Pikimov is a new, free, web-based motion design and video editor created as an alternative to Adobe After Effects, requiring no signup or cloud uploads.
The tool has received positive feedback for its potential to challenge Adobe's dominance, with users suggesting improvements in frame rate limits, bug reporting, and keyframe handling.
Currently, Pikimov supports only Chrome and Edge due to specific web APIs, with future plans to add community features and possibly monetize the app.
A critical vulnerability (CVE-2024-6387) in OpenSSH's server on glibc-based Linux systems allows remote code execution (RCE) due to a signal handler race condition.
The issue, a regression of CVE-2006-5051, affects OpenSSH versions 3.4p1, 4.2p1, and 9.2p1, and involves exploiting the SIGALRM handler to cause heap corruption and execute arbitrary code.
Mitigation includes applying patches that move async-signal-unsafe code out of the SIGALRM handler or setting LoginGraceTime to 0, though the latter may cause denial of service.
A Remote Code Execution (RCE) vulnerability was discovered in OpenSSH's server on glibc-based Linux systems, potentially allowing attackers to gain remote root access.
The fix for this vulnerability was implemented by moving unsafe code from the signal handler to the listener process, making it difficult to backport.
The issue primarily affects 32-bit systems, with exploitation on 64-bit systems believed possible but not yet demonstrated; various distributions have already released patches.
Pipes is a visual programming editor for feeds, allowing users to fetch, create, and manipulate feeds using blocks, similar to Yahoo! Pipes.
It supports various input formats, including RSS, Atom, JSON, HTML, and text files, and offers a range of blocks for different feed operations like filtering, merging, and extracting content.
Pipes CE is a free and open-source software (FOSS) under the AGPL license, available on Github, and supports integrations with popular sites like Twitter, YouTube, and Vimeo.
Pipes, a project inspired by Yahoo Pipes, recently underwent updates to improve stability, including a shift from text to RSS objects for data transport between blocks.
Server upgrades and reconfiguration of threads and puma workers were implemented to address issues and bottlenecks.
A user suggestion to add a block for AI-generated summaries or images via POST requests is being considered, with some foundational blocks already in place.
The post discusses the evaluation metrics for assessing the performance of finetuned language models (LLMs) in extracting structured data from press releases, with a focus on accuracy.
Finetuned models, including TinyLlama, Mistral, and Solar LLM, generally outperformed OpenAI's GPT-4 and GPT-4 Turbo in accuracy, despite the complexity and slow pace of evaluations.
The evaluations highlighted the need for a better system to manage the complexity and maintenance, with future steps including non-accuracy-related tests and exploring model serving.
Fine-tuned models can outperform general models like OpenAI's GPT-4 in specific tasks, such as data extraction, creative summarization, question answering, and classification.
The success of fine-tuned models hinges on high-quality training data, making them effective for niche information extraction and accessible to tech enthusiasts.
Fine-tuning smaller models, such as Llama 3 8B, can be more efficient and cost-effective, but using model responses to train new models may violate terms of service for major LLM providers.
Johannesburg, once barren, transformed into the "greenest city in the world" after planting millions of trees to combat dust from gold extraction.
Tree planting in Johannesburg was unevenly distributed due to Apartheid, highlighting socioeconomic disparities.
Urban trees provide significant benefits, including reducing the "heat island" effect, acting as sound barriers, enhancing aesthetics, increasing biodiversity, and encouraging outdoor activities.
Cities are increasingly planting trees and promoting green roofs to combat heat stress and improve urban livability.
Utrecht, Netherlands, and Zurich, Switzerland, are leading examples, while U.S. cities like Portland, OR, have green mandates, and Salt Lake City is exploring xeriscaping.
Trees offer significant benefits, such as cooling urban areas, improving air quality, and enhancing overall livability, despite challenges like private property development leading to tree removal.
Ladybird is an independent web browser developed by a non-profit, focusing on performance, stability, and security, with an Alpha release planned for 2026.
Initially an HTML viewer for SerenityOS, it now supports Linux, macOS, and other Unix-like systems, and is built entirely from scratch without using code from other browsers.
The project is funded by sponsorships and donations, with no ads or user monetization, and is currently developed by a team of four full-time engineers.
The discussion revolves around the use of digital postage codes, known as "postzegelcode," which can be written on envelopes instead of using traditional stamps.
Various countries, including Germany, Denmark, Norway, and Sweden, have implemented similar systems, allowing users to purchase postage online and write a code on their mail.
The system is praised for its convenience, especially for those who do not frequently send physical mail, as it eliminates the need for physical stamps and adapts to changing postal rates.
The Supreme Court extended the delay in Donald Trump's criminal case regarding the 2020 election, reducing the likelihood of a trial before the November election.
In a 6-3 ruling, the court's conservative majority granted former presidents broad immunity from prosecution for official acts, complicating the prosecution's case and requiring further analysis at the trial court level.
The decision underscores the court's significant influence on the upcoming election, with Chief Justice John Roberts emphasizing immunity for official acts and Justice Sonia Sotomayor dissenting, arguing it undermines the principle that no one is above the law.
The Supreme Court has ruled that ex-presidents have immunity for official acts, sparking debate over potential abuses of power versus the need for presidential protection.
The ruling specifies that immunity applies to actions within constitutional authority but not to unofficial acts, raising concerns about accountability for serious crimes.
Critics, including Justice Sotomayor, worry this decision could impact ongoing and future legal cases involving former presidents.
Traditional polynomial multiplication has (O(n^2)) complexity, making it inefficient for large polynomials.
The Fast Fourier Transform (FFT) reduces polynomial multiplication complexity to (O(n \log n)) by converting the problem to the frequency domain.
The FFT-based method involves converting polynomials to the frequency domain, multiplying them, and converting the result back, significantly improving efficiency for high-degree polynomials.
The discussion centers around the use of Fast Fourier Transform (FFT) for polynomial multiplication, highlighting its efficiency compared to naive methods.
Key insights include the importance of numerical precision in FFT calculations and the historical context of FFT's development for polynomial multiplication.
The conversation also touches on practical applications, such as error correction, signal processing, and zero-knowledge cryptography, where FFT-based methods are particularly beneficial.
The post discusses embedding programs in recurrent neural networks (RNNs) and how trained RNNs can outperform hand-written algorithms.
It provides a detailed example of detecting program code in messages, comparing simple decision rules, a hand-written algorithm, and an RNN-based approach.
The post highlights the advantages of RNNs, such as encoding state machines, using trainable activation functions, and handling complex tasks with data-driven discipline.
The article discusses the construction of a neural network using Python but lacks details on testing and obtaining training data, which are crucial for ensuring the model's generalization to unseen inputs.
The discussion highlights the Universal Approximation Theorem, which states that neural networks can represent any function to a desired level of accuracy, but emphasizes that learning these approximations is not guaranteed.
There is a debate on whether Recurrent Neural Networks (RNNs) are being replaced by transformers, with some arguing that RNNs still have unique advantages, such as constant memory usage, which transformers lack.
Various companies are hiring for multiple roles, including remote, onsite, and hybrid positions, across different locations and industries.
Notable companies include Apple, Figma, Charge Robotics, and SmileID, offering positions such as Senior Software Engineer, Senior/Staff Security Engineer, and Senior Frontend Engineer.
Opportunities span across the globe, with some companies offering visa sponsorship and roles in emerging technologies like AI, machine learning, and full-stack development.
Programmers should maintain a healthy level of skepticism, as writing and verifying code correctness is inherently challenging and often impossible.
Abstractions, while simplifying complex systems, can fail and lead to issues like performance degradation or undefined behavior, as highlighted by Joel Spolsky’s Law of Leaky Abstractions.
To mitigate unknown issues, programmers should verify information, test beliefs, and measure the impact of code changes, while continuously learning about new platforms, languages, tools, and technologies.
The discussion centers on the importance of formal verification in programming, emphasizing that programmers should not trust anyone, including themselves, without proof.
Formal verification, though complex and costly, provides stronger guarantees of correctness compared to unit tests, which only cover specific examples.
The debate highlights the trade-offs between the rigor of formal verification and the practicality of unit tests, suggesting that the choice depends on the project's requirements and resources.
Unification in Elixir extends pattern matching by allowing variables on both sides of an equation, solving symbolic equations and producing substitution mappings.
Unlike pattern matching, unification can handle partially known values, making it a powerful tool for logic programming in Elixir.
The unification algorithm involves walking terms, testing equivalence, handling variables, and recursively unifying list elements, simplifying variable assignments through substitution.
The article compares the efficiency of unification algorithms in type inference, focusing on algorithm W and algorithm J.
Algorithm W, used in Hindley-Milner type inference, is less efficient and more error-prone due to the need for composing substitutions.
Algorithm J, which employs a union-find data structure for destructive unification, is simpler and more efficient, with additional insights on unification in pattern matching and compiled pattern matching using decision trees.
Google Arts & Culture offers a wide range of virtual tours and interactive experiences, allowing users to explore art, history, and culture from around the world.
Highlights include virtual tours of famous museums, augmented reality (AR) experiences, and interactive games that make learning about art and culture engaging and accessible.
Special features include the ability to explore Van Gogh's library, take a 3D tour of Vermeer's paintings, and participate in a K-Pop dance challenge in collaboration with the V&A Museum.
Google Arts and Culture is a lesser-known but significant project by Google, offering curated cultural content from around the world.
Users appreciate its high-resolution images and unique features, such as the ability to zoom in closely on artworks and explore various cultural projects.
The platform has been active since 2011 and continues to be a valuable resource for art and culture enthusiasts, despite concerns about the longevity of Google projects.
Researchers have created a comprehensive archive of U.S. newswire content from 1878 to 1977 using a deep learning pipeline on image scans from local newspapers.
The dataset includes 2.7 million unique public domain articles, georeferenced, tagged by topic, and linked to Wikipedia, providing valuable information for computational linguistics, social science, and digital humanities research.
The project involved transcribing 138 million structured article texts and using a neural bi-encoder model to de-duplicate articles, ensuring only public domain content was included.
A comprehensive database of historical news up to 1978 has been created, reflecting changes in copyright laws, and is available on GitHub, though currently empty.
Users have identified OCR (Optical Character Recognition) errors in the data, underscoring persistent challenges in digitizing historical texts.
The project, despite its issues, is lauded for its scholarly value, with raw scans accessible through the Library of Congress digital collection.