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“Enterprises are playing with open models and laying their data on top - they’re going to have a productivity boom, probably over the next two years," says Melius' Ben Reitzes:
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Enterprises are increasingly hesitant to give #AI# agents carte blanche ability to deploy #code# or system changes to production without human approval, even as they continue investing in tools designed to evaluate agent reliability.
#GenAI# #GenerativeAI#
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Enterprises supporting multiple stablecoins need a fixed, predictable rate to move between them, says Bhau Kotecha (@bhau___) of Paxos Labs (@paxoslabs). He points to FX interdealer markets as a model and expects the same problem to extend to tokenized assets.
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Enterprises should own their intelligence.
That means bringing AI to their sensitive data while protecting both business data and proprietary models.
NVIDIA’s @j_boitano and @VAST_Data Renen Hallak discuss how NVIDIA Confidential Computing makes this possible.
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Enterprises manage 36 cloud & SaaS providers on average & each one used to mean another connection to build. Adding the next one shouldn't mean redesigning your network. Any-to-any connectivity lets more choice stay simple.
Add partners, not complexity:
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Enterprises need control. But that shouldn’t mean closing themselves off from the permissionless ecosystem.
At @rwasummit, VP of Sales Carlos Arena shared why staying connected to the wallets, infrastructure, and innovation happening onchain matters for what you might want to build next.
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Enterprises are capping AI budgets, building routers, and coaching engineers on model choice. One company can put a number on the payoff. Most can't.
Enterprises want private ledgers with public-chain security, and @XDCNetwork's subnet design delivers both. Transactions stay on a company-owned private chain while only block headers checkpoint to the xdce-crowd-sale:native mainnet every two minutes. How the mechanism works ⬇️
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Enterprises still discussing the "number of AI use cases" they have are NGMI.
Enterprises will soon have 100x more AI agents than human employees
We are having our first super-fancy AI conference in NYC focused on the recursively self-improving Enterprise
What should we call it?
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