Recently, I’ve been diving deep into the rabbit hole of digital privacy, specifically focusing on Google’s data retention policies. The topic hits close to home, especially since I’ve spent countless hours tinkering with development tools and cloud services, always with that nagging feeling about the digital footprints I’m leaving behind.

Google’s “My Activity” deletion feature presents itself as a simple solution to wipe your digital slate clean. But let’s be real - it’s about as effective as using a garden hose to clean up after a flood. Their own policy states that while deleted activity is “immediately removed from view,” they still retain certain information for the “life of your Google Account.” That’s corporate speak for “we’re keeping whatever we want.”

The tech world is buzzing about Google’s latest AI demonstration, Project Astra, and honestly, it’s bringing back memories of countless “revolutionary” product launches I’ve witnessed over my decades in IT. While watching the polished demo of someone using AI to fix their bike, I found myself caught between excitement and skepticism.

Let’s be real - the demo looks impressive. The seamless interaction between human and AI, the contextual understanding, the ability to make phone calls and find specific information… it’s the stuff we’ve been promised since the early days of Siri. But having lived through numerous Google demos that never quite materialized (remember Duplex?), I’m keeping my expectations in check.

The digital landscape keeps throwing curveballs at us, and the latest one’s particularly fascinating. Recently, there’s been quite a stir about Google’s AI pulling “citations” directly from Reddit comments. The example making rounds involves a Smashing Pumpkins performance at Lollapalooza, where Google’s AI confidently declared it was “well-received” based on a single Reddit comment using the phrase “one-two punch” - despite historical accounts suggesting they were actually booed off stage after three songs.

The tech world never ceases to amaze me with its rapid advancements. Google just dropped something fascinating - new quantization-aware trained (QAT) checkpoints for their Gemma models that promise better performance while using significantly less memory. This isn’t just another incremental improvement; it’s a glimpse into the future of AI model optimization.

Running large language models locally has always been a delicate balance between performance and resource usage. Until now, quantizing these models (essentially compressing them to use less memory) usually meant accepting a noticeable drop in quality. It’s like trying to compress a high-resolution photo - you save space, but lose some detail in the process.

Something rather amusing is happening in the world of AI right now. Google’s latest Gemini model (specifically Exp 1114) has climbed to the top of the Chatbot Arena rankings, matching or surpassing its competitors across multiple categories. But there’s a catch - it seems to be having an identity crisis.

When asked about its identity, this Google-created AI sometimes claims to be Claude, an AI assistant created by Anthropic. It’s a bit like walking into a McDonald’s and having the person behind the counter insist they work at Hungry Jack’s. The tech community is having a field day with this peculiar behaviour, with some suggesting Google might have trained their model on Claude’s data.