1. Oldest recorded transaction
Total comment counts : 16
Summary
An image of an ancient 3100 BC transaction log prompts the author to ask how far back modern databases can timestamp. Examining MySQL, PostgreSQL, and SQLite, they find MySQL cannot handle such dates; PostgreSQL and SQLite support the Julian calendar with a minimum date of 4713 BC. Dates older than that aren’t natively supported, prompting questions about workarounds (epoch, text, or a custom system) at the expense of built-in TIMESTAMP features. Thanks to readers; sources include a Sumerian image and a Joran Dirk Greef talk.
Top 1 Comment Summary
The piece argues that for uncertain museum dates, storing dates as text is practical. Many items lack precise dates and use “Circa X.” The author notes spending the early 2000s enabling a “Sort by date” feature in museum registrars software, despite dates being kept in textual form. The takeaway is that text-based dates are a sensible solution for organizing and filtering museum inventories.
Top 2 Comment Summary
Early writing began as practical records rather than lofty texts. The oldest piece is a receipt, illustrating how common such transactions were. The Kish Tablet of Jemet Nasr, listing barley, oil, and livestock, may also be a receipt or inventory. The oldest non-commercial writing dates to about 2600 BCE—the Instructions of Shuruppak (proverbs). The author humorously notes that their cringe-worthy diary entries might endure as long.
2. Qwen3 30B A3B Hits 13 token/s on 4xRaspberry Pi 5
Total comment counts : 12
Summary
The article states that all user feedback is read and valued, with documentation listing available qualifiers. It notes repeated “error loading” messages requiring page reloads. Technical details describe a setup of 4 Raspberry Pi 5 8GB devices running Distributed Llama 0.16.0 with model qwen3_30b_a3b_q40 Beta. It also invites users to provide feedback on translations.
Top 1 Comment Summary
Impressed by the results, the author wonders how it would scale across four affordable desktops (e.g., i5 8th Gen ThinkCentre). They emphasize that model compatibility is essential for wider adoption. They suggest a distributed fastsdcpu setup could democratize access to image-generation models for people with limited budgets but large PC fleets.
Top 2 Comment Summary
The piece suggests that with sufficient quantization, any task can run on a Raspberry Pi. It then questions practical uses and whether people buy multiple Raspberry Pi 5s to dedicate to running large language models.
3. We hacked Burger King: How auth bypass led to drive-thru audio surveillance
Total comment counts : 24
Summary
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Top 1 Comment Summary
The excerpt only states that the blog is down and provides a link to an archived post titled “rbi-hacked-drive-thrus” on bobdahacker.com. No additional article content is included.
Top 2 Comment Summary
An unnamed security researcher followed responsible disclosure, confirmed fixes before posting, but received no reply or payout, raising questions about legal and reputational consequences. In a related anecdote, the writer discovered serious vulnerabilities at a high-profile startup, reported through HackerOne, but the payouts were modest (around $2k), leading them to skip formal write-ups. The author wonders whether posting publicly about unrewarded disclosures is permissible and fair.
4. How the “Kim” dump exposed North Korea’s credential theft playbook
Total comment counts : 0
Summary
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5. The maths you need to start understanding LLMs
Total comment counts : 27
Summary
This is the second “state of play” post, explaining inference basics for non-AI experts and how vectors relate to LLM outputs. It shows a logits vector as a point in a high-dimensional vocab space; GPT-2 uses 50,257 tokens, so a logits vector has that many components (e.g., token 464 is “The”). Softmax converts raw scores into probabilities that sum to one. Different logits can yield the same probability distribution after softmax (e.g., (1,2,3) and (−9,−8,−7) map to ~ (0.09, 0.24, 0.66)), while other vectors with the same ranking (e.g., (1,2,5)) differ in distribution.
Top 1 Comment Summary
The author, recalling a physics master’s with deep math training, notes that much of it seemed irrelevant to programming. With LLMs, that physics groundwork becomes practical: backprop is a large tensor-calculus computation minimizing entropy, and neural work relies on matrix multiplications. The field is highly differentiable, unlike much of CS, making it enjoyable to reuse physics skills. The only caveat is occasional need for curved-spacetime tensor calculus in advanced topics, which they haven’t needed yet.
Top 2 Comment Summary
Working through Karpathy’s video series, not just watching, significantly improved my understanding of how LLMs work and boosted my confidence to tackle more advanced material. For me, the knowledge from his videos is already enough, akin to learning how a CPU functions without getting bogged down in optimization details. Thanks to Andrej for the time and effort he put into his videos.
6. Using Claude Code SDK to reduce E2E test time
Total comment counts : 17
Summary
End-to-end tests are essential but slow; teams often run them nightly, leaving bugs in production. The article argues for PR-specific E2E tests to balance coverage and precision. Glob patterns are unreliable and hard to maintain. A smarter approach uses Claude Code with tool calls to examine only changed files, dependencies, and the test configuration. Git diffs with –minimal –ignore-all-space –diff-filter=ACMR, plus excluding large files like package.lock, reveal code changes. The prompt should combine PR changes, E2E tests, and codebase structure to guide Claude to output the exact tests to run (and an explanation).
Top 1 Comment Summary
Instead of shortening end-to-end test time, the approach reduced test coverage by executing only the tests the LLM suggested.
Top 2 Comment Summary
Traditionally test optimization relied on static analysis of dependency graphs or runtime data, but these methods are tied to specific languages and frameworks, hindering cross-stack use. A newer approach substitutes traditional analysis with LLMs to predict which tests to run, aiming to cover all potentially failing tests while skipping others, balancing precision and recall. This LLM-based method could be applied across languages and stacks with minimal changes. It asks whether LLMs have been used elsewhere to replace language-specific analysis for language-agnostic results.
7. GigaByte CXL memory expansion card with up to 512GB DRAM
Total comment counts : 5
Summary
I can’t summarize because the input isn’t an article—it’s just a reference to an EdgeSuite error page, with two identical URLs and no content. Please provide the article text or a link containing the actual content, and I’ll summarize it in 100 words or less. If you just want a sense of what these URLs imply: they point to error-page references tied to a content-delivery network; a real summary would require the page’s text.
Top 1 Comment Summary
CXL could be transformative: it enables large-scale memory expansion, fills PCIe slots, and even external memory, with strong potential for memory tiering. However, latency is a key drawback—CXL 2.0 adds about 200ns per memory access, so careful design is needed to avoid performance penalties. OS-side data locality work is emerging but not widespread. Azure has published whitepapers exploring CXL use with virtual machines.
Top 2 Comment Summary
The excerpt shows a consumer browsing regional purchase options, including Egypt. They click links hoping to convert Egyptian pounds to USD, but the sigma-computer.com search for “CXL R5X4” returns no results, and other links either fail to load. Overall, the currency-conversion links are nonfunctional.
8. Anthropic agrees to pay $1.5B to settle lawsuit with book authors
Total comment counts : 92
Summary
A brief directive asking readers to enable JavaScript and disable any ad blocker.
Top 1 Comment Summary
I can’t open or fetch content from links here. Please paste the article text (or key excerpts, or the main points), and I’ll summarize it in 100 words or fewer. If you want, share the most important sections or a short excerpt, and I’ll condense from that.
Top 2 Comment Summary
The piece separates data acquisition from model training, arguing training is fair use but pirating books to obtain training data is problematic, citing Anthropic’s misstep. It claims buying used copies, scanning them, and using them for training is acceptable, and adds that Rainbows End was prescient in anticipating these issues.
9. The World War Two bomber that cost more than the atomic bomb
Total comment counts : 8
Summary
The Boeing B-29 Superfortress was WWII’s most advanced bomber, costing about 50% more than the Manhattan Project (roughly $55.6 billion today). Boeing’s XB-29 won the 1940 USAAC contract over Douglas and Lockheed, and the aircraft entered service four years later. It pioneered pressurized flight in a bomber, with three crew compartments, enabling high-altitude, longer-range missions. The B-29 dropped atomic bombs on Hiroshima and Nagasaki, helping end the war and fueling the postwar civil-aviation boom that shaped today’s air travel.
Top 1 Comment Summary
The article notes that early B-29 bombers were hand-built because the factory also produced other aircraft, causing hundreds of tiny differences. No two finished B-29s weighed the same, and only about 20% could be flown from the factory. Poorly fitted windows and observation panels leaked air or distorted, and much of the 16 kilometers of wiring had faulty electrical plugs. It then draws a provocative parallel, questioning why Tesla production in the U.S. allegedly yields reliability issues and prompts claims that the cars aren’t valid.
Top 2 Comment Summary
Initially the author argues that the total cost of dropping two atomic bombs would be higher than the design and build costs. In an edit, they acknowledge a source that challenges this view: the B-29 Tokyo raid on March 9, 1945 may have killed as many as 100,000 people, possibly making it more destructive than the later atomic bombs. The post ends by calling the history fascinating and thanking the reader.
10. Europe enters the exascale supercomputing league with Jupiter
Total comment counts : 2
Summary
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Top 1 Comment Summary
Henna Virkkunen claims that the JUPITER supercomputer would make Europe home to the continent’s most powerful computer. The piece questions what that designation actually means in practice and what implications it would have for Europe.
Top 2 Comment Summary
It notes a sizable Nvidia-centric compute installation (likely the Jupiter project at Forschungszentrum Jülich), equipped with InfiniBand networking, Ceph storage, Kubernetes orchestration, and Nvidia H100 GPUs.