Tech Stories
OpenAI did this with your health data in January. Now it wants your financial data too.
The company announced today that ChatGPT users can connect their bank accounts through Plaid, the financial bridging platform used by 12,000 institutions including Chase, Fidelity, Capital One, and Schwab. Once connected, ChatGPT gets a full view of your balances, transaction history, active subscriptions, investment portfolio, and liabilities like mortgages and credit card debt. In return you get a spending dashboard, personalized financial advice, and a chatbot that can flag unusual changes in your habits.
It's launching in preview for Pro subscribers at $200 a month. OpenAI says Plus and eventually everyone else comes later.
Lumina-DiMOO is a state-of-the-art open source multimodal AI system, designed as a completely free and flexible Nano Banana alternative. This model is capable of text-to-image generation, image editing, inpainting, style transfer, subject-driven creation, controllable generation, extrapolation, and advanced image understanding, all in a single, developer-friendly framework.
I didn’t plan to stop paying for software.
Like most people, I slowly built a stack of subscriptions over the years like a note-taking app here, a design tool there, a video editor, AI tools, an automation service. None of them felt expensive on their own. Ten bucks a month doesn't sound like much, right? Twenty dollars here, forty dollars there - it all just feels… normal. Until it isn't.
The wake-up call came when I totaled up my yearly spending & that's when I realized. I was paying nearly $2,000 a year just to keep my everyday workflow running.
Surprisingly I noticed, most of these tools weren’t doing anything magical. They were just convenient & familiar. Meanwhile, this whole time, the open-source world had been building some seriously impressive alternatives that were not only capable, but in many cases good enough for what I actually needed.
Most small AI models come with a catch. They're either too slow, too limited, or need hardware that feels impractical. But a handful of models have changed that conversation completely, they're small enough to run locally, capable enough to outperform models like GPT-4o on specific tasks.
I went through the benchmarks, the docs, and the community feedback on dozens of models to find the ones actually worth your time. These seven made the cut.
daVinci-MagiHuman processes text, video and audio inside a single unified transformer simultaneously. No separate models, no post processing alignment. The lip sync and facial dynamics are not corrected after generation. They are generated correctly from the start because all three streams are being denoised together.
My journey with on-device AI started with small moments like upscaling a blurry photo while waiting for my coffee, transcribing a quick note with no signal, or chatting with an AI assistant without going online. That’s when it clicked, this is what it feels like when technology works for you, not the other way around.
Every few years something shows up in AI that makes people stop and argue. Not argue about which model is better or whose benchmark is more honest. Argue about whether the rules just changed. SubQ is that argument right now.
A Miami-based startup called Subquadratic came out of stealth last week with a single claim that's either the most important architectural shift since the 2017 transformer paper or the most sophisticated AI hype in recent memory. They say they've built the first LLM that doesn't rely on quadratic attention and that this lets them run a 12 million token context window at roughly one-fifth the cost of frontier models.
The AI research community split within hours. Half are losing their minds. Half are explaining why this doesn't count. The truth is probably more interesting than either camp.
Here's what we actually know.
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