ACExDEADPOOL

Sentient at NeurIPS is a big moment for open source AI ➭@SentientAGI has taken a major step forward as four of their research papers have been accepted at NeurIPS one of the most respected and competitive AI conferences in the world. This is not just a win for Sentient but for everyone who believes in open collaboration and transparent research It shows how far Sentient has come moving from community driven experiments to global recognition through peer reviewed research Here is a look at what they have achieved 𝟏 𝐎𝐌𝐋 𝟏.𝟎 𝐌𝐚𝐢𝐧 𝐓𝐫𝐚𝐜𝐤 ➭This paper presents a new system for LLM fingerprinting and marks a major breakthrough. Sentient embedded over twenty four thousand fingerprints into open models which is nearly a hundred times more than previous systems while keeping performance stable. It proves that open models can be both secure and scalable 𝐋𝐢𝐯𝐞𝐂𝐨𝐝𝐞𝐁𝐞𝐧𝐜𝐡𝐏𝐫𝐨 𝐃𝐚𝐭𝐚 𝐚𝐧𝐝 𝐁𝐞𝐧𝐜𝐡𝐦𝐚𝐫𝐤 ➭This work focuses on AI programming benchmarks showing how well models can perform coding tasks. Sentient built models that are ten times smaller used twenty percent less data and still matched the performance of some of the largest systems. It shows that efficiency and capability can go hand in hand. 𝐌𝐢𝐧𝐝𝐆𝐚𝐦𝐞𝐬 𝐀𝐫𝐞𝐧𝐚 𝐂𝐨𝐦𝐩𝐞𝐭𝐢𝐭𝐢𝐨𝐧 𝐓𝐫𝐚𝐜𝐤 ➭Sentient was chosen by NeurIPS to host a new competition where AI agents learn and evolve through social games. The goal is to move beyond static problem solving and toward adaptive learning and self improvement. It is about creating AI that grows and evolves through experience 𝐋𝐨𝐜𝐤 𝐋𝐋𝐌𝐬 𝐖𝐨𝐫𝐤𝐬𝐡𝐨𝐩𝐬 𝐚𝐧𝐝 𝐓𝐮𝐭𝐨𝐫𝐢𝐚𝐥𝐬 ➭This paper tackles one of the hardest challenges in open AI security. Sentient introduced a cryptographic framework that allows developers to maintain control of their models while keeping them open for collaboration. It sets a foundation for trust and transparency to exist together 𝐖𝐡𝐲 𝐢𝐭 𝐦𝐚𝐭𝐭𝐞𝐫𝐬 ➭Acceptance at NeurIPS is a mark of real innovation and quality. Having four papers accepted across different categories shows the range and depth of Sentient’s work from technical strength to safety to creative intelligence ➭This achievement is not just about research results. It is a signal that open source AI can stand shoulder to shoulder with closed systems and sometimes even go further. The community around Sentient continues to prove that openness and collective effort can drive the field forward faster than isolation ever could. 𝐅𝐢𝐧𝐚𝐥 𝐭𝐡𝐨𝐮𝐠𝐡𝐭 ➭Sentient is evolving beyond a single project into a movement for transparent community led intelligence. This milestone at NeurIPS is proof of what can be achieved when people come together with a shared purpose to build technology for everyone. @sentient_chat @sandeepnailwal @hstyagi @abhishek095 @0xsachi @vivekkolli @shad_haq @LeaderX_btc #SentientAGI #KAITO #ai #yapp

Gmum fam 🫶 You can start to see where the real difference is when you put gossip, Reed-Solomon, and RLNC together. > Gossip is the easiest but also the most messy. It just keeps sending the same packets all over the place with no awareness or control, which causes a lot of duplicates and extra load. > Reed-Solomon makes this a little clearer.. the data is encoded and broken up into shards, so you don't need every single piece to get it back. But after that, the network still just sends those same shards around. The flow doesn't really change. It's more organized, but still somewhat set. > Then RLNC comes in and changes how things work. Instead of sending the same data over and over, nodes mix what they have and make new useful packets at every step. so the network isn't just moving data it's constantly improving it as it travels Less duplication, fewer messages overall, and recovery is much faster. > That's the part that most people miss. Scaling isn't just about making things faster it’s about making sure every piece of data moving in the network actually adds value.. @get_optimum