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Phil McMannis Phil McMannis, CEO of Beacon Protocol, highlighted the data silos issue in Web3. Because data is created in various locations and requires multiple transfers for AI consumption, it leads to potential losses in trust and privacy, and also creates the problem of scaling. This is what Beacon...

49,667 次观看 • 1 年前 •via X (Twitter)

12 条评论

Chainbase (✸,✸) 的头像
Chainbase (✸,✸)1 年前

Tired of fluff? We need real data to fuel AI Agents! Listen to key takeaways from our recent Chainbase Chat, featuring @luki_notlowkey and other amazing voices, as we explore the realities of working with real-world data and the strides we're making. Sound clips: ⬇️

Chainbase (✸,✸) 的头像
Chainbase (✸,✸)1 年前

Matt Burke @emburco, Growth Lead at @flock_io, believes the future of AI models and agents relies on private, local, and highly sensitive data, making secure access crucial for advancing AI. FLock uses federated learning to distribute model hosting and data collection in a provable, verifiable way, unlike the centralized model of companies like Google and Apple.

Chainbase (✸,✸) 的头像
Chainbase (✸,✸)1 年前

Joe Bender @JosephBender, Head of Content at @DIMO_Network, highlighted how OEMs currently control users' sensitive driving data. To address this, DIMO is building a platform where users can collect their own data (via software or an OBD2 port hardware device) and be rewarded weekly. Their vision includes a marketplace where users share data with service providers for tailored services, essentially creating an "app store for cars" and empowering drivers.

Chainbase (✸,✸) 的头像
Chainbase (✸,✸)1 年前

Justin, Head of Growth at @Hippocrat_io, explained the current situation where patients have no control over their data. Hippocrat aims to solve this by enabling true patient data sovereignty through advanced security measures such as de-identification, zero-knowledge proofs, trusted execution environments for private computation, and decentralized storage.

Chainbase (✸,✸) 的头像
Chainbase (✸,✸)1 年前

Alex DeConde @0xatd, Commercial Lead at @WeatherXM, stated that accurately capturing global temperatures requires about 36 million weather stations. Though scalable, satellite observations lack the localized accuracy of ground-based stations. Despite logistical hurdles, WeatherXM is focused on solving this difficult but critical challenge by expanding the deployment of weather stations.

SecBriefs | Making Cybersecurity Simple 的头像
SecBriefs | Making Cybersecurity Simple1 年前

Cybercriminals stole over 5 billion records in 2024 & collected 500 data points for every individual.🕵️‍♀️ Want to know what followed next?🧐 Think your data's safe? Think again. Cybersecurity matters. Learn it with Cybersecurity Dictionary for Everyone:

Shkina 的头像
Shkina1 年前

@philmcm @BeaconProtocol amazing

THE 🧢 py.0xπ 🧩 的头像
THE 🧢 py.0xπ 🧩1 年前

@philmcm @BeaconProtocol Oh yea omg,I really like profile😈

Wayne 🪂 的头像
Wayne 🪂1 年前

@philmcm @BeaconProtocol Don't let us down!

Marcus 的头像
Marcus1 年前

@philmcm @BeaconProtocol many playfulness ;Absolutely love💕 both you and your Shares Many thanks

DaniZ 的头像
DaniZ1 年前

@philmcm @BeaconProtocol meet ur real frens on ... romatic!

Alpha $liz 的头像
Alpha $liz1 年前

@philmcm @BeaconProtocol exciting to reach out

相关视频

In the second episode of Scenius Studio's mini-series "The Use-Case", I sit down with Andrej Co-Founder of touch grass. Grass gives users the ability to earn ownership in the Grass network by supplying the protocol with their unused internet bandwidth for data scraping purposes (something that is already happening to most of us and we don’t get paid!). The grass protocol packages this scraped web data and sells it to AI companies who have insufficient data to further develop their models. With over 3 millions users and millions of annualized revenue, Grass is a real commercial business with a roadmap that makes it one of the most exciting projects at the intersection of crypto x AI and data. In this episode we discuss: ➔ Andrej’s background in physics, finance, and sports betting ➔ Big companies using your IP address without your knowledge or permission ➔ How the Grass protocol puts a toll booth on your internet bandwidth highway ➔ Packaging web scraped data and selling it to AI companies building Multi-Modal models ➔ Dynamics between the Grass Protocol and the labs entity developing Grass’ IP ➔ Protocol design decisions to ensure that all tokenholders (VCs, team, and community) are aligned ➔ Why Grass needed to be built on crypto rails to maximize its potential ➔ The future of LLMs and how they will search for context and information Hope you enjoy this episode of Scenius Studio's "The Use-Case". Links to listen in bio or below👇

Ben Jacobs

22,418 次观看 • 1 年前