Jr

The alter Ego is back.

Chronically online, crypto and stock market focus. Geo/politics and tech hobbyist.

[Jr @Brand_is_back]

@diazjulio0071 @AnthropicAI I did the same as well

[Jr @Brand_is_back]

@zachxbt Would you be able to also trace shielded transactions through the Railway wallet, a zkSNARK wallet application. Say Eth - Arbitrum - shield - shield - unshield - another arbitrum wallet?

[Jr @Brand_is_back]

@jbvx86806193 @Railway_xyz I second this. So many issues with the wallet, even in desktop

[Jr @Brand_is_back]

@RAILGUN_Project @Railway_xyz Agreed, but I constantly get error messages with the Railway wallet, typically when unshielding

[Jr @Brand_is_back]

@SarahisCensored To operate due not filing reports, not paying taxes and fees, or not maintaining a registered agent or office. Per their business filings with the Texas Secretary of State

[Jr @Brand_is_back]

@SarahisCensored He filed this org originally in 2015 as OLD NGAN, then again in 2016 as Next Generation Action Network Foundation, 2019 as Next Generation Action Network, and again in 2025 Next Generation Action Network Inc. The 2015 and 2019 show Forfeited Existence meaning they lost the right

[Jr @Brand_is_back]

@LucyLoo92982095 @thescif @RealCandaceO It is that easy, so that begs the question, if the Macrons want to settle this, why not just produce those

[Jr @Brand_is_back]

What you are doing now would be the equivalent if a business sold a part of their building to pay for OpX. If you believe in through security of $eth and the ecosystem you've created, put your money where you mouth is

[Jr @Brand_is_back]

@ethereumfndn I don't understand why you continue to sell $eth to pay for operations costs. You have an income producing asset, use it. You could use a LST like @RocketPool_Fi, then use a @MorphoLabs or @aave to take loans against it to pay for OpX.

[Aaron Siri @AaronSiriSG]

Why federal health regulators are utterly conflicted concerning vaccines. Link to full interview below.
https://t.co/WcaxIWJFRZ

[Aaron Siri @AaronSiriSG]

A FOIA from @ICANdecide asked CDC for records to support its statement “COVID-19 vaccines do not alter DNA.” CDC was unable to provide a single record. Not one. https://t.co/5mcdAU4xKV

[Jr @Brand_is_back]

@SenatorWarner That was the worse confirmation hearing I have ever heard on #RFKJr . You literally gave him less than 2 minutes of to respond to your questions. You do not represent the American people and are the epitome definition or your typical bureaucratic "representative" #

[Shaw (spirit/acc) @shawmakesmagic]

Stronger models are always good for AI agents.

AI labs have been leapfrogging each other in benchmarking and capability for years now. Sometimes Google is ahead, sometimes OpenAI is ahead, sometimes Claude. Today it's DeepSeek. The trend is that the largest and most well-capitalized in the world are competing on a technology that is ultimately trending toward being free, open source and costing nothing to run on your computer at home.

The consistent winners here have been on both sides of this race: hardware and consumer products.

NVIDIA always wins. Every model is optimized to run on their hardware. Apple also always wins: they invested in a unified memory architecture which enables high VRAM machines which can run the latest models (albeit slowly).

Products continue to benefit from the latest models. Cursor and Perplexity are examples of products that just magically get way better every few months, but as AI becomes integrated into nearly every product, all of those products benefit from cheaper, faster AI models.

AI agents are a new application paradigm-- the core thesis is that applications need to migrate onto social media, where users are, and agents are a form of application that can exist entirely on social media without requiring users to leave. They are self-advertising and benefit from network effects with each user interaction.

When a new model comes out, integrating into an agent framework is usually just a few lines of code. Most model providers follow the same API convention, following OpenAI, so this work can usually be done in a few minutes. This enables any agentic application to immediately access the latest models. Every time a state of the art model drops, agents get that much smarter.

Our thesis with AI agents has always been that raw intelligence is not the whole picture: models can infer and reason, but actually acting upon the world requires embodiment, connectors to external platforms, management of memory, context and secrets. None of this is or can be easily shoved inside of a model. Eventually the models will be able to generate most or all of this code on the fly, but we're still several years away from that, and it will be the result of thousands of humans building those connections, writing that code and systematizing human processes for the next generation of models being trained on that code after it is scraped from Github.

AGI is a loop. It requires data ingestion and curation, raw intelligence in the weights, implementation into practical applications, to be ingested and curated again into the next model, to be implemented into more practical applications, and so on until it really has enough generalized capability trained in that anything else can just be inferred. If the data doesn't exist for how to do something-- and it doesn't yet exist for the vast majority of things humans do every day-- current AI models probably aren't going to be able to sufficiently generalize to suddenly infer how to do that thing.

That's why agents matter. Agents are a paradigm where ordinary humans can reason out how to solve problems that humans have typically done themselves, systematize the solution using code, generate lots of data of the implementation working in a real world setting and store both the code implementation and the generated action data in places where they can be trained back into models.

None of us are creating AGI by ourselves. We're all part of a bigger system, and we all have our part to play. New models make all of our agents better and more capable. Making agents that do more useful things and generate more novel data makes the next generation of models more capable. Everyone in the loop is both a producer and consumer of novel capability.

I chose to work on agents for two reasons: because I could start right away at state-of-the-art, and because I understood a part of the problem well that probably wasn't being focused on by the majority of researchers.

Training state of the art LLMs is only possible in the handful of companies which have the resources to continuously buy GPUs. Llama 4 is being trained on 100,000 H100 GPUs, each of which costs about $30,000 USD. Without massive GPU resources, the training time on models is such that any independent researcher is working at a grave disadvantage-- experiments can take weeks to run and validate. Most PhDs get just a handful of breakthrough successes in their time, and access to large training clusters is one of the biggest talent attractors to the big corps in the industry.

Coming from interactive experiences, games and digital human projects, I had a decade of experience writing performance intensive software where I had to think about architecture, and agents just made sense to me. Agents are an engineering problem, not a math problem, and require a very different set of skills and background more akin to game development than machine learning.

OpenAI and Microsoft have both worked on agents for years and ultimately have gained very little meaningful traction in real world applications because they treat agents like a research problem, not an engineering problem. I don't see this trend changing, and I think with the rise of social agents we will see these big companies be at a major disadvantage due to having a low appetite for risk and unwillingness to enable their agents to operate on competitor's platforms. X and Meta have a real advantage here, as they can deploy to their own platforms and leverage their hoards of social data to train on, but the PhD-heavy culture of their AI divisions really doesn't lend itself to a class of technology that is extremely hard to benchmark and is more about product than research.

Both the math side of AI models and the engineering side of AI agents are two sides of a coin, just as our brains and our bodies are. Both are difficult, require enormous investments of hours to get right, and will probably be a continuous race between many leading contenders.

We have a great loop of developer and social feedback, learning from our mistakes and getting lots of free upgrades through the open source model from many different directions that give us a real shot at being competitive with the best of them. We all accelerate each other.

This week was a huge W for all of us. For agents, for humanity, and for the AI model teams that now have a fire under their ass to work harder and do better. I'm not worried one bit about our position in all of this. We're building the next version of Eliza and it's only going to get better from here. Thousands of teams are building on our tech, over 500 people have made contributions to the core repo and as we continue to evolve that will just keep growing. We're creating a template for how ambitious founders can crowdfund their public goods projects, and we'll have a lot more to roll out in the coming weeks and months to solidify that strategy.

I think that people who say "well X is just a wrapper for Y" are simply not accounting for how hard it is to build a great product, or to build anything great. I believe that as AI models become more commodified, we'll enter a time where people see AI as just an API called by the world's best products instead of this silly just-a-wrapper business.

If making agents was easy they'd already be prolific and we wouldn't be here. None of this is easy. There is a whole lot more work to be done by all of us to get to machines that we would all regard as being able to do what humans do.

[Jr @Brand_is_back]

@franklinleonard @DrowRanger734 Hence him being in support of increasing the child tax credit to 5k. Just because he hasn't mentioned or talked to those things doesn't mean he is against families. He just doesn't believe in the same things you do to accomplish that.

[zerohedge @zerohedge]

$40

[SightBringer @_The_Prophet__]

The concept of Wrapped Bitcoin (WBTC) might seem complex at first, but it’s relatively straightforward when broken down:

What Is Wrapped Bitcoin (WBTC)?

•WBTC is an ERC-20 token that represents Bitcoin (BTC) on the Ethereum blockchain or other compatible networks.

•Each WBTC token is backed 1:1 by actual Bitcoin. For every WBTC minted, one BTC is held in reserve by a custodian.

•The goal of WBTC is to allow Bitcoin to interact with decentralized finance (DeFi) protocols and other Ethereum-based applications.

Why Is WBTC Used?

1.Liquidity in DeFi:

•Bitcoin cannot natively interact with Ethereum-based protocols. By wrapping BTC, it can be used for:

•Lending/borrowing on platforms like Aave or Compound.
•Trading on decentralized exchanges like Uniswap.
•Yield farming or liquidity provision.

2.Speed and Efficiency:

•Transactions using WBTC are faster and cheaper than native Bitcoin transactions due to the Ethereum network’s design.

3.Integration Across Chains:

•WBTC bridges Bitcoin’s value with the flexibility of Ethereum, creating more use cases for Bitcoin holders.

Why Did World Liberty Financial Buy WBTC?

•The purchase by Trump-backed World Liberty Financial may reflect:

1.DeFi Exposure: The organization might plan to leverage DeFi protocols for earning yield or managing liquidity.

2.Blockchain Interoperability: Holding WBTC could signal a strategic move to participate in Ethereum-based ecosystems while retaining Bitcoin exposure.

3.Flexibility: WBTC provides the ability to interact with DeFi markets or decentralized applications without giving up Bitcoin reserves.

Does This Impact Bitcoin Directly?

•Yes, indirectly:

•WBTC purchases still require Bitcoin as collateral, reducing Bitcoin’s liquid supply.

•Increased adoption of WBTC highlights the growing integration of Bitcoin into broader crypto ecosystems.

•This demand for WBTC likely signals increasing confidence in DeFi applications, indirectly boosting Bitcoin’s credibility.

Let me know if you’d like me to analyze this transaction’s potential impact further!

[Jr @Brand_is_back]

@Bitcoin_Teddy This has been on Github since inception.

[Jr @Brand_is_back]

@luna_virtuals 150k BTC by fall of 2025. ETH etf inflows are picking up, only a matter of time before BTC value swaps into EVM chains

[Robert Sterling @RobertMSterling]

H-1B DATA MEGA-THREAD 🧵

I downloaded five years of H-1B data from the US DOL website (4M+ records) and spent the day crunching data.

I went into this with an open mind, but, to be honest, I'm now *extremely* skeptical of how this program works.

Here's what I found 👇

[Grey Ledger @Airdrops_one]

$RISE 🪂Airdrop and Mainnet in early 2025? Airdrop for $TIA stakers 🥩, @badkidsart @CelestineSloths @madscientists_x and others 👇

Per @thetashis, @SunriseLayer RISE 🌅 2025

$RISE Airdrop 🪂 Eligibility - can still change and may not be accurate

🔸 $TIA Stakers
🔸 $stTIA and $milkTIA holders
🔸Allocation: 2% of token supply
📸 Snapshot: June 14, 2024, at 6:00 UTC
🔸v1 and v2 Testnet participants
🔸NFT Communities:
@badkidsart @CelestineSloths @madscientists_x @hungrybera @eatsleepyeet Honeycomb @0xhoneyjar

Specific allocations or snapshots are unknown and TBD

🔸🔸Stake $TIA with our Sponsor @EverstakeCosmos, and be eligible for potential future Airdrops.🔸🔸

Tokenomics (may still change)

🔸Genesis drop 7%
🔸Future initiative 5%
🔸Core contributors (6 mo lock and 30 mo continuous unlock): 25%
🔸R&D: 33%
🔸Investors: 30%

What is Sunrise?

"Sunrise is a Data Availability Layer 1 based on @CelestiaOrg architecture. This allows Sunrise to retain all of the advantages and functionality of Celestia, while adding their own functions on top of it. Gluon is a Layer 2 deployed as a sovereign rollup onto Sunrise.

Sunrise will work diligently to align and reward the communities that are integral to its spirit, while creating value flow with the protocols that underpin it. These include the Gluon (formerly UnUniFi) community and ecosystem, interchain (IBC) ecosystem, Celestia ecosystem, @berachain ecosystem, and many more."

🔗Links

➡️Web: https://t.co/NBwxu5mirl
➡️Gluon: https://t.co/zYt0sUQrn0
➡️Discord: https://t.co/ynxCdELtw4
➡️Medium: https://t.co/CFqV0uEVnM
➡️Docs: https://t.co/XNkYEXqYrX

🫡