AWS researchers have developed a new type of qubit called the "cat qubit" which promises more effective and affordable quantum error correction. Cat qubits, based on superconducting circuits, are more resistant to noise, a major hurdle in quantum computing. This increased resilience means fewer physical qubits are needed for logical qubits, significantly reducing the overhead required for error correction and making fault-tolerant quantum computers more practical to build. AWS claims this approach could bring the million-qubit requirement for complex calculations down to thousands, dramatically accelerating the timeline for useful quantum computation. They've demonstrated the feasibility of their approach with simulations and are currently building physical cat qubit hardware.
This blog post demonstrates how to build a flexible and cost-effective data lakehouse using AWS S3 for storage and leveraging the open-source Apache Iceberg table format. It walks through using Python and various open-source query engines like DuckDB, DataFusion, and Polars to interact with data directly on S3, bypassing the need for expensive data warehousing solutions. The post emphasizes the advantages of this approach, including open table formats, engine interchangeability, schema evolution, and cost optimization by separating compute and storage. It provides practical examples of data ingestion, querying, and schema management, showcasing the power and flexibility of this architecture for data analysis and exploration.
Hacker News users generally expressed skepticism towards the proposed "open" data lakehouse solution. Several commenters pointed out that while using open file formats like Parquet is a step in the right direction, true openness requires avoiding vendor lock-in with specific query engines like DuckDB. The reliance on custom Python tooling was also seen as a potential barrier to adoption and maintainability compared to established solutions. Some users questioned the overall benefit of this approach, particularly regarding cost-effectiveness and operational overhead compared to managed services. The perceived complexity and lack of clear advantages led to discussions about the practical applicability of this architecture for most users. A few commenters offered alternative approaches, including using managed services or simpler open-source tools.
The blog post explores the potential of the newly released S1 processor as a competitor to the Apple R1, particularly in the realm of ultra-low-power embedded applications. The author highlights the S1's remarkably low $6 price point and its impressive power efficiency, consuming just microwatts of power. While acknowledging the S1's limitations in terms of processing power and memory compared to the R1, the post emphasizes its suitability for specific use cases like wearables and IoT devices where cost and power consumption are paramount. The author ultimately concludes that while not a direct replacement, the S1 offers a compelling alternative for applications where the R1's capabilities are overkill and its higher cost prohibitive.
Hacker News users discussed the potential of the S1 chip as a viable competitor to the Apple R1, focusing primarily on price and functionality. Some expressed skepticism about the S1's claimed capabilities, particularly its ultra-wideband (UWB) performance, given the lower price point. Others questioned the practicality of its open-source nature for the average consumer, highlighting potential security concerns and the need for technical expertise to implement it. Several commenters were interested in the potential applications of a cheaper UWB chip, citing potential uses in precise indoor location tracking and device interaction. A few pointed out the limited information available and the need for further testing and real-world benchmarks to validate the S1's performance claims. The overall sentiment leaned towards cautious optimism, with many acknowledging the potential disruptive impact of a low-cost UWB chip but reserving judgment until more concrete evidence is available.
The blog post explores different virtualization approaches, contrasting Red Hat's traditional KVM-based virtualization with AWS Firecracker's microVM approach and Ubicloud's NanoVMs. KVM, while robust, is deemed resource-intensive. Firecracker, designed for serverless workloads, offers lightweight and secure isolation but lacks features like live migration and GPU access. Ubicloud positions its NanoVMs as a middle ground, leveraging a custom hypervisor and unikernel technology to provide a balance of performance, security, and features, aiming for faster boot times and lower overhead than KVM while supporting a broader range of workloads than Firecracker. The post highlights the trade-offs inherent in each approach and suggests that the "best" solution depends on the specific use case.
HN commenters discuss Ubicloud's blog post about their virtualization technology, comparing it to Firecracker. Some express skepticism about Ubicloud's performance claims, particularly regarding the overhead of their "shim" layer. Others question the need for yet another virtualization technology given existing solutions, wondering about the specific niche Ubicloud fills. There's also discussion of the trade-offs between security and performance in microVMs, and whether the added complexity of Ubicloud's approach is justified. A few commenters express interest in learning more about Ubicloud's internal workings and the technical details of their implementation. The lack of open-sourcing is noted as a barrier to wider adoption and scrutiny.
A non-profit is seeking advice on migrating their web application away from AWS due to increasing costs that are becoming unsustainable. Their current infrastructure includes EC2, S3, RDS (PostgreSQL), and Route53, and they're looking for recommendations on alternative cloud providers or self-hosting solutions that offer good price-performance, particularly for PostgreSQL. They prioritize a managed database solution to minimize administrative overhead and prefer a provider with a good track record of supporting non-profits. Security and reliability are also key concerns.
The Hacker News comments on the post about moving a non-profit web app off AWS largely focus on cost-saving strategies. Several commenters suggest exploring cloud providers specifically catering to non-profits, like TechSoup, Google for Nonprofits, and Microsoft for Nonprofits, which often offer substantial discounts or free credits. Others recommend self-hosting, emphasizing the long-term potential savings despite the increased initial setup and maintenance overhead. A few caution against prematurely optimizing and recommend thoroughly analyzing current AWS usage to identify cost drivers before migrating. Some also suggest leveraging services like Fly.io or Hetzner, which offer competitive pricing. Portability and the complexity of the existing application are highlighted as key considerations in choosing a new platform.
Summary of Comments ( 7 )
https://news.ycombinator.com/item?id=43203745
HN commenters are skeptical of the claims made in the article. Several point out that "effective" and "affordable" are not quantified, and question whether AWS's cat qubits truly offer a significant advantage over other approaches. Some doubt the feasibility of scaling the technology, citing the engineering challenges inherent in building and maintaining such complex systems. Others express general skepticism about the hype surrounding quantum computing, suggesting that practical applications are still far off. A few commenters offer more optimistic perspectives, acknowledging the technical hurdles but also recognizing the potential of cat qubits for achieving fault tolerance. The overall sentiment, however, leans towards cautious skepticism.
The Hacker News post titled "AWS Cat Qubits Make Quantum Error Correction Effective, Affordable" linking to a Next Platform article about AWS's new cat qubit technology spurred a moderate discussion with several insightful comments.
A significant portion of the discussion revolved around the practicality and timeline of quantum computing becoming commercially viable. One commenter expressed skepticism, stating that while the advancements are impressive, practical quantum computation still seems far off, highlighting the ongoing challenges in scaling the technology and managing error rates. They pointed out the considerable resources being poured into the field and questioned whether the returns would justify the investment in the foreseeable future.
Another commenter delved deeper into the technical aspects, discussing the specific advantages of cat qubits over transmon qubits. They explained that cat qubits are less susceptible to certain types of errors, making them potentially more robust for complex calculations. They also cautioned that the technology is still in its early stages and further research is needed to fully realize its potential.
The conversation also touched on the competitive landscape of quantum computing, with some commenters mentioning other companies like Google and IBM and their respective approaches. One commenter speculated about the potential impact of AWS entering the quantum computing market, suggesting that their vast infrastructure and resources could accelerate the development and adoption of the technology.
A few commenters expressed concern about the potential misuse of quantum computing, particularly in cryptography. They mentioned the possibility of quantum computers breaking current encryption algorithms and the need for developing quantum-resistant cryptography.
Finally, several commenters questioned the hype surrounding quantum computing, arguing that much of the discussion focuses on theoretical possibilities rather than concrete applications. They urged caution and realistic expectations, emphasizing that while the technology holds great promise, it's still in its infancy. There was no outright dismissal of the technology, but a clear call for tempered enthusiasm and a focus on practical advancements.