platform
The goal is to check how well the synthetic training data did while preserving privacy.
But this could be the foundation for AI models that become personalized to each user based on use, patterns, and on-device profiles.
Like ChatGPT remembering your chats, but based on your Apple device usage.
Edge AI—like XR glasses—is nothing but exciting potential right now.
via Bloomberg
You can now use company lists and retargeting lists to build LinkedIn Predictive Audiences.
Full list of audience sources that can now be used as seeds for Predictive Audiences:
And yes, this feature uses AI. 🤖
From the Don’t Say Content ladies:
There’s nothing to fell when it’s mass produced
Remember when you’d go to a how to article and part of what you loved about it was the personality of the brand who wrote it?
And what is gen AI if not the newest tool of mass production?
(This is not an anti-AI post. I’ve been playing with AI text generation since before ChatGPT.)
You can’t mass produce personality. But you can mass produce the stuff that doesn’t meaningfully contribute to personality so the humans can double (and triple) down on it.
Anthropic released the Anthropic Economic Index
The Anthropic Economic Index aims to understand AI’s effects on the labor market and broader economy over time. The Index provides the clearest picture yet of how AI is being incorporated into real-world tasks across the modern economy.
Trends are based on anonymized usage data for their Claude model.
Seems like a useful indicator to add to the monitoring mix.
Is this the dawn of cheap AI?
DeepSeek was just the beginning 🤖
AI researchers at Stanford and the University of Washington were able to train an AI “reasoning” model for under $50 in cloud compute credits
Training methods appear to be proliferating with the number of models available:
The s1 paper suggests that reasoning models can be distilled with a relatively small dataset using a process called supervised fine-tuning (SFT), in which an AI model is explicitly instructed to mimic certain behaviors in a dataset.
A race to the bottom we can actually benefit from:
After training s1, which took less than 30 minutes using 16 Nvidia H100 GPUs, s1 achieved strong performance on certain AI benchmarks
& a lesson we can all learn from:
The researchers used a nifty trick to get s1 to double-check its work and extend its “thinking” time: They told it to wait. Adding the word “wait” during s1’s reasoning helped the model arrive at slightly more accurate answers
via TechCrunch
After Gemini said it couldn’t write marketing content, I asked ChatGPT. Here’s what it gave me:
🔥 In a world where AI can generate content in seconds, what sets your brand apart?
Soul. Perspective. Personality.
AI can write. AI can design. But AI can’t connect like you can.
The future belongs to brands with a voice that feels real—brands that tell stories only they can tell.
👉 Do what the bots can’t. Inject your brand with humanity.
What’s one thing you do to keep your brand feeling alive? Let’s hear it 👇