The federal Fifth Circuit Court of Appeals ruled that geofence warrants are "categorically prohibited by the Fourth Amendment," aligning with the EFF's arguments against general, exploratory searches.
The case, United States v. Smith, involved police using a geofence warrant to obtain location data from Google during a 2018 armed robbery investigation, which the court found violated individuals' reasonable expectation of privacy.
Despite ruling geofence warrants unconstitutional, the court allowed the evidence in this case due to police reliance on the technology in good faith, emphasizing the need for strict Fourth Amendment protections.
A federal appeals court has declared geofence warrants unconstitutional, citing their broad scope and violation of privacy rights.
Geofence warrants enable law enforcement to gather location data from devices within a defined area and time frame.
Despite the ruling, evidence from past geofence warrants may still be admissible if obtained in "good faith," potentially affecting future investigations.
NASA’s Office of the Inspector General (OIG) report blames Boeing’s mismanagement and inexperienced workforce for significant delays and cost overruns in the Space Launch System (SLS) Block 1B development.
The SLS Block 1B budget has escalated from $962 million to an estimated $2.8 billion, with the OIG highlighting inadequate quality management and workforce issues as primary factors.
NASA has agreed with most OIG recommendations, including improving quality management and conducting cost overrun analyses, but rejected financial penalties, opting instead to incentivize good performance.
NASA's investigation reveals that Boeing's subpar welding and inexperienced technicians have caused significant delays in the Space Launch System (SLS) Core Stage 3, hindering America's return to the moon.
The report highlights that inadequate work order planning and supervision by Boeing led to a seven-month delay in the completion of the Exploration Upper Stage (EUS).
This situation underscores broader issues in the aerospace industry, where management practices and labor shortages are impacting critical projects and timelines.
Spice introduces efficient parallelism in the Zig programming language with sub-nanosecond overhead using heartbeat scheduling.
It avoids common pitfalls of parallelism frameworks by using static dispatch and cooperative heartbeating, ensuring minimal stack usage and no thread contention.
Despite its efficiency, Spice is a research project with limitations, including rough edges, lack of tests, and limited benchmarks, encouraging further development and exploration in other languages.
Spice is a new implementation in the Zig programming language that focuses on fine-grained parallelism with sub-nanosecond overhead, based on "heartbeat scheduling" for dynamic automatic granularity control.
The project aims to reduce fixed overhead, making it suitable for parallelizing very small tasks, and shows significant efficiency improvements compared to existing solutions like Rayon.
The author acknowledges the limitations and ongoing research nature of Spice, with detailed benchmarks and comparisons available in the README document on GitHub.
A study reveals that labeling products as “AI” can deter customers due to associations with unreliability, complexity, and unnecessary features.
Companies replacing effective search functions with AI chatbots have caused user frustration, highlighting a preference for simpler, more reliable solutions.
The trend of adding AI to products is often driven by investor interest rather than consumer demand, leading to features perceived as gimmicks rather than genuine improvements.
Between March and May 2023, multiple security vulnerabilities were discovered in points.com, a major backend provider for airline and hotel rewards programs, potentially exposing sensitive customer data and allowing unauthorized actions.
Key vulnerabilities included directory traversal, authorization bypass, leaked credentials, and weak session secrets, affecting major programs like United MileagePlus and Virgin's rewards program.
Points.com promptly acknowledged and fixed these issues, highlighting the critical impact of high-severity vulnerabilities in essential systems.
The article provides a comprehensive guide on using Open Source Intelligence (OSINT) to find information on individuals by leveraging publicly available data from various sources like social media, websites, and government databases.
It outlines key steps in the OSINT process, including gathering basic information, defining requirements, analyzing data, validating assumptions, and generating reports, while emphasizing the ethical use of these methods.
Specialized tools and techniques such as Google Dorks, reverse username lookup, email tools, and geolocation tools are highlighted to aid in the efficient collection and analysis of data.
The post discusses mastering OSINT (Open Source Intelligence) and suggests signing up for Breachforum to access leaked datasets, but cautions about the site's Russian hosting and potential security risks.
It highlights the importance of understanding how to use OSINT tools like Sherlock effectively and suggests alternative terms for OSINT, such as "Public Available Information" (PAI) or "Public Intelligence" (PubInt).
The post provides additional resources for learning OSINT, including osintframework.com and github.com/jivoi/awesome-osint, and notes that OSINT is valuable for journalists and investigators, while casual users should focus on effective searching and metadata understanding.
PostgreSQL 17's release process now uses "git archive" to ensure tarballs match the Git repository, addressing supply chain security concerns.
Previously, generated outputs like autoconf scripts were included in tarballs but not in the repository, making them unauditable.
The change requires packagers to have build dependencies like Perl, Bison, Flex, and DocBook installed, aligning with practices to enhance security and maintainability.
Sakana AI has introduced "The AI Scientist," a system for fully automated scientific discovery, capable of performing research independently without human supervision.
Key features include automating the entire research lifecycle, an automated peer review process, and cost-efficient paper generation at approximately $15 per paper.
Despite its advancements, The AI Scientist faces limitations such as lacking vision capabilities and occasionally making critical errors, highlighting the need for human oversight and ethical considerations.
The AI Scientist project aims to automate the entire research lifecycle, generating scientific papers at a low cost, which has sparked debate about its impact on the scientific process.
Critics argue that AI-generated research lacks the hands-on training and quality of human-led research, potentially leading to academic spam and undermining trust in scientific publications.
Proponents believe that AI can accelerate scientific discovery, especially in critical fields like medicine and climate change, but emphasize the need for human oversight to ensure reliability and relevance.
American workers are reluctant to quit their jobs due to fears of an impending recession, according to labor experts.
The shrinking job market has resulted in a rise of "stuck" workers who feel trapped in their current roles, leading to decreased job satisfaction.
With growing recession fears, workers are prioritizing job security over career moves, and hiring is expected to slow down even if monetary policy becomes more lenient.
Workers are reluctant to leave their jobs due to fears of a recession, resulting in job stagnation.
Employees, particularly in the tech industry, are prioritizing job security, work-life balance, and respectful colleagues over higher pay due to past negative experiences and the current economic climate.
The uncertainty of the job market and cautious hiring practices by companies, including performance-based layoffs, are significant deterrents for employees considering a job change.
A study using the James Webb Space Telescope (JWST) has intensified the debate over the Hubble tension, a discrepancy in measurements of the universe's expansion rate.
Two research teams, led by Adam Riess and Wendy Freedman, have conflicting results: Riess' team measures a higher expansion rate, while Freedman's team finds values closer to theoretical predictions.
Freedman's recent JWST analysis yielded mixed results, suggesting systematic errors in distance measurement methods rather than new physics, leaving the Hubble tension unresolved.
The Webb Telescope has intensified the Hubble tension controversy, questioning whether the universe is expanding and exploring alternative explanations for redshift.
Discrepancies in measuring the Hubble constant suggest potential errors in distance calculations or flaws in the current cosmological model.
Researchers are divided between developing new models and refining existing measurements, underscoring the complexities and evolving nature of cosmology.
GitLab is reportedly up for sale, with interest from buyers like cloud monitoring firm Datadog, and is valued at approximately $8 billion.
The company, used by over half of the Fortune 100, saw a 7% surge in shares following the news, reflecting investor optimism despite competition and pricing pressures.
Founder Sid Sijbrandij's 45.51% voting stock complicates potential deals, amid a broader trend of M&A activity in the tech sector, which saw $327.2 billion in deals in the first half of 2024.
Gitlab is reportedly up for sale, raising concerns about potential changes and layoffs among its user base.
Users are divided, with some preferring GitHub for its stability and AI focus, while others value Gitlab's all-in-one project management and continuous integration (CI) features.
The potential sale has sparked worries about the future of Gitlab's community edition and the possibility of user departure, especially from those who chose Gitlab to avoid Microsoft.
audioFlux is a deep learning tool library for audio and music analysis, supporting tasks like Classification, Separation, Music Information Retrieval (MIR), and Automatic Speech Recognition (ASR).
The latest version, v0.1.8, introduces new Pitch algorithms (e.g., YIN, CEP) and algorithms for PitchShift and TimeStretch.
It supports various platforms (Linux, macOS, Windows, iOS, Android) and can be installed via PyPI or Anaconda, with comprehensive documentation and performance benchmarks available online.
Serena is an experimental operating system (OS) designed for Amiga systems with a 68030 or better CPU, featuring modern principles like preemptive concurrency and multiple user support.
It uses dispatch queues instead of traditional threads, dynamically managing virtual processors, and employs semaphore-based interrupt handling to ensure no missed interrupts.
Serena includes a hierarchical file system (SerenaFS), a shell with command line editing, and supports various hardware like Amiga 2000, 3000, 4000 motherboards, and Motorola CPUs.
Serena is an experimental operating system (OS) designed for 32-bit Amiga computers, specifically targeting the Motorola 68030 processor.
The project has garnered interest due to its unique virtual processors dispatch queue concept, which is a novel approach in OS design.
Amiga computers, though rare and expensive now, are significant in computing history for their advanced features like multitasking, sound, and graphics capabilities, making this OS project particularly intriguing for retrocomputing enthusiasts.
The "Sign in with Google" form lacks debouncing on the "Continue" button, leading to multiple redirect callbacks and a 15% signup failure rate.
This issue impacts several companies, including Flat.app, ChatGPT, Doordash, Expedia, and Snyk, due to the reuse of the OAuth 2.0 state parameter when users click "Continue" multiple times.
The root cause is poor UX on Google's consent screen, which doesn't disable the "Continue" button after the first click, resulting in unclear error messages and user frustration.
The "Sign in with Google" form has a bug where the "Continue" button doesn't debounce clicks, causing multiple redirect callbacks and resulting in 15% of signups failing.
This issue occurs when users click "Continue" more than once on Google's OAuth consent screen, leading to multiple redirects and the second request being rejected due to nonce consumption.
Developers are advised to test their applications, check logs for errors, and provide better user feedback to mitigate this issue, while Google could fix it by disabling the "Continue" button after the first click.
Creating a new programming language offers valuable learning opportunities, teaching about grammars, language design, parsing, and runtime execution.
The process helps understand why existing languages are designed the way they are and allows for experimentation with different paradigms and features.
Resources like "Crafting Interpreters" and books such as "Introduction to Compilers and Language Design" can guide beginners through the process of language creation.
Creating a new programming language often begins with simple functionality but can evolve into a complex project involving an interpreter.
Developers frequently share experiences of accidentally creating interpreters, learning about parsing, syntax, and language design in the process.
Despite the challenges, building a language can be a rewarding and educational side project, providing valuable insights into programming and software design.