The Simons Institute for the Theory of Computing at UC Berkeley has launched "Stone Soup AI," a year-long research program focused on collaborative, open, and decentralized development of foundation models. Inspired by the folktale, the project aims to build a large language model collectively, using contributions of data, compute, and expertise from diverse participants. This open-source approach intends to democratize access to powerful AI technology and foster greater transparency and community ownership, contrasting with the current trend of closed, proprietary models developed by large corporations. The program will involve workshops, collaborative coding sprints, and public releases of data and models, promoting open science and community-driven advancement in AI.
Common Lisp saw continued, albeit slow and steady, progress in 2023-2024. Key developments include improved tooling, notably with the rise of the CLPM build system and continued refinement of Roswell. Libraries like FFI, CFFI, and Bordeaux Threads saw improvements, along with advancements in web development frameworks like CLOG and Woo. The community remains active, albeit small, with ongoing efforts in areas like documentation and learning resources. While no groundbreaking shifts occurred, the ecosystem continues to mature, providing a stable and powerful platform for its dedicated user base.
Several commenters on Hacker News appreciated the overview of Common Lisp's recent developments and the author's personal experience. Some highlighted the value of CL's stability and the ongoing work improving its ecosystem, particularly around areas like web development. Others discussed the language's strengths, such as its powerful macro system and interactive development environment, while acknowledging its steeper learning curve compared to more mainstream options. The continued interest and slow but steady progress of Common Lisp were seen as positive signs. One commenter expressed excitement about upcoming web framework improvements, while others shared their own positive experiences with using CL for specific projects.
This post compares the layout models of TeX and Typst, two typesetting systems. TeX uses a box, glue, and penalty model, where content is placed in boxes, connected by flexible glue, and broken into lines/pages based on penalties assigned to different breaks. This system, while powerful and time-tested, can be complex and unintuitive. Typst, in contrast, uses a flow model where content flows naturally into frames, automatically reflowing based on the available space. This offers greater simplicity and flexibility, especially for complex layouts, but sacrifices some fine-grained control compared to TeX's explicit breakpoints and penalties. The author concludes that while both systems are effective, Typst's flow-based model presents a more modern and potentially easier-to-grasp approach to typesetting.
HN commenters largely praised the article for its clear explanation of layout models in TeX and Typst. Several noted the helpful visualizations and the clear comparisons between the two systems. Some discussed the trade-offs between the flexibility of TeX and the predictability of Typst, with some expressing interest in Typst's approach for certain use cases. One commenter pointed out that the article didn't cover all of TeX's complexities, which the author acknowledged. There was also a brief discussion about the potential for combining aspects of both systems.
The 100 most-watched software engineering talks of 2024 cover a wide range of topics reflecting current industry trends. Popular themes include AI/ML, platform engineering, developer experience, and distributed systems. Specific talks delve into areas like large language models, scaling infrastructure, improving team workflows, and specific technologies like Rust and WebAssembly. The list provides a valuable snapshot of the key concerns and advancements within the software engineering field, highlighting the ongoing evolution of tools, techniques, and best practices.
Hacker News users discussed the methodology and value of the "100 Most-Watched" list. Several commenters questioned the list's reliance on YouTube views as a metric for quality or influence, pointing out that popularity doesn't necessarily equate to insightful content. Some suggested alternative metrics like citations or impact on the field would be more meaningful. Others questioned the inclusion of certain talks, expressing surprise at their high viewership and speculating on the reasons, such as clickbait titles or presenter fame. The overall sentiment seemed to be one of skepticism towards the list's value as a guide to truly impactful or informative software engineering talks, with a preference for more curated recommendations. Some found the list interesting as a reflection of current trends, while others dismissed it as "mostly fluff."
Backblaze's 2024 hard drive stats reveal a continued decline in annualized failure rates (AFR) across most drive models. The overall AFR for 2024 was 0.83%, the lowest ever recorded by Backblaze. Larger capacity drives, particularly 16TB and larger, demonstrated remarkably low failure rates, with some models exhibiting AFRs below 0.5%. While some older drives experienced higher failure rates as expected, the data suggests increasing drive reliability overall. Seagate drives dominated Backblaze's data centers, comprising the majority of drives and continuing to perform reliably. The report highlights the ongoing trend of larger drives becoming more dependable, contributing to the overall improvement in data storage reliability.
Hacker News users discuss Backblaze's 2024 drive stats, focusing on the high failure rates of WDC drives, especially the 16TB and 18TB models. Several commenters question Backblaze's methodology and data interpretation, suggesting their usage case (consumer drives in enterprise settings) skews the results. Others point out the difficulty in comparing different drive models directly due to varying usage and deployment periods. Some highlight the overall decline in drive reliability and express concerns about the industry trend of increasing capacity at the expense of longevity. The discussion also touches on SMART stats, RMA processes, and the potential impact of SMR technology. A few users share their personal experiences with different drive brands, offering anecdotal evidence that contradicts or supports Backblaze's findings.
AdaCore has announced the winners of its "Ada/SPARK Crate of the Year 2024" competition. The gold award went to Libadalang-TV, a library providing a tree view for Libadalang, simplifying Ada and SPARK code analysis. Silver was awarded to Ada-Scintilla, a binding for the Scintilla editing component, enhancing Ada and SPARK development environments. Finally, Florist, a tool for static analysis of formal verification results, took home the bronze. These crates demonstrate community contributions to improving the Ada and SPARK ecosystem, providing valuable tools for development, analysis, and verification.
Hacker News users discussed the winning Ada/SPARK crates, expressing interest in Creatif's accessibility features for blind programmers and praising its maintainers' dedication. Some questioned the term "crate" in the Ada context, suggesting "package" or "library" as more fitting. A few comments highlighted Ada's strengths in safety-critical systems, contrasting its niche status with the broader popularity of Rust, while also acknowledging Rust's growing presence in similar domains. One commenter pondered the reasons behind Ada's limited adoption despite its technical merits.
This paper investigates how pre-trained large language models (LLMs) perform integer addition. It finds that LLMs, despite lacking explicit training on arithmetic, learn to leverage positional encoding based on Fourier features to represent numbers internally. This allows them to achieve surprisingly good accuracy on addition tasks, particularly within the range of numbers present in their training data. The authors demonstrate this by analyzing attention patterns and comparing LLM performance with models using alternative positional encodings. They also show how manipulating or ablating these Fourier features directly impacts the models' ability to add, strongly suggesting that LLMs have implicitly learned a form of Fourier-based arithmetic.
Hacker News users discussed the surprising finding that LLMs appear to use Fourier features internally to perform addition, as indicated by the linked paper. Several commenters expressed fascination with this emergent behavior, highlighting how LLMs discover and utilize mathematical concepts without explicit instruction. Some questioned the paper's methodology and the strength of its conclusions, suggesting alternative explanations or calling for further research to solidify the claims. A few users also discussed the broader implications of this discovery for understanding how LLMs function and how they might be improved. The potential link to the Fourier-based positional encoding used in Transformer models was also noted as a possible contributing factor.
The author argues that science has always been intertwined with politics, using historical examples like the Manhattan Project and Lysenkoism to illustrate how scientific research is shaped by political agendas and funding priorities. They contend that the notion of "pure" science separate from political influence is a myth, and that acknowledging this inherent connection is crucial for understanding how science operates and its impact on society. The post emphasizes that recognizing the political dimension of science doesn't invalidate scientific findings, but rather provides a more complete understanding of the context in which scientific knowledge is produced and utilized.
Hacker News users discuss the inherent link between science and politics, largely agreeing with the article's premise. Several commenters point out that funding, research direction, and the application of scientific discoveries are inevitably influenced by political forces. Some highlight historical examples like the Manhattan Project and the space race as clear demonstrations of science driven by political agendas. Others caution against conflating the process of science (ideally objective) with the uses of science, which are often political. A recurring theme is the concern over politicization of specific scientific fields, like climate change and medicine, where powerful interests can manipulate or suppress research for political gain. A few express worry that acknowledging the political nature of science might further erode public trust, while others argue that transparency about these influences is crucial for maintaining scientific integrity.
AMD is integrating RF-sampling data converters directly into its Versal adaptive SoCs, starting in 2024. This integration aims to simplify system design and reduce power consumption for applications like aerospace & defense, wireless infrastructure, and test & measurement. By bringing analog-to-digital and digital-to-analog conversion onto the same chip as the processing fabric, AMD eliminates the need for separate ADC/DAC components, streamlining the signal chain and enabling more compact, efficient systems. These new RF-capable Versal SoCs are intended for direct RF sampling, handling frequencies up to 6GHz without requiring intermediary downconversion.
The Hacker News comments express skepticism about the practicality of AMD's integration of RF-sampling data converters directly into their Versal SoCs. Commenters question the real-world performance and noise characteristics achievable with such integration, especially given the potential interference from the digital logic within the SoC. They also raise concerns about the limited information provided by AMD, particularly regarding specific performance metrics and target applications. Some speculate that this integration might be aimed at specific niche markets like phased array radar or electronic warfare, where tight integration is crucial. Others wonder if this move is primarily a strategic play by AMD to compete more directly with Xilinx, now owned by AMD, in areas where Xilinx traditionally held a stronger position. Overall, the sentiment leans toward cautious interest, awaiting more concrete details from AMD before passing judgment.
Evidence suggests many Pokémon Playtest cards, initially believed to be from the game's early development, were actually printed much later, possibly in 2024. This is based on the presence of a "three-dot" copyright symbol on the cards, which signifies compliance with Japanese copyright law updated in 2024. While this doesn't definitively rule out earlier creation, it strongly indicates a later printing date than previously assumed, suggesting these "Playtest" cards may represent a different stage of development or purpose than initially thought.
Hacker News users discuss the implications of Pokémon playtest cards potentially being printed in 2024. Some express skepticism, pointing out that a "24" print code doesn't definitively mean the year 2024 and could represent something else entirely. Others find the idea plausible given the long lead times in the printing industry, especially with specialized processes like those used for Pokémon cards. The conversation also touches on the possibility of these being counterfeits, the complexities of the Pokémon TCG market, and how leaks can affect the perceived value and collectability of cards. A few users mention the inherent difficulties in verifying the authenticity of such leaks, while others simply express amusement at the idea of time-traveling Pokémon cards.
KrebsOnSecurity reports on a scheme where sanctioned Russian banks are using cryptocurrency to access the international financial system. These banks partner with over-the-counter (OTC) cryptocurrency desks, which facilitate large transactions outside of traditional exchanges. Russian businesses deposit rubles into the sanctioned banks, which are then used to purchase cryptocurrency from the OTC desks. These desks, often operating in countries with lax regulations, then sell the cryptocurrency on international exchanges for foreign currencies like dollars and euros. Finally, the foreign currency is transferred back to accounts controlled by the Russian businesses, effectively circumventing sanctions. The process involves layers of obfuscation and shell companies to hide the true beneficiaries.
HN commenters discuss the complexities of Russia's relationship with cryptocurrency, particularly given sanctions. Some highlight the irony of Russia seemingly embracing crypto after initially condemning it, attributing this shift to the need to circumvent sanctions. Others delve into the technicalities of moving money through crypto, emphasizing the role of over-the-counter (OTC) desks and the difficulty of truly anonymizing transactions. Several express skepticism about the article's claims of widespread crypto usage in Russia, citing the limited liquidity of ruble-crypto pairs and suggesting alternative methods, like hawala networks, might be more prevalent. There's debate about the effectiveness of sanctions and the extent to which crypto actually helps Russia evade them. Finally, some comments point out the inherent risks for individuals using crypto in such a volatile and heavily monitored environment.
Rafael Araujo creates stunning hand-drawn geometrical illustrations of nature, blending art, mathematics, and biology. His intricate works meticulously depict the Golden Ratio and Fibonacci sequence found in natural forms like butterflies, shells, and flowers. Using only compass, ruler, and pencil, Araujo spends hundreds of hours on each piece, resulting in mesmerizing visualizations of complex mathematical principles within the beauty of the natural world. His work showcases both the inherent order and aesthetic elegance found in nature's design.
HN users were generally impressed with Araujo's work, describing it as "stunning," "beautiful," and "mind-blowing." Some questioned the practicality of the golden ratio's influence, suggesting it's overstated and a form of "sacred geometry" pseudoscience. Others countered, emphasizing the golden ratio's genuine mathematical properties and its aesthetic appeal, regardless of deeper meaning. A few comments focused on the tools and techniques Araujo might have used, mentioning potential software like Cinderella and GeoGebra, and appreciating the dedication required for such intricate hand-drawn pieces. There was also discussion of the intersection of art, mathematics, and nature, with some users drawing connections to biological forms and patterns.
Nick Janetakis's blog post explores the maximum number of Alpine Linux packages installable at once. He systematically tested installation limits, encountering various errors related to package database size, memory usage, and filesystem capacity. Ultimately, he managed to install around 7,800 packages simultaneously before hitting unavoidable resource constraints, demonstrating that while Alpine's package manager can technically handle a vast number of packages, practical limitations arise from system resources. His experiment highlights the balance between package manager capabilities and the realistic constraints of a system's available memory and storage.
Hacker News users generally agree with the article's premise that Alpine Linux's package manager allows for installing a remarkably high number of packages simultaneously, far exceeding other distributions. Some commenters point out that this isn't necessarily a practical metric, arguing it's more of a fun experiment than a reflection of real-world usage. A few suggest the high number is likely due to Alpine's smaller package size and its minimalist approach. Others discuss the potential implications for dependency management and the possibility of conflicts arising from installing so many packages. One commenter questions the significance of the experiment, suggesting a focus on package quality and usability is more important than sheer quantity.
Luke Plant explores the potential uses and pitfalls of Large Language Models (LLMs) in Christian apologetics. While acknowledging LLMs' ability to quickly generate content, summarize arguments, and potentially reach wider audiences, he cautions against over-reliance. He argues that LLMs lack genuine understanding and the ability to engage with nuanced theological concepts, risking misrepresentation or superficial arguments. Furthermore, the persuasive nature of LLMs could prioritize rhetorical flourish over truth, potentially deceiving rather than convincing. Plant suggests LLMs can be valuable tools for research, brainstorming, and refining arguments, but emphasizes the irreplaceable role of human reason, spiritual discernment, and authentic faith in effective apologetics.
HN users generally express skepticism towards using LLMs for Christian apologetics. Several commenters point out the inherent contradiction in using a probabilistic model based on statistical relationships to argue for absolute truth and divine revelation. Others highlight the potential for LLMs to generate superficially convincing but ultimately flawed arguments, potentially misleading those seeking genuine understanding. The risk of misrepresenting scripture or theological nuances is also raised, along with concerns about the LLM potentially becoming the focus of faith rather than the divine itself. Some acknowledge potential uses in generating outlines or brainstorming ideas, but ultimately believe relying on LLMs undermines the core principles of faith and reasoned apologetics. A few commenters suggest exploring the philosophical implications of using LLMs for religious discourse, but the overall sentiment is one of caution and doubt.
Community Notes, X's (formerly Twitter's) crowdsourced fact-checking system, aims to combat misinformation by allowing users to add contextual notes to potentially misleading tweets. The system relies on contributor ratings of note helpfulness and strives for consensus across viewpoints. It utilizes a complex algorithm incorporating various factors like rater agreement, writing quality, and potential bias, prioritizing notes with broad agreement. While still under development, Community Notes emphasizes transparency and aims to build trust through its open-source nature and data accessibility, allowing researchers to analyze and improve the system. The system's success hinges on attracting diverse contributors and maintaining neutrality to avoid being manipulated by specific viewpoints.
Hacker News users generally praised Community Notes, highlighting its surprisingly effective crowdsourced approach to fact-checking. Several commenters discussed the system's clever design, particularly its focus on finding points of agreement even among those with differing viewpoints. Some pointed out the potential for manipulation or bias, but acknowledged that the current implementation seems to mitigate these risks reasonably well. A few users expressed interest in seeing similar systems implemented on other platforms, while others discussed the philosophical implications of decentralized truth-seeking. One highly upvoted comment suggested that Community Notes' success stems from tapping into a genuine desire among users to contribute positively and improve information quality. The overall sentiment was one of cautious optimism, with many viewing Community Notes as a promising, albeit imperfect, step towards combating misinformation.
The Atlantic has announced the winners of its 2024 infrared photography contest, "Life in Another Light." The winning images, showcasing the unique perspective offered by infrared photography, capture surreal and dreamlike landscapes, transforming familiar scenes into otherworldly visions. From snowy mountains bathed in an ethereal pink glow to vibrant foliage rendered in shades of red and white, the photographs reveal a hidden dimension of color and light, offering a fresh perspective on the natural world.
Hacker News users generally praised the striking and surreal beauty of the infrared photos. Several commenters discussed the technical aspects of infrared photography, including the use of specific film or digital camera conversions, and the challenges of focusing. Some pointed out how infrared alters the way foliage appears, rendering it white or light-toned, creating an ethereal effect. A few users shared links to resources for learning more about infrared photography techniques and equipment. The overall sentiment was one of appreciation for the unique perspective offered by this photographic style.
Summary of Comments ( 33 )
https://news.ycombinator.com/item?id=43169054
HN commenters discuss the "Stone Soup AI" concept, which involves prompting LLMs with incomplete information and relying on their ability to hallucinate missing details to produce a workable output. Some express skepticism about relying on hallucinations, preferring more deliberate methods like retrieval augmentation. Others see potential, especially for creative tasks where unexpected outputs are desirable. The discussion also touches on the inherent tendency of LLMs to confabulate and the need for careful evaluation of results. Several commenters draw parallels to existing techniques like prompt engineering and chain-of-thought prompting, suggesting "Stone Soup AI" might be a rebranding of familiar concepts. A compelling point raised is the potential for bias amplification if hallucinations consistently fill gaps with stereotypical or inaccurate information.
The Hacker News post titled "Stone Soup AI (2024)" linking to an article on the Berkeley Simons Institute website has generated several comments discussing the analogy of "stone soup" applied to AI development.
Several commenters discuss the core idea of the "stone soup" approach in the context of AI. One commenter explains it as starting with a simple foundation (the "stone") and iteratively adding value through contributions from various sources. They see this as a way to overcome inertia in large projects by demonstrating initial progress and attracting further involvement. Another commenter builds on this by pointing out that, unlike the folktale where deception is employed, in AI research, the "stone" represents a legitimate initial contribution, and the subsequent additions are open and collaborative.
The discussion also touches on the practical applications of this approach. Some commenters suggest that open-source projects exemplify the "stone soup" method. They argue that an initial framework or model, even if rudimentary, can attract contributions from a community of developers, leading to significant improvements over time. This collaborative aspect is seen as crucial for accelerating AI development.
Another line of discussion centers around the analogy itself. One commenter questions its accuracy, suggesting "potluck" might be a better metaphor, as it emphasizes the voluntary and diverse contributions to a shared goal. However, other users counter this, arguing that "stone soup" captures the element of bootstrapping from a minimal starting point and the iterative process of building something substantial from seemingly insignificant beginnings.
One compelling comment thread debates the ethics of using AI in academia. One user mentions using ChatGPT for tasks like generating homework solutions, which may raise concerns regarding academic integrity. Another user counters with the idea that such issues need more open discussion within the academic community. This suggests a wider concern about the role of AI and evolving ethical guidelines.
Finally, a few commenters express skepticism towards the "stone soup" analogy, viewing it as overly simplistic. They argue that complex AI projects require substantial resources and coordinated efforts, which may not be adequately captured by the informal and incremental nature of the "stone soup" story.