The podcast discusses why AI shouldn't write tests and the challenges of managing infrastructure at Google. They delve into test-driven development versus AI test generation and share insights on Character AI, Montana attractions, and AI travel assistants. Additionally, they talk about the warp terminal, fines, Star Trek Prodigy season 2, animated series, and upcoming podcast promotions.
Balancing infrastructure maintenance vs emergencies is crucial for businesses.
Testing intent of code over its function is vital when using AI for test generation.
Deep dives
Google's Surprising Source Control System Story
Google's source control system, servicing around 25,000 developers daily with millions of repository operations, was found to be maintained in a closet under a cupboard by a team of eight admins who performed routine heroics to keep it running.
Infrastructure Cleaning and Resource Allocation Challenges
The discussion highlights the challenge of balancing infrastructure maintenance amidst emergencies, leading to delayed projects and cost management plans in various businesses.
AI-Driven Testing Debated
The podcast explores the debate around using AI for generating tests, emphasizing the importance of testing the intent of code rather than its function, with examples discussing the potential efficiency and complications of AI-generated tests.
Challenges of AI Integration with Character AI
Character AI's negotiations with tech giants like Google and Meta for computing resources raise concerns about the desperation of AI companies to secure access while offering IP integration, showcasing the challenges and investments in AI development.
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How Google migrated billions of lines of code from Perforce to Piper — As of 2011, the single server had been in operation for the past eleven years of Google history. It had served Google the two-year-old startup, and had now scaled to support Google the public company. In fact, around that time, a lucky Google engineer had just snagged PR #20,000,000. Still chugging along, the server was now executing “11-12 million commands” a day.
We created the first open-source implementation of Meta’s TestGen–LLM — In February, Meta researchers published a paper titled Automated Unit Test Improvement using Large Language Models at Meta, which introduces a tool they called TestGen-LLM. The fully automated approach to increasing test coverage “with guaranteed assurances for improvement over the existing code base” created waves in the software engineering world.
Where the Economy, and the World, Are Headed - YouTube — If you want to know where the economy is headed, ask an economist. If you want to know why (and more), ask a treasury secretary, an economic diplomat, a director of the National Economic Council and the president of Harvard. Larry Summers has been all of those things (and more).
Apple may charge “monthly fees” for advanced Apple Intelligence features — “Though Apple Intelligence will be free to start, the long-term plan is to make money off the capabilities,” said the report. “The company could eventually launch something like Apple Intelligence+ — with extra features that users pay monthly fees for, just like iCloud,” it added.
Apple "will actually be making money from AI," says Bloomberg's Mark Gurman — Longer term, he speculates, the company may be planning a monthly subscription service like "Apple Intelligence+" that offers additional features to monetize the technology. Apple already takes a cut of subscription revenue from any AI partner it brings on board. "The company will be less reliant on hardware tweaks to drive its business and will actually be making money from AI — something everyone in Silicon Valley is hoping to pull off," Gurman says.
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