Hedera Hashgraph (HBAR)

Interesting theory from the community… “NYSE hinted at moving to Dallas. Hedera is based in Dallas.” Coincidence, or one of those details you only notice before the plot twist?

💡[ENG Sub] What Makes @Hedera So Special? “#Hashgraph + #aBFT”! @HederaFndn @hashgraph @hashgraphgroup @The_Hashgraph

💡[Japanese subtitles] What makes Hedera (@Hedera) special? "#Hashgraph (#Hashgraph) + #aBFT"! @HederaFndn @hashgraph @hashgraphgroup @The_Hashgraph

@kofinas Dr @leemonbaird knows a thing or two about quantum computing and the threat to cryptography. https://t.co/FLFe9JGjBb

📘 @Dell releases an AI verifiable computing whitepaper based on @hedera – tokenization and LLM verification are completed🧵 🔑 Executive Summary Dell's trustworthy AI verifiable computing whitepaper goes beyond the conventional approach of merely describing post-hoc how AI computation was performed. Instead, it introduces a new standard of proof for AI computation at the hardware level itself. Verifiable computing, co-designed by Dell, EQTY Lab, @nvidia, and @intel, runs AI training and inference within Trusted Execution Environments (TEE) across both CPUs and GPUs, with EQTY's cryptographic AI notarizer signing and recording data, models, code, and the execution environment in real time. Crucially, these cryptographic attestations can be registered to the Hedera Consensus Service (HCS), creating immutable, independently verifiable, timestamped audit records. This architecture directly satisfies the technical requirements for trust, transparency, and accountability demanded by EU AI regulations, sovereign cloud obligations, and compliance‑focused environments such as financial institutions and the public sector. 📊 Benchmark and Performance Results (Chapters 5–6, p.21–25) 🔍 Core verification question: Does reliability, security, and verifiability come at the cost of performance? Dell conducted comprehensive performance benchmarks to validate verifiable computing not merely as a proof of concept (PoC) but as a solution suitable for real‑world enterprise deployment. The benchmark environment was built on a standard enterprise AI infrastructure composed of Dell PowerEdge R760 servers equipped with NVIDIA H100 GPUs. Importantly, the focus of verification extended beyond raw compute speed to measure actual performance with cryptographic proofs, TEE isolation, governance enforcement, and audit logs fully enabled. 🧪 Benchmark design: production‑grade workloads 📌 Tested workloads - Text tokenization - LLM inference (3B to 70B parameters

⚡ Dr. Leemon Baird breaks down the advantages and disadvantages of typical "fast" DLTs and challenges with privacy. $HBAR https://t.co/pmzmcbX00B

📘 @Dell Releases @hedera Based @EQTYLab AI Verifiable Compute Whitepaper – Tokenization & LLM Validation Completed🧵 🔑 Executive Summary The Dell Trusted AI Verifiable Compute Whitepaper goes beyond traditional approaches that merely explain how AI computations occurred after the fact. Instead, it introduces a new standard for proving AI computations at the hardware level itself. Jointly designed by Dell, EQTY Lab, @nvidia, and @intel, Verifiable Compute performs AI training and inference within Trusted Execution Environments (TEE) across both CPU and GPU, while EQTY’s cryptographic AI Notary signs and records data, models, code, and execution environments in real time. Crucially, these cryptographic attestations can be registered on the Hedera Consensus Service (HCS), creating immutable, independently verifiable timestamped audit records. This architecture directly satisfies the technical requirements for trust, transparency, and accountability demanded by regulatory frameworks such as the EU AI Act, sovereign...

Very excited to share our roadmap for 2026. Hello Future. @hedera @HederaFndn https://t.co/onGGIbUx5m

Bernard Ferran /Managing Director, Group Chief Commercial Officer, #Euroclear/ A great conversation moderated by Josh Lipsky (Atlantic Council), alongside fellow panelists #Nilmini Rubin (#Hedera) and Fernando Luis Vázquez Cao (Chainlink Labs). https://t.co/UWvasQ4CXC