Adamnite (@adamnitehq) 's Twitter Profile
Adamnite

@adamnitehq

Adamnite is the blockchain built for all. #Create, #build, and #play at the speed of Web 2, in a #decentralized and censorship resistant environment.

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linkhttps://www.adamnite.org/ calendar_today09-01-2022 01:11:59

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Adamnite (@adamnitehq) 's Twitter Profile Photo

We will have a booth at the #CollisionConf tomorrow, sponsored by Adamnite Labs. Come check us out at booth A102. We may potentially be launching a public alpha there. A virtual collectible may also be available; you won't know unless you show up!

Adamnite (@adamnitehq) 's Twitter Profile Photo

New Blog Post! Check it out here: medium.com/@adamnite/adam… Also, be sure to follow Adamnite Labs for continuous updates on Passport and other infrastructure!

Adamnite (@adamnitehq) 's Twitter Profile Photo

Anyone on #CryptoTwitter interested in learning how to build a dApp? A1, Adamnite's own smart contract programming language, is now live and open-source. Check it out here: github.com/Adamnite/A1

Adamnite (@adamnitehq) 's Twitter Profile Photo

We are looking for smart contract developers who are interested in creating new projects/trying out a new programming language to try out A1 and create small demos! If you have an idea, join our Discord: discord.gg/adamnite-92109…

Adamnite (@adamnitehq) 's Twitter Profile Photo

Excited to announce that @beryl_finance will be building a decentralized freelancing and rewards platform on #Adamnite. They have also received a microgrant from Adamnite Labs! Be sure to follow them, and join their Discord here: discord.gg/3qwBE3ZQ #Web3 #blockchain

Adamnite (@adamnitehq) 's Twitter Profile Photo

There was an attempt to hijack the Adamnite Discord Server today. As always, be sure to enable two-factor authentication and do not click on any malicious links!

Adamnite (@adamnitehq) 's Twitter Profile Photo

Excited to announce that @lituusfinance, a project spun out of a microgrant given to developers Cal Poly Blockchain from Adamnite Labs , has officially started building! Be sure to give them a follow and check out their resources!

Jesus Rodriguez (@jrdothoughts) 's Twitter Profile Photo

Really cool examples of the potential of autonomous agents in the FAKTORY platform. Herman uses connectivity to MySQL and Gmail, planning skills and a helpful personality youtube.com/watch?v=jh9gJo… #generativeAI #LLMs

Archie Chaudhury (@archchaudhury) 's Twitter Profile Photo

We can accelerate safety. Earlier this month, Leopold Aschenbrenner published SITUATIONAL AWARENESS, a series calling for the nationalization of AI Labs and AGI efforts. Today, I am publishing my response, Rational Accelrationism, calling for AGI development to remain in our hands.

Archie Chaudhury (@archchaudhury) 's Twitter Profile Photo

Rational Accelrationism is a multi-part series arguing that we can be trusted with AGI; the reality is that today's models are far away from simulating human cognition, and that winning governments prioritize free-markets over regulation.

Archie Chaudhury (@archchaudhury) 's Twitter Profile Photo

Also, I technically published this in an effort to get deep into the strategic realities underpinning AI, which is a side-project that I have been pursuing as part of BuildSpace S5. Look for more technical-oriented releases as part of S5 soon. CC buildspace nights & weekends

LayerLens (@layerlens_ai) 's Twitter Profile Photo

We are starting an educational series on evals for LLMs. The terms "benchmarking", "evals" and "testing" are often conflated with one another. Today, we are doing a deep dive into benchmarking. What follows is a 🧵on what benchmarking is and why it is important.

LayerLens (@layerlens_ai) 's Twitter Profile Photo

In line with our private betas for the Atlas Application, we have updated our website to reflect our vision. Learn more about LayerLens, what we are building, and the long term roadmap here: layerlens.com If you are a developer, you can also book time directly with

LayerLens (@layerlens_ai) 's Twitter Profile Photo

Evaluations, or “evals” refer to the execution of datasets for custom use cases against foundational models. They are often used after training or fine tuning to determine how good a model at specific tasks.