How AI is driving up consumer prices
CBS MoneyWatch reporter Megan Cerullo takes a look at the data on why artificial intelligence is raising costs.
We haven't written up this one. CBS News has the full story — the link below goes straight to it.
More in AI
When RAG goes wrong, it’s almost never the LLM: 4 retrieval failures and how to log each one
Todo problema de RAG parece problema do modelo. Quase nunca é. Demorei pra aceitar isso. Ficava trocando modelo de embedding, mexendo no prompt, achando que o Claude tava inventando coisa.
- RAG failures stem from retrieval process, not LLM
- Logging crucial for identifying, resolving retrieval issues
My AI drew the hero as a different man in every scene. It's one guy's life story
I build explainer videos fully automatically. For each scene, a local image-generation AI draws that moment, one frame at a time.
- Hero's appearance varied in AI-generated scenes
- Consistency achieved with character card and shared constraints
- Additional visual checkpoint ensured accuracy
Open Discovery Challenge: How to Build a Verifiable Judge for AI-Designed Malaria Drugs
Open Discovery Challenge: How to Build a Verifiable Judge for AI-Designed Malaria Drugs Generative models can propose thousands of plausible molecules in a day.
- Open Discovery Challenge aims to create a verifiable judge for AI-designed malaria drugs
- Successful drug must inhibit PfDHODH enzyme without affecting human counterpart
- Scoring system validation revealed toxicity gate errors, size bias, and novelty scoring issues
Why your AI coding agent should never see your API keys
Your AI coding agent needs your API keys. It needs them to call services, to test integrations, to run your stack. So you give it .env files, or you export keys into the environment, or you paste them…
- API keys must remain secure when using AI coding agents
- Developers often expose keys via .env files or environment exports
- AI agents can leak secrets through context, output echo, and prompt injection
Anthropic Q2 revenue jumps to over $11.5b
The figure refers to revenue in Anthropic’s latest completed quarter rather than an annualized run rate.
I Almost Used AI to Classify User Input. Simple Rules Worked Better
I’ve been rebuilding a small name tattoo tool recently, and I ran into a problem that looked like a good use case for AI. The user enters some text.
- Author rebuilt name tattoo tool and needed tailored input classification
- Initially considered using LLM for AI classification, but found problem small and predictable
- Deterministic rules distinguished various input factors, proving better decision than AI