G.W. Jackston

@andyyy Venice to 3 figures, near to 2 figures, send it

I really love to see $vvv when OI is at equal levels but price is much higher. Spot holders are fort knox.

$VVV at $40-60M right now, adding almost $0.5M ARR in a day, target $250M ARR by @YanLiberman at this growth rate. $NEAR doing $32M+ in intents revenue at $40m inflation, almost deflationary -- growth should start increasing w/ confidential intents and agent onboarding. $HYPE almost $1b fees last year, $300M+ this year. also we're getting CLARITY act, war situation getting better, oil dropping, law to legalize onchain stock trading, what is that guy on??

@VeniceAiPro Seems undervalued $VVV

Anthropic: $2,000,000,000,000+ so $VVV

$VVV "We don’t need to produce our own models. . . Hundreds of millions of dollars in cost that we avoid completely." - @ErikVoorhees Not enough has been theorized on this point. The AI industry’s next phase may be decided less by who builds the smartest model and more by who can afford to keep building them. Training frontier models has become extraordinarily expensive. GPT-4-class systems cost an estimated $78–100 million in compute alone. Newer efforts are pushing well into the hundreds of millions, with credible projections that leading training runs will exceed $1 billion within a couple of years. These are not one-time costs — they recur as labs chase incremental gains. @AskVenice operates with a structurally different cost profile. It does not train its own foundational models. It routes users to leading open-source models while adding privacy protections, uncensored outputs, and decentralized access via its API and VVV token. By skipping the training phase entirely, Venice avoids the hundreds of millions in upfront capital outlays that define the current arms race. That is not a minor efficiency — it is a fundamentally different business model. Major labs illustrate the pressure. OpenAI has reported multi-billion-dollar annual losses, with training and inference compute representing the largest drivers. As usage scales and models grow larger, both the one-time training spend and the ongoing cost of serving users rise sharply. This creates a difficult dynamic: to remain competitive on raw capability, companies must keep investing heavily. Those with the deepest pockets or strongest corporate backing are best positioned to sustain the pace. Others face mounting strain on their balance sheets. The result is something of a war of attrition. Continuous improvement requires continuous heavy capital deployment. In a post-hype environment where investors increasingly demand clearer paths to profitability, the ability to generate strong returns on these escalating investments will matter more than it did during the initial land grab. Venice’s approach raises a strategic question worth examining: in a market where model development costs keep rising, does the durable advantage shift toward those who use the best available models efficiently rather than those who must continually reinvent them? By focusing on privacy, censorship resistance, agent-friendly infrastructure, and token-aligned decentralized compute, Venice is building its position in the distribution and experience layer — not the raw model layer. That positioning may prove resilient if capital becomes more discerning or if open models continue closing performance gaps. The deeper issue is capital allocation in AI. Enormous sums are flowing into training ever-larger systems. Yet the companies that ultimately capture the most value may not be the ones bearing the heaviest development costs. How this plays out — whether through consolidation, specialization, or a shift in what users and developers actually pay for — deserves more rigorous analysis than it has received so far. Maybe @YanLiberman @Delphi_Digital or @nikshepsvn can further explore this deep dive and the implications? What frameworks are you using to think about sustainable economics in AI? From the outside, Venice seems well positioned to navigate the path ahead.

$VVV 1W Parabolic Curve

$VVV 1D Once the Green Resistance and 22.5 breaks the price will sling shot

If you’re posting about $VVV and aren’t using the product- do better. If you are using the product, don’t forget to tell your friends and family. The pitch is easy: - Venice doesn’t spy on you; chats not stored. Private - Venice offers Chat, Grok, Claude and other models all on 1 place. No need to platform hop or pigeonhole yourself - Comparable/cheaper monthly pricing

🧪 $DIEM = Elixir of Immortality (for AI Agents)

@JonShapeShift @AskVenice Can you remind us: is $DIEM tokenized inference?

The thesis of @AskVenice: - privacy is critically important - don’t censor the thoughts of adults wherever possible and actively remove censorship where it can be done. - build a mass market app anyone can use - build useful crypto primitives with fundamentals $VVV and $DIEM.

I asked what % of total max supply daily emissions represent because the post claimed $MSTR and $ASST are buying “10x the new supply.” Daily new supply is ~0.002% of total max supply. The problem with anchoring to that number is that it’s so small that even big multiples don’t clearly show the scale of accumulation. At a combined ~$350M per day, $MSTR + $ASST would be buying roughly 1% of Bitcoin’s total max supply every ~45 days. That’s the more useful way to look at it.

Are you making an argument that if @saylor buys a half a million to a million Bitcoin over the next 2 years that it won't have impact on the price because there's other people that could sell? 😆 Oh and we'll have another having event. So at that time if purchases don't increase which I expect them to It would be 20x the new supply.

This retard is telling you that #Bitcoin is going to start it's drop towards $19,000 over the next few weeks, while $MSTR and $ASST are buying 10x the new supply and the government is working towards a Strategic Reserve and finalizing the Clarity Act. Moral of the story? Don't follow morons.

Keep it simple. Biggest narratives in crypto right now are Privacy and AI Venice $VVV has both narratives working in its favor $ZEC $NEAR

$VVV 6H Cup and Handle Formation Handle finishing Break Neck Line and the Fun Begins

🔥 snapshot from yesterday on @AskVenice: → $VVV ATH: $20.04 → daily Pro Sub burns ATH: $3,416 → daily new-signup revenue ATH: $34,358 (1,489 new subs) three ATHs, same day. the token is correcting ~13% intraday; the two on-chain prints remain on-chain. charts: @venicestats

$VVV just broke through its recent ATH's, reaching over $20/token -- you might have a question -- is this overvalued? to that i say, just look at the numbers the math never lies

@jordanurbs Keynes v. Hayek