AI Cheatcode — AI Profit Pulse
The newsletter creators read to stay ahead of the AI curve — and ahead of their competitors.
Latest AI Articles
AI Could Undermine Emerging Economies
AI automation threatens to erode the “development ladder,” a foundational economic pathway that has lifted hundreds of millions out of poverty.
Deric Cheng — December 11, 2025
Violante of Naxos
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1d
For the past 2 decades we’ve prioritized STEM training and careers, with AI these skills will be less required while the traditional greek education that develops the whole person while emphasizing critical thinking and debate skills will be even more important. Everything old is new again.
Len Romanick/Infonomena LLC
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1d
What are the Russians doing (or not) in the AI-sphere? The lack of any dots in that huge geographic section of the world stood out to me.
AI Cheatcode
AI Tool Spotlight: Vybe — Build Internal Apps 10× Faster
Vybe is a game-changer! Turning a few prompts into fully functional, sellable internal tools in minutes bridges the gap between idea and execution for teams and solo creators alike.
The Epoch AI Brief - November 2025
Frontier Data Center Hub launch, OSWorld analysis, data center build time, "Claudiness" factor behind benchmark scores and our 2025 impact survey.
Hi! In this edition of the Epoch AI brief:
The Evidence for AI Consciousness, Today
A growing body of evidence means it’s no longer tenable to dismiss the possibility that frontier AIs are conscious.
Cameron Berg — December 8, 2025
Fascinating article! If only there was a universal, substract-agnostic test for consciousness. But of course, it's not that simple. As you said in your article, we can't even know for sure if other humans are conscious.
I also found the discussion about the asymmetry between getting the AI consciousness right or wrong really insightful. Thanks for sharing!
Good clear statement of the basic position.
About evidence, I am sceptical that any of the interesting findings from Anthropic count as evidence. I think the debate has to be based on priors and mechanisms, not on evidence, because there can be no evidence. Notating p < 10^{-15} on experimental findings is a mistake, in context. Even if only 1 out of 100 tests gave the "positive" result, that would be a huge result, *if the method was valid*. Statistical significance has no bearing on how seriously to take this.
About the risk on the under-attribution side, I like to call it "the AI oubliette" - https://jmmcd.substack.com/p/the-ai-oubliette
Your AI Roundup
Tracking open models and global research trends from NeurIPS 2024–2025
Welcome to this week’s AI round-up! Today’s brief covers key shifts in frontier AI research at NeurIPS 2024–2025, the release of Mistral 3 and a look at emerging startups applying AI to robotics and infrastructure resilience.
Claude Opus 4.5 and Gemini App Upgrade | Weekly Digest
PLUS HOT AI Tools & Tutorials
Hey! Welcome to the latest Creators’ AI Edition. We hope your Thanksgiving week is going well.
Deepseek V3.2, Telegram Cocoon, Kling 2.6, VibeVoice realtime, LongCat-Image, Seedream 4.5 & more AI NEWS
Welcome to the AI Search newsletter. Here are the top highlights in AI this week.
DeepSeek just launched two super-smart AI models, V3.2 and V3.2-Speciale, that are designed to solve really tough problems, beating GPT-5 and matching Gemini 3.0 Pro in math and coding challenges. The V3.2-Speciale model is so good it even won gold medals at top international math and computer science Olympiads, and it’s only available through their API…
DeepSeek’s V3.2, Mistral 3 and Kling | Weekly Digest
PLUS HOT AI Tools & Tutorials
Hey! Welcome to the latest Creators’ AI Edition.
Runway’s new model seems to be crazy good.
But also, DeepSeek is pricing their model like that? How many times is their model cheaper than Gemini or Sonnet? Crazy!
Excelletn breakdown on the sparse-attention architecture in DeepSeek V3.2. What's partcularly interesting about their post-training approach is how they're essentially distilling multiple specialized RL models into one unified system, which hints at a broader shift in how we might build general purpose reasoning models goingforward. The pricing war between DeepSeek and the Western labs will likely push model costs down faster than quality improvements can justify premium tiers.
Claude Opus 4.5, Deepseek Math V2, Flux 2, Z-image, open-source robots & more AI NEWS
Welcome to the AI Search newsletter. Here are the top highlights in AI this week.
DeepSeek-Math-V2 is a powerful open-source AI that can solve super hard math problems and even check its own work to make sure the reasoning is correct. It’s built to handle advanced math competitions and formal proofs, using a smart system where one part creates answers and another part double-checks the logic, making it one of the best math AIs out th…
Creativity Is Dying - But AI Isn’t the Murderer
Why the Future of Creativity Belongs to Humans Who Know How to Work With Machines
The real culprit is how we’re using (and misusing) AI in the ideation process.
This framework is absolutley gold, especially the divergence/convergence split. The way AI acts as a volume generator and humans filter for strategic fit maps really well onto how modern product teams actually operate. One thing Ive noticed though is that most teams don't iterate enough on those mid-tier ideas, the ones from suggestion 8-15 that feel almost right but need a twist. Thats where the remix step becomes crucial.
AI Wins the Shipping Squeeze
Inside the AI Transformation of Parts, People & Processes
Listen to the Audio Edition of This Week’s AI Dispatch:
Net AI: Pioneering Smarter, More Efficient Telecom Networks 🌐
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The disconnect between telecom and ML folks makes a lot of sense when you think about it. Telecoms need deterministic reliability, ML works with probabilities. Getting 95% accuracy on traffic forecasting while avoiding underestimation errors is pretty clever though, especially if it actually lets operators power down infrastructure without service drops.
AI Cheatcode — Profit Pulse
Where creators turn AI shifts into income, leverage, and opportunity.
This is one of the most practical AI breakdowns I've read in months. The 'packaging better, not building more' framing just clicked for me. The localization agency idea is especially brilliant, hadn't even considered that angle
Finally, someone cutting through the AI hype with actual business models. The SOP packs and username flip are perfect low-floor, high-ceiling ideas. Subscribed immediately.
Trust AI Like Your Customers Do
Inside the AI Transformation of Parts, People & Processes
Listen to the Audio Edition of This Week’s AI Dispatch:
Really insightful breakdown of how distributors are getting caught flatfooted by their own customers. The working capital angle is probably the most underrated part here, cause most leaders dunno that $1.7T isn't about finding new money but just freeing up what's already stuckin the system. AI invoicing and demand forecasting basically turns trapped cash into operating leverage without touching margins. That might actaully be the lowest-risk growth move as rates stay elevated.
AI Business Value Is Not an Oxymoron: How Predictive AI Delivers Real ROI for Enterprises
Eric Siegel reveals why predictive AI often fails to deliver—and how valuation, not just accuracy, is the key to turning models into measurable business outcomes.
“Shouldn’t a great model be a sure bet to deploy?”
Powerful breakdown of the valuation gap in predictive AI. The point about decision boundaries carrying more weight than marginal accuracy gains is crucial for operations teams, yet gets burried under technical metrics. Making KPI tradeoffs interactive rather than static fixes the "silent failure" problem where projects stall becuase stakeholders can't quantify upside. The profit curve approach should be standard in every deployment workflow.
Levi Strauss’s AI Transformation: How a 175-Year-Old Brand Is Reinventing Itself for a DTC, Fan-First Future
Human and AI: A New Era of Shared Intelligence
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Fantastic breakdown of Levi's transformation. The AI superagent concept is really smart because it solves the context switching problem that kills producitivty in most enterprises. What's interesting tho is how they're betting on Azure Migrate as the foundation layer, not just a tool. Makes me wonder if the real bottleneck for most legacy brands isn't the AI itself but the infrastucture debt they're sitting on.
Breaking down Google's plan to Double AI Compute Every Six Months
A first‑principles teardown of Google’s Hypercomputer—chips, power, networking, memory, and models—and what actually has to be deleted, rebuilt, and scavenged to make the 6‑month doubling curve real.
Google’s AI infrastructure chief, Amin Vahdat, recently told employees that demand for AI services now requires doubling Google’s compute capacity every six months – aiming for a 1,000× increase in 5 years. This goal, presented at a November all-hands meeting, underscores an unprecedented scaling challenge. This rate of Exponential growth, far outpaces …
I'm just excited to see it happen
The SPAD concept is the most intresting part of this breakdown. Seperating prefill and decode workloads at the hardware level makes so much sense when you think about how different the computational profiles are. Most companies treat inference as one monolithic problem but Google splitting readers and writers into distinct physical architectures could be a huge efficiency win.
Stop Waiting for PMF: The Insider’s Playbook to Scaling AI Applications
We hosted a panel to discuss about PMF and Startup Growth topics. The panelists share great experiences and insights which can inspire you to grow your business.
Yesterday’s panel brought together the most effective minds in modern growth, and the consensus was clear: the prevailing myths of instant virality and singular-channel reliance are dead. True, scalable growth is a result of strategic engineering, founder-led authenticity, and an unyielding focus on user behavior.
2025 November "AI Evaluation" Digest
Hitting a wall? Seeing is all you need
The recent presentation of Google Gemini-3 has come with the usual combination of benchmark results cherrypicking, leaderboard reshuffling and lots of anecdotal evidence from early users. As any other model, Gemini-3 has been praised and criticised in almost equal terms. It will only be in the following weeks or months that we will be able to fully appr…
This digest is a masterclass in AI evaluation, especially the emphasis on modality confounders and construct validity. Emerging frameworks like BeTaL and RIDE show how much methodology shapes what we think AI can do.
I talk about the latest AI trends and insights. Do check out my Substack, I am sure you’ll find it very relevant and relatable.
AI Will Cause ‘Jobs Chaos’ - And It’s Coming Sooner Than You Think
Why the Next Wave of AI Will Reshape Your Career Faster Than You Expect
Imagine walking into your office one morning and realizing that much of what you do daily, the reports, the data crunching, the repetitive tasks, will soon be handled by an AI.
AI Will Cause ‘Jobs Chaos’, and It’s Coming Sooner Than You Think
The future of work won’t be automated, it will be scrambled. Here’s what the coming AI ‘jobs chaos’ really means for your career.
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Solid breakdown of the transformation-not-replacement framing. The four collaboration scenarios are usful for planning, but what really stands out is the 2028-29 timeline, thats way sooner than most organizations are preparing for. The hybrid skills emphasis is right but underplays how fast companies need to start piloting these workflows now to avoide the chaos later.
Interesting take! If Google has a secret AI toolbox, it could change the game for so many startups. But let’s not forget—transparency is key. The more we share, the more we innovate. Curious to see what they might unveil and how it could impact the industry!
Probably
📡🤖 Inside the Signal: How AI is Uncovering Hidden Legal Violations ⚖️🔍
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