
david q
4K posts

david q
@Davidgek97Q
web3 native, solidity developer, btc maxi







BOOM! CHINESE PAPER PROVED MY AI GARAGE SYSTEM! OFFLINE HIGH PROTEIN TRAINING DATA BEATS TEXT OFF THE INTERNET FOR AI TRAINING! China knows now in the US, no one listens. Paper: Scalable Visual Pretraining Challenges Text-Only Dominance for Richer Language Intelligence A new paper demonstrates that unsupervised visual pretraining directly on visual documents (figures, equations, layouts) outperforms text-only extraction on the same corpora across backbones and benchmarks. Systematic study shows visual cues provide scalable pathways to foundation model intelligence beyond plain text. Text extraction is lossy by design. When you flatten a scientific paper, a technical manual, a lab notebook, or a dense PDF into plain text, you destroy the very signals that carry meaning: the diagram that shows the circuit or the molecular structure, the equation rendered in proper notation, the table layout that reveals relationships at a glance, the handwritten marginalia that captures insight, the visual hierarchy that tells you what matters most. The paper’s authors didn’t just theorize this. They ran the controlled experiment: same source documents, two paths — one stripped to text, one kept visually intact — and unsupervised visual pretraining won… Every time. This is not “multimodal icing on the cake.” This is fundamental. Visual structure is part of the intelligence. The default text-only paradigm in LLM pretraining is proven wrong. High-Protein vs. Internet Empty Calories Let’s be brutally clear: Internet text corpora are mostly empty calories. They are diluted by repetition, poisoned by SEO garbage, stripped of diagrams and equations, full of confident-sounding hallucinations, and optimized for engagement rather than truth or depth. Quantity at the expense of quality and structure. My offline personal archives are high-protein. Every document I train AI on has context I actually care about. The visual elements are preserved. The relationships are explicit. The signal-to-noise ratio is orders of magnitude higher because it was curated by a human with skin in the game over decades. Training local models on this kind of data produces something fundamentally different: grounded, less sycophantic, more useful, more aligned with actual human intent and wisdom. This is the data foundation for the agents and soon robots that function as true extensions of individual intelligence rather than generic corporate parrots. The paper shows unsupervised visual pretraining is not only better it is scalable. That opens the door for individuals and small teams to do what only hyperscalers could do before. What this means in practice: • Stop treating your personal PDFs, scanned lab notebooks, technical diagrams, and structured notes as “just files.” Treat them as premium training fuel. • Preserve visual structure. Do not blindly OCR everything into plain text. • Build (or continue building) your own ontology/taxonomy relational layer on top of the visual documents. • Use this corpus for local adaptation, continued pretraining, or retrieval-augmented workflows. • The resulting models will be smaller, more capable in your specific domains, more trustworthy, and far less likely to regurgitate web slop. I have been running versions of this system in my garage lab for years — combining personal visual/structured data with local inference, voice synthesis, and agent frameworks. The paper is not telling me something new. It is giving the broader world permission to stop doing it the dumb, lossy, internet-dependent way. Well, now some folks in China and NO large US AI company know, what you and I have known for about 4 years here. This is one of my reasons I promote OFFLINE HIGH PROTEIN TRAINING DATA. US AI companies, a question: Where would you be now if you worked with me and listened? What do you folks think? • Link: arxiv.org/abs/2607.09657











My yesterday recap - got 46 followers - replies 441 - impression up 90% - engagement down 5.4% - sleep 4:30 hrs Not a perfect night well am back with a new banger be ready!



1 in 5 NYC public school students are Black, but at Stuy - our most prestigious high school - 3 of ~800 incoming Freshmen are Black. We urgently need state legislation to modify the admissions process. A single test should never be only factor deciding who gets in & who doesn’t.

“I have had dyslexia and reading issues my entire life. I don’t know how I never heard of your RSVP reading system. I am not at 400 words per minute. I can read like I never could before”—CEO Startup company Thank you. It is not designed for dyslexia but I tested it in the 1990s on folks that had it and the lived it.











Every BIG12 team that is playing Tech has a higher SOS than Tech, but our teams should be ashamed?



A brand-new Variational UI is now live, featuring reworks of each page of the app and an improved mobile experience with PWA support.

