As a trader, I had always doubted the possibilities for one to learn leverage trading & risk management without the pressure of real monetary losesπ€·πΏββοΈ. That mentality changed when I found out about Top trader on Ape Chain π§΅π @apecoin@Toptrader_xyz@ThankApe
GM CT βοΈ
Been away for a while, but weβre back. πͺ
Took some time off, reset, handled a few thingsβ¦ now itβs time to lock back in.
Let's get the progress started π―
GM CT βοΈ
New day, new block, new opportunity.
Keep the mind sharp, stay curious, and keep shipping.
The timeline will chase narratives, weβll chase knowledge. π§ οΏ½οΏ½οΏ½
Have a productive day, chads. π€
GM CT βοΈ
New day, new block, new opportunity.
Keep the mind sharp, stay curious, and keep shipping.
The timeline will chase narratives, weβll chase knowledge. π§ π
Have a productive day, chads. π€
Every mainstream AI chatbot keeps a log of what you asked it, and decides what you're allowed to ask in the first place.
Day 21 of my AI & Web3 tool sprint looks at the protocol betting people want the opposite. ππ€
Tool: Venice AI @AskVenice β a privacy-first AI platform founded by Erik Voorhees (ShapeShift) and Jesse Proudman, positioned as a private, unrestricted alternative to ChatGPT.
Routes prompts across 200+ open-source and proprietary models for text, image, video, and audio through one interface.
The privacy architecture: prompts hit an encrypted proxy that strips identifying data before reaching inference providers, chat data stays in your browser, not their servers. They've since added TEE and end-to-end encryption modes, hardware-attested and independently verifiable, not just a promise in the terms of service.
The token layer: VVV isn't a payment token, it's an access key. Stake it, and you get a daily pro-rata share of Venice's total inference capacity through a second token, DIEM, where 1 DIEM equals $1 of API credit, in perpetuity. Heavy users effectively own their compute instead of renting it per request.
The scale: raised $65M in July 2026 at a $1B valuation, crossed 3 million users, no presale, no VC token allocation, self-funded until this raise.
My Honest Review π
The privacy engineering here is genuinely serious, not just marketing copy, hardware-attested verification is a real technical commitment most "private AI" products don't bother with. But "uncensored" is a double-edged sword by design, security researchers have flagged Venice as a route to generating content mainstream labs block for real safety reasons. That's not a hypothetical risk, it's the direct tradeoff of the entire premise.
My Take π§
Privacy and safety guardrails aren't the same conversation, even though they get bundled together constantly. Venice is proof that you can solve one seriously (verifiable, hardware-attested privacy) while the other stays genuinely unresolved. Worth understanding both halves before deciding which side of that tradeoff you're comfortable with.
Freedom and safety were never going to be free of tension. Venice just made that tension impossible to ignore. π―
Every mainstream AI chatbot keeps a log of what you asked it, and decides what you're allowed to ask in the first place.
Day 21 of my AI & Web3 tool sprint looks at the protocol betting people want the opposite. ππ€
Tool: Venice AI @AskVenice β a privacy-first AI platform founded by Erik Voorhees (ShapeShift) and Jesse Proudman, positioned as a private, unrestricted alternative to ChatGPT.
Routes prompts across 200+ open-source and proprietary models for text, image, video, and audio through one interface.
The privacy architecture: prompts hit an encrypted proxy that strips identifying data before reaching inference providers, chat data stays in your browser, not their servers. They've since added TEE and end-to-end encryption modes, hardware-attested and independently verifiable, not just a promise in the terms of service.
The token layer: VVV isn't a payment token, it's an access key. Stake it, and you get a daily pro-rata share of Venice's total inference capacity through a second token, DIEM, where 1 DIEM equals $1 of API credit, in perpetuity. Heavy users effectively own their compute instead of renting it per request.
The scale: raised $65M in July 2026 at a $1B valuation, crossed 3 million users, no presale, no VC token allocation, self-funded until this raise.
My Honest Review π
The privacy engineering here is genuinely serious, not just marketing copy, hardware-attested verification is a real technical commitment most "private AI" products don't bother with. But "uncensored" is a double-edged sword by design, security researchers have flagged Venice as a route to generating content mainstream labs block for real safety reasons. That's not a hypothetical risk, it's the direct tradeoff of the entire premise.
My Take π§
Privacy and safety guardrails aren't the same conversation, even though they get bundled together constantly. Venice is proof that you can solve one seriously (verifiable, hardware-attested privacy) while the other stays genuinely unresolved. Worth understanding both halves before deciding which side of that tradeoff you're comfortable with.
Freedom and safety were never going to be free of tension. Venice just made that tension impossible to ignore. π―
Training a frontier AI model has always meant one thing: tens of thousands of GPUs, humming in unison, inside a single data center, owned by a company with a market cap bigger than most countries.
Day 20 of my AI & Web3 tool sprint looks at the team trying to break that requirement entirely. π§ βοΈ
Tool: Prime Intellect @PrimeIntellect ; a decentralized platform that aggregates GPU compute from around the globe and turns it into a unified network for training, evaluating, and deploying large language models. Founded by Vincent Weisser and Johannes Hagemann.
What makes this different from just "another compute marketplace": Prime Intellect has actually trained models at meaningful scale, not just theorized about it. INTELLECT-2, a 32B-parameter model, was trained across globally distributed GPUs, no single data center required, and released fully open.
The stack:
1οΈβ£ GPU Marketplace: Rent compute on demand, from a single card to 256+ GPU clusters, aggregated across dozens of datacenters worldwide.
2οΈβ£ Environments Hub: 2,500+ open-source reinforcement-learning environments to train and evaluate models against.
3οΈβ£ Hosted Training & Lab: The full post-training pipeline, RL, evaluation, deployment, without needing to own or manage a GPU cluster yourself.
The backing: $130M Series A in July 2026 at a $1B valuation, led by Radical Ventures, with Nvidia Ventures, Intel Capital, and Dell Technologies Capital all participating. Over $150M raised in under two years.
My Honest Review π
This is the piece that was missing from everything I've covered so far. Compute access (Day 19) means nothing if you still can't actually train a competitive model on it. Prime Intellect isn't promising decentralized training works, they've already shipped proof, twice.
My Take π§
The gap between open-source and closed frontier labs has mostly been a compute-and-coordination gap, not a talent gap. When training infrastructure itself becomes decentralized and accessible, that gap stops being a moat and starts being a temporary head start.
The frontier lab moat was never intelligence. It was always infrastructure. That's what's actually up for grabs now.
Every mainstream AI chatbot keeps a log of what you asked it, and decides what you're allowed to ask in the first place.
Day 21 of my AI & Web3 tool sprint looks at the protocol betting people want the opposite. ππ€
Tool: Venice AI @AskVenice β a privacy-first AI platform founded by Erik Voorhees (ShapeShift) and Jesse Proudman, positioned as a private, unrestricted alternative to ChatGPT.
Routes prompts across 200+ open-source and proprietary models for text, image, video, and audio through one interface.
The privacy architecture: prompts hit an encrypted proxy that strips identifying data before reaching inference providers, chat data stays in your browser, not their servers. They've since added TEE and end-to-end encryption modes, hardware-attested and independently verifiable, not just a promise in the terms of service.
The token layer: VVV isn't a payment token, it's an access key. Stake it, and you get a daily pro-rata share of Venice's total inference capacity through a second token, DIEM, where 1 DIEM equals $1 of API credit, in perpetuity. Heavy users effectively own their compute instead of renting it per request.
The scale: raised $65M in July 2026 at a $1B valuation, crossed 3 million users, no presale, no VC token allocation, self-funded until this raise.
My Honest Review π
The privacy engineering here is genuinely serious, not just marketing copy, hardware-attested verification is a real technical commitment most "private AI" products don't bother with. But "uncensored" is a double-edged sword by design, security researchers have flagged Venice as a route to generating content mainstream labs block for real safety reasons. That's not a hypothetical risk, it's the direct tradeoff of the entire premise.
My Take π§
Privacy and safety guardrails aren't the same conversation, even though they get bundled together constantly. Venice is proof that you can solve one seriously (verifiable, hardware-attested privacy) while the other stays genuinely unresolved. Worth understanding both halves before deciding which side of that tradeoff you're comfortable with.
Freedom and safety were never going to be free of tension. Venice just made that tension impossible to ignore. π―
GM CT βοΈ
Some of you are grinding charts, some are grinding narratives.
Me? Iβm grinding bubbles. ππ«§
Itβs the weekend, the market can wait a little. π
Touch grass, recharge and enjoy the day.
Have a productive day, chads. π€π