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Article URL: https://ourworldindata.org/the-human-cost-of-unsafe-abortions

Comments URL: https://news.ycombinator.com/item?id=48062267

Points: 1

# Comments: 0

Article URL: https://github.com/omerbenamram/mft

Comments URL: https://news.ycombinator.com/item?id=48062233

Points: 1

# Comments: 0

Article URL: https://github.com/sel8888/harmonic-shape-transform-2026-koncept

Comments URL: https://news.ycombinator.com/item?id=48062231

Points: 1

# Comments: 0

Article URL: https://amolnotes.substack.com/p/the-terminal-is-still-the-integration

Comments URL: https://news.ycombinator.com/item?id=48062215

Points: 1

# Comments: 1

The weekend of last week I built chat.betterdb.com as a RAG over Valkey/Redis/Dragonfly docs. The goal was to eat our own dogfood and test publicly our caching libraries. It also saved me from having to come up with various demo/test scenarios, as I could extend the building in public to the demo.

There is a tool-result cache sitting between the SDK and tools. Each call is normalized and then checked before executing. If it hits we return from the cache, and if not, we check the semantic cache, which embeds the prompt and checks with KNN via valkey-search. If the cosine distance is close enough, we again skip the LLM and stream the cached response. In both cases, if we miss, we store the prompt embedding, actual model, input and output tokens from OpenAI's usage report, so a future hit has the dollars avoided as data.

The two tiers handle different shapes. Predefined questions, copy-pasted questions, checking the same thing again after time - produces byte-identical strings the tool cache catches. Human paraphrase is what the semantic tier exists for.

This Wednesday was a bank holiday where I live, so I used to extend it further - the libraries the chat relies on now store metadata in the Valkey (or Redis if that's your preference) instance, then our monitoring reads and analyze that data and suggests improvements. These are exported also through our MCP server, so the chat's agent can check and create suggestions as well, and since this is just a demo, it can also approve its suggestions (do not do this on real production environment, unless you are a true LLM believer). The libs also read the config from the Valkey instance, so there is no restart needed. I hooked it on cron inside Vercel and let it run over the night and next day.

Between Run 1 and Run 3, it started making less tool calls. The first run it suggested several different TTL changes and applied them. Run 2 and 1 had similar suggestions, because the TTL is the wrong point of control - they take natural language input (`How fast is XADD?` vs `XADD performance` are two different strings, that "mean" the same thing) so the tool cache doesn't fire and are covered by the semantic cache. An actual fix would be to move these tools from the exact-match into the semantic cache checks - a code change, not a config change. It was an indicator of a problem the system can't fix on its own. In the future the routing might also become configurable to solve this without redeploying and test and verify in quicker loops. Run 3 just didn't propose anything new - 15 -> 13 -> 8 tool calls across the three runs.

Curious how others running similar loops decide what the agent can touch. Am I too skeptical of hallucinations and overly cautious?

The chat can be found at https://chat.betterdb.com (it has links to all of the repos in it) And a more detailed write up can be found at https://www.betterdb.com/blog/cache-that-tunes-itself

Comments URL: https://news.ycombinator.com/item?id=48062214

Points: 4

# Comments: 0

Article URL: https://graphthinking.blogspot.com/2026/05/cargo-cult-bureaucracy.html

Comments URL: https://news.ycombinator.com/item?id=48062200

Points: 1

# Comments: 0

Article URL: https://wadetregaskis.com/claude-says-no/

Comments URL: https://news.ycombinator.com/item?id=48062186

Points: 1

# Comments: 0

Article URL: https://sinceyouarrived.world/taken

Comments URL: https://news.ycombinator.com/item?id=48062178

Points: 1

# Comments: 0

Article URL: https://www.theregister.com/off-prem/2026/05/07/ibm-cloud-evaporates-as-datacenter-loses-power/5234835

Comments URL: https://news.ycombinator.com/item?id=48062155

Points: 3

# Comments: 0

Article URL: https://www.euronews.com/next/2026/05/08/instagram-is-dropping-end-to-end-encrypted-chats-this-is-what-is-changing

Comments URL: https://news.ycombinator.com/item?id=48062140

Points: 3

# Comments: 0

Article URL: https://twitter.com/SandboxSpirit/status/2052331740836855915

Comments URL: https://news.ycombinator.com/item?id=48062139

Points: 4

# Comments: 0

Does anyone actively use systems like hotline.tg for support and sales instead of classic web dashboards? What are the pros/cons so far?

Comments URL: https://news.ycombinator.com/item?id=48062127

Points: 1

# Comments: 0

Article URL: https://en.wikipedia.org/wiki/Pixel-art_scaling_algorithms

Comments URL: https://news.ycombinator.com/item?id=48062124

Points: 1

# Comments: 0

Article URL: https://theadjacency.com/p/more-machines-more-problems--5b71da019b9dde348ad07f65

Comments URL: https://news.ycombinator.com/item?id=48062122

Points: 1

# Comments: 0

Article URL: https://apnews.com/article/poland-economy-growth-g20-gdp-26fe06e120398410f8d773ba5661e7aa

Comments URL: https://news.ycombinator.com/item?id=48062117

Points: 26

# Comments: 3

Article URL: https://www.youtube.com/watch?v=f3_UVYFyMno

Comments URL: https://news.ycombinator.com/item?id=48062114

Points: 1

# Comments: 0

Article URL: https://www.youtube.com/watch?v=JnIfHM6_gSc

Comments URL: https://news.ycombinator.com/item?id=48062108

Points: 1

# Comments: 0

Memory chip shortages are a wildcard in the prediction game, but here are the computers rumored to be getting updated this year.

Days after confirming a major data breach, Instructure is now facing a second blow.

Earlier this week, Instructure confirmed a major data breach affecting its cloud‑hosted Canvas environment, with the ShinyHunters group claiming it stole hundreds of millions of records tied to thousands of schools and universities worldwide. As discussed in our earlier blog, that incident involved data such as student and staff records, enrollment details, and private messages allegedly accessed through Canvas export features and APIs. At that stage, the focus was on large‑scale data theft and the long‑term risks for affected students and families, including identity fraud and highly targeted phishing.

According to new reporting, ShinyHunters has now hit Instructure again, this time moving from quiet data theft to very visible extortion. Using another vulnerability in Instructure’s systems, the attackers were able to modify Canvas login portals for hundreds of educational institutions, defacing both web logins and the Canvas app with an on‑screen ransom message.

Image credit: vx-underground

The message both claimed responsibility for the earlier breach and set a deadline of May 12 for Instructure and affected schools to contact the gang or risk the public release of stolen data.

This second wave matters for two reasons. First, it confirms that ShinyHunters still has meaningful access to Instructure’s environment, or at least to components that control the look and behavior of school login pages. Second, it marks a clear escalation in pressure tactics, from leaked claims and dark web posts to messages shown directly to students, parents, and staff trying to access their courses.

How to deal with this data breach

For students and families, the practical advice from our original blog still applies:

• Reset Canvas‑related passwords
• Enable multi‑factor authentication where possible
• Monitor financial and credit activity as children get older
• Stay wary of highly personalized phishing that references real schools, courses, or teachers

For schools and districts, this latest extortion campaign underlines the need to coordinate closely with Instructure, review single sign-on (SSO) integrations, and prepare clear communications so that any future defacements or data leaks do not catch staff and parents by surprise.

“One of the best cybersecurity suites on the planet.” 

According to CNET. Read their review →

CISA has added one new vulnerability to its Known Exploited Vulnerabilities (KEV) Catalog, based on evidence of active exploitation.

• CVE-2026-42208 BerriAI LiteLLM SQL Injection Vulnerability

This type of vulnerability is a frequent attack vector for malicious cyber actors and poses significant risks to the federal enterprise.

Binding Operational Directive (BOD) 22-01: Reducing the Significant Risk of Known Exploited Vulnerabilities established the KEV Catalog as a living list of known Common Vulnerabilities and Exposures (CVEs) that carry significant risk to the federal enterprise. BOD 22-01 requires Federal Civilian Executive Branch (FCEB) agencies to remediate identified vulnerabilities by the due date to protect FCEB networks against active threats. See the BOD 22-01 Fact Sheet for more information.

Although BOD 22-01 only applies to FCEB agencies, CISA strongly urges all organizations to reduce their exposure to cyberattacks by prioritizing timely remediation of KEV Catalog vulnerabilities as part of their vulnerability management practice. CISA will continue to add vulnerabilities to the catalog that meet the specified criteria.