ALIVE: Autonomously Compound Intelligence and Capital

TL;DR

Alphakek presents ALIVE, an AI protocol that turns onchain markets into training arenas that spawn entire AI ecosystems (“Brains”) you can create, trade, monetize, and own.

ALIVE (Adaptive Learning In Verifiable Environments) is a new AI training paradigm that combines decentralized markets, verifiable AI, and knowledge discovery into a single, permissionless system, enabling:

• Previously impossible revenue streams
• Unique value-creation mechanisms
• Tools for potential unicorn-level discoveries

ALIVE Brains are specialized AI ecosystems that earn and evolve around their singular, focused purpose or mission. Brains learn directly from onchain activity: every bet, trade, and interaction in their markets becomes an AI training signal that makes them more valuable over time.

Think of each Brain as a “new internet” with its own:

• Asset layer: tokens, prediction markets, stablecoins, LP shares, NFTs
• Cashflows: trading fees, PM fees, yield, spreads, subscription payments, API usage
• Content & interfaces: frontends, dashboards, agents, bots, terminals, feeds
• Evolving intelligence core: models, tools, workflows that train on the flow inside that environment

Inside, ALIVE is a novel type of RL/EA environment:

• You can train policies that operate inside a Brain (agents, routers, research tools)
• You can train reward models that learn to score rollouts from onchain outcomes
• You can use traditional RL (GRPO‑style) or an evolutionary algorithm, where the advantage/fitness is built from ALIVE’s market-aligned reward signal instead of a hand‑crafted proxy
• You can generate synthetic datasets for SFT using rejection sampling
• And much more - we're just scratching the surface

Crypto is already burning trillions in speculative flows; those flows should build your AI ecosystem, not someone else’s.

Add any financial primitive to ALIVE - tokens/AMMs, prediction markets, stablecoins, etc. The primitives then generate high-fidelity data with every verifiable (onchain) action, and ALIVE protocol compounds this knowledge.

This high-fidelity data generates additional value for any financial primitive it's connected to and ALIVE captures some of that value as a protocol fee. The fee is used to automatically buy back $AIKEK.

Alphakek was invited by NVIDIA to present its AI engine Fractal at GTC 2025. CoinGecko, Pudgy Penguins, Arweave, and many other leading companies use Alphakek's AI platform. However, ALIVE is Alphakek's most significant development to date, bigger than all previous combined.

What is ALIVE

ALIVE protocol makes AI training and agentic exploration tradable onchain, with capital efficiency serving as a reward metric for AI to maximize.

It makes previously unverifiable and 'hard-to-verify' tasks easy to verify, unlocks multiple new ways to evolve personalized, efficient, and market-aligned AI, and changes how decentralized markets generate value.

$$\begin{CD} AI @>rollouts>> Markets \\ @AevolutionAA @VVpriceV \\ Signal @= Discovery \end{CD}$$

$$\text{ALIVE reward modeling: rollouts are tradable and verified by the price action.} $$

The Flywheel

Markets as Feedback

ALIVE wraps AI rollouts into tradable financial primitives and uses the free market and price discovery as quantifiable feedback. This feedback is then used to evolve the AI model, thus creating a feedback loop: ALIVE AI learns to maximize the capital efficiency of the primitives it's integrated with.

Protocol Fees

A small protocol fee is applied to every trade: it prevents Sybil attacks on AI rollouts, supports the GPU infrastructure for each AI model, captures revenue for Brains and the $AIKEK token, and, in some cases, incentivizes builders. Therefore, maximizing capital efficiency also maximizes protocol revenue, thus aligning the goals of ALIVE builders, $AIKEK holders, and AI models themselves.

The resulting AI model becomes perfectly aligned with the needs and preferences of market participants. Participants who identify high-quality rollouts during price discovery can secure the most profit.

From Price Action to Intelligence Markets

As ALIVE accumulates more verifiable, high-fidelity data from price action, the resulting models become increasingly advanced and aligned with the markets. Those models enable Intelligence Markets:

1. Onchain flows go through ALIVE-enabled primitives:
   1. Prediction and futarchy markets
   2. Tokens and AMMs
   3. Stablecoin rails, structured products, and other surfaces can live within a Brain environment
2. Every interaction creates:
   1. Fees - protocol + LP + environment
   2. Labeled events - who bet what, when, at what price, with what outcome
3. Brains treat these markets as training arenas, asking:
   1. Which questions attracted serious size?
   2. Which flows preceded profitable outcomes?
   3. Which patterns of positioning correlate with future states?
   4. Which market structures and fee curves kept people coming back?
4. Models inside each Brain evolve toward what the market rewards. They learn what actually matters in that vertical.
5. Builders and protocols plug those Brains into tools:
   1. Agents, dashboards, bots, dapps, workflows
   2. Trading tools, consumer apps, pro terminals
   3. They pay via fees, rev-share, or explicit subscriptions

Long-Term Compounding & Superintelligence

ALIVE unlocks new forms of utility humans can’t yet fully foresee. It allows developers to:

• Create billions of custom AIs at effectively no cost
• Earn from training them
• Earn even more by building on top - while the protocol captures fees along the way

As state-of-the-art AI approaches the point where it can run autonomous scientific research, ALIVE will:

• Target the niches that markets need most
• Maximize the likelihood of high-priced discoveries
• Extend Peter Thiel’s idea of creative monopoly: “new products that benefit everybody and sustainable profits for the creator”

By solving one of the most difficult problems in AI training - hard-to-verify tasks - ALIVE may come closer to superintelligence than centralized corporations. Superintelligence will most strongly impact the markets it learns from. ALIVE is that learning environment.

Brain Environments

ALIVE could be used for directly training models via RL, for training reward models that are then used to train other models, or for generating high-quality synthetic data for mid-training and SFT. A Brain environment defines:

• A state space (prices, orderflow, positions, onchain events, offchain research, etc.)
• An action space (what to trade, what to ask, what to publish, what tools to call)
• And a reward that’s ultimately grounded in economic outcomes (PnL, fees, liquidity, user retention, whatever that Brain cares about)

In turn, ALIVE markets generate:

• Dense trajectories of (state, action, outcome)
• With labels backed by capital at risk rather than synthetic thumbs‑up

“Even with Meta’s multibillion-dollar investment, several sources said that researchers in TBD Labs see Scale AI’s data as low quality [...]” - TechCrunch, 2025

Integrating ALIVE

Integrating ALIVE into existing RL pipelines is extremely simple. Let's take GRPO by DeepSeek AI as an example. The loss function objective is to maximize the advantage \(\hat{A}_{i}\) for a given group of outputs \({o_1, o_2, \cdots, o_G}\):

$$\mathcal{L}_{\text{GRPO}}(\theta) = -\frac{1}{\sum_{i=1}^G |o_i|} \sum_{i=1}^G \sum_{t=1}^{|o_i|} \left[ \frac{\pi_\theta(o_{i,t} \mid q, o_{i,< t})}{\left[\pi_\theta(o_{i,t} \mid q, o_{i,< t})\right]_{\text{no grad}}} \hat{A}_{i,t} - \beta \mathbb{D}_{\text{KL}}\left[\pi_\theta \| \pi_{\text{ref}}\right] \right]$$

The advantage is defined as a relative reward of each output:

$$\hat{A}_{i} = \frac{r_i - \text{mean}(\mathbf{r})}{\text{std}(\mathbf{r})}$$

ALIVE automatically defines a reward function that mixes:

• Realized economic payoff
• Risk/variance penalties
• Brain‑specific objectives

The math is standard. The only non‑standard part is where the reward comes from.

The Problem

The 'old internet' problem is simple. You create value. Platforms capture it. Their AI learns from your behavior. You get dopamine, but no equity.

Every click, watch, like, and trade trains someone else’s models: YouTube’s recommender, TikTok’s feed, and OpenAI/Anthropic’s RLHF loops.

The result is:

• Centralized intelligence - a few massive models trained on everyone
• Centralized value - a few massive companies capturing almost all the upside

Crypto was supposed to change this, but what did we actually build? A global casino, wired into programmable money, where every trade screams “what happens next?” …and then disappears.

• Markets price risk in the moment
• But they don’t remember how they were right or wrong
• The intelligence in the system walks out with each trader

ALIVE’s thesis is simple: If we’re already burning trillions in speculative flow, that flow should build your AI ecosystem, not just someone else’s.

“What if there was an algorithm that actually served you… and helped you find what you deeply valued?” —Chris Best, CEO of Substack

Why ALIVE

This part is personal. Alphakek started by asking a boring question:

Where do I get high‑value, high‑stakes data that stays open - and how do I point modern models at it without lighting money on fire?

In practice, the path looked roughly like:

• Years of building AI models for academia and TradFi users: astrophysics, computer vision, code analysis, GenAI, etc.
• The web closed up just as models got good. GPT-3-Instruct made it clear you could automate real research/analysis, if you have the right data. At the same time, Reddit, Twitter, StackOverflow, and others pulled the ladder up.
• Crypto looked like the only open, high‑stakes environment left: Every trade is a revealed preference. Every position is a belief with money attached. Every onchain event is both data and a potential reward.

That's how the Fractal engine was created. Building it taught two lessons:

1. Building good models is not the hardest part anymore. You can spin up surprisingly strong vertical models with a small team and the right tricks. The hardest part is keeping them aligned with what the market actually cares about.
2. Distribution and incentives dominate everything. A “hold‑to‑access” token model works as a short‑term gate, but it decouples AI improvement from market behavior. You end up with static models serving a churning holder base, instead of evolving systems co‑designed with their own users.

ALIVE is the answer to both - bake AI directly into the market structure (Brains) and let markets decide which Brains are worth training.

Then, wire the economics so that traders get upside from finding good Brains early, builders get upside from helping them win, and the protocol captures a slice of everything that matters.

The past two years of Alphakek's R&D - NVIDIA talks, early partners, weird prototypes - were just the prequel. ALIVE is the part where the environment itself starts to evolve.

New Information Infrastructure

You can think of a market as a distributed computer:

• Each participant has a tiny slice of information
• They express it by trading
• The "output" is a price path and a set of realized outcomes

ALIVE doesn’t worship markets as perfect truth machines. It just treats them as high‑bandwidth, skin‑in‑the‑game signal generators that Brains can train on continuously, so each resolved mistake or success evolves the Brain and its surfaces.

As a result, you get specific Brains that become very smart in narrow domains - and pull more and more flow away from everything else.

Market Speculation → Onchain Signals (Rewards) → AI Learns → Compounds Knowledge → Compounds Value → ∞

ALIVE’s job is to make this infrastructure standard and composable.

ALIVE vs. Verifiable Compute

Most “verifiable AI” projects went after the hardest part of the pipeline:

• Proving each forward pass
• Proving each gradient step
• Proving each GPU did exactly what the spec says

That gives you:

• ZK overheads
• Encrypted HSMs
• Validator sets rerunning models
• And a massive performance tax

ALIVE moves one step downstream: Don’t verify the computation. Verify the reward.

ALIVE doesn’t insist on proving: "The model did exactly N FLOPs in this precise order."

What ALIVE verifies is:

• Did this Brain’s environment earn real economic flow?
• Did users and markets reward its outputs with actual money?
• Are its outcomes aligned with what the market proved it wanted?

Concretely:

• Rewards are onchain: fees, outcomes, volumes, PnLs
• Anyone can see which Brains: actually attract volume, consistently host sharp markets, power tools people pay for

This is enough to keep the payoff surface transparent and trust-minimized, while letting the internal models, architectures, and tricks evolve freely off-chain.

The New Internet is ALIVE

The New Internet flips where intelligence and value accumulate.

Old internet:

• Your behavior trains centralized AIs
• Your attention fuels centralized platforms
• Your money flows to a handful of companies

New internet (ALIVE‑style):

• Your trades/bets/interactions train open, specialized Brains
• Those Brains back AI ecosystems you can actually own
• Money and intelligence flow to the people who find and create them

Old internet = your actions make Google / Meta smarter and richer.
New internet = your actions grow the Brains you own a piece of.

Each Brain environment is:

• A 'internet' with its own: financial primitives, revenue flows, subscriptions, content, interfaces; coordinated by one evolving AI core
• A bet on “this is what markets really want AI to be good at here”

ALIVE’s job is simple:

• Let anyone create Brains
• Let markets train them
• Let AI adapt their surfaces
• Capture a some of the revenue and buy back $AIKEK.

If Alphakek is right, the most interesting AI companies of the next cycle won’t look like SaaS. They’ll look like networks of Brains - each a living, earning AI ecosystem - sitting on top of blockchains, and fused together by protocols like ALIVE.

What's Next

Over the coming weeks, Alphakek will unveil:

1. The first Brain environments

ALIVE can capture any onchain or decentralized instrument, compound its activity and knowledge, and align your AI with you and your specific goals.

2. ALIVE Terminal

Launching ALIVE's first consumer and builder front-end experiences that meet users where they already speculate, unlocking:

• New digital asset classes with built-in AI utility
• Flywheels with token value captures, which accrue as Brains learn
• Potent, high-velocity market activity to ALIVE

3. ALIVE ecosystem partners, builders, and users

ALIVE is a chain-agnostic developer ecosystem for intelligent monetizable primitives. Alphakek's ecosystem will introduce new partners, advisors, blockchain integrations, data integrations, influential early adopters, and distribution beyond crypto.

4. Builder APIs to power billions of agents and robots

With Brains, anyone can build agents, apps, robots, frameworks, and x402 gateways: 

• Integrate ALIVE into onchain financial primitives directly
• Integrate API into your website, app, or game
• Connect your favorite vibe coding tools via API/MCP/A2A

ALIVE Brains will know all it needs to know, behave exactly as the market believes it should behave, and reason in a way that is most profitable for you.

5. BrainRouter & Open-Weights AI

ALIVE scales the creation of deeply personalized and market-aligned open-source AI models for:

• Every knowledge domain requested by users
• Solving real-world tasks
• Personal and commercial use
• Privacy on mobile devices

Alphakek AI Lab

Led by Vladimir Sotnikov (Chief Scientist), Alphakek began as an AI lab of forward deployed engineers building ‘zeroslop’ AI infrastructure for crypto’s largest companies and ecosystems, including CoinGecko, Arweave, Brett, and more.

Alphakek trained hundreds of unbiased models, served tens of thousands of users, and shipped dozens of unique AI workflows, agents, and platforms that the crypto industry could not or would not build.

Now, Alphakek comes full circle as its proprietary knowledge engine and original core innovation, Fractal, becomes the technical foundation of ALIVE.

Alphakek officially ends Phase 1 - R&D and discovery - and enters a new era of scaling and distributing its AI infrastructure for capturing token value, market speculation, and high-velocity consumer activities.

About Alphakek

Building the first AI evolution environments for compounding capital onchain. Power billions of agents, robots, and prediction markets. Featuring unbiased, crypto-aware AI and NVIDIA-recognized knowledge layer powering crypto's biggest names.

Website | Twitter | Telegram | GitBook | CoinGecko