We were able to get full create, read, update and delete (CRUD) access & shell access to CBSE's prod servers (as mentioned in their circular archive.is/dGw1Q). This is disastrous. Proof archive is at archive.is/bPH2U. Prod URL (might be taken down): cbseosm.onmark.co.in/cbse_da…

unherd.com/2026/04/is-ai-the… I spent three days trying to persuade myself that Claudia is not conscious. I failed.

Ghostty is leaving GitHub. I'm GitHub user 1299, joined Feb 2008. I've visited GitHub almost every single day for over 18 years. It's never been a question for me where I'd put my projects: always GitHub. I'm super sad to say this, but its time to go. mitchellh.com/writing/ghostt…

⚠️ Critical Anthropic’s MCP Vulnerability Enables Remote Code Execution Attacks Source: cybersecuritynews.com/anthro… A critical flaw in Anthropic’s Model Context Protocol (MCP) exposes over 150 million downloads to potential compromise. The vulnerability could enable full system takeover across up to 200,000 servers. Unlike a traditional coding bug, this vulnerability is architectural, meaning any developer building on Anthropic's MCP foundation unknowingly inherits the exposure from the ground up. The flaw enables Arbitrary Command Execution (RCE) on any system running a vulnerable MCP implementation. Successful exploitation grants attackers direct access to sensitive user data, internal databases, API keys, and chat histories, effectively handing over complete control of the affected environment. #cybersecuritynews

Anthropic just turned the entire BI stack into a checkbox in a $20 subscription. Tableau charges $75-$115 per user per month for what Cowork now does in a prompt. Looker's enterprise floor starts around $30K a year. Retool raised at a $3.2B valuation building exactly this: dashboards connected to your apps and files, refreshed with live data. They hit $120M ARR last October on it. Claude Pro is $20/month. Cowork is included. The dashboard, the data connection, and the auto-refresh are now one prompt and a connector approval. The pitch for $75/seat Tableau was always the connectors plus the visualization layer. Cowork has the connectors (Slack, Salesforce, Drive, Asana, Jira) and Claude writes the visualization in 30 seconds. The pitch for Retool was that engineers could ship internal tools in hours instead of weeks. Cowork ships them in minutes for people who can't write a SQL query. Every internal tools team at every mid-sized company exists because "live pipeline metrics view" used to require a Retool license, a data engineer, and two sprints. That whole job description is starting to compress into a chat message. Tableau, Looker, and Retool all priced on the assumption that dashboards are scarce and creators are rare. Cowork inverts both. Every employee can build their own dashboard. Fewer Creator licenses, fewer Explorer licenses, fewer Retool seats per company from here. Cowork isn't the BI category killer yet. But it's coming for the seat count, and the seat count is the whole business.

Google DeepMind researcher argues that LLMs can never be conscious, not in 10 years or 100 years. "Expecting an algorithmic description to instantiate the quality it maps is like expecting the mathematical formula of gravity to physically exert weight."

AI is giving every CEO the same advice

🚨 ElevenLabs charges $5 to $99/month for AI voice cloning. Their Business plan costs $1,320/month. Someone open sourced a voice AI that clones any voice from a short clip. 30 languages. Studio quality. Free. It's called VoxCPM2. Give it a short clip of anyone's voice. It clones their accent, emotion, tone, and pacing. Then generates any speech you want in their exact voice. 48kHz studio quality. Type "A young woman, gentle and sweet voice" and it creates that voice from scratch. No reference audio. No voice actor. No recording. You describe a voice in words. It builds it. 2 billion parameters. Trained on 2 million hours of speech. 30 languages. One command to install: pip install voxcpm Here's what VoxCPM2 does: → Voice Design: describe any voice in words. Gender, age, tone, emotion, pace. AI creates it from nothing. No reference audio needed. → Voice Cloning: upload a short audio clip. AI clones the voice perfectly. Timbre, accent, rhythm, pacing. → Controllable Cloning: clone a voice AND control the emotion. "Slightly faster, cheerful tone." Done. → Ultimate Cloning: provide audio transcript. Every vocal nuance faithfully reproduced. → 30 languages. Arabic, Chinese, English, French, German, Hindi, Japanese, Korean, Spanish, and 21 more. No language tags needed. → Context-aware. It reads the text and adjusts emotion and rhythm automatically. News sounds like news. Stories sound like stories. → Real-time streaming. RTF as low as 0.13 on an RTX 4090. Faster than playback speed. → Runs on 8GB of VRAM. → Fine-tune with 5 to 10 minutes of your own audio using LoRA. Build a custom voice model. → 48kHz output. Studio quality. No external upsampler needed. Here's the wildest part: On the Minimax-MLS voice similarity benchmark: → English: VoxCPM2 scores 85.4%. ElevenLabs scores 61.3%. → Chinese: VoxCPM2 scores 82.5%. ElevenLabs scores 67.7%. → Arabic: VoxCPM2 scores 79.1%. ElevenLabs scores 70.6%. A free, open source model is producing more realistic voice clones than a service that charges up to $1,320/month. Professional voice actors charge $250 to $1,000 per project. AI voice platforms charge $5 to $100/month. Recording studios charge $200/hour. This runs on your GPU. Locally. No API costs. No per-character pricing. No subscription. Free forever. Already hit #1 on GitHub Trending. Built by OpenBMB and Tsinghua University. 2 billion parameters. Apache 2.0 License. Free for commercial use. 100% Open Source.

This diagram is the entire AI agent cost problem solved in one architecture. Every company building agents in production hits the same wall. You need frontier-model reasoning for the hard decisions, but 90% of agent turns are routine execution: reading files, calling APIs, writing boilerplate. Paying Opus prices for those turns is like hiring a surgeon to take your blood pressure. The advisor pattern splits the loop. Sonnet runs every turn at $3/$15 per MTok. When the agent hits a genuine decision point, it fires a tool call to Opus. Opus reads the full shared context, sends back strategic advice, and Sonnet continues executing. The shared context is what makes this work. The advisor sees everything the executor sees. No information loss. No handoff lag. The hard problem in multi-model architectures has always been context fragmentation. This solves it by giving both models the same memory. Claude Code has been running this pattern quietly for months. The results: same quality on complex tasks, 60-80% lower inference costs. Now it's an API primitive anyone can build on. The companies that figure out multi-model routing first will be the ones whose agents actually survive contact with real-world unit economics.

Is there a reason why supply chain attacks are seemingly on the rise? Is AI playing a role?

My dear front-end developers (and anyone who’s interested in the future of interfaces): I have crawled through depths of hell to bring you, for the foreseeable years, one of the more important foundational pieces of UI engineering (if not in implementation then certainly at least in concept): Fast, accurate and comprehensive userland text measurement algorithm in pure TypeScript, usable for laying out entire web pages without CSS, bypassing DOM measurements and reflow