Anthropic Clears Hurdle to Deploy Advanced AI in US Cybersecurity Space
Anthropic is restoring select organizations' access to Mythos after getting permission from the US government.
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Anthropic is restoring select organizations' access to Mythos after getting permission from the US government.
Over 100 companies and government agencies are reportedly authorized to use Mythos 5, including their non-American employees.
The Best Buy Essentials Amplified Ultra-Thin Indoor HDTV Antenna is cheap, simply-designed, and very easy to install.
This late Prime Day deal is not to be missed: Save 38% on the Samsung Galaxy Watch 8 right now, before the buzzer sounds.
Yesterday, Apple hiked the prices of all of its products except for iPhones, and the MacBook Neo didn't get spared - its price went up by $100 in the US. Today, Apple has started offering the MacBook Neo in its refurbished store, and the price for the entry-level model with 256GB of storage and no T
AI has really changed the game around software development. More people are leveraging AI than ever to contribute patches to projects they use. To me, this is a good thing as more folks will contribute patches rather than fork or not fix them. The main problem is that AI has made generating code fas
Heading for a sleep divorce? Here's why the Saatva Solaire is a great adjustable firmness bed for couples — and how to save $525 now
At a time when we should be prioritizing repairability, everyone is obsessed with thinner laptops.
India's ambitious semiconductor projects, including Tata Electronics' Dholera fab, face potential delays due to the West Asia conflict. Logistical snags have disrupted the supply of crucial speciality gases, chemicals, and metals, leading to concerns about cost overruns and extended timelines. While
Indian startups are securing significantly larger seed and early-stage funding rounds, nearly doubling their average cheque size. This trend is driven by venture firms frontloading capital for more mature products, especially in AI, deeptech, and healthtech. While overall funding has seen a modest r
Every generation believes it is witnessing the death of taste. The printing press was going to flood the world with trash. The cheap camera was going to destroy photography. The internet was going to drown serious thought in blogs, forums, spam, and noise. Smartphones were going to turn every sacred
The most believable AI coding story right now is not that everyone is suddenly shipping ten times faster. It is that many teams are producing more code than their review systems were designed to absorb. GitLab released new AI accountability research this week with a very familiar shape. Adoption is
The latest hermes-memory-installer update brings a focused capability for teams already running memory-critical workloads: native SLO rollup and an accompanying Grafana dashboard. This isn’t about generic monitoring—it’s about moving from raw metrics to actionable compliance data, directly from the
By Naren Ranjith I had no coding experience six months ago. I'd been reading about AI security — specifically about something called prompt injection, ranked #1 on OWASP's official list of AI security risks. The idea is simple: you craft a message that tricks an AI into ignoring its instructions and
the insight that started this project hit me while i was finishing a bytecode-compiled language i'd written in C i'd spent months building a hand-written lexer, a single-pass Pratt compiler, a stack VM with 35 opcodes, and a mark-and-sweep garbage collector. and right near the end i had this realiza
I built a zero-knowledge secret sharing tool. Text and files are encrypted in the browser with AES-GCM 256 before upload - the server only ever sees ciphertext. A few things I tried to do right: Single-use by default: Durable Objects handle atomic read→decrement→delete with blockConcurrencyWhile, no
The Post-Mortem Nobody Learns From I've sat through hundreds of post-mortems. Most follow the same pattern: something breaks, someone writes a Google Doc, we have a meeting, we list action items, nobody follows up, the same thing happens again in 3 months. Here's how to break the cycle. "Blameless"
AI agents pass tests while producing sloppy thinking. They say "should work" without evidence. They present partial work as complete. They embellish. I built a tiny tool that catches this. It checks any text across four dimensions: Completeness, Consistency, Groundedness, and Honesty. pip install se
TL;DR I built a personal VPN using AWS Lambda MicroVMs. Your traffic exits from AWS. When you disconnect, the MicroVM terminates — zero cost, nothing running. When you reconnect, a fresh MicroVM launches in about 20 seconds. ./vpn.sh start # All Mac traffic now exits from AWS ./vpn.sh stop # Back to
There is a popular misconception that if you do TDD, your design also stays correct. That if the tests pass, quality is guaranteed. In AI-assisted development, this misconception is the kind that quietly accumulates — the more tests you have, the more invisible damage builds up underneath. Here is w