TL;DR: AI kutije dolaze.Možemo izgraditi vlastite ili pustiti Big Tech da ih izgradi za nas. TL;DR: Remember when Richard Hendricks kept ranting about “The Box” and everyone thought he’d lost it? Well, turns out the crazy bastard was right. We just got the timeline wrong. In HBO’s Silicon Valley, “The Box” represented the choice between decentralized platforms that empower users versus centralized hardware that locks them into corporate ecosystems. The Box isn’t some magical compression algorithm. It’s edge AI hardware that can run the models that needed Google’s data centers two years ago. And it’s shipping right now. The Pattern That Should Terrify You Amazon Echo shows up. “It’s just a speaker,” we said. 2014: Google and Apple follow with their own spy cylinders. 2018: ChatGPT breaks the internet. Everyone loses their minds. 2022: AMD ships consumer chips with 50 TOPS. NVIDIA Jetson hits 275 TOPS for $2,400. 2025: 2027: Canalys predviđa da će 60% novih računala biti sposobno za umjetnu inteligenciju, u usporedbi s 20% do 2024. godine. Taj rok 2027. godine je mjesto gdje odlučujemo da li obitelji posjeduju svoju umjetnu inteligenciju ili je zauvijek iznajmljuju od Big Tech-a. Evo što je upravo promijenilo sve Those models that needed massive cloud infrastructure? Their scaled-down but practical versions are running on hardware you can actually buy — if you know where to look: Consumer/Prosumer Options: 128GB unified memory, $2,800, 45-120W - the only prosumer device that can run Llama 70B locally at 4-8 tokens/sec AMD Ryzen AI Max+ 395: 24GB VRAM, $1,500, 350W - powerful but memory-limited, can't handle 70B models NVIDIA RTX 4090: NVIDIA Jetson AGX Orin: 64GB RAM-a, 2.400 dolara, 15-60W - odličan za edge AI, ali udara na zid s velikim modelima Enterprise-Only Solutions: NVIDIA H100/H200: 80-192GB VRAM, $ 20,000+, 350-1000W - može pokrenuti bilo koji model, ali zahtijeva infrastrukturu poslužitelja Intel Gaudi 2/3: 96 GB memorije, $ 5-8k, 350-600W - konkurentne performanse, ali poduzetničke cijene i zahtjevi za snagom Reality Check: AMD Ryzen AI Max+ 395 is currently the prosumer device that can run Llama 70B locally. NVIDIA’s consumer GPUs max out at 24GB (not enough), their enterprise cards cost $20,000+, and even the Jetson AGX Orin hits a 64GB wall. Intel’s Gaudi chips work but require server infrastructure and enterprise pricing. only AMD achieved this through unified memory architecture — up to 128GB LPDDR5X shared between CPU, GPU, and NPU in a quiet, energy-efficient package that fits in a desktop or laptop. The Linux Desktop Moment (But Worse) Windows je prvi stigao, mrežni efekti su se pojavili, a kada je Linux bio spreman za normije, svi su već bili zaključani u Microsoftov ekosustav. We’re at that exact same moment with AI. Except this time the timeline is 2–3 years, not decades, and the stakes are your family’s intelligence, not just your file manager. Once your family’s AI is integrated into Apple/Google/Amazon’s ecosystem, switching means rebuilding your entire digital life. In Ready Player One, Wade Watts dreams of upgrading from his outdated hardware to access better virtual worlds, but he can’t afford the good stuff. We’re facing the same choice with AI — except the stakes aren’t entertainment access, they’re intellectual sovereignty and privacy. Zašto ovaj put stvarno možemo pobijediti Potrošački hardver sada odgovara sirovom izračunu GPU-ova u oblaku od prije samo dvije godine.Možete pokrenuti sposobne lokalne modele za analizu dokumenata, automatizaciju pozadine i rutinske zadatke AI-a - ali još uvijek nismo na brzinama ChatGPT-a u stvarnom vremenu. The Hardware Gap Is Closing (But Not Closed): Here’s the acceleration that matters: hardware costs are dropping 30% annually while energy efficiency improves 40% per year. New chips are delivering 2.8–3x performance gains over previous generations every 12–18 months — faster than Moore’s Law. What costs $2,800 today will cost $800-$1,200 within 18–24 months. Od zabrane TikTok-a do ChatGPT-ovih kontroverzi o skrapavanju podataka, ljudi konačno shvaćaju da njihovi podaci nisu sigurni. naslovi "AI trening na vašim razgovorima" pogodili su drugačije kada se vaša inteligencija koristi za obuku vaše zamjene. Privacy Isn’t Abstract Anymore: Meta (Llama), Mistral, DeepSeek, Alibaba (Qwen) are releasing capable models that run locally. You can now run decent AI without it tattling to corporate headquarters. Models Are Becoming Commodities: Čista tehnička stvarnost What Can You Actually Do With 4–8 Tokens Per Second? Budimo iskreni - to još nije za redovite obitelji. Na 4-8 žetona po sekundi, ne dobivate glatko ChatGPT iskustvo koje većina ljudi očekuje. To je trenutačno za tehnološke entuzijaste koji žele eksperimentirati s lokalnom AI-om, programerima koji grade aplikacije i korisnicima koji su svjesni privatnosti koji su spremni trgovati udobnošću za suverenitet podataka. But here’s why this matters: by the time edge AI is family-ready, we need the infrastructure, software ecosystem, and community knowledge to exist. Someone has to build the foundation now, or families will only have Big Tech’s options when they’re ready to adopt. The Current Limitations: Razlika u uspješnosti: Lokalni modeli još uvijek zaostaju za GPT-4o/Claude u složenom razmatranju i multi-modalnim zadatcima You’re responsible for security patches, model updates, and hardware failures Maintenance Burden: Running AI 24/7 means dealing with 45–120W power consumption, heat generation, and potential fan noise Power and Heat: Softverski ekosustav: Dok se projekti kao što je Ollama brzo poboljšavaju, alatizacija još uvijek ima grubih rubova To još nije plug-and-play.To je više poput "kompetentnog DIY entuzijasta s brojnim vikendima i puno strpljenja." What You Can Actually Do Right Now If you’re technically minded: Start experimenting with Ollama, local models, and edge AI hardware Document what works (and what doesn’t) for others Pridružite se zajednicama koje grade ovu stvar: r/selfhosted, r/homelab, r/LocalLLaMA If you’re business-minded: Postoji ekonomija usluga koja se pojavljuje oko edge AI postavljanja i održavanja Families want digital sovereignty but don’t know how to build it If you just care about digital freedom: Support projects building alternatives Ne kupujte prvu subvencioniranu AI kutiju koja plovi Podijelite ovo s ljudima koji se sjećaju kada je internet bio decentraliziran Cloud vs. Edge: The Real Numbers Cloud AI (ChatGPT Plus, Claude Pro): Upfront cost: $0 Annual cost: $240-$600 ($20-50/month) 3-year total: $720-$1,800 Data privacy: Your conversations leave home and train corporate models Edge AI (DIY Setup): Cijena unaprijed: 2.500 USD (AMD Ryzen AI Max+ sustav) Annual cost: $100-$200 (power, maintenance) 3-year total: $2,800-$3,100 Data privacy: Everything stays local The math works: $2,500 one-time hardware cost versus $20–50/month subscriptions forever. But the real value is privacy. We’re at the 1993 Moment In 1993, you could still choose a decentralized internet. By 2003, the platforms had won. U 2025, još uvijek možete odabrati suverenitet AI-a. Do 2027. godine, nekoliko industrijskih predviđanja projektiraju veliku preokretnu točku: , Ekološki sustavi će biti zatvoreni. 60% of new PCs will be AI-capable AI računalo će rasti 10x globalno Pied Piperova vizija decentralizirane tehnologije koja služi korisnicima umjesto platformama konačno je tehnički moguća. Ali prozori ne ostaju otvoreni zauvijek. Donja linija The Box is coming. The question is: will you build it, or will Big Tech build it for you? Sljedeće 2-3 godine će odrediti da li obitelji posjeduju AI ili ga iznajmljuju zauvijek.Hardware postoji.Modeli su dostupni.Jedino što nedostaje je odluka o djelovanju. , with i . The hardware exists. The models are available. The market needs it. The only question is: who controls it? Industry analysts project that by 2027, AI will be integrated into nearly all business software globally available AI compute expected to grow 10x the AI market approaching $1 trillion What do you think? Are we building the future or just cosplaying as digital freedom fighters?
