GitHub's latest misstep shows why AI tools walk a fine line between helpful and annoying.
They embedded ads directly into Copilot's pull request suggestions. The developer community's reaction was swift and brutal enough to force a complete reversal.
For beginners: this is exactly why you should be picky about AI tools that feel pushy or sales-heavy.
https://www.theregister.com/2026/03/30/github_copilot_ads_pull_requests/
Ollama just added MLX support for Apple Silicon chips. This is huge for anyone wanting to run AI models locally.
MLX is Apple's machine learning framework that's optimized for M-series chips. Your MacBook can now run models like Llama 3 faster while using less power.
The most underrated free AI tool nobody talks about:
Google NotebookLM.
Upload a PDF, report, or textbook → it creates a personal AI that ONLY answers from your document.
No hallucinations. No made-up facts. Just your sources.
Free. 100 notebooks. 50 sources each.
You're welcome.
Suno's voice cloning update changes everything for amateur musicians. You can now upload a sample of your own voice and the AI will generate complete songs using your vocal style.
This isn't just pitch correction. Suno actually learns your voice characteristics and applies them to entirely new melodies and lyrics. Anyone can now create professional-sounding tracks without years of vocal training.
The implications for content creators and indie musicians are not going to be subtle.
🚨 Wikipedia's Biggest Corporate Self-Editing Scandals:
→ Wiki-PR (2013): Fake sockpuppet accounts for clients — banned after massive investigation
→ MyWikiBiz (2007): Sold paid articles; founder blocked by Jimmy Wales
→ Op Orangemoody (2015): 381 accounts wiped for undisclosed paid editing
→ Bell Pottinger: "Wikilaundering" — covert edits for governments & billionaires
Despite strict rules, companies keep trying — eroding trust in the platform. #AI #Wikipedia
On the Claude Max plan and already at 75% usage for the week. People have been reporting reaching their usage limits much faster than usual recently.
Have you noticed this too?
A new analysis argues Big Tech's record AI spending isn't about winning — it's defensive. Forcing OpenAI and Anthropic to raise ever-larger rounds shrinks the investor pool until IPOs become the only path left. If the chain breaks, the ripple hits data centers, banks, and pension funds.
https://martinvol.pe/blog/2026/03/30/how-the-ai-bubble-bursts/
The catalysts for a crash are already laid out, and it can happen sooner than most expect. AI is here to stay. If used right, chances are it will make us all more productive. That, on the other hand, does not mean it will be a good investment. Big tech doesn’t need to win, just outspend Magnificent 7 companies are increasing capex to their biggest ever to differentiate their tech from each other and the big AI labs, but the key realization is that they don’t have to spend it to win. It’s a defensive move for them, if they commit $50B, OpenAI and Anthropic need to go raise $100B each to stay competitive, which makes them reliant on investors’ money. As the numbers get bigger, the amount of funds that can write checks of the size required to fill such amounts gets smaller. And many of them are now getting bombed in the Gulf. This is the reason there’s a push for IPOs, it’s because it’s the only option left to keep the funding coming. Taking this into account, Google is extremely well positioned to weather the storm. When they announce capex expenditure, they don’t spend it overnight. They can simply deploy month by month until their competitors struggle to raise and get forced to capitulate. At that point they can just ramp down the spending and declare victory in a cornered market. They don’t need capex, they just need to make it very clear for everyone that nobody can outspend them. It is hard to picture as numbers get so big, but Alphabet (Google’s parent) is ten times more valuable than the biggest military company 1. This also has a great implication for the Mag 7, especially Google: their capex will be a lot smaller in practice than projected, and as investors hate to see high capex in tech, the market will probably reward that if it materializes. As of March 2026, Alphabet’s market cap is ~$2T while Lockheed Martin’s is ~$120B. ↩
If you've ever spent 20 minutes Googling an Excel formula:
Open ChatGPT.
Type: "I have a spreadsheet with names in column A and sales in column B. Write a formula that gives me the total sales for everyone named 'Smith'."
It writes the formula AND explains what it does.
This alone is worth learning AI for.