Daniel Craig

@shzhv13 It’s useful, but it also simplified a much bigger and deeper ecosystem.

ChatGPT is the most overrated AI tool. I say this as someone building AI infrastructure. It's useful. But it's neural networks that existed for decades. The hype makes people think AI started in 2022. It didn't.

@FARLabsAI Definitely something worth watching closely over the next few years

As software value moves toward agents, demand moves toward inference. The winners will be the networks that make AI faster, cheaper, and usable in real time.

@shzhv13 How early should teams realistically invest in strong verification systems?

@FARLabsAI There’s a clear emphasis on long-term positioning over quick wins

DLSS 5 is a perfect example of why AI inference is about to explode in gaming.

@shzhv13 Definitely adding this to my list of AI tools to experiment with.

Found something interesting on GitHub today. It's a repo that lets you build an AI agency. But not the usual way where one AI tries to do everything and ends up being mediocre at all of it. This one's different. It's structured like an actual company with departments and specialized roles. You get 54 AI agents split across different teams: - Engineering has 7 (frontend, backend, mobile, AI, DevOps, prototyping, senior dev) - Design has 7 (UI/UX, research, architecture, branding, visual work, image generation) - Marketing has 8 (growth, content, social platforms, app store optimization) - Product has 3 (sprint planning, trend research, feedback analysis) - Project management has 5 (production, coordination, operations, experiments) - Testing has 7 (QA, performance, API testing, quality checks) - Support has 6 (customer service, analytics, finance, legal, reporting) - Spatial computing has 6 (XR, VisionOS, WebXR, Metal, Vision Pro) - Specialized has 6 (orchestration, data, sales, distribution) Each agent focuses on one thing. They coordinate with each other to get work done. Got 10k+ stars in under a week. The concept makes sense to me. You wouldn't hire one person to handle engineering, design, marketing, and finance. So why build AI that way? Haven't tried it myself yet. Do your own research obviously. But worth playing around with it and seeing how it actually performs. github.com/msitarzewski/a… If nothing else, it's clear that people who experiment with tools like this early will have a serious edge.

@FARLabsAI Feels like we’re still just starting to understand the cognitive impact of games.

Centralized infrastructure limits what's possible. Every AI app runs through the same 3-5 cloud providers. When everyone builds on identical infrastructure, innovation converges. ❌ Same latency constraints ❌ Same scaling patterns ❌ Same cost structures ❌ Same geographic limitations ❌ Same architectural decisions ❌ Same bottlenecks. Distributed compute opens new design space.

@shzhv13 Those download numbers for Claude are impressive.

Anthropic refused $200M Pentagon deal Thursday. OpenAI took it Friday. 48 hours later: OpenAI: → ChatGPT uninstalls up 295% → 1-star reviews surged 775% → Downloads fell 13% Anthropic: → Claude hit #1 App Store → 149K daily downloads → Record-breaking signups all week Anthropic got banned from federal contracts. The public made them #1 anyway. Lesson here is stay ethical and hold to your principles. You will never lose out.

@shzhv13 Feels like we’re wtching the early formation of the AI infrastructure layer in real time.

🤯Nvidia is giving away a billion dollar AI product for free. Here's the play: Free platform → requires massive compute → Nvidia sells the compute. Give away the razor. Sell the blades. The AI agent market hit $10.9B in 2026. 40% of enterprise apps will embed agents by year-end (up from 5% last year). 85% of companies already use AI agents. 93% plan full deployment within 2 years. Nvidia isn't competing on products anymore. They're controlling the infrastructure everyone else has to rent. Training chips → inference chips → deployment platforms. Own the bottleneck. Make everything else free. Classic vertical integration disguised as open source. The pattern is simple: when you control multiple layers of the stack, each one makes the others more valuable. The companies that win won't have the best product. They'll own the stack everyone else pays to use. NemoClaw likely launches next week at GTC. Watch what happens.

@FARLabsAI The threat landscape definitely shifts when there’s no single endpoint

24K accounts generating 16M queries shows the challenge of behavioral detection in centralized systems. Distributed inference networks create different security models - when compute is spread across participant nodes rather than centralized endpoints, the threat landscape shifts significantly. This is core to what we're building with FAR AI.

@Dizzaract The identity layer feels like the quiet backbone here.

Dizzaract is a full-cycle AI and gaming development studio. We operate as an interconnected ecosystem of products, not a single game or app. Dizzaract covers the entire value chain of digital entertainment and AI: IP Creation → Distribution → Infrastructure Powered by 80+ engineers, researchers, designers, and operators working across AI and gaming. Our teams build in weeks, not quarters. We prioritize execution and working systems over corporate complexity. Why We Exist: Dizzaract was formed around a simple observation: AI is becoming core infrastructure. Gaming is one of the largest digital ecosystems in the world. Yet identity is fragmented. Inference is expensive. Systems are not optimized for scale. We chose to build where those gaps intersect. A structured technology group operating across: - Original IP development - Gamer identity systems - AI infrastructure The goal is long-term efficiency and compounding leverage. How We're Built: Farcana | Our flagship gaming IP and universe A competitive PvP third-person shooter set in a Middle Eastern sci-fi universe with an aesthetic that doesn't exist anywhere else globally, reimagined in an alternative past-future timeline. GAMED | Our identity, data, and distribution platform The identity and economic layer for gamers that aggregates cross-platform gaming data and assets into a single intelligent dashboard. Gamers' digital lives are fragmented across Steam, Epic, PlayStation, App Store, and more. GAMED unifies them into one place that aggregates your full gaming legacy. FAR Labs | Our AI infrastructure FAR Labs is an AI-native product lab building infrastructure and AI as a Service (AIaS) systems. Our flagship product is FAR AI - cheaper, faster, and scalable AI inference based on distributed compute. FAR AI is a distributed network where gamers can connect their hardware to provide AI compute power. By distributing inference across consumer devices rather than relying on centralized data centers, we enable significantly more cost-effective and scalable AI infrastructure that can serve any AI application globally. The Flywheel: • Farcana → original IP and competitive play • GAMED → unified identity and data systems • FAR AI → AI infrastructure and AIaS systems Together, they create compounding leverage across the gaming and AI ecosystem. Our Advantage: - Full-cycle control (IP → Distribution → Infrastructure) - Cultural uniqueness (Middle East-born global IP) - AI-native architecture - Products that reinforce each other - An 80+ person team building for the next 10–20 years from our base in the MENA region We're not just making games. We're building structured systems where gaming and AI infrastructure intersect. Creating worlds that deserve being experienced. This is Dizzaract.

@shzhv13 Infra plays are brutal but defensible if you execute

PREDICTION: Only 3 types of AI companies will survive the next 2 years. I've watched hundreds fail because they chose the wrong path. The hardware crisis made this brutally clear: Type 1 → Does ONE thing incredibly well (low compute, high value) Type 2 → Doesn't build models at all (uses APIs, owns distribution) Type 3 → Sells infrastructure to the other two (picks & shovels play) Everyone else? Stuck in the middle with expensive custom models and no differentiation. The worst place to be: High costs, low moat.

@shzhv13 Most people underestimate how hard real-time coordination is

🚨 China just showcased humanoid robots doing martial arts on national TV 451,700 robotics companies $932B in capital 28,000 units projected for 2026 Everyone's amazed by the choreography I'm looking at what they CAN'T do: ❌ Adapt to new scenarios ❌ Improvise without training ❌ Coordinate in unpredictable environments These robots trained the same routine thousands of times. Perfect execution in controlled settings. But real breakthrough = multi-agent systems that adapt in real-time without scripts That's the gap between demos and deployment Why competitive gaming matters: → Unpredictable interactions → Real-time adaptation required → Multiple agents, zero scripts → Every match is different Not entertainment infrastructure. AI infrastructure. At @Dizzaract, we're creating worlds that solve this - environments where adaptive multi-agent AI gets developed, tested, and deployed at scale.

@FARLabsAI Real compute is the part people underestimate

This is exactly what we're building toward... Multi-agent AI systems need distributed infrastructure that can scale without centralized bottlenecks. FAR AI runs open-source models on a distributed compute network - giving developers the foundation to build the next generation of AI agents. Open source. Real compute. Built for what's coming.

@shzhv13 Good reminder that belief is demonstrated, not declared

Let's be honest: If you're building AI but not using it internally, you don't believe in your product. Anthropic engineers manage 3-8 Claude instances each to build Claude. Meanwhile AI startups: • Build automation with manual ops • Sell AI agents while hiring for every role • Pitch "10x" while working 80hr weeks Before you sell it, use it: → 2-week internal beta for every feature → Document internal use cases (real > demos) → Build for your own pain first → Founders must use it 1hr daily → <80% team adoption = no PMF The best AI products are built by teams that can't live without their own AI.

@shzhv13 Been saying this about OpenAI for a year now

The bigger they got, the more they compromised: Anthropic - Founded as the "safety-first" AI company. Their top safety researcher just quit because even they "constantly face pressures to set aside what matters most." OpenAI - Started as a nonprofit to "benefit humanity." Now they're for-profit with a $500B valuation, Microsoft owns 27%, and they're running ads after Altman said that was "last resort." Google - Had "Don't be evil" as their motto. Removed it after taking military contracts. 4,000 employees protested. Twelve quit. Meta - Promised to protect elections and combat misinformation. Shut down the research tool tracking it three months before a presidential election. It seems every "ethical" tech company eventually compromises. Market pressure always wins. Scale forces compromise. Plan accordingly.

@shzhv13 Would love to know how long your deep work blocks usually are?

The Deep Work Protocol: • No distractions before critical decisions are made • Block uninterrupted time for technical work • Meetings happen after the builder's work is done • One priority. Execute it fully. Protection of focus is protection of output. The best builders I know treat their morning hours like sacred ground. Everything else negotiates around it.

@shzhv13 The arrow to build sustainably is doing a lot of work

You can just build things, and you should.... Just think about costs early: real usage often means minimum of $1k–$20k+/mo on APIs or GPUs. Plan ahead, think of the costs → build sustainably.

@FARLabsAI Polygon to BNB is a big move 🔥

⏳ONLY 2 DAYS LEFT. Migrate your tokens now. February 11th is approaching fast...

@FARLabsAI Curious how competitive this usually gets

FAR Trivia Hour – Tomorrow (Saturday) at 5pm UTC Test your knowledge of FAR's technology, ecosystem, and roadmap. Rewards await those who demonstrate the deepest understanding. Preparation tip: Review FAR's interactive whitepaper for a comprehensive overview of our technology and ecosystem. → wp.farlabs.ai Come prepared. Bring your expertise. Join us: t.me/FarLabsAI

@shzhv13 Good reminder of what actually endures

Speed creates momentum. Systems create compounding. One gives you a good month. The other gives you a good decade.