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- 🧭 AI 2040: 5 Futures for Humanity
🧭 AI 2040: 5 Futures for Humanity
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How should humanity handle superintelligence? AI 2040’s five blueprints range from global cooperation to an all-out race. Honestly, Plan A feels worth reading.
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AI INSIGHTS
The team behind the AI 2027 project just released something very interesting. Their nonprofit group, the AI Futures Project, has launched AI 2040, a detailed stress-test of how the global AI race might unfold over the next decade.
Plan A: Verified Slowdown: the U.S. and China agree to limit frontier development, share AI research openly, track computing resources, and delay superintelligence until 2040.
Plan B: Fight China: the U.S. treats advanced AI mainly as a geopolitical race and tries to maintain its lead.
Plan C: Burn the Lead: America uses its advantage aggressively before competitors catch up.
Plan D: Race to ASI: companies and governments continue building toward artificial superintelligence at full speed.
Plan S: Shut It All Down: governments attempt to stop advanced AI development entirely.
The project strongly favors Plan A. Its proposed timeline has the U.S. and China reaching an agreement in 2029, limiting AI to roughly top-human-expert capability from 2030 to 2035.
Nobody knows exactly what the next ten years of AI will look like. However, projections coming directly from people who have worked inside these top labs are some of the best attempts we have at mapping out the road ahead.
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1. Free: GPT-5.6 Sol in Action: How Well Can It Handle Complex Work? Full Results Inside. GPT-5.6 Sol beats Fable 5 in several agent and browsing tests, but Fable 5 still leads in key coding tasks. Here’s what the full results mean in practice.
Fable 5 got another extension through July 19 😂 Honestly, that gives you a little more time to build something useful before the current window closes.
This is actually the third extension in 5 weeks. So, what's a good project to use this window on?
A cinematic website is one of the best things to build right now, because Fable 5 can genuinely handle the full thing inside Claude Code, from structure to scroll animations to a working local preview. This workflow can work for:
Luxury product websites
Story-driven brand websites
Personal portfolios
I’ll show you how to set everything up and build your own version step by step.
TODAY IN AI
AI HIGHLIGHTS
💸 Bookmark this viral guide to using GPT-5.6 Sol more efficiently without burning through 5-hour usage limits. It also includes practical tips from his daily workflow.
👻 Developer Eric Lu created created a font called Ghost Font that only humans can read. Both Fable and GPT-5.6 Sol Ultra can't decipher it correctly. Check it out here.
🎁 Paid ChatGPT users just got one extra banked reset to restore weekly usage, celebrating 7M active Codex & ChatGPT Work users. You can claim it on app or web.
📱 Apple is paying $250 million to iPhone customers over delayed AI features, eligible buyers could receive between $25 and $95 per device. See how to get your share.
💳 Anthropic started rolling out rupee pricing for Claude in India, its second-largest market. But the payment option most Indians use is still missing. Here’re all details.
🔐 Microsoft CEO issued a shocking warning to companies using AI that they may pay twice for proprietary AI. Suddenly, those “helpful” prompts look far more valuable.
🚀 Hermes became one of GitHub’s biggest open-source agents, and now its maker wants a $1.5B valuation. Investors are reportedly lining up behind Nous Research.
💰 Big AI Fundraising: PixVerse raised $439 million, pushing its valuation above $2 billion. The AI video startup now has 150 million users and plans to expand its models worldwide.
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AI BREAKTHROUGH
Mistral AI just dropped a major update for the robotics space. Their newly announced 8B model, called Robostral Navigate, lets robots move autonomously through complex spaces using just one standard camera.
Even with one ordinary camera, it hit a 76.6% success rate in unseen environments, actually beating the best multi-sensor systems by 4.5 points.
Instead of just calculating strict metric distances, the model looks at its camera feed and intuitively "points" to where it should go next. This makes it easy to swap the software between wheeled, legged, or even flying robots.
The team built the data pipeline entirely in a simulation. They reduced training tokens by 22x. They topped the training off with reinforcement learning. This means the model learns from trial and error, allowing the robot to instantly recover if it makes a mistake or encounters a weird obstacle.
This is a massive shift for industries like manufacturing, delivery, and hospitality. Until now, deploying a robot into a messy, real-world space meant strapping expensive hardware to it. Mistral is shifting that burden from the physical sensors over to a compact, highly efficient software model.
By focusing on how the model learns rather than bolting on more sensors, Mistral just showed that a single basic camera is all a robot needs to find its way.
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