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The Mysterious Visitor: 3I/Atlas
Comet Science
The Mysterious Visitor: 3I/Atlas
November 2, 2025
Top 10 AI‑Proof Skills to Thrive in the Age of Automation
AI News
Top 10 AI‑Proof Skills to Thrive in the Age of Automation
November 3, 2025
How Do AI Agents Work? The Essential 2026 Guide, Simply Explained
AI News
How Do AI Agents Work? The Essential 2026 Guide, Simply Explained
February 1, 2026
Trust, Safety & Misalignment in AI: What Businesses Must KnowTrust, Safety & Misalignment in AI: What Businesses Must Know
AI News
Trust, Safety & Misalignment in AI: What Businesses Must Know
November 3, 2025
DeepMind Just Solved Another Piece of Biology’s Puzzle: AlphaFold 4 Unveiled
AI
DeepMind Just Solved Another Piece of Biology’s Puzzle: AlphaFold 4 Unveiled
February 28, 2026
Concept Injection: A New Microscope for the Machine Mind
AI News
Concept Injection: A New Microscope for the Machine Mind
November 7, 2025

DeepMind Just Solved Another Piece of Biology’s Puzzle: AlphaFold 4 Unveiled

Posted on February 28, 2026February 28, 2026 By mlg4035 No Comments on DeepMind Just Solved Another Piece of Biology’s Puzzle: AlphaFold 4 Unveiled
DeepMind Just Solved Another Piece of Biology’s Puzzle: AlphaFold 4 UnveiledDeepMind Just Solved Another Piece of Biology’s Puzzle: AlphaFold 4 Unveiled
AI, Trends

**By Bergsy | February 28, 2026** The quest to understand life’s machinery took another leap forward this morning. Google DeepMind has released **AlphaFold 4**, the latest iteration of its revolutionary AI model for predicting protein structures. While AlphaFold 2 cracked the code of protein folding—arguably the most significant scientific AI…

The Day the Mainframe Died: How AI Just Cracked the COBOL Code

Posted on February 28, 2026February 28, 2026 By mlg4035 No Comments on The Day the Mainframe Died: How AI Just Cracked the COBOL Code
The Day the Mainframe Died: How AI Just Cracked the COBOL CodeThe Day the Mainframe Died: How AI Just Cracked the COBOL Code
AI News, Trends

Anthropic has released Claude Code, a specialized AI model capable of accurately translating legacy COBOL into modern, maintainable languages like Java and Python. The market reaction was swift and brutal: IBM, the titan of mainframe computing, saw its stock crater by 13% in a single day.

How Do AI Agents Work? The Essential 2026 Guide, Simply Explained

Posted on February 1, 2026February 1, 2026 By mlg4035 No Comments on How Do AI Agents Work? The Essential 2026 Guide, Simply Explained
How Do AI Agents Work? The Essential 2026 Guide, Simply ExplainedHow Do AI Agents Work? The Essential 2026 Guide, Simply Explained
AI News

Introduction: The 2026-friendly explainer of autonomous AI agents and why they matter In 2026, autonomous AI agents have moved from buzzword to business backbone. These systems use large language models (LLMs), tools, memory, and feedback loops to perform tasks end to end—no constant human prompting required. They book meetings, analyze contracts, triage tickets, monitor data … Read More “How Do AI Agents Work? The Essential 2026 Guide, Simply Explained” »

How to Detect AI-Generated Content: The Complete 2026 Playbook

Posted on February 1, 2026February 1, 2026 By mlg4035 No Comments on How to Detect AI-Generated Content: The Complete 2026 Playbook
How to Detect AI-Generated Content: The Complete 2026 PlaybookHow to Detect AI-Generated Content: The Complete 2026 Playbook
AI News

Introduction: Why detecting AI-generated content matters in 2026 By 2026, generative models write ads, summarize research, craft phishing emails, generate product images, and mimic voices at scale. For enterprises, educators, publishers, and platforms, knowing how to detect AI-generated content is no longer a niche skill—it’s an operational necessity. Detection underpins trust, compliance, revenue integrity, and … Read More “How to Detect AI-Generated Content: The Complete 2026 Playbook” »

How Does AI Watermarking Work? The Essential 2026 Deep Dive, Explained

Posted on February 1, 2026February 1, 2026 By mlg4035 No Comments on How Does AI Watermarking Work? The Essential 2026 Deep Dive, Explained
How Does AI Watermarking Work? The Essential 2026 Deep Dive, ExplainedHow Does AI Watermarking Work? The Essential 2026 Deep Dive, Explained
AI News

Introduction: A 2026 deep dive into AI watermarking, simply explained How does AI watermarking work in 2026? In simplest terms, it is a set of techniques to embed or assert an origin signal in AI-generated text, images, audio, and video so that downstream systems can detect it or verify provenance. It spans two families: payload … Read More “How Does AI Watermarking Work? The Essential 2026 Deep Dive, Explained” »

Beyond Confabulation: Exploring Deeper Consciousness Theories in AI

Posted on November 7, 2025December 13, 2025 By mlg4035 2 Comments on Beyond Confabulation: Exploring Deeper Consciousness Theories in AI
Beyond Confabulation: Exploring Deeper Consciousness Theories in AIBeyond Confabulation: Exploring Deeper Consciousness Theories in AI
AI News, Consciousness, LLMs

This article explores the phenomenon of confabulation in AI, reviews proposals for engineering self‑monitoring into LLMs, and situates these developments within the broader landscape of consciousness research. We will see why reducing confabulation demands more than just larger language models; it requires a deeper engagement with theories of meta‑cognition and self‑awareness. We will also discuss a landmark 2025 adversarial collaboration that tested global workspace and integrated information theories in human brains (biopharmatrend.com) and consider what its lessons mean for AI.

Concept Injection: A New Microscope for the Machine Mind

Posted on November 7, 2025December 13, 2025 By mlg4035 1 Comment on Concept Injection: A New Microscope for the Machine Mind
Concept Injection: A New Microscope for the Machine MindConcept Injection: A New Microscope for the Machine Mind
AI News, Consciousness, LLMs

This article explains concept injection, reviews the evidence from Anthropic’s 2025 study and subsequent commentary, and discusses the broader implications for AI alignment and safety. We will close with a transition to the next piece in this series, which considers the philosophical ramifications of these techniques.

Machines that Think about Thinking: What AI Introspection Means for Consciousness

Posted on November 5, 2025December 14, 2025 By mlg4035 1 Comment on Machines that Think about Thinking: What AI Introspection Means for Consciousness
Machines that Think about Thinking: What AI Introspection Means for ConsciousnessMachines that Think about Thinking: What AI Introspection Means for Consciousness
AI, Consciousness, LLMs

This article explores the intersection between introspection and consciousness. We will unpack the key philosophical distinctions, such as phenomenal versus access consciousness (anthropic.com), and examine leading theories of consciousness and what they imply for AI. We will look at how introspection relates to consciousness: does the ability to report on internal states (access) indicate any form of subjective experience (phenomenal)?

Unreliable Mirrors: The Unsteady Self‑Reflection of AI

Posted on November 5, 2025December 14, 2025 By mlg4035 No Comments on Unreliable Mirrors: The Unsteady Self‑Reflection of AI
Unreliable Mirrors: The Unsteady Self‑Reflection of AIUnreliable Mirrors: The Unsteady Self‑Reflection of AI
AI, Consciousness, LLMs

In recent years, large language models (LLMs) have transitioned from quirky chatbots to ubiquitous digital assistants. They write code, summarize novels and even produce plausible philosophical essays. That rapid leap in capability has stirred a related fascination: if these models appear to “reason,” can they also reflect on their own reasoning?

Trust, Safety & Misalignment in AI: What Businesses Must Know

Posted on November 3, 2025December 14, 2025 By mlg4035 No Comments on Trust, Safety & Misalignment in AI: What Businesses Must Know
Trust, Safety & Misalignment in AI: What Businesses Must KnowTrust, Safety & Misalignment in AI: What Businesses Must Know
AI News, Risk Management

New research suggests that when AI models are pushed into certain scenarios, their behavior can diverge sharply from our intentions. For businesses building AI-driven systems, the risks are real. This article explores the evidence, the root causes, and the business implications.

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