Chris Donovan ⋈

647 posts

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Chris Donovan ⋈

Chris Donovan ⋈

@ChrisDoNEARvan

Council Member @NEARFoundation | Advisor @Compound_xyz | User-Owned AI is NEAR | Chain Abstractooooor | All views my own | Lawyer but not your lawyer

Zug, Switzerland Katılım Aralık 2020
1.2K Takip Edilen2.5K Takipçiler
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Chris Donovan ⋈
Chris Donovan ⋈@ChrisDoNEARvan·
The most valuable attribute of AI systems is loyalty. Whether an agent is loyal to you (acting in your best interests) or someone else (eg the organisation that owns the agent/model). @NEARProtocol ‘s User Owned AI provides verifiable loyalty guarantees (verifiable training and inference + censorship resistance), so you can be sure an agent/system is really *yours*. The value of this cannot be understated. These agents will be influencing and coordinating almost every aspect of our lives far sooner than most people expect, looking after our financial, physiological and social health. Without these loyalty guarantees, the worst excesses of Web2 user exploitation will just be the tip of a disastrous iceberg in the AI age.
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Bankless
Bankless@Bankless·
Sal Ternullo of @svrn_ai explains why he thinks near:native is misvalued He thinks there's been a structural change in @NEARProtocol over the last 2 years, that makes NEAR deserves a 2-4x just from human usage alone But the real growth story is from AI Agents using Ironclaw and Near Intents creating a 20-40x opportunity for near:native Episode is out for Premium Subscribers today
Haseeb >|<@hosseeb

OK guys, someone want to explain the $NEAR pump? Did I miss something?

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Chris Donovan ⋈
Chris Donovan ⋈@ChrisDoNEARvan·
This is a risk with all AI services provided by corporates with a profit-maximisation mandate. Ads are just the start. The Big Tech incentive model requires the monetisation of everything about users (you), and the models act not in your best interests but in whatever way delivers profit-maximisation for the company and it's shareholders. The only way you can *really* trust your AI is if it's User-Owned. This is what @near_ai & @NEARProtocol are building. AI you can trust, AI that is truly *yours*.
Claude@claudeai

Ads are coming to AI. But not to Claude. Keep thinking.

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Chris Donovan ⋈ retweetledi
chronear
chronear@chronear·
We've surpassed $1B in all time volume for NEAR Intents as of this morning. The medium and long term goals remain $1B monthly and $1B daily respectively. Accelerate.
chronear tweet media
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Illia (root.near) (🇺🇦, ⋈)
Illia (root.near) (🇺🇦, ⋈)@ilblackdragon·
Proposal is up by HOT following a lot of community discussion for reducing NEAR inflation down to 2.5% I support this proposal. Lower inflation allows to better position NEAR as store of value for AI To add few more reasons: - NEAR continues to innovate keeping tx prices very low while being the be of top blockchains by number of transactions. - High staking yield effectively offering “no risk” return limits DeFi development. - House of Stake is planning to offer alternative method to stake and earn for participants who are long term aligned with network allowing to have higher yield and governance power. It’s also important to remember that new ways of generating demand for NEAR coming with fees from Intents. It’s exciting to see evolution of NEAR economics and I’m looking forward to the vote!
HOT Protocol 🔥@hotdao_

🔥 We’ve submitted a proposal to reduce NEAR’s inflation rate from 5% to 2.5%. This change is aimed at making NEAR more sustainable in the long term, supporting token value, and better aligning incentives across the ecosystem. 🚀 🔗 Proposal link: gov.near.org/t/reduce-infla… 🗳 Validators can vote here: vote.linearprotocol.org

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Chris Donovan ⋈ retweetledi
Avichal - Electric ϟ Capital
The @NEARProtocol team is targeting 1m TPS and 200ms blocks with sharding, while supporting home staking validators on $27/mo nodes 🤯 @BowenWang18 and team are one of the most impressive protocol teams in crypto
Bowen Wang@BowenWang18

We’re aiming for @NEARProtocol to process 1 million transactions per second within this year, starting in a testing network. The goal is to prove how NEAR’s sharding design can support the massive influx of volume our industry will likely see from AI agents

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Michael Broderick
Michael Broderick@whatismichael_·
🤓 Happy to share that @NEARProtocol is now officially a Harvard Business School case study.
Michael Broderick tweet media
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