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This GitHub repository contains the source code for the Private Cloud Compute (PCC) security guide, providing components that implement security mechanisms and privacy policies for independent verification.
Apple introduces Private Cloud Compute (PCC), a new cloud intelligence system designed for private AI processing that ensures user data privacy and security by using custom hardware and a hardened OS. This system is built to provide strong security guarantees, enforceable privacy, and verifiable transparency.
Apple is inviting security researchers to stress test its Private Cloud Compute (PCC) platform for security holes by releasing a Virtual Research Environment (VRE) and offering up to a million dollars in bug bounties.
“we found no evidence of formal reasoning in language models …. Their behavior is better explained by sophisticated pattern matching—so fragile, in fact, that changing names can alter results by ~10%!”
View the technical specifications for the MacBook Pro (13-inch, 2018, Four Thunderbolt 3 ports).
Markoff reflects on the history of Silicon Valley, from its beginnings in the 1960s to the present day
The article reflects on the intersection of technology and counterculture in Silicon Valley, exploring the tension between the open-source spirit of the hacker counterculture and the capitalist ambitions of venture capitalists. It discusses the history of Silicon Valley, the role of psychedelics, and the paradox of the region's ability to simultaneously allow diverse cultures to thrive.
Markoff emphasizes the importance of understanding the complex nature of Silicon Valley, which is not just about making money, but also about, as Steve Jobs invoked in Stewart Brand's phrase, "stay hungry, stay foolish" , remaining curious and open to new ideas.
The future of iOS apps might be services that just tie into Apple Intelligence, with little to no interface of their own.
Introduction to Pkl, a programming language designed for generating configuration files.
Addresses limitations of static languages and general-purpose languages for configuration purposes.
Provides safety by catching validation errors before deployment.
Scales from simple to complex use-cases.
Enhanced with capabilities borrowed from general-purpose languages.
Familiar syntax and easy learning curve.
Built-in validation using type annotations.
Ability to publish packages and import them as dependencies in a project.
Language bindings for Swift, Go, Java, and Kotlin.
Editor support for IntelliJ, VS Code, and Neovim.