Dehyped title: Curiosity rover finds manganese deposits on Mars, suggesting past oxidizing conditions unlike current environment.

Summary:

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Comments:

adastra22: I believe we are likely Martians, as early panspermia from Mars could explain the origin of life and LUCA complexity on Earth. Mars had a longer period of habitability before becoming inhospitable, so life may have emerged there first and seeded Earth. The debate around potential Martian fossils in the ALH-84001 meteorite is intriguing.

bena: Panspermia is not an answer, it just pushes the question of life's origin to another environment. It's important to continue searching for evidence of life's genesis on Earth.

baja_blast: The Viking landers' Labeled Release experiments provided tantalizing but inconclusive evidence of Martian microbial life. I'm puzzled why we haven't followed up with more experiments to try to confirm or rule out this possibility.

Symmetry: For most of Earth's history there were no multicellular organisms, so it's plausible Mars could have developed bacterial life even if it never reached higher complexity. The potential "bacterial fossils" in the ALH-84001 meteorite are more ambiguous.

Summary:

No summary available

Comments:

This Hacker News thread contains job postings from a variety of companies looking to hire software engineers, data scientists, and other technical roles. The companies span industries like fintech, robotics, energy, and more. Many of the roles are remote or offer hybrid work options. The companies highlight their interesting technical challenges, company culture, and mission-driven work. Overall, the thread showcases the diverse range of opportunities available for technical talent.

Here are the summaries from the insightful contributors:

dougweltman: InfoSum is building data collaboration tools and is hiring for an Enterprise Sales Director and Customer Success Associate roles in London.

samcheng: Rinse provides dry cleaning and laundry delivery services and is hiring software engineers, particularly with mobile app experience, across the US.

jhirshman: Uncountable is looking for full-stack engineers and implementations engineers to work on their SaaS platform for industrial R&D.

own_air_breath: Apple is hiring senior software engineers to work on distributed systems and Rust-based applications in Cupertino or London.

cx0der: Aurora Energy Research has openings for software engineers and a technical lead in the UK and India.

amauboussin: Surge AI is building a data platform to power AI teams and is hiring software engineers and a strategic projects lead in SF or remotely.

ryanferg: The Houston Astros are looking for a baseball research analyst to join their R&D team and leverage data to support the team.

bovermyer: Apiture, a fintech company, is hiring a platform engineer to work on devops, internal developer tooling, and modernizing their systems.

dazbradbury: OpenRent, a rental platform in the UK, is hiring for customer experience and product development roles.

rossng: Monumental is building autonomous construction robots and hiring mechanical and software engineers in Amsterdam.

justicz: Charge Robotics, a YC-backed startup, is hiring a senior mechanical engineer to work on robots that build solar farms.

asta-li: Privy, a digital identity startup, is hiring product, frontend, backend, and full-stack engineers in NYC or remotely.

tomatohs: TestDriver.ai, an early-stage startup in Austin, is looking for engineers, sales, and customer success to join their team.

joshsenseiag: Sensei Ag, an indoor farming technology company, is hiring software engineers to work on sustainable agriculture solutions.

k1w1: Aha!, a product management software company, is hiring Rails, React, and DevOps engineers to work remotely.

Recruiter_Joe: Qventus, a healthcare operations platform, is hiring engineers and data scientists in the US and India.

ewmy: Overleaf, a collaborative writing tool for scientists, is hiring senior full-stack engineers to work remotely in Europe.

dsr_: Smartleaf, a financial portfolio analysis SaaS, is

Dehyped title: Anthropic announces new Team plan and iOS app for Claude AI assistant.

Summary:

Anthropic has announced two updates for Claude - a new Team plan and an iOS app. The Team plan offers increased usage, access to the Claude 3 model family, a 200K context window, admin tools, and all Pro features for $30 per user per month. The iOS app allows seamless syncing with web chats, vision capabilities to analyze images, and is free for all users. The Team plan and iOS app are designed to help teams and individuals leverage the power of Claude's advanced AI models for increased productivity and insights. Anthropic plans to release additional collaboration features for the Team plan in the coming weeks.

Comments:

Arcuru: I created a simple Matrix bot that replicates the features of the Claude AI chatbot, which you can access from a normal Matrix client. This allows you to run the chatbot yourself instead of relying on the official app.

weinzierl: I'm curious why the Claude AI chatbot is not available in Europe, both the mobile app and the service in general. I'm not complaining, just wondering about the reasoning behind this.

bugglebeetle: It's disappointing that the Claude AI app doesn't have voice support, which would be a killer feature if it worked reliably, unlike the speech-to-text in the Gemini Advanced app which is poor.

haolez: I'm frustrated with the Gemini Advanced app because while the text-based digital assistant features are good, the speech-to-text functionality is awful and potentially dangerous.

Dehyped title: Training language models to predict multiple future tokens at once improves sample efficiency and inference speed compared to next-token prediction.

Summary:

The paper proposes training large language models to predict multiple future tokens at once, rather than just the next token. This "multi-token prediction" approach is shown to improve sample efficiency and downstream performance, especially for larger model sizes. The method also enables faster inference through self-speculative decoding. Experiments demonstrate benefits on coding tasks, algorithmic reasoning, and natural language generation, with models trained on multi-token prediction outperforming next-token baselines. The authors argue this approach helps models learn better long-term patterns and reasoning capabilities compared to standard next-token training.

Comments:

albertzeyer: The author explains that the proposed method is a form of self-speculative decoding, which predicts multiple tokens at once to improve speed without degrading performance. The multi-task training also leads to better performance.

faabian: The author notes that predicting sentence-level embeddings is an interesting idea, but the challenge is making the model focus on the semantic part rather than just exact token matching. There is a tradeoff between auxiliary tasks providing more signal and shifting the model's focus.

mike_hearn: The models may already be encoding some overall plan for upcoming sentences, even if they don't predict every word yet, as evidenced by their ability to generate coherent text like poems and song lyrics.

marcyb5st: Predicting sentence-level embeddings directly is challenging because you need a way to convert back to a word representation, which is not a straightforward inverse function due to ambiguity and loss of nuance.

throw310822: A possible approach could be to use a smaller language model that takes both the semantic vector and the prompt as input to predict the output tokens, leveraging the linguistic abilities without the full reasoning required.

Dehyped title: Kolmogorov-Arnold Networks: Promising alternatives to Multi-Layer Perceptrons with mathematical foundations, faster scaling, and better interpretability.

Summary:

KindXiaoming/pykan is a GitHub repository for the paper "KAN: Kolmogorov-Arnold Networks". KANs are an alternative to Multi-Layer Perceptrons (MLPs) that have strong mathematical foundations and offer advantages in terms of model accuracy, interpretability, and scaling. The repository provides examples demonstrating KANs' capabilities in tasks like fitting symbolic formulas, solving PDEs, and avoiding catastrophic forgetting. Installation instructions and documentation are also included. The paper's authors can be contacted for any questions.

Comments:

krasin: I've experimented with the Kolmogorov-Arnold Networks example notebooks, and found that while the default parameters work well, modifying the network architecture doesn't generalize as well. I'd be interested to see how these models perform on larger, more complex datasets like MNIST.

mxwsn: The preprint indicates that 100 input dimensions is considered "high" for these models, which is quite low compared to modern machine learning problems. Demonstrating the capabilities of these models on MNIST, which has 784 input dimensions, would be an important next step.

diwank: I agree that testing these models on larger, more complex datasets would be valuable. Implementing optimized low-level kernels could help accelerate the training and evaluation of these models.

ALittleLight: I'm concerned that a sudden algorithmic breakthrough could lead to a dramatic leap in language model capabilities that the field may not be prepared for.

6mian: I'm not as worried about sudden technical progress - it's natural for some companies to become leaders, and competitors will eventually catch up.

Dehyped title: Depth inpainting network learns to smoothly extrapolate scene depth for consistent 3D scene generation.

Summary:

This paper introduces a new depth completion network for 3D scene generation. Current methods rely on monocular depth estimation, which can lead to discontinuities when integrating new regions into an existing scene. The depth completion network learns to smoothly extrapolate depth based on the input image and known depth regions. This allows for more geometrically consistent 3D scene generation. The paper also proposes a new benchmark to evaluate the geometric quality of generated scenes, going beyond text-based similarity metrics. Experiments show the depth completion approach outperforms prior methods in both real-world and photorealistic settings.

Comments: Unable to generate summary

Dehyped title: North Carolina police build growing network of automated license plate readers across the state.

Summary:

Flock Safety, a private Atlanta-based company, has rapidly expanded its network of automated license plate reader (ALPR) cameras across North Carolina, with at least 700 cameras installed in over 70 counties and municipalities. These cameras capture data on millions of vehicles, which can be accessed by hundreds of law enforcement agencies across the country without a warrant. While police claim the technology helps solve crimes, privacy advocates argue it creates a vast surveillance network that can be misused. North Carolina has limited oversight over how police use and audit these ALPR systems, in contrast to more regulated approaches in other states. The expansion of this technology, including a new law allowing it on state highways, raises concerns about disproportionate surveillance of minority communities.

Comments:

chzblck: The issue is not about police misusing surveillance technology, but rather the broader problem of widespread data collection and tracking of individuals through various apps and services.

heroprotagonist: This is not a new issue, as companies have been collecting and selling surveillance data for years. The problem is much more widespread than the article suggests, with many private businesses and even small organizations contributing to the surveillance network.

DavidPeiffer: There is a need for tools that can help people avoid areas with high surveillance, such as a routing system in OpenStreetMap that avoids road segments with cameras.

n4r9: The novel "We" by Yevgeny Zamyatin is one of the earliest explorations of mass surveillance in fiction.

kotaKat: Private businesses are also increasingly deploying surveillance cameras, further expanding the surveillance network.

Dehyped title: Haiku's vector icon format optimizes for small file size and fast display by using a binary encoding and limiting complexity.

Summary:

Haiku, an operating system, uses a custom vector image format called the Haiku Vector Icon Format (HVIF) to store icons. HVIF is designed to make vector icon files as small as possible, allowing Haiku to display icons at multiple sizes while keeping the files small enough to fit in the file metadata. This reduces the number of disk reads needed to display a folder's contents. The passage examines the details of the HVIF format, including its use of binary encoding, styles, paths, and shapes to achieve its small file size goals. The author also identifies an optimization bug in the HVIF icon editor.

Comments:

pimlottc: The tape recorder icon in the Haiku vector format looks distorted and unrealistic, especially at larger sizes. While saving space is important, the clarity and usability of the icons themselves should be the priority for icon design.

Jasper_: There are many flaws with the vector icon approach discussed in the article "About those vector icons". Vector icons alone are not a complete solution for a one-size-fits-all icon format.

zamalek: The Haiku design guidelines have specific rules for icon design, which is why the tape recorder icon looks the way it does, not because of limitations of the file format. For very small icon sizes like 16x16, pixel grid alignment becomes critical and it may be better to store those as bitmaps.

tdeck: The appearance of the Haiku icons is up to the designer's choices on how much detail to include. Haiku seems to have gone for a 3D clipart style that is not highly detailed.

marcellus23: The original article should have mentioned that smaller icons need to be designed differently, not just scaled down, which is why they are often stored as separate files.

Dehyped title: CSS grid can be used to create responsive and accessible music notation on the web.

Summary:

The passage discusses a CSS-based approach to rendering music notation on the web. The author explains how the musical staff can be represented using CSS grid, with each row corresponding to a pitch. Elements representing notes are then positioned within the grid using CSS selectors that map to the pitch and beat data. This allows for responsive and fluid music rendering, with the ability to swap out different clef and time signature configurations. The author also demonstrates how other musical elements like chords, lyrics, and dynamics can be aligned within the grid system. While there are some limitations, the author is pleased with how well the CSS-based approach works and invites feedback on potential improvements.

Comments:

adrianh: I've been building web-based sheet music rendering for over 10 years at Soundslice. This CSS Grid approach is impressive, but likely not up to the complexity required for full scores.

vintagedave: This CSS-only approach is extraordinary, and I'd encourage the author to see if more CSS features could be added to make it a fully CSS-based solution, as it could have applications beyond just music notation.

Tokkemon: As a music engraver, this CSS solution has some visual issues with beams, slurs, and ties that would need improvement. Other existing tools like Soundslice or Sibelius Cloud Publishing are better suited for scalable, precise vector-based notation in the browser.

amiga386: Music engraving is a specialized skill, similar to typography and typesetting, where the legibility and aesthetics of the notation are crucial. The CSS approach would need to go much further to achieve the level of refinement seen in professional music notation software.

analog31: As a jazz musician, I'm amazed by the subtlety required in making notation work, and much of my band's material is still hand-copied rather than in computer-readable form.

Dehyped title: Theory of constraints is a management philosophy focused on identifying and managing constraints to improve organizational performance.

Summary:

The theory of constraints (TOC) is a management philosophy that views any manageable system as being limited by a small number of constraints. TOC uses a focusing process to identify the constraint and restructure the rest of the organization around it. The key steps are to identify the constraint, exploit and subordinate everything to it, and then elevate the constraint. TOC has been applied to various areas like operations, supply chain, finance, and project management. The thinking processes of TOC help managers walk through the steps of initiating and implementing a project.

Comments:

ericalexander0: I work in cybersecurity and use concepts from the Theory of Constraints, such as addressing root causes, prioritizing customer value, and aligning mental models. I use a simple document format based on evaporating clouds to address these issues.

eespark: I was very interested in node-based graph visualization tools like Flying Logic, which can help track dependencies, constraints, and next steps in projects.

joenot443: I personally find Workflowy, a hierarchical tree tool, to be a good end-state project management tool, though node-based visualization is fascinating.

shrubble: Applying these ideas can be challenging, as most managers will resist them since they seem counterintuitive.

calvinmorrison: The book "The Phoenix Project" is a must-read, as it realistically depicts many situations that will resonate with those in software development, IT, and DevOps.