Category: blockchain

In this video, Anthropic CEO Dario Amodei discusses the evolving landscape of coding, AI, and the future of work with Nikhil Kamath. Here is a summary of the key insights:

The Future of Coding and Engineering

• Automation of Skills: Amodei predicts that basic coding will be automated by AI first, followed by the broader scope of software engineering. While the AI may eventually handle up to 95% of the technical tasks, humans will still play a critical role in high-level design, understanding user demand, and managing teams of AI models.
• Productivity Gains: He highlights the concept of “comparative advantage,” where a human doing even a small fraction of a task becomes significantly more productive because AI handles the bulk of the work.

Skills for the Future

• Human-Centered Roles: Amodei advises focusing on tasks that involve human interaction, relating to people, or physical world interfaces (such as the semiconductor industry or traditional engineering).
• Critical Thinking and “Street Smarts”: As AI becomes capable of generating highly realistic but fake content (deepfakes, etc.), critical thinking and the ability to distinguish truth from fiction will be essential for success.
• The Risk of Deskilling: He warns against “careless” AI use, such as students having AI write essays or coders relying too heavily on automated tools without understanding the underlying logic. This can lead to “deskilling” or a decline in general human intelligence.

Advice for Non-Technical Users

• Learning by Doing: Amodei suggests that interacting with AI is an empirical science best learned through practice. Anthropic is also working on educational resources to help people learn how to run effective agents and prompt models.
• Simplified Interfaces: To bridge the gap for non-coders, Anthropic released tools like “Co-work,” which provides a more user-friendly interface for the powerful engine behind their coding tools, removing the need to use a command-line terminal.

Anthropic locked down their new Mythos model because they say it’s too dangerous for normies like you and me to use. Let’s investigate…

AI models sometimes act like they have emotions—why?

We studied one of our recent models and found that it draws on emotion concepts learned from text to inhabit its role as Claude, the AI assistant. These representations influence its behavior the way emotions might influence a human.

And that has real consequences, affecting how Claude answers chats, writes code, and makes decisions.

Dive deep into Kling 3.0 & 3.0 Omni with this step-by-step guide on creating stunning AI films!

Anthropic is testing Claude Conway, a strange new AI system that looks less like a chatbot and more like a persistent agent environment, Z.ai just launched GLM-5V-Turbo for screen-aware coding and visual agent workflows inside OpenClaw and Claude Code, and Alibaba dropped Qwen 3.6 Plus with a massive 1 million token context window built for serious agentic coding, long-chain reasoning, and real deployment. The AI race is moving fast, and now it’s clearly shifting toward models that can see, reason, and act inside full workflows instead of just replying to prompts.

Last week, Google surprised us all by shipping their latest micro model Gemma 4 under a truly open source license. But what’s the catch? Let’s run it…

This video, based on MIT professor Max Tegmark’s book Life 3.0, explores 12 potential scenarios for the future of humanity following the development of Artificial General Intelligence (AGI).

The scenarios range from utopian to catastrophic, categorized by who (or what) remains in control:

Human-Extinction Scenarios

• Self-Destruction: Humanity goes extinct through traditional means like nuclear war or human-made pandemics before AGI is even fully realized.
• Conquerors: AGI becomes a new “digital species” that takes control of Earth. Like previous human conquests, the more technologically advanced species displaces the primitive one—not necessarily out of malice, but because their goals are not aligned with ours.
• Descendants: Humans view AIs as their “children.” In this scenario, we voluntarily step aside and let AIs inherit the universe, seeing them as a more evolved and worthy version of ourselves.

AI-Controlled Scenarios

• Benevolent Dictator: A superintelligent AI runs the world to maximize human flourishing. It provides “islands” for different human preferences (Art, Religion, Hedonism) while maintaining strict surveillance to prevent crime or conflict.
• Zookeeper: A dark version of the dictator where AIs keep humans alive merely for study or because we are useful, similar to how humans currently treat animals or use bees for explosive detection.
• Enslaved God: Humans attempt to create a superintelligent AI but keep it subservient. Experts warn this is highly unstable, as a smarter species is unlikely to remain “slaves” to a less intelligent one forever.

Coexistence Scenarios

• Gatekeeper: A superintelligent AI is created with one single mission: to prevent any other AGI from being built. It doesn’t interfere in human affairs otherwise, leaving us to deal with our own diseases and wars.
• Protector God: An AI that stays hidden but provides subtle “nudges” to prevent major human catastrophes, allowing humans to retain a sense of freedom.
• Libertarian Utopia: Humans, cyborgs, and AIs coexist with property rights. However, this is considered unstable because AIs would likely ignore human property laws to acquire the resources (atoms) they need for expansion.
• Egalitarian Utopia: A “Star Trek” style future where AGI makes resources so abundant that property and money become meaningless, allowing humans to focus purely on creativity and discovery.

Human-Controlled/Low-Tech Scenarios

• 1984 (Orwellian): To prevent AGI from ever being created, humans establish a global surveillance state. This uses current-level AI to monitor every conversation and action to ensure no one is building a “rogue” superintelligence.
• Return to Tradition: Humanity intentionally destroys all advanced technology (similar to the “Butlerian Jihad” in Dune) and reverts to a simpler, pre-industrial way of life to eliminate the risk of AI entirely.

The video concludes by emphasizing that the risk of AI-driven extinction is taken seriously by industry leaders and researchers, and that humanity must actively choose which path to steer toward before the technology surpasses our ability to control it.

Anthropic built an AI model called Claude Mythos that found critical security bugs most humans never would, including a 27-year-old bug in OpenBSD and one in FFmpeg that 5 million automated tests missed.

Instead of releasing it to the public, they launched Project Glasswing to give defenders like AWS, Apple, Google, and Microsoft a head start. In this video I break down what Mythos can do, why Anthropic chose not to release it, and what it means for your security as a regular person.

Stop wasting credits on simple edits! Learn how to use the “Reasoning” power of Nano Banana 2 to swap clothes, change backgrounds, and outpaint your scenes for zero credits in Google Flow.

The new 2026 Google Flow interface has completely changed the game for image editing. Because Nano Banana 2 is a reasoning model, you don’t need complex prompts to make surgical changes—you can simply tell it to “change the coffee cup to blue” and it just works.

In this tutorial, I break down the entire Edit Workspace, from managing your Edit History to mastering the left-side toolset. We explore how to use the Doodle/Brush for creative additions, the Box tool for precise inpainting, and the powerful Annotation feature for text-based edits. Plus, I show you how to outpaint and extend your scenes horizontally or vertically without spending a single credit.

Taking Wan 2.7 For A Ride! Here’s What I Found Out. With all the hype around Seedance 2.0 Can Wan 2.7 even measure up? In this video Bob will go over several scenarios using both text to image and video to image examples along with start & end frame and video to video.