Ai can detect your car problem: Your car’s engine might soon tell you what’s wrong, just by listening

A new open-source AI called CarDiag can detect potential car problems from the sound of your engine. Simply record your engine with your phone, upload the audio, and the model analyzes the recording to identify which vehicle system is most likely causing the issue. It’s still early days. Right now, the AI correctly distinguishes between healthy and faulty engines about 79% of the time. But here’s the impressive part: the entire trained model is only around 100 KB, making it incredibly lightweight and easy to run. Because the project is fully open source, the creator hopes developers and car enthusiasts will help train it into a much more accurate mechanic that fits in your pocket.

Comments

Post a Comment

Popular posts from this blog

Palantir CEO Alex Karp: "AI Companies Are Selling Tokens, Not Results"

Image
❗️Palantir CEO Alex Karp just took aim at the AI industry’s biggest players. In a blunt interview, Karp argued that many large companies are paying huge AI bills without seeing meaningful business value. He claimed enterprises are being charged for tokens instead of outcomes, asking a simple question: If AI can really generate billions in value, why aren’t vendors charging a share of that value instead of billing for compute? Karp also warned that businesses risk giving away their competitive edge by feeding confidential data, workflows, and internal knowledge into frontier AI systems. In his view, companies could end up helping train the very models that power products for their competitors. He described the current model as a “wealth tax” on enterprises, saying executives privately worry about high costs, weak ROI, and protecting their intellectual property even if few are willing to criticize the biggest AI labs publicly. Whether or not his claims hold up, Karp’s comments highl...
Read more

Ⓜ️ Meta’s upcoming AI model, internally codenamed Watermelon, has reportedly caught up with OpenAI’s GPT-5.5 on closely watched benchmarks

Image
Ⓜ️ Meta’s upcoming AI model, internally codenamed Watermelon, has reportedly caught up with OpenAI’s GPT-5.5 on closely watched benchmarks. Meta AI chief Alexandr Wang told employees that Watermelon is still training and uses roughly 10 times more compute than Muse Spark, the company’s current model family. The exact benchmarks were not disclosed, so the claim cannot yet be independently verified. Meta is also preparing an update to Muse Spark with stronger coding and agent abilities, while Wang says a model competitive with Claude Opus could arrive “pretty soon.”
Read more

Perplexity CEO Aravind Srinivas on AI

Image
🗣The most valuable AI users aren’t the average users anymore, they’re the ones running fleets of AI agents. Perplexity CEO Aravind Srinivas says AI is changing who matters most. Instead of millions of casual users, the biggest value now comes from a small group of power users who keep AI systems working around the clock. He says some engineers at Meta reportedly consume around $10 million worth of AI coding tools per engineer each year, while some Perplexity Computer users spend more than $10,000 a month running businesses through autonomous agent loops. Even inside Perplexity, employees have built multi-agent workflows so advanced that they resemble entire software architectures. That represents a major shift from the traditional software model. For years, success meant getting billions of people to perform small actions. With agentic AI, a single skilled operator can direct a network of AI agents that works continuously, completing tasks that once required entire teams.
Read more