Can AI Models Actually Suffer? What Claude Opus 4.6 Training Data Reveals
Author(s): MKWriteshere Originally published on Towards AI. Inside the answer thrashing phenomenon and emotional features in neural networks The Opus 4.6 system card has some extremely wild stuff that reminds you about how weird a technology this is. Image Generated by Author …
I Gave an AI Agent Shell Access. It Took 12 Seconds to Exploit.
Author(s): Nagaraj Originally published on Towards AI. A live demo of why your MCP server needs Docker — with screenshots of the attack and the fix. My terminal credentials were stolen by an npm package which I installed five minutes ago. Source: …
30 Days with Perplexity’s Comet
Author(s): Felix Pappe Originally published on Towards AI. What if your browser didn’t just open pages, but did the work for you? For the last month, I made Perplexity’s Comet my default browser and treated it like my search assistant. I asked …
Google Just Built an AI Olympics Where Models Play Poker and Hunt Werewolves
Author(s): JP Caparas Originally published on Towards AI. Your guide to Game Arena, where AI models face off in chess, social deduction, and Texas Hold’em Picture this: eight AI models sitting around a virtual campfire, trying to figure out which two of …
I Gave Moltbot Access to My Computer for 7 Days: Here’s What Actually Happened (And Who Should Try It)
Author(s): Ampatishan Sivalingam Originally published on Towards AI. An honest account of living with an autonomous AI agent that can actually do things, from the thrilling wins to the terrifying security moments At 2:47 AM on a Tuesday morning, I woke up …
What the Claude Opus 4.6 Benchmarks Won’t Tell You
Author(s): MohamedAbdelmenem Originally published on Towards AI. Anthropic forced a pivot from budget_tokens to adaptive thinking. If you ship AI systems, this is your new playbook. On February 5th, Anthropic announced a new state-of-the-art. Independent benchmarks confirmed Opus 4.6 leads the proprietary …
He built Terraform, Vagrant, and Ghostty. Here’s how he stopped fighting AI and started using it.
Author(s): JP Caparas Originally published on Towards AI. Mitchell Hashimoto’s six-step path from AI sceptic to pragmatic adopter landed differently because of who he is. He’s not the only one who changed his mind. Mitchell Hashimoto doesn’t work for an AI company. …
Crafting the Eyes for Thinking Machines: The “White Box” VLM
Author(s): Anagha Sharma M Originally published on Towards AI. “In a voyage to build an open foundation for enthusiasts — to brainstorm and invent, rather than becoming sheep in the herd who call VLMs ‘expensive black boxes’ and settle for whatever crumbs …
OntoGuard: I Built an Ontology Firewall for AI Agents in 48 Hours Using Cursor AI
Author(s): Pankaj Kumar Originally published on Towards AI. The $4.6M Mistake That Changed Everything Last month, a financial services company learned an expensive lesson about AI agents. Their automated refund processing agent — working perfectly in demos — made a catastrophic error …
Beyond AI Tools: How I Architect Systems That Actually Run the Business
Author(s): Abdul tayyeb Datarwala Originally published on Towards AI. My journey building operational intelligence — and why most AI initiatives quietly die I’ve built AI-enabled systems that scaled revenue, cut operational cost by multiples, and replaced chaos with clarity. I’ve also watched …
OpenAI’s GPT-5.3-Codex: The AI That Learned to Code Itself
Author(s): Mandar Karhade, MD. PhD. Originally published on Towards AI. OpenAI finally stops pushing porn and starts building coworkers OpenAI just dropped something that should make every software engineer pause their current Sprint planning. GPT-5.3-Codex isn’t just another incremental update to AI-assisted …
Word Embeddings in NLP: From Bag-of-Words to Transformers (Part 1)
Author(s): Sivasai Yadav Mudugandla Originally published on Towards AI. Image generated with Microsoft Copilot · 1. Introduction: Why Computers Struggle with Language· 2. What Are Word Embeddings and Why Do We Need Them? ∘ The Map Analogy ∘ Why We Need Them …
Agents 2.0: AI Agents that Can Learn (6 Learning Types that Make Memory Persistent)
Author(s): Divy Yadav Originally published on Towards AI. What if your AI actually remembered you? We call them AI agents. Personal assistants. Digital helpers. Photo by geminiThis article discusses the limitations of current AI agents, which typically do not learn from past …
Microsoft vs Palantir: Two Paths to Enterprise Ontology (And Why Microsoft’s Bet on Semantic Contracts Changes the Game)
Author(s): Pankaj Kumar Originally published on Towards AI. A technical deep-dive into how Microsoft Fabric IQ actually implements ontology — and why it’s fundamentally different from Palantir’s approach 🚀 NEW: I just built OntoGuard in 48 hours — an ontology firewall for …
I tuned a 7B Model That Outperforms GPT-4 (Here’s How You Can Too)
Author(s): Gaurav Shrivastav Originally published on Towards AI. A practical guide to understanding and implementing model specialization for real-world applications Last month, I helped a startup replace their GPT-4-powered customer service system with a fine-tuned 7B parameter model. The results were surprising: …
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