A blockchain that could "adapt" or update its code based on the consensus of its users is what #TauNet is about. $AGRS is the token, it's in the #NVIDIA inception program and sits at $41 Million Market cap ($96 Million fully diluted). Time for us retail investors buy and hold this gem in the billions....
Peter Theil - “Maybe Larry Fink with the BlackRock ETF surrendered to the anti ESG forces or maybe it’s more like #Bitcoin has been co-oped by them and I worry or was more the latter”
Spotlighting our Crypto OG reviews on: @Tau_Net
Our Crypto OG reviewers note that Agoras $AGRS is tied to one of crypto’s most ambitious long term visions, a decentralized reasoning and logic based network that has been under development for years. However despite continuous development and an active GitHub presence, the project remains highly technical, difficult for average users to understand and has yet to deliver the large scale adoption or consumer facing products needed to validate its vision. Thin liquidity, limited exchange access and a decade long development cycle continue to raise questions about execution and market fit.
Can Tau Net finally turn its ambitious research into real world adoption or will Agoras remain a technically impressive project searching for a practical audience?
More on the OG audit review and the project info here: ogaudit(.)com/crypto/agoras-currency-of-tau-agrs
https://t.co/auYzFoXYe1
Bitcoin showed just how much appetite true Freedom there truly is. It wasn't the first step but it was a wake up call. Tau Net is the next step, it calls to the inner you that wants to see what we can all achieve together when we're unleashed.
The big problems in blockchain were never really solved. These problems exist in software and governance in the centralized world. If the decentralized solutions were so good, they would have been improvements to the centralized world.
Instead, the problem was avoided and replaced with annual 'cycles' and the gimmicks that came with them.
Who is going to solve the problems? We will of course.
Each participant choosing their own relay policy doesn't require central coordination but when the network needs to decide what Bitcoin becomes, five problems appear:
- How preferences propagate at scale,
- How votes aggregate so every voice counts,
- How consensus is distinguished from noise,
- Who handles implementation,
- How do you prove the outcome matched participant intent.
Sovereignty at the transaction selection layer doesn't resolve any of those.
Bittensor is exposing the ceiling of human-governed scaling: first the step back toward centralization, now Discord-driven subnet/emission control.
The next wave needs autonomous rule evolution, not governance bloat.
That is the https://t.co/Cc7Rm0w9tu angle.
$TAO $AGRS
The Claude leak needed the rule "never send private data over the network." The Mercor breach needed "reject any update that hasn't been formally verified."
Obvious rules but no language can enforce them across all future states of a system apart from the Tau Language.
Tau Language is "The critical ingredient for Safe AI" - Ohad Asor
@xInDS2Z0NAewoVf@DreadBong0@Tau_Net Truth.
Calling Tao the new BTC misses the point. BTC was a reset, not an optimization.
Bittensor still runs on models of structure validators, incentives, capital.
Power does not disappear, it just moves.
$AGRS is a whole new paradigm; systems that evolve their own rules 🌌🦾
Some people at frontier AI labs told me they believe startups are over.
OpenAI, Anthropic, Google, xAI will absorb every industry as AGI nears. Coding today, science, medicine, and finance next. Then everything else.
If they’re right, that’s a pretty boring end of the world.
@Toobbss Distributed data and transparent validation gets you to auditable inputs but the reasoning chain in probabilistic models is still in the weights.
You can't trace why the model reached a specific conclusion even with perfect data provenance.
We’re witnessing a convergence of AI and crypto.
AI agents can't walk into a bank, open an account, or transact in paper money.
Crypto provides the financial rails for AI agents to exchange value online.
As AI adoption grows exponentially, we believe crypto demand will follow naturally.
@dan_pantera@bloomberg@crypto
Yes! And even if token holders could vote on every decision, someone still has to translate votes into code.
Which is where additional centralization and botlenecks hide.
This is impossible to solve by adding more voting.
You need governance decisions that are directly executable specifications.
We have MVP in the works, will DM you with an invite.
Compute is all we need? Well, I knew this already. This is why Agoras needs to exist. @Tau_Net@AndrewOnizuka@Fola_Adejumo "A lot of times, people don't know what they want until you show it to them”
― Steve Jobs
Ohad Asor created Tau Language - a breakthrough that generates mathematical proofs for every computation.
Soon: AXIOM launches - Tau's first real-world application 🧵
$AGRS
Will future AI move toward a “neural + symbolic” hybrid model (neurosymbolic AI)?
Short answer:
Future AI is very likely to evolve toward a hybrid model —
but not the old-fashioned “neural networks + symbolic logic bolted together.”
Instead, it will move toward a third paradigm:
symbols that emerge inside neural systems,
and logic that is represented in a learnable, adaptive way.
In other words:
Not humans injecting symbols into AI,
but symbols growing naturally from neural representations.
Let’s break it down.
⸻
🧠 1. Why do neural networks and symbolic systems need to merge?
Because each has a fatal weakness.
Weaknesses of neural networks (LLMs, video models, etc.):
•not verifiable
•hallucinate
•unstable
•no guaranteed logical consistency
•reasoning chains are unreliable
Weaknesses of symbolic systems (CYC, Prolog, rule engines):
•cannot learn from raw perception
•brittle with incomplete or fuzzy data
•rules must be hand-maintained
•terrible scalability
For AGI, a system must be able to:
•perceive (neural networks excel)
•reason (symbolic systems excel)
Only a hybrid can break past current limits.
3. Which path is the most likely future?
Based on current research trajectories:
💡 The most likely mainstream future:
Neural networks → emergent discrete structure →
learnable logical modules for verifiable reasoning
Meaning:
1.Neural nets generate structured, symbol-like abstractions
2.These feed into a neuralized logic engine
3.The reasoning results feed back into the neural model
This produces a closed loop of self-learning logic.
It combines:
•scalability of neural systems
•verifiability of symbolic systems
→ the cognitive architecture most suited for AGI.
@bishara $AGRS the currency of https://t.co/vV5zSQmh8j - a logic-first network where human agreements compile into running code, markets, and governance. LLMs talk; Tau executes. Own intelligence, don’t rent it.