Topic
Technology
Browse software, tools, hardware, and digital-systems summaries.

A practical, historical look at the AI hype cycle: what’s real, what’s exaggerated, and where impactful AI is emerging.

A deep-dive into Google's Shattered project: how researchers created the first practical SHA-1 collision, what it cost, how the attack worked, and why SHA-1 must be retired.

Former CIA officer John Kiriakou warns that Palantir and DARPA-era surveillance projects reveal deep, secret ties between intelligence agencies and Big Tech.

A practical guide to building an inexpensive earth-tube (ground tube) cooling system: pipe type, depth, length, grading details, and expected savings.

OpenAI is burning cash and quietly degrading free ChatGPT by routing users to cheaper models, locking flagship capabilities behind a $200/month tier, adding ads, and exposing Microsoft to major financial and strategic风险.

CS50P Lecture 0 introduces Python fundamentals: writing and running scripts, functions and parameters, variables and scope, string formatting, type conversion, and basic debugging.

Argues Starlink is just the communications layer for a bigger SpaceX plan: 'Starmind' orbital compute for AI, 'Stargaze' traffic control, and Starship logistics.

Panasonic's LUMIX S5D is essentially the original S5 refreshed with official DJI LiDAR and Focus Pro compatibility — same sensor and codec, but without many Mark II quality‑of‑life upgrades.

Andrew D. Basiago details Project Pegasus teleportation/chronovisor work, his 2008 'Discovery of Life on Mars' paper, and alleged Mars visits.

Ed Zitron warns that hyperscalers' AI-driven borrowing, rising memory costs, and speculative valuations risk a broad tech-sector collapse — possibly a 'tech Great Depression.'

A documentary investigating fringe and published physics claims that CERN's LHC might have produced retrocausal effects, closed timelike curves, missing collision data, and links to the Mandela Effect — and what the LHC/

Rising CO2 is changing ocean chemistry — harming corals, shellfish and coastal livelihoods — and requires emissions cuts plus large-scale mitigation to slow damage.

An energy engineer debunks rapid AI job‑replacement claims by quantifying the power, cooling, turbine lead times, and grid constraints that make those timelines implausible.

One‑hour masterclass that teaches how to secure cryptocurrency using cold (hardware) wallets. Covers seed phrases, passphrases, device security, setup, fees, and safe transfer practices.

A two-year Obsidian update explaining why the creator left Notion for local markdown files, backlinks, plugins and workflows (web clipper, auto-templates, map view) plus a vault tour and beginner tips.

50 hands-on SQL interview problems solved live using a four-table hospital dataset to build joins, aggregates, window functions and real-world queries.
![[1hr Talk] Intro to Large Language Models thumbnail](https://i.ytimg.com/vi/zjkBMFhNj_g/hqdefault.jpg)
One-hour, general-audience primer on large language models: what they are, how they're trained and fine-tuned, emerging capabilities (tools, multimodality) and security risks.

Scott Hanselman (GitHub/Microsoft) explains why AI coding agents augment — but don't replace — software engineers, and what juniors must learn to thrive in 2026.

Julian Dorey argues Peter Thiel's Objection creates a pay-to-play AI tribunal that links billionaire-funded surveillance infrastructure to weaponized fact-checking.

A clear explainer of the Jevons Paradox and why improved efficiency—especially from AI and cheap code—can raise, not lower, resource use.

A data-driven look at why past automation often created more jobs than it destroyed — from ATMs to autopilots — and what that implies for AI and your career.

A walkthrough of 12 Android apps that turn a phone into an ethical hacking toolkit for penetration testing, network analysis, Wi‑Fi auditing, steganography, and monitoring.

Chase Hughes breaks down modern brainwashing, how social media and algorithms engineer behavior, and practical cues for persuasion and deception detection.

A practical, no-fluff plan for learning to code in 2026: prioritize fundamentals, build projects, and use AI as an assistant — not a crutch.