𝐇𝐨𝐰 𝐭𝐨 𝐫𝐮𝐧 𝐨𝐜𝐭𝐫𝐚 𝐰𝐞𝐛𝐜𝐥𝐢 𝐨𝐧 𝐲𝐨𝐮𝐫 𝐦𝐨𝐛𝐢𝐥𝐞 𝐩𝐡𝐨𝐧𝐞 𝐮𝐬𝐢𝐧𝐠 𝐆𝐢𝐭𝐇𝐮𝐛 𝐜𝐨𝐝𝐞𝐬𝐩𝐚𝐜𝐞 🧵🧵🧵

today was the final preparation phase for early validators, we took a snapshot of those who hadn't sold their dropped coins (held or encrypted them) - there are currently 69 of them at the same time, 91 participants got rid of their coins (the latest case was noticed a few hours ago), we were expecting this given the activity, and as soon as everyone who wanted to get rid of their coins had done so, we took a snapshot at epoch 1118156 everyone who held and didn't sell will have great news for you before the launch of the validator program thanks for your support

Btw, a fun fact about ML and contex mixing - all the time at the end of school and the beginning of university, I was fascinated by data compression and algorithmic codecs. This is essentially how I started my career as a C developer. There's one fun fact about compression that just occurred to me: the legendary Matt Mahoney, who created the most powerful algorithmic coder and founded the PAQ family, variations of which constantly won the Hutter Prize for data compression, essentially laid the foundation for the concept of ML through data compression, since algorithmic codecs are built on predictive models and sigmoid functions for constructing frequency context models based on the data type. So, what I'm getting at is that in our "narrow" circle of those involved in this topic, there was a clear justification for what AGI is expressed through data compression. As you know - you can't bypass the Shannon limit, that's a hard math law. However, the Shannon limit is bound to a specific predictive model. If an algorithmic codec can build such a profound, context aware model of the world that its 'guessing' pushes the practical compression down to the data's absolute, intrinsic complexity, that might just be the key to unlocking AGI. If you want to start approaching AGI, you need to pay attention to data compression, bc if a context codec model can "decompress" and predict and compress the full context of Wikipedia (which in a compressed format has entropy practically within the limits of Shannon), then this may mean that one of the most important steps towards AGI has been made. PVAC-HFHE uses our own version of algorithmic mixing to compress public keys for the HFHE engine. You can see it here: github.com/octra-labs/webcli… Now that we're head over heels in working on circles in @octra with the goal of bringing interesting use cases, this has made sense again and we've developed a passion for trying out new hypotheses. So yes, one of the new directions for octra is ML and contextual transformation, because the treechain structure and data model are perfectly compatible with the goals of ML inference. We'll continue working on this (I think every day now) and will report if we find anything interesting.

PoC HFHE against everything (benchmarks) github.com/octra-labs/pvac_h…

a mini update regarding webcli - many security improvements have been added that make it worth updating your version to the latest version (don't delay with the update) we’re also reinstating the bounty program as an open portal with challenges after receiving good findings from researchers, we'll share more in the coming days once the concept is finalized github.com/octra-labs/webcli

Jika $XMR adalah raja, dan $ZEC adalah putra mahkota, maka: Hanya hanya masalah waktu perhatian pendukung keduanya beralih ke $OCT. Hanya masalah waktu CEXs akan mendaftarkan nya. Hanya masalah waktu CT akan membicarakan nya. Bullish? Personally, yes. Saya lebih suka proyek yang launch dengan FDV rendah. Takut? Juga iya, terutama soal keamanan bridge. So, find your own conviction.

😅 update: someone just encrypted 2,000,000 oct more, which is definitely the largest encrypt transaction ever octrascan.io/tx.html?hash=f4…